Cover of book: Code Capital
Buy in shop
, to see if you have full access to this publication.
Book Titles No access

Code Capital

A Sociotechnical Framework to Understand the Implications of Artificially Intelligent Systems from Design to Deployment
Authors:
Publisher:
 2022

Summary

Um die vielfältigen Wirkungsdimensionen von Künstlicher Intelligenz zu verstehen, dient das innovative Konzept des Codekapitals als Analyse soziotechnischer Faktoren, die diese Systeme prägen. Es verbindet die Evolution verschiedener Kapitalformen mit der Technologiewissenschaft und ermöglicht so eine Analyse entlang von vier Dimensionen – Conception, Operations, Data und Environment. Zwei Fallstudien über Gesichtserkennungtechnologie und synthetische Spracherzeugung zeigen, wie Codekapital interdisziplinäre Akteur:innen befähigt, die Auswirkungen angewandter KI zu antizipieren und zu steuern.

Dr. Léa Steinacker ist Forscherin, Journalistin und Unternehmerin an der Schnittstelle zwischen menschlichen und maschinellen Systemen.

Keywords

Bibliographic data

Copyright year
2022
ISBN-Print
978-3-8487-8890-3
ISBN-Online
978-3-7489-2945-1
Publisher
Nomos, Baden-Baden
Language
English
Pages
239
Product type
Book Titles

Table of contents

ChapterPages
  1. Titelei/Inhaltsverzeichnis No access 1 - 22
      1. 1.1.1 Calls for Action No access
      2. 1.1.2 Institutional Responses No access
    2. 1.2 Objectives No access
    3. 1.3 Contributions No access
      1. 1.4.1 Methodology No access
      2. 1.4.2 Structure No access
    5. 1.5 Conclusion No access
    1. 2.1 Introduction No access
    2. 2.2 A Brief History of AI No access
      1. 2.3.1 Classifications and Predictions No access
      2. 2.3.2 Rankings and Recommendations No access
      3. 2.3.3 Generation and Alteration No access
    4. 2.4 Contextualizing Central Issues No access
    5. 2.5 Conclusion No access
    1. 3.1 Introduction No access
      1. 3.2.1 Technology as Trajectory No access
        1. 3.2.2.1 Actor-Network-Theory No access
        2. 3.2.2.2 Large Technical Systems No access
      1. 3.3.1 Material features No access
      2. 3.3.2 Constitutive Entanglement No access
      1. 3.4.1 Relevant actors No access
      2. 3.4.2 Material features No access
      3. 3.4.3 Sociomaterial practice and structures No access
      4. 3.4.4 External forces No access
    5. 3.5 Conclusion No access
    1. 4.1 Introduction No access
      1. 4.2.1 Money and Goods No access
      2. 4.2.2 People and Labor No access
      3. 4.2.3 Intangibles and Disputes No access
      1. 4.3.1 Interpersonal Phenomena No access
      2. 4.3.2 Debate No access
      1. 4.4.1 The What: Commodifying Knowledge No access
      2. 4.4.2 The How: Elevating Digital Technologies No access
      3. 4.4.3 The Why: Surveilling Others No access
    5. 4.5 Discussion No access
    6. 4.6 Conclusion No access
    1. 5.1 Introduction No access
    2. 5.2 Code Capital: The Concept No access
        1. 5.3.1.1 Sensegiving Actors No access
        2. 5.3.1.2 Narratives No access
        3. 5.3.1.3 Investments and Expected Returns No access
        1. 5.3.2.1 Model Infrastructure No access
        2. 5.3.2.2 User Interface No access
        3. 5.3.2.2 Device No access
        1. 5.3.3.1 Collection No access
        2. 5.3.3.2 Pre-Processing No access
        3. 5.3.3.3 Ethical Concerns No access
        1. 5.3.4.1 Sensemaking Actors No access
        2. 5.3.4.2 Social Acceptance No access
        3. 5.3.4.3 Regulatory Boundaries No access
    4. 5.4 Discussion No access
    5. 5.5 Conclusion No access
      1. 6.1.1 Facial Recognition Technology and its Global Use No access
      2. 6.1.2 Issues of Concern: Bias, Accuracy, Privacy, and Abuse No access
      3. 6.1.3 Interaction with the Public No access
      1. 6.2.1 Sensegiving Actors No access
      2. 6.2.2 Narratives No access
      3. 6.2.3 Investment and Expected Return No access
        1. 6.3.1.1 Open-source Set-up No access
        2. 6.3.1.2 Detection vs Recognition No access
        1. 6.3.2.1 Accuracy No access
        2. 6.3.2.2 User privacy No access
        3. 6.3.2.3 Abuse No access
      1. 6.4.1 Collection No access
      2. 6.4.2 Processing No access
        1. 6.5.1.1 Surveillance No access
        2. 6.5.1.2 Public acceptance No access
      2. 6.5.2 Regulatory Boundaries No access
    6. 6.6 Discussion No access
    7. 6.7 Conclusion No access
      1. 7.1.1 Text-to-Speech Synthesis No access
        1. 7.1.2.1 Automation No access
        2. 7.1.2.2 Authenticity No access
        3. 7.1.2.3 Participation No access
        4. 7.1.2.4 Intimacy No access
      1. 7.2.1 Sensegiving Actors No access
        1. 7.2.2.1 Trust No access
        2. 7.2.2.2 Revenue Diversification No access
        1. 7.2.3.1 Funding No access
        2. 7.2.3.2 Business Model No access
      4. 7.3 Operations No access
      5. 7.3.1 Model Architecture No access
      6. 7.3.2 Evaluation No access
      7. 7.3.3 User Interface No access
      1. 7.4.1 Collection No access
      2. 7.4.2 Pre-Processing No access
      3. 7.4.3 Storage No access
      1. 7.5.1 Sensemaking Actors No access
      2. 7.5.2 Regulatory Boundaries No access
    5. 7.6 Discussion No access
    6. 7.7 Conclusion No access
    1. 8.1 Summary No access
    2. 8.2 Limitations No access
        1. 8.3.1.1 Accumulation No access
        2. 8.3.1.2 Reproducibility No access
        3. 8.3.1.3 Conversion No access
      2. 8.3.2 Practical Applications No access
    4. 8.4 Outlook for Further Research No access
    5. 8.5 Concluding Remarks No access
  10. References No access 199 - 237
  11. Appendix No access 238 - 239

Bibliography (649)

  1. § 12 BGB - Einzelnorm. (n.d.). Retrieved January 28, 2021, from https://www.gesetze-im-internet.de/bgb/__12.html Open Google Scholar doi.org/10.5771/9783748929451
  2. § 22 KunstUrhG - Einzelnorm. (n.d.). Retrieved January 28, 2021, from https://www.gesetze-im-internet.de/kunsturhg/__22.html Open Google Scholar doi.org/10.5771/9783748929451
  3. Abdi, H., Valentin, D., Edelman, B., & O’Toole, A. J. (1995). More about the difference between men and women: Evidence from linear neural networks and the principal-component approach. Perception, 24(5), 539–562. Open Google Scholar doi.org/10.5771/9783748929451
  4. Act on Copyright and Related Rights (Urheberrechtsgesetz – UrhG). (n.d.). Retrieved January 28, 2021, from https://www.gesetze-im-internet.de/englisch_urhg/englisch_urhg.html Open Google Scholar doi.org/10.5771/9783748929451
  5. Adam, A. (2006). Artificial knowing: Gender and the thinking machine. Routledge. Open Google Scholar doi.org/10.5771/9783748929451
  6. Adams, R., & McIntyre, N. (2020, August 13). England A-level downgrades hit pupils from disadvantaged areas hardest. The Guardian. http://www.theguardian.com/education/2020/aug/13/england-a-level-downgrades-hit-pupils-from-disadvantaged-areas-hardest Open Google Scholar doi.org/10.5771/9783748929451
  7. Adobe. (2017, October 21). #ProjectCloak: Adobe MAX 2017 [Video]. YouTube. https://www.youtube.com/watch?v=TzBZWBht02I Open Google Scholar doi.org/10.5771/9783748929451
  8. Adomavicius, G., Bockstedt, J. C., Curley, S. P., & Zhang, J. (2018). Effects of online recommendations on consumers’ willingness to pay. Information Systems Research, 29(1), 84–102. Open Google Scholar doi.org/10.5771/9783748929451
  9. Adomavicius, G., & Tuzhilin, A. (2005). Toward the next generation of recommender systems: A survey of the state-of-the-art and possible extensions. IEEE Transactions on Knowledge and Data Engineering, 17(6), 734–749. Open Google Scholar doi.org/10.5771/9783748929451
  10. AFP. (2019, September 4). Smile-to-pay: Chinese shoppers turn to facial payment technology. The Guardian. https://www.theguardian.com/world/2019/sep/04/smile-to-pay-chinese-shoppers-turn-to-facial-payment-technology Open Google Scholar doi.org/10.5771/9783748929451
  11. Agarwal, S. (2021, March 11). India’s new social media law spells trouble for tech giants. Fast Company. https://www.fastcompany.com/90613579/india-social-media-rules-twitter-facebook-free-speech Open Google Scholar doi.org/10.5771/9783748929451
  12. Aguiar, L., & Waldfogel, J. (2018). Platforms, promotion, and product discovery: Evidence from spotify playlists (NBER Working Papers 24713). National Bureau of Economic Research. https://economics.ucdavis.edu/events/papers/515Waldfogel.pdf Open Google Scholar doi.org/10.5771/9783748929451
  13. AI Ethics Lab. (2020). TOOLBOX: Dynamics of AI Principles. AI ETHICS LAB. https://aiethicslab.com/big-picture/ Open Google Scholar doi.org/10.5771/9783748929451
  14. Ajder, H. (2019, June 16). The ethics of deepfakes aren’t always black and white. The Next Web. https://thenextweb.com/podium/2019/06/16/the-ethics-of-deepfakes-arent-always-black-and-white/ Open Google Scholar doi.org/10.5771/9783748929451
  15. Akrich, M. (1992). The de-scription of Technical Objects. In W. E. Bijker & J. Law (Eds.), Shaping Technology, building society (pp. 205–224). MIT Press. https://www.scribd.com/document/389890486/The-de-scription-of-Technical-Objects-Madeleine-Akrich Open Google Scholar doi.org/10.5771/9783748929451
  16. Akrich, M., & Latour, B. (1992). A Summary of a Convenient Vocabulary for the Semiotics of Human and Nonhuman Assemblies. In Shaping Technology, Building Society. MIT Press. Open Google Scholar doi.org/10.5771/9783748929451
  17. Alexander, C. P. (1983, May 30). The New Economy. Time. http://content.time.com/time/subscriber/article/0,33009,926013-1,00.html Open Google Scholar doi.org/10.5771/9783748929451
  18. Allyn, B. (2020, June 10). Amazon Halts Police Use Of Its Facial Recognition Technology. NPR. https://www.npr.org/2020/06/10/874418013/amazon-halts-police-use-of-its-facial-recognition-technology Open Google Scholar doi.org/10.5771/9783748929451
  19. Alper, M. (2017a). Giving voice: Mobile communication, disability, and inequality. MIT Press. Open Google Scholar doi.org/10.5771/9783748929451
  20. Alper, M. (2017b, July 21). Talking Like a “Princess”: What Speaking Machines Say About Human Biases. The New Inquiry. https://thenewinquiry.com/blog/talking-like-a-princess-what-speaking-machines-say-about-human-biases/ Open Google Scholar doi.org/10.5771/9783748929451
  21. Ananny, M. (2016). Toward an ethics of algorithms: Convening, observation, probability, and timeliness. Science, Technology, & Human Values, 41(1), 93–117. Open Google Scholar doi.org/10.5771/9783748929451
  22. Anderson, A., Maystre, L., Anderson, I., Mehrotra, R., & Lalmas, M. (2020). Algorithmic effects on the diversity of consumption on spotify. Proceedings of The Web Conference 2020, 2155–2165. Open Google Scholar doi.org/10.5771/9783748929451
  23. Anderson, C. (2012). The Impact of Social Media on Lodging Performance. Cornell Hospitality Report, 12(15), 6–11. Open Google Scholar doi.org/10.5771/9783748929451
  24. Anderson, CW. (2013). Towards a sociology of computational and algorithmic journalism. New Media & Society, 15(7), 1005–1021. https://doi.org/10.1177/1461444812465137 Open Google Scholar doi.org/10.5771/9783748929451
  25. Angwin, J., Larson, J., Mattu, S., & Kirchner, L. (2016, May 23). Machine Bias. ProPublica. https://www.propublica.org/article/machine-bias-risk-assessments-in-criminal-sentencing Open Google Scholar doi.org/10.5771/9783748929451
  26. Anonymous. (2021). Capitol Map. http://capitolmap.com/ Open Google Scholar doi.org/10.5771/9783748929451
  27. Arrieta, A. B., Díaz-Rodríguez, N., Del Ser, J., Bennetot, A., Tabik, S., Barbado, A., García, S., Gil-López, S., Molina, D., & Benjamins, R. (2020). Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI. Information Fusion, 58, 82–115. Open Google Scholar doi.org/10.5771/9783748929451
  28. Arrieta-Ibarra, I., Goff, L., Jiménez-Hernández, D., Lanier, J., & Weyl, E. G. (2018). Should We Treat Data as Labor? Moving beyond" Free". Aea Papers and Proceedings, 108, 38–42. Open Google Scholar doi.org/10.5771/9783748929451
  29. Art. 4 GDPR – Definitions, European Commission (2016). https://gdpr-info.eu/art-4-gdpr/ Open Google Scholar doi.org/10.5771/9783748929451
  30. Art. 5 GDPR – Principles relating to processing of personal data, European Commission (2016). https://gdpr-info.eu/art-5-gdpr/ Open Google Scholar doi.org/10.5771/9783748929451
  31. Art. 6 GDPR – Lawfulness of processing, European Commission (2016). https://gdpr-info.eu/art-6-gdpr/ Open Google Scholar doi.org/10.5771/9783748929451
  32. Art. 12 GDPR – Transparent information, communication and modalities for the exercise of the rights of the data subject, European Commission (2016). https://gdpr-info.eu/art-12-gdpr/ Open Google Scholar doi.org/10.5771/9783748929451
  33. Art. 25 GDPR – Data protection by design and by default, European Commission (2016). https://gdpr-info.eu/art-25-gdpr/ Open Google Scholar doi.org/10.5771/9783748929451
  34. Aru, O. E., & Gozie, I. (2013). Facial Verification Technology for Use In Atm Transactions. American Journal of Engineering Research, 2(5), 188–193. Open Google Scholar doi.org/10.5771/9783748929451
  35. Audio Advertising—Austria. (n.d.). Statista Market Forecast. Retrieved January 20, 2021, from https://www.statista.com/outlook/20200/128/audio-advertising/austria?currency=eur Open Google Scholar doi.org/10.5771/9783748929451
  36. Audio Advertising—Germany. (n.d.). Statista Market Forecast. Retrieved January 20, 2021, from https://www.statista.com/outlook/20200/137/audio-advertising/germany Open Google Scholar doi.org/10.5771/9783748929451
  37. Audio Advertising—Switzerland. (n.d.). Statista Market Forecast. Retrieved January 20, 2021, from https://www.statista.com/outlook/20200/155/audio-advertising/switzerland Open Google Scholar doi.org/10.5771/9783748929451
  38. Azzi, C., & Ehrenberg, R. (1975). Household allocation of time and church attendance. Journal of Political Economy, 83(1), 27–56. Open Google Scholar doi.org/10.5771/9783748929451
  39. Bai, X., Cambazoglu, B. B., Gullo, F., Mantrach, A., & Silvestri, F. (2017). Exploiting search history of users for news personalization. Information Sciences, 385, 125–137. Open Google Scholar doi.org/10.5771/9783748929451
  40. Baker, J. (2016, August 22). Germany eyes facial recognition tech for airports, train stations. Ars Technica. https://arstechnica.com/tech-policy/2016/08/germany-facial-recognition-tech-airports-train-stations/ Open Google Scholar doi.org/10.5771/9783748929451
  41. Baker, P., & Potts, A. (2013). ‘Why do white people have thin lips?’ Google and the perpetuation of stereotypes via auto-complete search forms. Critical Discourse Studies, 10(2), 187–204. Open Google Scholar doi.org/10.5771/9783748929451
  42. Bandura, A. (1986). Social foundations of thought and action. Englewood Cliffs, N.J., Prentice-Hall. Open Google Scholar doi.org/10.5771/9783748929451
  43. Banfield, E. (1961). Political Influence. The Free Press of Glencoe. Open Google Scholar doi.org/10.5771/9783748929451
  44. Barad, K. (2003). Posthumanist performativity: Toward an understanding of how matter comes to matter. Signs: Journal of Women in Culture and Society, 28(3), 801–831. Open Google Scholar doi.org/10.5771/9783748929451
  45. Barad, K. (2007). Meeting the universe halfway: Quantum physics and the entanglement of matter and meaning. Duke University Press. Open Google Scholar doi.org/10.5771/9783748929451
  46. Barassi, V. (2019). Datafied citizens in the age of coerced digital participation. Sociological Research Online, 24(3), 414–429. Open Google Scholar doi.org/10.5771/9783748929451
  47. Barfield, W. (2018). Liability for autonomous and artificially intelligent robots. Paladyn, Journal of Behavioral Robotics, 9(1), 193–203. Open Google Scholar doi.org/10.5771/9783748929451
  48. Barocas, S., & Selbst, A. D. (2016). Big data’s disparate impact. Calif. L. Rev., 104(3), 671–732. Open Google Scholar doi.org/10.5771/9783748929451
  49. Baron, J. N., & Hannan, M. T. (1994). The impact of economics on contemporary sociology. Journal of Economic Literature, 32(3), 1111–1146. Open Google Scholar doi.org/10.5771/9783748929451
  50. Barr, A. (2015, July 1). Google Mistakenly Tags Black People as ‘Gorillas,’ Showing Limits of Algorithms. WSJ. https://blogs.wsj.com/digits/2015/07/01/google-mistakenly-tags-black-people-as-gorillas-showing-limits-of-algorithms/ Open Google Scholar doi.org/10.5771/9783748929451
  51. Bates, J. (2009). Airport Security: CCTV Takes Off. International Airport Review, 13(4), 21–24. Open Google Scholar doi.org/10.5771/9783748929451
  52. Bathaee, Y. (2017). The artificial intelligence black box and the failure of intent and causation. Harv. JL & Tech., 31(2), 889–937. Open Google Scholar doi.org/10.5771/9783748929451
  53. Bayerische Landeszentrale für neue Medien. (2020). Online-Audio-Monitor 2020. Bayerische Landeszentrale für neue Medien. https://www.online-audio-monitor.de/wp-content/uploads/Bericht-OAM_2020_010920_FINAL_V3.pdf Open Google Scholar doi.org/10.5771/9783748929451
  54. Becker, G. (1962). Investment in human capital: A theoretical analysis. Journal of Political Economy, 70(5), 9–49. Open Google Scholar doi.org/10.5771/9783748929451
  55. Bell, D. (1976). The coming of the post-industrial society. The Educational Forum, 40(4), 574–579. Open Google Scholar doi.org/10.5771/9783748929451
  56. Bell, D. A. (1995). Who’s afraid of critical race theory. U. Ill. L. Rev., 893. Open Google Scholar doi.org/10.5771/9783748929451
  57. Bellman, R. (1978). An introduction to artificial intelligence: Can computers think? Boyd & Fraser Publishing Company. Open Google Scholar doi.org/10.5771/9783748929451
  58. Bender, E. M., Gebru, T., McMillan-Major, A., & Shmitchell, S. (2021). On the Dangers of Stochastic Parrots: Can Language Models Be Too Big??. Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency, 610–623. Open Google Scholar doi.org/10.5771/9783748929451
  59. Benitez-Quiroz, C. F., Srinivasan, R., Feng, Q., Wang, Y., & Martinez, A. M. (2017). EmotioNet Challenge: Recognition of facial expressions of emotion in the wild. ArXiv Preprint:1703.01210 [Cs]. http://arxiv.org/abs/1703.01210 Open Google Scholar doi.org/10.5771/9783748929451
  60. Benjamin, R. (2019). Race after technology: Abolitionist tools for the new jim code. Polity. Open Google Scholar doi.org/10.5771/9783748929451
  61. Berdux, S. (2015). “Eine kempelensche Sprechmaschine”. New insights in speaking machines in the late 18th and early 19th centuries. HSCR@ INTERSPEECH, 50–51. https://www.isca-speech.org/archive/hscr_2015/papers/hs15_050.pdf Open Google Scholar doi.org/10.5771/9783748929451
  62. Berg, F., Koelbel, J. F., & Rigobon, R. (2019). Aggregate confusion: The divergence of ESG ratings. MIT Sloan School of Management. Open Google Scholar doi.org/10.5771/9783748929451
  63. Bergmann, S. (1999). Publicity Rights in the United States and Germany: A Comparative Analysis. Loyola of Los Angeles Entertainment Law Journal, 19(3), 45. Open Google Scholar doi.org/10.5771/9783748929451
  64. Berinsky, A. J., Huber, G. A., & Lenz, G. S. (2012). Evaluating online labor markets for experimental research: Amazon.com’s Mechanical Turk. Political Analysis, 20(3), 351–368. Open Google Scholar doi.org/10.5771/9783748929451
  65. Bialek, C. (2020, July 29). Audio-Markt: Nachfrage nach Podcasts und Hörbüchern wächst in der Coronazeit rasant. Handelsblatt. https://www.handelsblatt.com/unternehmen/it-medien/audio-markt-nachfrage-nach-podcasts-und-hoerbuechern-waechst-in-der-coronazeit-rasant/26047506.html Open Google Scholar doi.org/10.5771/9783748929451
  66. Big Brother Watch UK Team. (2019, August 16). Facial Recognition ‘Epidemic’ in the UK – Big Brother Watch. https://bigbrotherwatch.org.uk/all-media/facial-recognition-epidemic-in-the-uk/ Open Google Scholar doi.org/10.5771/9783748929451
  67. Bijker, W. E., Hughes, T. P., & Pinch, T. (Eds.). (1987). The Social construction of technological systems: New directions in the sociology and history of technology. MIT Press. Open Google Scholar doi.org/10.5771/9783748929451
  68. Bimber, B. (1990). Karl Marx and the Three Faces of Technological Determinism. Social Studies of Science, 20(2), 333–351. JSTOR. https://doi.org/10.1177/030631290020002006 Open Google Scholar doi.org/10.5771/9783748929451
  69. Birch, K., Cochrane, D., & Ward, C. (2021). Data as asset? The measurement, governance, and valuation of digital personal data by Big Tech. Big Data & Society, 8(1), 1–15. Open Google Scholar doi.org/10.5771/9783748929451
  70. Bodén, L. (2013). Seeing red? The agency of computer software in the production and management of students’ school absences. International Journal of Qualitative Studies in Education, 26(9), 1117–1131. Open Google Scholar doi.org/10.5771/9783748929451
  71. Böhm-Bawerk, E. von. (1890). Capital and interest. Macmillan. Open Google Scholar doi.org/10.5771/9783748929451
  72. Bollier, D. (2010). The promise and peril of big data. Aspen Institute. https://www.aspeninstitute.org/publications/promise-peril-big-data/ Open Google Scholar doi.org/10.5771/9783748929451
  73. Bolukbasi, T., Chang, K.-W., Zou, J. Y., Saligrama, V., & Kalai, A. T. (2016). Man is to computer programmer as woman is to homemaker? Debiasing word embeddings. Advances in Neural Information Processing Systems, 29, 4349–4357. Open Google Scholar doi.org/10.5771/9783748929451
  74. Bonham, J. (2021, January 25). Their faces should be published. Every last one of them should be charged, tried and convicted of sedition. #FacesOfTheRiot https://t.co/YCABCnCMGv [Tweet]. @b0nham_J. https://twitter.com/b0nham_J/status/1353711411139137537 Open Google Scholar doi.org/10.5771/9783748929451
  75. Bostrom, N. (2014). Superintelligence: Paths, Dangers, Strategies. Oxford University Press. Open Google Scholar doi.org/10.5771/9783748929451
  76. Bourdieu, P. (1977). Outline of a Theory of Practice. Cambridge University Press. Open Google Scholar doi.org/10.5771/9783748929451
  77. Bourdieu, P. (1983). Ökonomisches Kapital, kulturelles Kapital, soziales Kapital. In R. Kreckel (Ed.), Soziale Ungleichheiten (pp. 183–198). Schwartz. Open Google Scholar doi.org/10.5771/9783748929451
  78. Bourdieu, P. (1986). The Forms of Capital. In J. Richardson (Ed.), Handbook of Theory and Reseqarch for the Sociology of Education (pp. 241–258). Greenwood. Open Google Scholar doi.org/10.5771/9783748929451
  79. Bourdieu, P. (2015). Die verborgenen Mechanismen der Macht (M. Steinrücke, Ed.). VSA Verlag. Open Google Scholar doi.org/10.5771/9783748929451
  80. Bowles, S., & Gintis, H. (2002). Social Capital And Community Governance. The Economic Journal, 112(483), 419–436. Open Google Scholar doi.org/10.5771/9783748929451
  81. Bowyer, K. W. (2004). Face recognition technology: Security versus privacy. IEEE Technology and Society Magazine, 23(1), 9–19. Open Google Scholar doi.org/10.5771/9783748929451
  82. Boyarskaya, M., Olteanu, A., & Crawford, K. (2020). Overcoming Failures of Imagination in AI Infused System Development and Deployment. ArXiv:2011.13416 [Cs]. http://arxiv.org/abs/2011.13416 Open Google Scholar doi.org/10.5771/9783748929451
  83. boyd, danah, & Crawford, K. (2012). Critical Questions for Big Data. Information, Communication & Society, 15(5), 662–679. https://doi.org/10.1080/1369118X.2012.678878 Open Google Scholar doi.org/10.5771/9783748929451
  84. Braca, A. (2017). An investigation into Bias in Facial Recognition using Learning Algorithms [Master’s Thesis]. National College of Ireland. Open Google Scholar doi.org/10.5771/9783748929451
  85. Brey, P., & Søraker, J. H. (2009). Philosophy of computing and information technology. In A. Meijers (Ed.), Philosophy of technology and engineering sciences (pp. 1341–1407). Elsevier. Open Google Scholar doi.org/10.5771/9783748929451
  86. Brivot, M., & Gendron, Y. (2011). Beyond panopticism: On the ramifications of surveillance in a contemporary professional setting. Accounting, Organizations and Society, 36(3), 135–155. https://doi.org/10.1016/j.aos.2011.03.003 Open Google Scholar doi.org/10.5771/9783748929451
  87. Brown, T. B., Mann, B., Ryder, N., Subbiah, M., Kaplan, J., Dhariwal, P., Neelakantan, A., Shyam, P., Sastry, G., Askell, A., Agarwal, S., Herbert-Voss, A., Krueger, G., Henighan, T., Child, R., Ramesh, A., Ziegler, D. M., Wu, J., Winter, C., … Amodei, D. (2020). Language Models are Few-Shot Learners. ArXiv Preprint ArXiv:2005.14165. http://arxiv.org/abs/2005.14165 Open Google Scholar doi.org/10.5771/9783748929451
  88. Brundage, M., Avin, S., Wang, J., Belfield, H., Krueger, G., Hadfield, G., Khlaaf, H., Yang, J., Toner, H., & Fong, R. (2020). Toward trustworthy AI development: Mechanisms for supporting verifiable claims. ArXiv Preprint ArXiv:2004.07213. Open Google Scholar doi.org/10.5771/9783748929451
  89. Brunelli, R., & Poggio, T. (1993). Face recognition: Features versus templates. IEEE Transactions on Pattern Analysis and Machine Intelligence, 15(10), 1042–1052. Open Google Scholar doi.org/10.5771/9783748929451
  90. Brynjolfsson, E., Eggers, F., & Gannamaneni, A. (2018). Using Massive Online Choice Experiments to Measure Changes in Well-being. National Bureau of Economic Research Working Paper Series. https://www.nber.org/papers/w24514.pdf Open Google Scholar doi.org/10.5771/9783748929451
  91. Buchanan, R. A. (2005). History of Technology. In Encyclopedia Britannica: History of technology. https://www.britannica.com/technology/history-of-technology Open Google Scholar doi.org/10.5771/9783748929451
  92. Buckley, O., & Nurse, J. R. (2019). The language of biometrics: Analysing public perceptions. Journal of Information Security and Applications, 47, 112–119. Open Google Scholar doi.org/10.5771/9783748929451
  93. Bundesrepublik Deutschland. (n.d.-a). Art 1 GG - Einzelnorm. Grundgesetz. Retrieved January 28, 2021, from https://www.gesetze-im-internet.de/gg/art_1.html Open Google Scholar doi.org/10.5771/9783748929451
  94. Bundesrepublik Deutschland. (n.d.-b). Art 2 GG - Einzelnorm. Grundgesetz. Retrieved January 28, 2021, from https://www.gesetze-im-internet.de/gg/art_2.html Open Google Scholar doi.org/10.5771/9783748929451
  95. Bundesverband Digitale Wirtschaft. (2020, December 2). Online-Audio-Umsätze in Deutschland verdoppeln sich innerhalb von nur drei Jahren / Podcast-Umsätze steigen 2020 von neun auf 14 Millionen Euro. BDVW News. https://www.bvdw.org/der-bvdw/news/detail/artikel/online-audio-umsaetze-in-deutschland-verdoppeln-sich-innerhalb-von-nur-drei-jahren-podcast-umsaetze/ Open Google Scholar doi.org/10.5771/9783748929451
  96. Bunge, M. (1999). Social science under debate: A philosophical perspective. University of Toronto Press. Open Google Scholar doi.org/10.5771/9783748929451
  97. Buolamwini, J., & Gebru, T. (2018). Gender shades: Intersectional accuracy disparities in commercial gender classification. Conference on Fairness, Accountability and Transparency, 81, 77–91. Open Google Scholar doi.org/10.5771/9783748929451
  98. Burgess, M. (2019, June 17). Inside the urgent battle to stop UK police using facial recognition. Wired UK. https://www.wired.co.uk/article/uk-police-facial-recognition Open Google Scholar doi.org/10.5771/9783748929451
  99. Burns, T. (Ed.). (1969). Industrial Man: Selected Readings. Penguin. https://trove.nla.gov.au/version/43718768 Open Google Scholar doi.org/10.5771/9783748929451
  100. Burrell, J. (2016). How the machine ‘thinks’: Understanding opacity in machine learning algorithms. Big Data & Society, 3(1), 2053951715622512. Open Google Scholar doi.org/10.5771/9783748929451
  101. Buschak, D. M. (1999). Increases in natural speech production following experience with synthetic speech. Journal of Special Education Technology, 14(2), 44–53. Open Google Scholar doi.org/10.5771/9783748929451
  102. Butler, J. (1997). The psychic life of power: Theories in subjection. Stanford University Press. Open Google Scholar doi.org/10.5771/9783748929451
  103. Butler, J. (2021). Excitable speech: A politics of the performative. Routledge. Open Google Scholar doi.org/10.5771/9783748929451
  104. Caliskan, A., Bryson, J. J., & Narayanan, A. (2017). Semantics derived automatically from language corpora contain human-like biases. Science, 356(6334), 183–186. Open Google Scholar doi.org/10.5771/9783748929451
  105. Callaway, E. (2020). ‘It will change everything’: DeepMind’s AI makes gigantic leap in solving protein structures. Nature, 588(7837), 203–204. https://doi.org/10.1038/d41586-020-03348-4 Open Google Scholar doi.org/10.5771/9783748929451
  106. Callon, M. (1987). Society in the Making: The Sudy of Technology as a Tool for Sociological Analysis. In W. E. Bijker, T. Hughes, & T. Pinch (Eds.), The Social Construction of Technological Systems (pp. 83–103). MIT Press. Open Google Scholar doi.org/10.5771/9783748929451
  107. Cameron, D. (2021, January 11). Every Deleted Parler Post, Many With Users’ Location Data, Has Been Archived. Gizmodo. https://gizmodo.com/every-deleted-parler-post-many-with-users-location-dat-1846032466 Open Google Scholar doi.org/10.5771/9783748929451
  108. Campbell-Dollaghan, K. (2016, November 14). The Algorithmic Democracy. Co.Design. https://www.fastcodesign.com/3065582/the-algorithmic-democrac⁠yeng Open Google Scholar doi.org/10.5771/9783748929451
  109. Campbell-Wilson, G. (2020, April 29). RIP Lyrebird AI—which alternatives should I try? Replica Blog. https://blog.replicastudios.com/lyrebird-alternatives/?gclid=CjwKCAiAl4WABhAJEiwATUnEF47s26mvFyibN2kWb6VLjjYY9aALrRqJv8W15sB6moCioASnZnKV5hoCnJAQAvD_BwE Open Google Scholar doi.org/10.5771/9783748929451
  110. Cannan, E. (1921). Early History of the Term Capital. The Quarterly Journal of Economics, 35(3), 469–481. JSTOR. https://doi.org/10.2307/1884097 Open Google Scholar doi.org/10.5771/9783748929451
  111. Carstensen, T. (2021a). Parler Videos. Capitol Terrorist Attack. https://www.tommycarstensen.com/terrorism/index.html Open Google Scholar doi.org/10.5771/9783748929451
  112. Carstensen, T. (2021b). @ParlerVideos I am an anti-fascist! I tweet mostly in English and Danish USDK I block anonymous profiles and those using ad hominem arguments ?. @hologram_stan. https://twitter.com/carstensenpol Open Google Scholar doi.org/10.5771/9783748929451
  113. Cassell, J., & Bickmore, T. (2000). External manifestations of trustworthiness in the interface. Communications of the ACM, 43(12), 50–56. Open Google Scholar doi.org/10.5771/9783748929451
  114. Castells, M. (2011). The rise of the network society (Vol. 12). John Wiley & Sons. Open Google Scholar doi.org/10.5771/9783748929451
  115. Cave, S., Craig, C., Dihal, K., Dillon, S., Montgomery, J., Singler, B., & Taylor, L. (2018). Portrayals and perceptions of AI and why they matter. The Royal Society. https://royalsociety.org/-/media/policy/projects/ai-narratives/AI-narratives-workshop-findings.pdf Open Google Scholar doi.org/10.5771/9783748929451
  116. Cave, S., Dihal, K., & Dillon, S. (2020). AI narratives: A history of imaginative thinking about intelligent machines. Oxford University Press. Open Google Scholar doi.org/10.5771/9783748929451
  117. Center, J. L. (1998). Practical application of facial recognition: Automated facial recognition access control system. In H. Wechsler, P. Philips, V. Bruce, F. F. Soulié, & T. S. Huang (Eds.), Face Recognition (Vol. 163, pp. 402–411). Springer. Open Google Scholar doi.org/10.5771/9783748929451
  118. Char, D. S., Abràmoff, M. D., & Feudtner, C. (2020). Identifying ethical considerations for machine learning healthcare applications. The American Journal of Bioethics, 20(11), 7–17. Open Google Scholar doi.org/10.5771/9783748929451
  119. Char, D. S., Shah, N. H., & Magnus, D. (2018). Implementing machine learning in health care—Addressing ethical challenges. The New England Journal of Medicine, 378(11), 981–983. Open Google Scholar doi.org/10.5771/9783748929451
  120. Charniak, E. (1985). Introduction to artificial intelligence. Pearson Education India. Open Google Scholar doi.org/10.5771/9783748929451
  121. Chavan, M. (2009). The balanced scorecard: A new challenge. Journal of Management Development, 28(5), 393–406. Open Google Scholar doi.org/10.5771/9783748929451
  122. Chawla, R. (2019). Deepfakes: How a pervert shook the world. International Journal of Advance Research and Development, 4(6), 4–8. Open Google Scholar doi.org/10.5771/9783748929451
  123. Chee, F. Y. (2020, January 16). EU mulls five-year ban on facial recognition tech in public areas. Reuters. https://www.reuters.com/article/uk-eu-ai-idINKBN1ZF2Q⁠Neng Open Google Scholar doi.org/10.5771/9783748929451
  124. Chen, A. (2019, March 25). Tech journalist Clive Thompson examines the people behind the software changing the world. The Verge. https://www.theverge.com/2019/3/25/18277279/clive-thompson-coders-silicon-valley-software-engineers-programming-interview-books Open Google Scholar doi.org/10.5771/9783748929451
  125. Cheney-Lippold, J. (2016). Jus Algoritmi: How the National Security Agency Remade Citizenship. International Journal of Communication, 10, 1721–1742. Open Google Scholar doi.org/10.5771/9783748929451
  126. Chitika Insights. (2013). The value of Google result positioning. Chitika Insights. Open Google Scholar doi.org/10.5771/9783748929451
  127. Chu, X., Ilyas, I. F., Krishnan, S., & Wang, J. (2016). Data cleaning: Overview and emerging challenges. Proceedings of the 2016 International Conference on Management of Data, 2201–2206. Open Google Scholar doi.org/10.5771/9783748929451
  128. Cialdini, R. B., & Goldstein, N. J. (2004). Social influence: Compliance and conformity. Annu. Rev. Psychol., 55(1), 591–621. Open Google Scholar doi.org/10.5771/9783748929451
  129. Citron, D. K., & Pasquale, F. (2014). The Scored Society: Due Process for Automated Predictions. WASHINGTON LAW REVIEW, 89(1), 1–33. Open Google Scholar doi.org/10.5771/9783748929451
  130. Clark, A., & Chalmers, D. (1998). The extended mind. Analysis, 58(1), 7–19. Open Google Scholar doi.org/10.5771/9783748929451
  131. Clark, J. (1886). Capital and its earnings. Publications of the American Economic Association, 3(2), 9–69. Open Google Scholar doi.org/10.5771/9783748929451
  132. Clarke, R. (2019). Principles and business processes for responsible AI. Computer Law & Security Review, 35(4), 410–422. Open Google Scholar doi.org/10.5771/9783748929451
  133. Cohen, A. J., & Harcourt, G. C. (2003). Retrospectives Whatever Happened to the Cambridge Capital Theory Controversies? Journal of Economic Perspectives, 17(1), 199–214. https://doi.org/10.1257/089533003321165010 Open Google Scholar doi.org/10.5771/9783748929451
  134. Cohen, G. A. (1978). Karl Marx’s Theory of History. Clarendon Press. https://press.princeton.edu/titles/320.html Open Google Scholar doi.org/10.5771/9783748929451
  135. Cohen, J. E. (2017). Law for the Platform Economy. UCDL Rev., 51, 133–204. Open Google Scholar doi.org/10.5771/9783748929451
  136. Cohen, Z. C., & Wild, W. (2021, April 28). Internal emails reveal Capitol security officials dismissed warnings about troubling social media posts before January 6 riot. CNN. https://www.cnn.com/2021/04/28/politics/capitol-security-emails-social-media-riot/index.html Open Google Scholar doi.org/10.5771/9783748929451
  137. Coleman, J. (1988). Social Capital in the Creation of Human Capital. American Journal of Sociology, 94(1). https://www.jstor.org/stable/2780243?seq=1#metadata_info_tab_contents Open Google Scholar doi.org/10.5771/9783748929451
  138. Collins, H. (1981). Stages in the Empirical Programme of Relativism. Social Studies of Science, 11 (1), 3–10. Open Google Scholar doi.org/10.5771/9783748929451
  139. Corrado, C. A., Hulten, C. R., & Sichel, D. E. (2006). Intangible Capital and Economic Growth. National Bureau of Economic Research Working Paper Series, 11948. https://doi.org/10.3386/w11948 Open Google Scholar doi.org/10.5771/9783748929451
  140. Crawford, K. (2021). The Atlas of AI. Yale University Press. Open Google Scholar doi.org/10.5771/9783748929451
  141. Creator of FacesOfTheRiot. (2021, February 23). Personal Communication [Personal communication]. Open Google Scholar doi.org/10.5771/9783748929451
  142. Danaher, J. (2016). The Threat of Algocracy: Reality, Resistance and Accommodation. Philosophy & Technology, 29(3), 245–268. https://doi.org/10.1007/s13347-015-0211-1 Open Google Scholar doi.org/10.5771/9783748929451
  143. Data Ethics Commission. (2019). Opinion of the Data Ethics Commission. Bundesministerium der Justiz und für Verbraucherschutz. https://www.bmjv.de/SharedDocs/Downloads/DE/Themen/Fokusthemen/Gutachten_DEK_EN.pdf?__blob=publicationFile&v=2 Open Google Scholar doi.org/10.5771/9783748929451
  144. Datta, A., Tschantz, M. C., & Datta, A. (2015). Automated experiments on ad privacy settings. Proceedings on Privacy Enhancing Technologies, 2015(1), 92–112. Open Google Scholar doi.org/10.5771/9783748929451
  145. Davis, K. (2012). Ethics of Big Data: Balancing risk and innovation. O’Reilly Media. Open Google Scholar doi.org/10.5771/9783748929451
  146. Dawson, M., & Foster, J. B. (1996). Virtual Capitalism: The Political Economy of the Information Highway. Monthly Review, 48(3), 40–58. Open Google Scholar doi.org/10.5771/9783748929451
  147. De Swarte, T., Boufous, O., & Escalle, P. (2019). Artificial intelligence, ethics and human values: The cases of military drones and companion robots. Artificial Life and Robotics, 24(3), 291–296. Open Google Scholar doi.org/10.5771/9783748929451
  148. De Visser, E. J., Monfort, S. S., McKendrick, R., Smith, M. A., McKnight, P. E., Krueger, F., & Parasuraman, R. (2016). Almost human: Anthropomorphism increases trust resilience in cognitive agents. Journal of Experimental Psychology: Applied, 22(3), 331–349. Open Google Scholar doi.org/10.5771/9783748929451
  149. DeepMind. (2020, November 30). AlphaFold: A solution to a 50-year-old grand challenge in biology. DeepMind Blog. /blog/article/alphafold-a-solution-to-a-50-year-old-grand-challenge-in-biology Open Google Scholar doi.org/10.5771/9783748929451
  150. del Rio, J. S., Moctezuma, D., Conde, C., de Diego, I. M., & Cabello, E. (2016). Automated border control e-gates and facial recognition systems. Computers & Security, 62, 49–72. Open Google Scholar doi.org/10.5771/9783748929451
  151. Delcker, J. (2018, September 13). Big Brother in Berlin. POLITICO. https://www.politico.eu/article/berlin-big-brother-state-surveillance-facial-recognition-technolog⁠y⁠/eng Open Google Scholar doi.org/10.5771/9783748929451
  152. Delcker, J. (2021, May 6). Opinion: Trump’s Facebook ban could have global impact. Deutsche Welle. https://www.dw.com/en/opinion-trumps-facebook-ban-could-have-global-impact/a-57442639 Open Google Scholar doi.org/10.5771/9783748929451
  153. Dencik, L., Hintz, A., & Cable, J. (2016). Towards data justice? The ambiguity of anti-surveillance resistance in political activism. Big Data & Society, 3(2), 1–12. Open Google Scholar doi.org/10.5771/9783748929451
  154. DeSanctis, G., & Poole, M. S. (1994). Capturing the complexity in advanced technology use: Adaptive structuration theory. Organization Science, 5(2), 121–147. Open Google Scholar doi.org/10.5771/9783748929451
  155. Desmedt, Y., Hou, S., & Quisquater, J.-J. (1998). Audio and optical cryptography. International Conference on the Theory and Application of Cryptology and Information Security, 392–404. Open Google Scholar doi.org/10.5771/9783748929451
  156. Diakopoulos, N., & Johnson, D. (2019). Anticipating and Addressing the Ethical Implications of Deepfakes in the Context of Elections (SSRN Scholarly Paper ID 3474183). Social Science Research Network. https://doi.org/10.2139/ssrn.347418⁠3eng Open Google Scholar doi.org/10.5771/9783748929451
  157. Digital News Initiative. (n.d.). Digital News Initiative. Retrieved January 8, 2021, from https://newsinitiative.withgoogle.com/ Open Google Scholar doi.org/10.5771/9783748929451
  158. Dignum, V. (2021). AI — the people and places that make, use and manage it. Nature, 593(7860), 499–500. https://doi.org/10.1038/d41586-021-01397-x Open Google Scholar doi.org/10.5771/9783748929451
  159. Dijkstra, J. J., Liebrand, W. B. G., & Timminga, E. (1998). Persuasiveness of expert systems. Behavior & Information Technology, 17(3), 155–163. Open Google Scholar doi.org/10.5771/9783748929451
  160. DiMaggio, P. (1979). Reproduction in Education, Society and Culture. By Pierre Bourdieu, Jean-Claude Passeron and Richard Nice; Outline of a Theory of Practice. By Pierre Bourdieu and Richard Nice. American Journal of Sociology, 84(6), 1460–1474. Open Google Scholar doi.org/10.5771/9783748929451
  161. DNI Final Impact Report. (2020). Digital News Initiative. https://newsinitiative.withgoogle.com/dnifund/documents/46/DNI_Fund_Impact_Report_v3.pdf Open Google Scholar doi.org/10.5771/9783748929451
  162. DNI Terms and Conditions. (n.d.). Digital News Initiative. Retrieved January 8, 2021, from https://newsinitiative.withgoogle.com/dnifund/documents/22/DNI-App-TC-02082018.pdf Open Google Scholar doi.org/10.5771/9783748929451
  163. Donde, J. (2017, September 21). Self-Driving Cars Will Kill People. Who Decides Who Dies? WIRED. https://www.wired.com/story/self-driving-cars-will-kill-people-who-decides-who-dies/ Open Google Scholar doi.org/10.5771/9783748929451
  164. Doyle, A. (2011). Revisiting the synopticon: Reconsidering Mathiesen’s ‘The Viewer Society’ in the age of Web 2.0. Theoretical Criminology, 15(3), 293–299. Open Google Scholar doi.org/10.5771/9783748929451
  165. Drucker, P. F. (1992, September). The New Society of Organizations. Harvard Business Review. https://hbr.org/1992/09/the-new-society-of-organizations Open Google Scholar doi.org/10.5771/9783748929451
  166. D’Souza, D. (2002). The virtue of prosperity: Finding values in an age of technoaffluence. Simon and Schuster. Open Google Scholar doi.org/10.5771/9783748929451
  167. Dudley, H., & Tarnoczy, T. H. (1950). The speaking machine of Wolfgang von Kempelen. The Journal of the Acoustical Society of America, 22(2), 151–166. Open Google Scholar doi.org/10.5771/9783748929451
  168. Durkin, E. (2019, May 30). New York tenants fight as landlords embrace facial recognition cameras. The Guardian. https://www.theguardian.com/cities/2019/may/29/new-york-facial-recognition-cameras-apartment-complex Open Google Scholar doi.org/10.5771/9783748929451
  169. Dzindolet, M. T., Peterson, S. A., Pomranky, R. A., Pierce, L. G., & Beck, H. P. (2003). The role of trust in automation reliance. International Journal of Human-Computer Studies, 58(6), 697–718. Open Google Scholar doi.org/10.5771/9783748929451
  170. Economist. (2017, May 6). Data is giving rise to a new economy. The Economist. https://www.economist.com/briefing/2017/05/06/data-is-giving-rise-to-a-new-economy Open Google Scholar doi.org/10.5771/9783748929451
  171. Eitel-Porter, R. (2021). Beyond the promise: Implementing ethical AI. AI and Ethics, 1(1), 73–80. Open Google Scholar doi.org/10.5771/9783748929451
  172. Ellul, J. (1904). The Technological Society. Vintage Book. Open Google Scholar doi.org/10.5771/9783748929451
  173. Epstein, R., & Robertson, R. (2015). The search engine manipulation effect (SEME) and its possible impact on the outcomes of elections. Proceedings of the National Academy of Sciences, 112, E4512–E4521. Open Google Scholar doi.org/10.5771/9783748929451
  174. Espinoza, J., & Murgia, M. (2020, February 11). EU backs away from call for blanket ban on facial recognition tech. Financial Times. https://www.ft.com/content/ff798944-4cc6-11ea-95a0-43d18ec715f5 Open Google Scholar doi.org/10.5771/9783748929451
  175. EU High-Level Expert Group on AI. (2019). Ethics guidelines for trustworthy AI. European Commission. https://ec.europa.eu/digital-single-market/en/news/ethics-guidelines-trustworthy-ai Open Google Scholar doi.org/10.5771/9783748929451
  176. Eubanks, V. (2018). Automating inequality: How high-tech tools profile, police, and punish the poor. St. Martin’s Press. Open Google Scholar doi.org/10.5771/9783748929451
  177. European Commission. (2021a). Announcement: Proposal for a Regulation laying down harmonised rules on artificial intelligence (Artificial Intelligence Act). https://ec.europa.eu/newsroom/dae/items/709090 Open Google Scholar doi.org/10.5771/9783748929451
  178. European Commission. (2021b). Proposal for a Regulation laying down harmonised rules on artificial intelligence (Artificial Intelligence Act). https://ec.europa.eu/newsroom/dae/items/709090 Open Google Scholar doi.org/10.5771/9783748929451
  179. Evans, M. P. (2007). Analysing Google rankings through search engine optimization data. Internet Research, 17(1), 21–37. Open Google Scholar doi.org/10.5771/9783748929451
  180. Evelyn, K. (2021, January 8). Capitol attack: The five people who died. The Guardian. http://www.theguardian.com/us-news/2021/jan/08/capitol-attack-police-officer-five-deaths Open Google Scholar doi.org/10.5771/9783748929451
  181. Eyal, N. (2014). Hooked: How to Build Habit-Forming Products (R. Hoover, Ed.). Portfolio. Open Google Scholar doi.org/10.5771/9783748929451
  182. Faces of the Riot. (2021). https://facesoftheriot.com/ Open Google Scholar doi.org/10.5771/9783748929451
  183. Fairfield, J. A. (2021). Runaway Technology: Can Law Keep Up? Cambridge University Press. Open Google Scholar doi.org/10.5771/9783748929451
  184. Fanta, A. (2018, September 26). The Publishers’ Patron. Tech Transparency Project. https://www.techtransparencyproject.org/articles/publishers-patron-how-googles-news-initiative-redefining-journalism Open Google Scholar doi.org/10.5771/9783748929451
  185. Faulkner, P., & Runde, J. (2012). On sociomateriality. Materiality and Organizing: Social Interaction in a Technological World, 49–66. Open Google Scholar doi.org/10.5771/9783748929451
  186. Faulkner, Philip, & Runde, J. (2011). The social, the material, and the ontology of non-material technological objects. European Group for Organizational Studies (EGOS) Colloquium, Gothenburg, 985, 4–8. Open Google Scholar doi.org/10.5771/9783748929451
  187. Federal Buerau of Investigation. (2021). FBI Most Wanted: Capitol Violence. Federal Bureau of Investigation. https://www.fbi.gov/wanted/capitol-violence Open Google Scholar doi.org/10.5771/9783748929451
  188. Federal Trade Commission. (2020, January 28). You Don’t Say: An FTC Workshop on Voice Cloning Technologies. https://www.ftc.gov/news-events/events-calendar/you-dont-say-ftc-workshop-voice-cloning-technologies Open Google Scholar doi.org/10.5771/9783748929451
  189. Ferry, G. (2015). Ada Lovelace: In search of “a calculus of the nervous system.” The Lancet, 386(10005), 1731. https://doi.org/10.1016/S0140-6736(15)00686-8 Open Google Scholar doi.org/10.5771/9783748929451
  190. Fetter, F. (1937). Capital. In E. R. A. Seligman & A. Johnson (Eds.), Encyclopedia Of The Social Sciences Vol-III (1937) (pp. 187–190). Macmillan. http://archive.org/details/in.ernet.dli.2015.14950 Open Google Scholar doi.org/10.5771/9783748929451
  191. Fischer, C. (1994). America Calling. University of California Press. https://www.ucpress.edu/book/9780520086470/america-calling Open Google Scholar doi.org/10.5771/9783748929451
  192. Fisher, I. (1904). Precedents of Defining Capital. Quarterly Journal of Economics, 18(3), 386–408. Open Google Scholar doi.org/10.5771/9783748929451
  193. Fisher, I. (1906). The nature of capital and income. Macmillan. http://archive.org/details/natureofcapitali00fishuoft Open Google Scholar doi.org/10.5771/9783748929451
  194. Fiss, P. C., & Zajac, E. J. (2006). The symbolic management of strategic change: Sensegiving via framing and decoupling. Academy of Management Journal, 49(6), 1173–1193. Open Google Scholar doi.org/10.5771/9783748929451
  195. Fletcher, J. (2018). Deepfakes, artificial intelligence, and some kind of dystopia: The new faces of online post-fact performance. Theatre Journal, 70(4), 455–471. Open Google Scholar doi.org/10.5771/9783748929451
  196. Floridi, L. (2014). The fourth revolution: How the infosphere is reshaping human reality. Oxford University Press. Open Google Scholar doi.org/10.5771/9783748929451
  197. Floridi, L. (2019). Establishing the rules for building trustworthy AI. Nature Machine Intelligence, 1(6), 261–262. Open Google Scholar doi.org/10.5771/9783748929451
  198. Floridi, L., & Chiriatti, M. (2020). GPT-3: Its nature, scope, limits, and consequences. Minds and Machines, 30(4), 681–694. Open Google Scholar doi.org/10.5771/9783748929451
  199. Forster, Y., Naujoks, F., & Neukum, A. (2017). Increasing anthropomorphism and trust in automated driving functions by adding speech output. 2017 IEEE Intelligent Vehicles Symposium (IV), 365–372. Open Google Scholar doi.org/10.5771/9783748929451
  200. Foucault, M. (1977). Discipline and punish: The birth of the prison. Penguin Books. Open Google Scholar doi.org/10.5771/9783748929451
  201. Foucault, M. (1984). On the genealogy of ethics: An overview of work in progress. The Foucault Reader, 340, 372. Open Google Scholar doi.org/10.5771/9783748929451
  202. Fouquet, H. (2019, October 3). France Set to Roll Out Nationwide Facial Recognition ID Program. Bloomberg. https://www.bloomberg.com/news/articles/2019-10-03/french-liberte-tested-by-nationwide-facial-recognition-id-plan Open Google Scholar doi.org/10.5771/9783748929451
  203. Franck, G. (1998). Die Ökonomie der Aufmerksamkeit. Carl Hanser. Open Google Scholar doi.org/10.5771/9783748929451
  204. Friedman, B., & Nissenbaum, H. (2017). Bias in computer systems. Routledge. Open Google Scholar doi.org/10.5771/9783748929451
  205. Fuchs, C. (2010). Labor in Informational Capitalism and on the Internet. The Information Society, 26(3), 179–196. Open Google Scholar doi.org/10.5771/9783748929451
  206. Fuchs, C. (2013). Capitalism or information society? The fundamental question of the present structure of society. European Journal of Social Theory, 16(4), 413–434. Open Google Scholar doi.org/10.5771/9783748929451
  207. Fuchs, C. (2019). Karl Marx in the age of big data capitalism. In D. Chandler & C. Fuchs (Eds.), Digital Objects, Digital Subjects: Interdisciplinary Perspectives on Capitalism, Labour and Politics in the Age of Big Data (pp. 53–71). University of Westminster Press. Open Google Scholar doi.org/10.5771/9783748929451
  208. Fuegi, J., & Francis, J. (2003). Lovelace & Babbage and the creation of the 1843’notes’. IEEE Annals of the History of Computing, 25(4), 16–26. Open Google Scholar doi.org/10.5771/9783748929451
  209. Fukuyama, F. (1995). Trust: The Social Virtues and the Creation of Prosperity. The Free Press. Open Google Scholar doi.org/10.5771/9783748929451
  210. Fukuyama, F. (2000). Social Capital and Civil Society (SSRN Scholarly Paper ID 879582). Social Science Research Network. https://papers.ssrn.com/abstract=879582 Open Google Scholar doi.org/10.5771/9783748929451
  211. Fussell, S. (2019, June 28). The Strange Politics of Facial Recognition. The Atlantic. https://www.theatlantic.com/technology/archive/2019/06/democrats-and-republicans-passing-soft-regulations/592558/ Open Google Scholar doi.org/10.5771/9783748929451
  212. Garrahan, M., & Khan, M. (2018, June 26). Google criticised for push against EU copyright reform. Financial Times. https://www.ft.com/content/a8031d7a-78a0-11e8-bc55-50daf11b720d Open Google Scholar doi.org/10.5771/9783748929451
  213. Garvie, C. (2019, May 16). Garbage In. Garbage Out. Face Recognition on Flawed Data. Flawed Face Data. https://www.flawedfacedata.com Open Google Scholar doi.org/10.5771/9783748929451
  214. Garvie, C., Bedoya, A. M., & Jonathan, F. (2016). The Perpetual Line-Up: Unregulated police face recognition in America. Georgetown Law Center on Privacy & Technology. https://www.perpetuallineup.org/ Open Google Scholar doi.org/10.5771/9783748929451
  215. Gasser, U. (2017, June 26). AI and the Law: Setting the Stage. Medium. https://medium.com/berkman-klein-center/ai-and-the-law-setting-the-stage-48516fda1b11 Open Google Scholar doi.org/10.5771/9783748929451
  216. Gates, K. A. (2011). Our biometric future: Facial recognition technology and the culture of surveillance (Vol. 2). NYU Press. Open Google Scholar doi.org/10.5771/9783748929451
  217. German Criminal Code (Strafgesetzbuch – StGB). (n.d.). Retrieved January 28, 2021, from https://www.gesetze-im-internet.de/englisch_stgb/englisch_stgb.html#p⁠1⁠8⁠4⁠2 Open Google Scholar doi.org/10.5771/9783748929451
  218. Gholipour, B. (n.d.). New AI Tech Can Mimic Any Voice. Scientific American. Retrieved January 14, 2021, from https://www.scientificamerican.com/article/new-ai-tech-can-mimic-any-voice/ Open Google Scholar doi.org/10.5771/9783748929451
  219. Gibson, W. (2010, August 31). Opinion | Google’s Earth. The New York Times. https://www.nytimes.com/2010/09/01/opinion/01gibson.html Open Google Scholar doi.org/10.5771/9783748929451
  220. Giddens, A. (1984). The Constitution of Society. Wiley. Open Google Scholar doi.org/10.5771/9783748929451
  221. Gillespie, T. (2014). The Relevance of Algorithms. In T. Gillespie, P. J. Boczkowski, & K. A. Foot (Eds.), Media Technologies (pp. 167–194). The MIT Press. https://doi.org/10.7551/mitpress/9780262525374.003.0009 Open Google Scholar doi.org/10.5771/9783748929451
  222. Gioia, D. A., & Chittipeddi, K. (1991). Sensemaking and sensegiving in strategic change initiation. Strategic Management Journal, 12(6), 433–448. Open Google Scholar doi.org/10.5771/9783748929451
  223. Glaser, B. G., & Strauss, A. L. (2017). Discovery of grounded theory: Strategies for qualitative research. Routledge. Open Google Scholar doi.org/10.5771/9783748929451
  224. Goguen, J. (1997). Towards a social, ethical theory of information. In G. C. Bowker, S. L. Star, W. Turner, & L. Gasser (Eds.), Social science, technical systems and cooperative work: Beyond the great divide (pp. 27–56). Psychology Press. Open Google Scholar doi.org/10.5771/9783748929451
  225. Gong, L. (2008). How social is social responses to computers? The function of the degree of anthropomorphism in computer representations. Computers in Human Behavior, 24(4), 1494–1509. https://doi.org/10.1016/j.chb.2007.05.007 Open Google Scholar doi.org/10.5771/9783748929451
  226. Goodfellow, I. J., Pouget-Abadie, J., Mirza, M., Xu, B., Warde-Farley, D., Ozair, S., Courville, A., & Bengio, Y. (2014). Generative adversarial networks. ArXiv Preprint ArXiv:1406.2661. Open Google Scholar doi.org/10.5771/9783748929451
  227. Graham, S., & Wood, D. (2003). Digitizing Surveillance: Categorization, Space, Inequality. Critical Social Policy, 23(2), 227–248. https://doi.org/10.1177/0261018303023002006 Open Google Scholar doi.org/10.5771/9783748929451
  228. Gray, M. (2003). Urban Surveillance and Panopticism: Will we recognize the facial recognition society? Surveillance & Society, 1(3), 314–330. https://doi.org/10.24908/ss.v1i3.3343 Open Google Scholar doi.org/10.5771/9783748929451
  229. Greenberg, A. (2021, January 20). This Site Published Every Face From Parler’s Capitol Riot Videos. Wired. https://www.wired.com/story/faces-of-the-riot-capitol-insurrection-facial-recognition/ Open Google Scholar doi.org/10.5771/9783748929451
  230. Greene, J. (2020, June 11). Microsoft won’t sell police its facial-recognition technology, following similar moves by Amazon and IBM. Washington Post. https://www.washingtonpost.com/technology/2020/06/11/microsoft-facial-recognition/ Open Google Scholar doi.org/10.5771/9783748929451
  231. Greig, J. (2021, May 26). One year after Amazon, Microsoft and IBM ended facial recognition sales to police, smaller players fill void. ZDNet. https://www.zdnet.com/article/one-year-after-amazon-microsoft-and-ibm-ended-facial-recognition-sales-to-police-smaller-players-fill-void/ Open Google Scholar doi.org/10.5771/9783748929451
  232. Grevatt, N. (2018). Google’s Duplex and Deception through Power and Dignity [Final Paper, University of Virginia]. https://aipavilion.github.io/docs/papers/duplex.p⁠d⁠feng Open Google Scholar doi.org/10.5771/9783748929451
  233. Greve, J. (2021, March 2). FBI chief calls Capitol attack “domestic terrorism” and defends US intelligence. The Guardian. http://www.theguardian.com/us-news/2021/mar/02/fbi-christopher-wray-capitol-attack-domestic-terrorism Open Google Scholar doi.org/10.5771/9783748929451
  234. Grimshaw, M. (2009). The audio Uncanny Valley: Sound, fear and the horror game. Audio Mostly, 21–26. Open Google Scholar doi.org/10.5771/9783748929451
  235. Grossmann, M. (1972). On the concept of healthcapital and the demand for health. Journal of Political Economy, 80(2), 223–255. Open Google Scholar doi.org/10.5771/9783748929451
  236. Groth, O., Nitzberg, M. J., & Russell, S. (2019, August 15). AI Algorithms Need FDA-Style Drug Trials. Wired. https://www.wired.com/story/ai-algorithms-need-drug-trials/ Open Google Scholar doi.org/10.5771/9783748929451
  237. Habermas, J. (1970). Technology and science as “ideology.” In Toward a Rational Society (pp. 81–122). Beacon. Open Google Scholar doi.org/10.5771/9783748929451
  238. Haenlein, M., & Kaplan, A. (2019). A brief history of artificial intelligence: On the past, present, and future of artificial intelligence. California Management Review, 61(4), 5–14. Open Google Scholar doi.org/10.5771/9783748929451
  239. Haggerty, K., & Ericson, R. (2000). The surveillant assemblage. British Journal of Sociology, 51(4), 605–622. https://doi.org/10.1080/00071310020015280 Open Google Scholar doi.org/10.5771/9783748929451
  240. Hakim, C. (2010). Erotic capital. European Sociological Review, 26(5), 499–518. Open Google Scholar doi.org/10.5771/9783748929451
  241. Halpern, S. (2021, May 2). Facebook and the Normalization of Deviance. The New Yorker. https://www.newyorker.com/news/daily-comment/facebook-and-the-normalization-of-deviance Open Google Scholar doi.org/10.5771/9783748929451
  242. Hamann, S. (2016, July 18). Kriminalität: So will die Polizei Einbrüche in NRW voraussagen. RP ONLINE. http://www.rp-online.de/nrw/panorama/predictive-policing-so-sagt-die-polizei-einbrueche-in-nrw-voraus-aid-1.6097807 Open Google Scholar doi.org/10.5771/9783748929451
  243. Hamm, J., Kohler, C. G., Gur, R. C., & Verma, R. (2011). Automated facial action coding system for dynamic analysis of facial expressions in neuropsychiatric disorders. Journal of Neuroscience Methods, 200(2), 237–256. Open Google Scholar doi.org/10.5771/9783748929451
  244. Hanifan, L. J. (1916). The rural school community center. Annals of the American Academy of Political and Social Science, 67, 130–138. Open Google Scholar doi.org/10.5771/9783748929451
  245. Hansen, A. H. (1921). The Technological Interpretation of History. The Quarterly Journal of Economics, 36(1), 72–83. https://doi.org/10.2307/1883779 Open Google Scholar doi.org/10.5771/9783748929451
  246. Hao, K. (2020, August 14). A college kid created a fake, AI-generated blog. It reached #1 on Hacker News. MIT Technology Review. https://www.technologyreview.com/2020/08/14/1006780/ai-gpt-3-fake-blog-reached-top-of-hacker-news/ Open Google Scholar doi.org/10.5771/9783748929451
  247. Hao, K. (2021, April 13). Big Tech’s guide to talking about AI ethics. MIT Technology Review. https://www.technologyreview.com/2021/04/13/1022568/big-tech-ai-ethics-guide/ Open Google Scholar doi.org/10.5771/9783748929451
  248. Harari, Y. N. (2016). Homo Deus: A brief history of tomorrow. Random House. Open Google Scholar doi.org/10.5771/9783748929451
  249. Harwell, D. (2019a, July 7). FBI, ICE find state driver’s license photos are a gold mine for facial-recognition searches. Washington Post. https://www.washingtonpost.com/technology/2019/07/07/fbi-ice-find-state-drivers-license-photos-are-gold-mine-facial-recognition-searches/ Open Google Scholar doi.org/10.5771/9783748929451
  250. Harwell, D. (2019b, September 5). An artificial-intelligence first: Voice-mimicking software reportedly used in a major theft. Washington Post. https://www.washingtonpost.com/technology/2019/09/04/an-artificial-intelligence-first-voice-mimicking-software-reportedly-used-major-theft/ Open Google Scholar doi.org/10.5771/9783748929451
  251. Haskel, J., & Westlake, S. (2018). Capitalism without capital: The rise of the intangible economy. Princeton University Press. Open Google Scholar doi.org/10.5771/9783748929451
  252. Haugeland, J. (1989). Artificial intelligence: The very idea. MIT Press. Open Google Scholar doi.org/10.5771/9783748929451
  253. Hayles, N. K. (2008). How we became posthuman: Virtual bodies in cybernetics, literature, and informatics. University of Chicago Press. Open Google Scholar doi.org/10.5771/9783748929451
  254. Healy, J., Nicholson, D., & Pekarek, A. (2017). Should we take the gig economy seriously? Labour & Industry: A Journal of the Social and Economic Relations of Work, 27(3), 232–248. Open Google Scholar doi.org/10.5771/9783748929451
  255. Heilbroner, R. L. (1967). Do Machines Make History? Technology and Culture, 8(3), 335–345. JSTOR. https://doi.org/10.2307/3101719 Open Google Scholar doi.org/10.5771/9783748929451
  256. Hern, A. (2018, May 11). Google’s “deceitful” AI assistant to identify itself as a robot during calls. The Guardian. http://www.theguardian.com/technology/2018/may/11/google-duplex-ai-identify-itself-as-robot-during-calls Open Google Scholar doi.org/10.5771/9783748929451
  257. Hian, L. B., Chuan, S. L., Trevor, T. M. K., & Detenber, B. H. (2004). Getting to know you: Exploring the development of relational intimacy in computer-mediated communication. Journal of Computer-Mediated Communication, 9(3), 9–24. Open Google Scholar doi.org/10.5771/9783748929451
  258. Hibbard, B. (2014). Ethical artificial intelligence. ArXiv Preprint ArXiv:1411.1373. Open Google Scholar doi.org/10.5771/9783748929451
  259. Hill, K. (2020a, January 18). The Secretive Company That Might End Privacy as We Know It. The New York Times. https://www.nytimes.com/2020/01/18/technology/clearview-privacy-facial-recognition.html Open Google Scholar doi.org/10.5771/9783748929451
  260. Hill, K. (2020b, March 5). Before Clearview Became a Police Tool, It Was a Secret Plaything of the Rich. The New York Times. https://www.nytimes.com/2020/03/05/technology/clearview-investors.html Open Google Scholar doi.org/10.5771/9783748929451
  261. Hill, K. (2020c, June 24). Wrongfully Accused by an Algorithm. The New York Times. https://www.nytimes.com/2020/06/24/technology/facial-recognition-arrest.html Open Google Scholar doi.org/10.5771/9783748929451
  262. Hill, K. (2020d, December 29). Another Arrest, and Jail Time, Due to a Bad Facial Recognition Match. The New York Times. https://www.nytimes.com/2020/12/29/technology/facial-recognition-misidentify-jail.html Open Google Scholar doi.org/10.5771/9783748929451
  263. Hill, K. (2021a, February 3). Clearview AI’s Facial Recognition App Called Illegal in Canada. The New York Times. https://www.nytimes.com/2021/02/03/technology/clearview-ai-illegal-canada.html Open Google Scholar doi.org/10.5771/9783748929451
  264. Hill, K. (2021b, February 27). How One State Managed to Actually Write Rules on Facial Recognition. The New York Times. https://www.nytimes.com/2021/02/27/technology/Massachusetts-facial-recognition-rules.html Open Google Scholar doi.org/10.5771/9783748929451
  265. Hill, K. (2021c, March 18). What Happens When Our Faces Are Tracked Everywhere We Go? The New York Times. https://www.nytimes.com/interactive/2021/03/18/magazine/facial-recognition-clearview-ai.html Open Google Scholar doi.org/10.5771/9783748929451
  266. Hill, K. (2021d, March 18). What We Learned About Clearview AI and Its Secret ‘Co-Founder.’ The New York Times. https://www.nytimes.com/2021/03/18/technology/clearview-facial-recognition-ai.html Open Google Scholar doi.org/10.5771/9783748929451
  267. Hines, D., Saris, R. N., & Throckmorton-Belzer, L. (2002). Pluralistic ignorance and health risk behaviors: Do college students misperceive social approval for risky behaviors on campus and in media? Journal of Applied Social Psychology, 32(12), 2621–2640. Open Google Scholar doi.org/10.5771/9783748929451
  268. Hirsh, R. F., & Sovacool, B. K. (2006). Technological systems and momentum change: American electric utilities, restructuring, and distributed generation. The Journal of Technology Studies, 72–85. https://doi.org/10.21061/jots.v32i2.a.2 Open Google Scholar doi.org/10.5771/9783748929451
  269. Hjelmaas, E., & Low, B. K. (2001). Face detection: A survey. Computer Vision and Image Understanding, 83(3), 236–274. Open Google Scholar doi.org/10.5771/9783748929451
  270. Hodgson, G. M. (2014). What is capital? Economists and sociologists have changed its meaning: should it be changed back? Cambridge Journal of Economics, 38(5), 1063–1086. https://doi.org/10.1093/cje/beu013 Open Google Scholar doi.org/10.5771/9783748929451
  271. Hoffmann, E. T. A. (1967). The Sandman. In R. Robertson (Trans.), The Golden Pot and Other Tales (pp. 85–118). Oxford University Press. Open Google Scholar doi.org/10.5771/9783748929451
  272. Hollan, J., Hutchins, E., & Kirsh, D. (2000). Distributed cognition: Toward a new foundation for human-computer interaction research. ACM Transactions on Computer-Human Interaction (TOCHI), 7(2), 174–196. Open Google Scholar doi.org/10.5771/9783748929451
  273. Holmes, D. (2001). From Iron Gaze to Nursing Care: Mental Health Nursing in the Era of Panopticism. Journal of Psychiatric and Mental Health Nursing, 8(1), 7–15. Open Google Scholar doi.org/10.5771/9783748929451
  274. Huang, T., Xiong, Z., & Zhang, Z. (2005). Face recognition applications. In S. Z. Li & A. K. Jain (Eds.), Handbook of Face Recognition (pp. 371–390). Springer. Open Google Scholar doi.org/10.5771/9783748929451
  275. Huber, B. M., & Comstock, M. (2017, July 27). ESG Reports and Ratings: What They Are, Why They Matter. The Harvard Law School Forum on Corporate Governance. https://corpgov.law.harvard.edu/2017/07/27/esg-reports-and-ratings-what-they-are-why-they-matter/ Open Google Scholar doi.org/10.5771/9783748929451
  276. Huff, C., & Tingley, D. (2015). “Who are these people?” Evaluating the demographic characteristics and political preferences of MTurk survey respondents. Research & Politics, 2(3), 1–15. https://doi.org/10.1177/2053168015604648 Open Google Scholar doi.org/10.5771/9783748929451
  277. Hughes, T. (1983). Networks of Power: Electrification in Western Society, 1880-1930. The John Hopkins University Press. Open Google Scholar doi.org/10.5771/9783748929451
  278. Hughes, T. (1986). The Seamless Web: Technology, Science, Etcetera, Etcetera. Social Studies of Science, 16(2), 281–292. Open Google Scholar doi.org/10.5771/9783748929451
  279. Hughes, T. (1987). The Evolution of Large Technological Systems. In W. E. Bijker, T. Hughes, & T. Pinch (Eds.), The Social Construction of Technological Systems (pp. 50–82). MIT Press. Open Google Scholar doi.org/10.5771/9783748929451
  280. Hughes, T. (1989). American Genesis: A century of invention and technological enthusiasm, 1870-1970. University of Chicago Press. Open Google Scholar doi.org/10.5771/9783748929451
  281. Hultin, L. (2019). On becoming a sociomaterial researcher: Exploring epistemological practices grounded in a relational, performative ontology. Information and Organization, 29(2), 91–104. https://doi.org/10.1016/j.infoandorg.2019.04.004 Open Google Scholar doi.org/10.5771/9783748929451
  282. Hutson, M. (2021, February 15). Who Should Stop Unethical A.I.? The New Yorker. https://www.newyorker.com/tech/annals-of-technology/who-should-stop-unethical-ai Open Google Scholar doi.org/10.5771/9783748929451
  283. Hvistendahl, M. (2016, September 27). Can ‘predictive policing’ prevent crime before it happens? Science. http://www.sciencemag.org/news/2016/09/can-predictive-policing-prevent-crime-it-happens Open Google Scholar doi.org/10.5771/9783748929451
  284. Icelandic Institute for Intelligent Machines. (2015). Ethics Policy. https://www.iiim.is/ethics-policy/ Open Google Scholar doi.org/10.5771/9783748929451
  285. International Network of Privacy Law Professionals. (2020, October 26). Facial recognition technologies from a Swedish data protection perspective. INPLP Latest News. https://inplp.com/latest-news/article/facial-recognition-technologies-from-a-swedish-data-protection-perspective/ Open Google Scholar doi.org/10.5771/9783748929451
  286. International Standards Organization. (2015). Societal security—Business continuity management systems—Guidelines for business impact analysis (ISO Standard No ISO/TS 22317). International Standards Organization. https://www.iso.org/obp/ui/#iso:std:iso:ts:22317:ed-1:v1:en Open Google Scholar doi.org/10.5771/9783748929451
  287. International Standards Organization. (2018). Risk management—Guidelines (ISO Standard No. 31000:2018). International Standards Organization. https://www.iso.org/obp/ui/#iso:std:iso:31000:en Open Google Scholar doi.org/10.5771/9783748929451
  288. International Standards Organization. (2020). Guidance for the governance of organizations (ISO Standard No. ISO 37000). International Standards Organization. https://www.iso.org/cms/render/live/en/sites/isoorg/contents/data/standard/06/50/65036.html Open Google Scholar doi.org/10.5771/9783748929451
  289. Introna, L. D., & Nissenbaum, H. (2000). Shaping the Web: Why the politics of search engines matters. The Information Society, 16(3), 169–185. Open Google Scholar doi.org/10.5771/9783748929451
  290. Introna, L. D., & Nissenbaum, H. (2010). Facial Recognition Technology: A survey of policy and implementation issues. NYU Center for Catastrophe Preparedness and Response. https://nissenbaum.tech.cornell.edu/papers/facial_recognition_report.pdf Open Google Scholar doi.org/10.5771/9783748929451
  291. Introna, L., & Wood, D. (2004). Picturing algorithmic surveillance: The politics of facial recognition systems. Surveillance & Society, 2(2/3), 177–198. Open Google Scholar doi.org/10.5771/9783748929451
  292. Jackman, T. (2021, January 28). Police union says 140 officers injured in Capitol riot. Washington Post. https://www.washingtonpost.com/local/public-safety/police-union-says-140-officers-injured-in-capitol-riot/2021/01/27/60743642-60e2-11eb-9430-e7c77b5b0297_story.html Open Google Scholar doi.org/10.5771/9783748929451
  293. Jaiman, A. (2020, August 27). Debating the ethics of deepfakes. Observer Research Foundation. https://www.orfonline.org/expert-speak/debating-the-ethics-of-deepfakes/ Open Google Scholar doi.org/10.5771/9783748929451
  294. Jasanoff, S., & Kim, S.-H. (2009). Containing the Atom: Sociotechnical Imaginaries and Nuclear Power in the United States and South Korea. Minerva, 47(2), 119–146. Open Google Scholar doi.org/10.5771/9783748929451
  295. Jennings, R. (2021, January 14). Scraped Parler data is truly revealing. Tech Beacon. https://techbeacon.com/security/scraped-parler-data-reveals-countless-capitol-perpseng Open Google Scholar doi.org/10.5771/9783748929451
  296. Joerges, B. (1988). Large Technical Systems: Concepts and issues. In R. Mayntz & T. P. Hughes (Eds.), The Development of Large Technical Systems (pp. 9–36). Campus. Open Google Scholar doi.org/10.5771/9783748929451
  297. Johnson. (2020, June 25). Congress introduces bill that bans facial recognition use by federal government. VentureBeat. https://venturebeat.com/2020/06/25/congress-introduces-bill-that-bans-facial-recognition-use-by-federal-government/ Open Google Scholar doi.org/10.5771/9783748929451
  298. Johnson, C. (2015, November 16). From Idea to Execution: Spotify’s Discover Weekly [PowerPoint slides]. https://www.slideshare.net/MrChrisJohnson/from-idea-to-execution-spotifys-discover-weekly Open Google Scholar doi.org/10.5771/9783748929451
  299. Johnson, D., & Wiles, J. (2003). Effective affective user interface design in games. Ergonomics, 46(13–14), 1332–1345. Open Google Scholar doi.org/10.5771/9783748929451
  300. Jones, A., & Jenkins, K. (2008). Indigenous Discourse and “the Material” A Post-interpretivist Argument. International Review of Qualitative Research, 1(2), 125–144. Open Google Scholar doi.org/10.5771/9783748929451
  301. Jumper, J., Evans, R., Pritzel, A., Green, T., Figurnov, M., Tunyasuvunakool, K., Ronneberger, O., Bates, R., Zidek, A., & Bridgland, A. (2020). High accuracy protein structure prediction using deep learning. In Critical Assessment of Techniques for Protein Structure Prediction (pp. 22–24). Abstract Book. https://predictioncenter.org/casp14/doc/CASP14_Abstracts.pdf Open Google Scholar doi.org/10.5771/9783748929451
  302. Kallinikos, J. (2010). Governing through technology: Information artefacts and social practice. Springer. Open Google Scholar doi.org/10.5771/9783748929451
  303. Kaplan, R. S. (2009). Conceptual foundations of the balanced scorecard. In A. G. Hopwood, C. S. Chapman, & M. D. Shields (Eds.), Handbooks of management accounting research (Vol. 3, pp. 1253–1269). Elsevier Science. Open Google Scholar doi.org/10.5771/9783748929451
  304. Kaplan, R. S., & Norton, D. P. (1998). Putting the balanced scorecard to work. The Economic Impact of Knowledge, 27(4), 315–324. Open Google Scholar doi.org/10.5771/9783748929451
  305. Karapapa, S., & Borghi, M. (2015). Search engine liability for autocomplete suggestions: Personality, privacy and the power of the algorithm. International Journal of Law and Information Technology, 23(3), 261–289. Open Google Scholar doi.org/10.5771/9783748929451
  306. Karras, T., Laine, S., & Aila, T. (2019). A style-based generator architecture for generative adversarial networks. Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 4401–4410. Open Google Scholar doi.org/10.5771/9783748929451
  307. Karras, T., Laine, S., Aittala, M., Hellsten, J., Lehtinen, J., & Aila, T. (2020). Analyzing and improving the image quality of stylegan. Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 8110–8119. Open Google Scholar doi.org/10.5771/9783748929451
  308. Kasy, M., & Abebe, R. (2021). Fairness, equality, and power in algorithmic decision-making. Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency, 576–586. Open Google Scholar doi.org/10.5771/9783748929451
  309. Katz, M. L., & Shapiro, C. (1985). Network externalities, competition, and compatibility. The American Economic Review, 75(3), 424–440. Open Google Scholar doi.org/10.5771/9783748929451
  310. Katz, M. L., & Shapiro, C. (1994). Systems competition and network effects. Journal of Economic Perspectives, 8(2), 93–115. Open Google Scholar doi.org/10.5771/9783748929451
  311. Kauflin, J., Gara, A., & Klebnikov, S. (2020, August 19). The Inside Story Of Robinhood’s Billionaire Founders, Option Kid Cowboys And The Wall Street Sharks That Feed On Them. Forbes. https://www.forbes.com/sites/jeffkauflin/2020/08/19/the-inside-story-of-robinhoods-billionaire-founders-option-kid-cowboys-and-the-wall-street-sharks-that-feed-on-them/ Open Google Scholar doi.org/10.5771/9783748929451
  312. Kember, S. (2003). Cyberfeminism and Artificial Life. FEMINIST THEORY, 4(3), 369–370. Open Google Scholar doi.org/10.5771/9783748929451
  313. Kenney, M., & Zysman, J. (2016). The rise of the platform economy. Issues in Science and Technology, 32(3), 61. Open Google Scholar doi.org/10.5771/9783748929451
  314. Kharpal, A. (2020, January 28). Big Tech’s calls for more regulation offers a chance for them to increase their power. CNBC. https://www.cnbc.com/2020/01/28/big-techs-calls-for-ai-regulation-could-lead-to-more-power.html Open Google Scholar doi.org/10.5771/9783748929451
  315. Klare, B. F., Burge, M. J., Klontz, J. C., Bruegge, R. W. V., & Jain, A. K. (2012). Face recognition performance: Role of demographic information. IEEE Transactions on Information Forensics and Security, 7(6), 1789–1801. Open Google Scholar doi.org/10.5771/9783748929451
  316. Klein, S., & Kao, J. (2021, January 17). Why We Published More Than 500 Videos Taken by Parler Users of the Capitol Riot. ProPublica. https://www.propublica.org/article/why-we-published-parler-users-videos-capitol-attack?token=T9DMO_4oncWnPFNlubLC6K7JtywmqAu3 Open Google Scholar doi.org/10.5771/9783748929451
  317. Kline, R. R. (2015). Technological Determinism. In International Encyclopedia of the Social & Behavioral Sciences (pp. 109–112). Elsevier. https://doi.org/10.1016/B978-0-08-097086-8.85034-5 Open Google Scholar doi.org/10.5771/9783748929451
  318. Knight, W. (2017a). The dark secret at the heart of al. Technology Review, 120(3), 54–61. Open Google Scholar doi.org/10.5771/9783748929451
  319. Knight, W. (2017b, November 4). The Dark Secret at the Heart of AI. MIT Technology Review. https://www.technologyreview.com/s/604087/the-dark-secret-at-the-heart-of-ai/ Open Google Scholar doi.org/10.5771/9783748929451
  320. Korolova, A. (2010). Privacy violations using microtargeted ads: A case study. 2010 IEEE International Conference on Data Mining Workshops, 474–482. Open Google Scholar doi.org/10.5771/9783748929451
  321. Kostka, G. (2019). China’s social credit systems and public opinion: Explaining high levels of approval. New Media & Society, 21(7), 1565–1593. Open Google Scholar doi.org/10.5771/9783748929451
  322. Kostka, G., Steinacker, L., & Meckel, M. (2021a). Between security and convenience: Facial recognition technology in the eyes of citizens in China, Germany, the United Kingdom, and the United States. Public Understanding of Science, 21(5), 556–572. Open Google Scholar doi.org/10.5771/9783748929451
  323. Kostka, G., Steinacker, L., & Meckel, M. (2021b). Between security and convenience: Facial recognition technology in the eyes of citizens in China, Germany, the United Kingdom, and the United States. Public Understanding of Science, 09636625211001555. https://doi.org/10.1177/09636625211001555 Open Google Scholar doi.org/10.5771/9783748929451
  324. Kotler, P. (2010). The prosumer movement. In Prosumer Revisited (pp. 51–60). Springer. Open Google Scholar doi.org/10.5771/9783748929451
  325. Kranzberg, M. (1986). Technology and History: “Kranzberg’s Laws.” Technology and Culture, 27(3), 544–560. https://doi.org/10.2307/3105385 Open Google Scholar doi.org/10.5771/9783748929451
  326. Krol, K., Parkin, S., & Sasse, M. A. (2016). “ I don’t like putting my face on the Internet!”: An acceptance study of face biometrics as a CAPTCHA replacement. 2016 IEEE International Conference on Identity, Security and Behavior Analysis (ISBA), 1–7. Open Google Scholar doi.org/10.5771/9783748929451
  327. Kurwa, R. (2019). Building the Digitally Gated Community: The Case of Nextdoor. Surveillance & Society, 17(1/2), 111–117. Open Google Scholar doi.org/10.5771/9783748929451
  328. Kurzweil, R., Richter, R., Kurzweil, R., & Schneider, M. L. (1990). The age of intelligent machines (Vol. 579). MIT Press. Open Google Scholar doi.org/10.5771/9783748929451
  329. Kuss, P., & Leenes, R. (2020). The Ghost in the Machine-Emotionally Intelligent Conversational Agents and the Failure to Regulate’Deception by Design’. SCRIPTed, 17(2), 320–358. Open Google Scholar doi.org/10.5771/9783748929451
  330. Lambert, T. A., Kahn, A. S., & Apple, K. J. (2003). Pluralistic ignorance and hooking up. Journal of Sex Research, 40(2), 129–133. Open Google Scholar doi.org/10.5771/9783748929451
  331. Lambrecht, A., & Tucker, C. (2019). Algorithmic Bias? An Empirical Study of Apparent Gender-Based Discrimination in the Display of STEM Career Ads. Management Science, 65(7), 2966–2981. Open Google Scholar doi.org/10.5771/9783748929451
  332. Latour, B. (1990). Technology is Society Made Durable. The Sociological Review, 38(1_suppl), 103–131. Open Google Scholar doi.org/10.5771/9783748929451
  333. Latour, B. (2017). On Actor-Network Theory. A Few Clarifications, Plus More Than a Few Complications. Philosophical Literary Journal Logos, 27(1), 173–197. https://doi.org/10.22394/0869-5377-2017-1-173-197 Open Google Scholar doi.org/10.5771/9783748929451
  334. Lattimore, R., & Baskin, L. (2011). The Iliad of Homer. University of Chicago Press. Open Google Scholar doi.org/10.5771/9783748929451
  335. Law, J. (1987). Technology and Heterogeneous Engineering: The Case of Portuguese Expansion. In The Social Construction of Technological Systems (pp. 111–134). MIT Press. Open Google Scholar doi.org/10.5771/9783748929451
  336. Law, J. (2001). Notes on the Theory of the Actor Network: Ordering, Strategy and Heterogeneity. In Organizational Studies: Critical Perspectives on Business and Management. Routledge. Open Google Scholar doi.org/10.5771/9783748929451
  337. Leavy, S. (2018). Gender bias in artificial intelligence: The need for diversity and gender theory in machine learning. Proceedings of the 1st International Workshop on Gender Equality in Software Engineering, 14–16. Open Google Scholar doi.org/10.5771/9783748929451
  338. Lecher, C. (2019, July 10). Congress faces ‘hard questions’ on facial recognition as activists push for ban. The Verge. https://www.theverge.com/2019/7/10/20688932/congress-facial-recognition-hearing-ban Open Google Scholar doi.org/10.5771/9783748929451
  339. Lee, E. A. (2017). Plato and the Nerd: The Creative Partnership of Humans and Technology. MIT Press. Open Google Scholar doi.org/10.5771/9783748929451
  340. Lee, K.-F. (2017, June 24). The Real Threat of Artificial Intelligence. The New York Times. https://www.nytimes.com/2017/06/24/opinion/sunday/artificial-intelligence-economic-inequality.html Open Google Scholar doi.org/10.5771/9783748929451
  341. Leibold, J. (2020). Surveillance in China’s Xinjiang region: Ethnic sorting, coercion, and inducement. Journal of Contemporary China, 29(121), 46–60. Open Google Scholar doi.org/10.5771/9783748929451
  342. Lenglet, M. (2011). Conflicting Codes and Codings: How Algorithmic Trading Is Reshaping Financial Regulation. Theory, Culture & Society, 28(6), 44–66. https://doi.org/10.1177/0263276411417444 Open Google Scholar doi.org/10.5771/9783748929451
  343. Leonardi, P. M. (2007). Activating the informational capabilities of information technology for organizational change. Organization Science, 18(5), 813–831. Open Google Scholar doi.org/10.5771/9783748929451
  344. Leonardi, P. M. (2011). When flexible routines meet flexible technologies: Affordance, constraint, and the imbrication of human and material agencies. MIS Quarterly, 35(1), 147–167. Open Google Scholar doi.org/10.5771/9783748929451
  345. Leonardi, P. M. (2012). Materiality, sociomateriality, and socio-technical systems: What do these terms mean? How are they different? Do we need them. In P. M. Leonardi, B. A. Nardi, & J. Kallinikos (Eds.), Materiality and Organizing: Social Interaction in a Technological World (pp. 25–48). Oxford University Press. https://ssrn.com/abstract=2129878 or http://dx.doi.org/10.2139/ssrn.2129878 Open Google Scholar doi.org/10.5771/9783748929451
  346. Leonardi, P. M. (2013). Theoretical foundations for the study of sociomateriality. Information and Organization, 23(2), 59–76. Open Google Scholar doi.org/10.5771/9783748929451
  347. Leong, N., & Belzer, A. (2016). The new public accommodations: Race discrimination in the platform economy. Geo. LJ, 105, 1271. Open Google Scholar doi.org/10.5771/9783748929451
  348. Leporini, B., Buzzi, M. C., & Buzzi, M. (2012). Interacting with mobile devices via VoiceOver: Usability and accessibility issues. Proceedings of the 24th Australian Computer-Human Interaction Conference, 339–348. Open Google Scholar doi.org/10.5771/9783748929451
  349. Lessig, L. (1999). Code: And Other Laws of Cyberspace. Basic Books. Open Google Scholar doi.org/10.5771/9783748929451
  350. Lessig, L. (2006). Code 2.0. Basic Books. http://codev2.cc/download+remix/Lessig-Codev2.pdf Open Google Scholar doi.org/10.5771/9783748929451
  351. Lev, B. (2004). Sharpening the intangibles edge. Harvard Business Review, 109–116. Open Google Scholar doi.org/10.5771/9783748929451
  352. Levy, S. (2010, December 27). The AI Revolution Is On. Wired. https://www.wired.com/2010/12/ff-ai-essay-airevolution/ Open Google Scholar doi.org/10.5771/9783748929451
  353. Li, J. (2019, October 3). Getting a new mobile number in China will involve a facial-recognition test. Quartz. https://qz.com/1720832/china-introduces-facial-recognition-step-to-get-new-mobile-number/ Open Google Scholar doi.org/10.5771/9783748929451
  354. Liakin, D., Cardoso, W., & Liakina, N. (2017). The pedagogical use of mobile speech synthesis (TTS): Focus on French liaison. Computer Assisted Language Learning, 30(3–4), 325–342. https://doi.org/10.1080/09588221.2017.1312463 Open Google Scholar doi.org/10.5771/9783748929451
  355. Lin, H.-T., Balcan, M. F., Hadsell, R., & Ranzato, M. (2020, October 16). What we learned from NeurIPS 2020 reviewing process. Medium. https://neuripsconf.medium.com/what-we-learned-from-neurips-2020-reviewing-process-e24549eea38f Open Google Scholar doi.org/10.5771/9783748929451
  356. Liu, Y., Kohlberger, T., Norouzi, M., Dahl, G. E., Smith, J. L., Mohtashamian, A., Olson, N., Peng, L. H., Hipp, J. D., & Stumpe, M. C. (2019). Artificial Intelligence-Based Breast Cancer Nodal Metastasis Detection: Insights Into the Black Box for Pathologists. Archives of Pathology & Laboratory Medicine, 143(7), 859–868. https://doi.org/10.5858/arpa.2018-0147-OA Open Google Scholar doi.org/10.5771/9783748929451
  357. Lomas, N. (2021, February 12). Sweden’s data watchdog slaps police for unlawful use of Clearview AI. TechCrunch. https://social.techcrunch.com/2021/02/12/swedens-data-watchdog-slaps-police-for-unlawful-use-of-clearview-ai/ Open Google Scholar doi.org/10.5771/9783748929451
  358. Lovelace, A. & Steinacker, L. (2033). How we built the analytical engine - finally. Morals & Machines, 13(3), 67-89. Open Google Scholar doi.org/10.5771/9783748929451
  359. Luhmann, N. (2018). Unterwachung. In Schriften zur Organisation 1 (pp. 415–424). Springer. Open Google Scholar doi.org/10.5771/9783748929451
  360. Luo, X., Tong, S., Fang, Z., & Qu, Z. (2019). Frontiers: Machines vs. humans: The impact of artificial intelligence chatbot disclosure on customer purchases. Marketing Science, 38(6), 937–947. Open Google Scholar doi.org/10.5771/9783748929451
  361. Luthans, F., Youssef, C. M., & Avolio, B. (2007). Psychological capital: Developing the human competitive edge. Oxford University Press. Open Google Scholar doi.org/10.5771/9783748929451
  362. Lyons, M. J., Budynek, J., & Akamatsu, S. (1999). Automatic classification of single facial images. IEEE Transactions on Pattern Analysis and Machine Intelligence, 21(12), 1357–1362. https://doi.org/10.1109/34.817413 Open Google Scholar doi.org/10.5771/9783748929451
  363. MacKenzie, D. (1984). Marx and the Machine. Technology and Culture, 25(3), 473–502. https://doi.org/10.2307/3104202 Open Google Scholar doi.org/10.5771/9783748929451
  364. Malle, B. F., Magar, S. T., & Scheutz, M. (2019). AI in the sky: How people morally evaluate human and machine decisions in a lethal strike dilemma. In M. I. Aldinhas Ferreira, J. Silva Sequeira, V. Gurvinder, O. Tokhi, & E. Kadar (Eds.), Robotics and well-being (pp. 111–133). Springer. Open Google Scholar doi.org/10.5771/9783748929451
  365. Mann, M., & Smith, M. (2017). Automated facial recognition technology: Recent developments and approaches to oversight. UNSWLJ, 40(1), 121–145. Open Google Scholar doi.org/10.5771/9783748929451
  366. Manokha, I. (2018). Surveillance, Panopticism, and Self-Discipline in the Digital Age. Surveillance & Society, 16(2), 219–237. https://doi.org/10.24908/ss.v16i2.834⁠6eng Open Google Scholar doi.org/10.5771/9783748929451
  367. Manovich, L. (2011). Trending: The promises and the challenges of big social data. Debates in the Digital Humanities, 2(1), 460–475. Open Google Scholar doi.org/10.5771/9783748929451
  368. Manyika, J., Lund, S., Bughin, J., Robinson, K., Mischke, J., & Mahajan, D. (2016). Independent work: Choice, necessity, and the gig economy. McKinsey Global Institute, 1–16. Open Google Scholar doi.org/10.5771/9783748929451
  369. Maras, M.-H., & Alexandrou, A. (2019). Determining authenticity of video evidence in the age of artificial intelligence and in the wake of Deepfake videos. The International Journal of Evidence & Proof, 23(3), 255–262. Open Google Scholar doi.org/10.5771/9783748929451
  370. Marche, S. (2021, April 30). The Computers Are Getting Better at Writing, Thanks to Artificial Intelligence. The New Yorker. https://www.newyorker.com/culture/cultural-comment/the-computers-are-getting-better-at-writing Open Google Scholar doi.org/10.5771/9783748929451
  371. Marcus, J. (2020, February 20). How Technology Is Changing the Future of Higher Education. The New York Times. https://www.nytimes.com/2020/02/20/education/learning/education-technology.html Open Google Scholar doi.org/10.5771/9783748929451
  372. Markoff, J. (2011, October 10). U.S. Intelligence Unit Aims to Build a ‘Data Eye in the Sky.’ The New York Times. https://www.nytimes.com/2011/10/11/science/11predict.html Open Google Scholar doi.org/10.5771/9783748929451
  373. Martinez-Martin, N. (2019). What Are Important Ethical Implications of Using Facial Recognition Technology in Health Care? AMA Journal of Ethics, 21(2), 180–187. Open Google Scholar doi.org/10.5771/9783748929451
  374. Marx, K. (1971). The Poverty of Philosophy. Progress Publishers. Open Google Scholar doi.org/10.5771/9783748929451
  375. Marx, K. (2010a). Capital: A Critique of Political Economy—Volume II (F. Engels, Ed.). Progress Publishers. https://libcom.org/files/Capital-Volume-II.pdf Open Google Scholar doi.org/10.5771/9783748929451
  376. Marx, K. (2010b). Capital: A Critique of Political Economy—Volume III (F. Engels, Ed.). Progress Publishers. https://www.marxists.org/archive/marx/works/download/pdf/Capital-Volume-III.pdf Open Google Scholar doi.org/10.5771/9783748929451
  377. Marx, K. (2015). Capital: A Critique of Political Economy—Volume I. Progress Publishers. https://www.marxists.org/archive/marx/works/download/pdf/Capital-Volume-I.pdf Open Google Scholar doi.org/10.5771/9783748929451
  378. Marx, K., & Engels, F. (1970). The German Ideology (C. Arthur, Ed.). International Publishers Co. Open Google Scholar doi.org/10.5771/9783748929451
  379. Marx, L. (1994). The Idea of “Technology” and Postmodern Pessimism. In Y. Ezrahi, E. Mendelsohn, & H. Segal (Eds.), Technology, Pessimism, and Postmodernism (pp. 11–28). Springer Netherlands. https://doi.org/10.1007/978-94-011-0876-8_2 Open Google Scholar doi.org/10.5771/9783748929451
  380. Marx, L., & Smith, M. R. (1994). Introduction. In M. R. Smith & L. Marx (Eds.), Does Technology Drive History?: The Dilemma of Technological Determinism. MIT Press. Open Google Scholar doi.org/10.5771/9783748929451
  381. Massachusetts State Government. (2020, December 31). Governor Baker Signs Police Reform Legislation. https://www.mass.gov/news/governor-baker-signs-police-reform-legislation Open Google Scholar doi.org/10.5771/9783748929451
  382. Mathiesen, T. (1997). The viewer society: Michel Foucault’s “Panopticon” revisited. Theoretical Criminology, 1(2), 215–234. Open Google Scholar doi.org/10.5771/9783748929451
  383. McCarthy, J., Minsky, M. L., Rochester, N., & Shannon, C. E. (2006). A proposal for the dartmouth summer research project on artificial intelligence, august 31, 1955. AI Magazine, 27(4), 12–12. Open Google Scholar doi.org/10.5771/9783748929451
  384. McClurg, A. J. (2007). In the face of danger: Facial recognition and the limits of privacy law. Harvard Law Review, 120(7), 1870–1891. Open Google Scholar doi.org/10.5771/9783748929451
  385. McCorduck, P. (2004). Machines who think: A personal inquiry into the history and prospects of artificial intelligence. CRC Press. Open Google Scholar doi.org/10.5771/9783748929451
  386. McCormack, D. (2003). Can Corporate America Secure Our Nation-An Analysis of the Identix Framework for the Regulation and Use of Facial Recognition Technology. BUJ Sci. & Tech. L., 9, 128. Open Google Scholar doi.org/10.5771/9783748929451
  387. McCoy, S. (2002). O’Big Brother Where Art Thou?: The Constitutional Use of Facial-Recognition Technology. The John Marshall Journal of Information Technology & Privacy Law, 20(3), 471–493. Open Google Scholar doi.org/10.5771/9783748929451
  388. McKinlay, A., & Starkey, K. (1997). Foucault, Management and Organization Theory: From Panopticon to Technologies of Self. SAGE. Open Google Scholar doi.org/10.5771/9783748929451
  389. McMullan, T. (2015, July 23). What does the panopticon mean in the age of digital surveillance? The Guardian. https://www.theguardian.com/technology/2015/jul/23/panopticon-digital-surveillance-jeremy-bentham Open Google Scholar doi.org/10.5771/9783748929451
  390. Meckel, M., & Steinacker, L. (2021). Hybrid reality: The rise of deepfakes and diverging truths. Morals & Machines, 1(1), 10–20. Open Google Scholar doi.org/10.5771/9783748929451
  391. Menebrea, L. F., & Lovelace, A. (1842). Sketch of the Analytical Engine Invented by Charles Babbage. R. & J. E. Taylor. https://johnrhudson.me.uk/computing/Menabrea_Sketch.pdf Open Google Scholar doi.org/10.5771/9783748929451
  392. Metcalfe, B. (2013). Metcalfe’s law after 40 years of ethernet. Computer, 46(12), 26–31. Open Google Scholar doi.org/10.5771/9783748929451
  393. Metcalfe, R. (1995). Metcalfe’s law. Infoworld, 2. Open Google Scholar doi.org/10.5771/9783748929451
  394. Metz, R. (2019, July 17). Beyond San Francisco, more cities are saying no to facial recognition. CNN. https://www.cnn.com/2019/07/17/tech/cities-ban-facial-recognition/index.html Open Google Scholar doi.org/10.5771/9783748929451
  395. Miailhe, N. (2017). Understanding the Rise of Artificial Intelligence. Introduction. Field Actions Science Reports. The Journal of Field Actions, Special Issue 17, 5. Open Google Scholar doi.org/10.5771/9783748929451
  396. Midler v. Ford Motor Co. 549 F. 2d 460 (9th Cir.). (1988). https://cyber.harvard.edu/people/tfisher/1988%20Midler.pdf Open Google Scholar doi.org/10.5771/9783748929451
  397. Milan, S. (2015). When Algorithms Shape Collective Action: Social Media and the Dynamics of Cloud Protesting. Social Media + Society, 1(2), 1–10. https://doi.org/10.1177/2056305115622481 Open Google Scholar doi.org/10.5771/9783748929451
  398. Miller, R. W. (1984). Analyzing Marx. Princeton University Press. https://press.princeton.edu/titles/1565.html Open Google Scholar doi.org/10.5771/9783748929451
  399. Milligan, C. S. (1999). Facial recognition technology, video surveillance, and privacy. S. Cal. Interdisc. LJ, 9, 295. Open Google Scholar doi.org/10.5771/9783748929451
  400. Mittelstadt, B. (2019). Principles alone cannot guarantee ethical AI. Nature Machine Intelligence, 1(11), 501–507. Open Google Scholar doi.org/10.5771/9783748929451
  401. Mittelstadt, B. D., Allo, P., Taddeo, M., Wachter, S., & Floridi, L. (2016). The ethics of algorithms: Mapping the debate. Big Data & Society, 3(2), 1–21. https://doi.org/10.1177/2053951716679679 Open Google Scholar doi.org/10.5771/9783748929451
  402. Mori, M., MacDorman, K. F., & Kageki, N. (2012). The uncanny valley [from the field]. IEEE Robotics & Automation Magazine, 19(2), 98–100. Open Google Scholar doi.org/10.5771/9783748929451
  403. Morris, M. R. (2020). AI and accessibility. Communications of the ACM, 63(6), 35–⁠3⁠7⁠.eng Open Google Scholar doi.org/10.5771/9783748929451
  404. Morse, J. (2019, October 9). California just scored a major privacy win against facial-recognition tech. Mashable. https://mashable.com/article/california-facial-recognition-tech-body-cam-ban/ Open Google Scholar doi.org/10.5771/9783748929451
  405. Moses, L. B., & Chan, J. (2018). Algorithmic prediction in policing: Assumptions, evaluation, and accountability. Policing and Society, 28(7), 806–822. https://doi.org/10.1080/10439463.2016.1253695 Open Google Scholar doi.org/10.5771/9783748929451
  406. Mozur, P. (2019, April 17). One Month, 500,000 Face Scans: How China Is Using A.I. to Profile a Minority. The New York Times. https://www.nytimes.com/2019/04/14/technology/china-surveillance-artificial-intelligence-racial-profiling.html Open Google Scholar doi.org/10.5771/9783748929451
  407. Mozur, P., Kang, C., Satariano, A., & McCabe, D. (2021, April 20). A Global Tipping Point for Reining In Tech Has Arrived. The New York Times. https://www.nytimes.com/2021/04/20/technology/global-tipping-point-tech.html Open Google Scholar doi.org/10.5771/9783748929451
  408. Mueller, B., Renken, U., & van Den Heuvel, G. (2016). Get your act together: An alternative approach to understanding the impact of technology on individual and organizational behavior. ACM SIGMIS Database: The DATABASE for Advances in Information Systems, 47(4), 67–83. Open Google Scholar doi.org/10.5771/9783748929451
  409. Mueller, M. (1989). The switchboard problem: Scale, signaling, and organization in manual telephone switching, 1877-1897. Technology and Culture, 30(3), 534–560. Open Google Scholar doi.org/10.5771/9783748929451
  410. Murgia, M. (2019, August 12). London’s King’s Cross uses facial recognition in security cameras. Financial Times. https://www.ft.com/content/8cbcb3ae-babd-11e9-8a88-aa6628ac896c Open Google Scholar doi.org/10.5771/9783748929451
  411. Mutch, A. (2013). Sociomateriality—Taking the wrong turning? Information and Organization, 23(1), 28–40. Open Google Scholar doi.org/10.5771/9783748929451
  412. Nahaphiet, J., & Ghoshal, S. (1998). Social capital, intellectual capital, and the organizational advantage. Academy of Management Review, 23(2), 242–266. Open Google Scholar doi.org/10.5771/9783748929451
  413. Nakamura, L. (2013). Cybertypes: Race, ethnicity, and identity on the Internet. Routledge. Open Google Scholar doi.org/10.5771/9783748929451
  414. Naker, S., & Greenbaum, D. (2017). Now you see me: Now you still do: Facial recognition technology and the growing lack of privacy. BUJ Sci. & Tech. L., 23, 88–123. Open Google Scholar doi.org/10.5771/9783748929451
  415. Nass, C., Steuer, J., & Tauber, E. R. (1994). Computers are social actors. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, 72–78. Open Google Scholar doi.org/10.5771/9783748929451
  416. NBC News. (2021, September 2). House Impeachment Managers Play Video Of Capitol Riot During Impeachment Trial. https://www.youtube.com/watch?v=ERIbhsCzZwk Open Google Scholar doi.org/10.5771/9783748929451
  417. Neyman, C. J. (2017). A survey of addictive software design. Digital Commons@Cal Poly. Open Google Scholar doi.org/10.5771/9783748929451
  418. Ngan, M., & Grother, P. J. (2015). Face recognition vendor test (FRVT) performance of automated gender classification algorithms. US Department of Commerce, National Institute of Standards and Technology. https://nvlpubs.nist.gov/nistpubs/ir/2015/NIST.IR.8052.pdf Open Google Scholar doi.org/10.5771/9783748929451
  419. Nguyen, T. T., Nguyen, C. M., Nguyen, D. T., Nguyen, D. T., & Nahavandi, S. (2019). Deep learning for deepfakes creation and detection. ArXiv Preprint ArXiv:1909.11573, 1. Open Google Scholar doi.org/10.5771/9783748929451
  420. Nietzsche, F. (1910). Human, all too human (Zimmern, Trans.). T.N. Foulis. Open Google Scholar doi.org/10.5771/9783748929451
  421. Nilsson, N. J. (1998). Artificial intelligence: A new synthesis. Morgan Kaufmann. Open Google Scholar doi.org/10.5771/9783748929451
  422. Nitzan, J., & Bichler, S. (2009). Capital as power. Routledge. Open Google Scholar doi.org/10.5771/9783748929451
  423. Ogburn, W. F. (1936). Technology and Governmental Change. The Journal of Business of the University of Chicago, 9(1), 1–13. JSTOR. Open Google Scholar doi.org/10.5771/9783748929451
  424. O’Neil, C. (2017). Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy. Penguin. Open Google Scholar doi.org/10.5771/9783748929451
  425. Oppermann, R. (2002). User-interface design. In H. H. Adelsberger & J. M. Palowski (Eds.), Handbook on information technologies for education and training (pp. 233–248). Springer. Open Google Scholar doi.org/10.5771/9783748929451
  426. Orlikowski, W. J. (2000). Using technology and constituting structures: A practice lens for studying technology in organizations. Organization Science, 11(4), 404–428. Open Google Scholar doi.org/10.5771/9783748929451
  427. Orlikowski, W. J. (2007). Sociomaterial practices: Exploring technology at work. Organization Studies, 28(9), 1435–1448. Open Google Scholar doi.org/10.5771/9783748929451
  428. Orlikowski, W. J., & Scott, S. V. (2008). Sociomateriality: Challenging the separation of technology, work and organization. Academy of Management Annals, 2(1), 433–474. Open Google Scholar doi.org/10.5771/9783748929451
  429. Orlikowski, W. J., & Scott, S. V. (2015). The algorithm and the crowd: Considering the materiality of service innovation. MIS Quarterly, 39(1), 201–216. Open Google Scholar doi.org/10.5771/9783748929451
  430. Orlikowski, W. J., Walsham, G., Jones, M. R., & DeGross, J. I. (1996). Information technology and changes in organizational work. Springer Science & Business Media. Open Google Scholar doi.org/10.5771/9783748929451
  431. Owuor, J., & Larkan, F. (2017). Assistive Technology for an Inclusive Society for People with Intellectual Disability. Studies in Health Technology and Informatics, 242, 805–812. Open Google Scholar doi.org/10.5771/9783748929451
  432. Pace, J. (2018). The concept of digital capitalism. Communication Theory, 28(3), 254–269. Open Google Scholar doi.org/10.5771/9783748929451
  433. Page, L., Brin, S., Motwani, R., & Winograd, T. (1998). The PageRank Citation Ranking: Bringing Order to the Web. Stanford InfoLab. http://ilpubs.stanford.edu:8090/422/1/1999-66.pdf Open Google Scholar doi.org/10.5771/9783748929451
  434. Paine, T. L., Khorrami, P., Chang, S., Zhang, Y., Ramachandran, P., Hasegawa-Johnson, M. A., & Huang, T. S. (2016). Fast wavenet generation algorithm. ArXiv Preprint ArXiv:1611.09482. Open Google Scholar doi.org/10.5771/9783748929451
  435. Pal, D., Arpnikanondt, C., Funilkul, S., & Varadarajan, V. (2019). User experience with smart voice assistants: The accent perspective. 2019 10th International Conference on Computing, Communication and Networking Technologies (ICCCNT), 1⁠–⁠⁠6.eng Open Google Scholar doi.org/10.5771/9783748929451
  436. Paluck, E. L. (2009). What’s in a norm? Sources and processes of norm change. Journal of Personality and Social Psychology, 96(3), 594–600. https://doi.org/10.1037/a0014688 Open Google Scholar doi.org/10.5771/9783748929451
  437. Paluck, E. L., & Green, D. P. (2009). Prejudice reduction: What works? A review and assessment of research and practice. Annual Review of Psychology, 60, 339–367. Open Google Scholar doi.org/10.5771/9783748929451
  438. Paluck, E. L., & Shepherd, H. (2012). The salience of social referents: A field experiment on collective norms and harassment behavior in a school social network. Journal of Personality and Social Psychology, 103(6), 899–915. https://doi.org/10.1037/a0030015 Open Google Scholar doi.org/10.5771/9783748929451
  439. Parkhi, O. M., Vedaldi, A., & Zisserman, A. (2015). Deep Face Recognition. Proceedings of the British Machine Vision Conference 2015, 80, 41.1-41.12. https://doi.org/10.5244/C.29.41 Open Google Scholar doi.org/10.5771/9783748929451
  440. Partnership On AI. (2016). Tenets. Partnership on AI. https://www.partnershiponai.org/tenets/ Open Google Scholar doi.org/10.5771/9783748929451
  441. Pasinetti, L. L., Fisher, F. M., Felipe, J., McCombie, J. S. L., & Greenfield, R. L. (2003). Cambridge Capital Controversies. The Journal of Economic Perspectives, 17(4), 227–232. Open Google Scholar doi.org/10.5771/9783748929451
  442. Pasquale, F. (2016a). The Black Box Society. Harvard University Press. Open Google Scholar doi.org/10.5771/9783748929451
  443. Pasquale, F. (2016b). Two narratives of platform capitalism. Yale L. & Pol’y Rev., 35, 309. Open Google Scholar doi.org/10.5771/9783748929451
  444. Pennachin, C., & Goertzel, B. (2007). Contemporary approaches to artificial general intelligence. In B. Goertzel & C. Pennachin (Eds.), Artificial general intelligence (pp. 1–30). Springer. Open Google Scholar doi.org/10.5771/9783748929451
  445. Perkowitz, S. (2021). The Bias in the Machine: Facial Recognition Technology and Racial Disparities. MIT Case Studies in Social and Ethical Responsibilities of Computing. https://mit-serc.pubpub.org/pub/bias-in-machine/release/1 Open Google Scholar doi.org/10.5771/9783748929451
  446. Pettman, D. (2016). Infinite distraction. John Wiley & Sons. Open Google Scholar doi.org/10.5771/9783748929451
  447. Phillips, P., Barnes, S., Zigan, K., & Schegg, R. (2016). Understanding the Impact of Online Reviews on Hotel Performance: An Empirical Analysis. Journal of Travel Research, 56(2), 235–249. https://doi.org/10.1177/0047287516636481 Open Google Scholar doi.org/10.5771/9783748929451
  448. Picard, R. (2002). Affective medicine: Technology with emotional intelligence. Studies in Health Technology and Informatics, 69–84. Open Google Scholar doi.org/10.5771/9783748929451
  449. Pichai, S. (2020, January 20). Why Google thinks we need to regulate AI. Financial Times. https://www.ft.com/content/3467659a-386d-11ea-ac3c-f68c10993b04 Open Google Scholar doi.org/10.5771/9783748929451
  450. Pickering, A. (2010). The mangle of practice: Time, agency, and science. University of Chicago Press. Open Google Scholar doi.org/10.5771/9783748929451
  451. Pidd, H. (2020, August 14). “Punishment by statistics”: The father who foresaw A-level algorithm flaws. The Guardian. http://www.theguardian.com/education/2020/aug/14/punishment-by-statistics-the-father-who-foresaw-a-level-algorithm-flaws Open Google Scholar doi.org/10.5771/9783748929451
  452. Piketty, T. (2014). Capital in the twenty-first century. Harvard University Press. Open Google Scholar doi.org/10.5771/9783748929451
  453. Pinch, T., & Bijker, W. E. (1987). The Social Construction of Facts and Artifacts: Or How the Sociology of Science and the Sociology of Technology Might Benefit Each Other. In W. E. Bijker & T. P. Hughes (Eds.), The Social Construction of Technological Systems (pp. 17–50). MIT Press. Open Google Scholar doi.org/10.5771/9783748929451
  454. Platform for the Information Society. (2018). Artificial Intelligence Impact Assessment. Platform for the Information Society. https://static1.squarespace.com/static/5b7877457c9327fa97fef427/t/5c368c611ae6cf01ea0fba53/1547078768062/Artificial+Intelligence+Impact+Assessment+-+English.pdf Open Google Scholar doi.org/10.5771/9783748929451
  455. Pomerantz, S., & Raby, R. (2020). Bodies, hoodies, schools, and success: Post-human performativity and smart girlhood. Gender and Education, 32(8), 983–1000. Open Google Scholar doi.org/10.5771/9783748929451
  456. Poole, D., Mackworth, A., & Goebel, R. (1998). Computational intelligence: A logical approach. Oxford University Press. Open Google Scholar doi.org/10.5771/9783748929451
  457. Porter, J. (2021, February 24). Australia passes law requiring Facebook and Google to pay for news content. The Verge. https://www.theverge.com/2021/2/24/22283777/australia-new-media-bargaining-code-facebook-google-paying-news Open Google Scholar doi.org/10.5771/9783748929451
  458. Prassl, J. (2018). Humans as a service: The promise and perils of work in the gig economy. Oxford University Press. Open Google Scholar doi.org/10.5771/9783748929451
  459. Prentice, D. A., & Miller, D. T. (1996). Pluralistic ignorance and the perpetuation of social norms by unwitting actors. In M. P. Zanna (Ed.), Advances in experimental social psychology (Vol. 28, pp. 161–209). Academic Press. Open Google Scholar doi.org/10.5771/9783748929451
  460. Press Association. (2019, March 30). Mark Zuckerberg calls for stronger regulation of internet. The Guardian. http://www.theguardian.com/technology/2019/mar/30/mark-zuckerberg-calls-for-stronger-regulation-of-internet Open Google Scholar doi.org/10.5771/9783748929451
  461. Prokoshyna, N., Szlichta, J., Chiang, F., Miller, R. J., & Srivastava, D. (2015). Combining quantitative and logical data cleaning. Proceedings of the VLDB Endowment, 9(4), 300–311. Open Google Scholar doi.org/10.5771/9783748929451
  462. Purdy, G. (2010). ISO 31000: 2009—setting a new standard for risk management. Risk Analysis: An International Journal, 30(6), 881–886. Open Google Scholar doi.org/10.5771/9783748929451
  463. Puschmann, T., & Alt, R. (2016). Sharing economy. Business & Information Systems Engineering, 58(1), 93–99. Open Google Scholar doi.org/10.5771/9783748929451
  464. Putnam, R. D. (1993). What makes democracy work? National Civic Review, 82(2), 101–107. https://doi.org/10.1002/ncr.4100820204 Open Google Scholar doi.org/10.5771/9783748929451
  465. Putnam, R. D. (2000). Bowling alone: America’s declining social capital. Simon and Schuster. Open Google Scholar doi.org/10.5771/9783748929451
  466. Qiu, L., & Benbasat, I. (2005). An investigation into the effects of Text-To-Speech voice and 3D avatars on the perception of presence and flow of live help in electronic commerce. ACM Transactions on Computer-Human Interaction (TOCHI), 12(4), 329–355. Open Google Scholar doi.org/10.5771/9783748929451
  467. Rahwan, I. (2018). Society-in-the-loop: Programming the algorithmic social contract. Ethics and Information Technology, 20(1), 5–14. https://doi.org/10.1007/s10676-017-9430-8 Open Google Scholar doi.org/10.5771/9783748929451
  468. Rahwan, I., Cebrian, M., Obradovich, N., Bongard, J., Bonnefon, J.-F., Breazeal, C., Crandall, J. W., Christakis, N. A., Couzin, I. D., Jackson, M. O., Jennings, N. R., Kamar, E., Kloumann, I. M., Larochelle, H., Lazer, D., McElreath, R., Mislove, A., Parkes, D. C., Pentland, A. ‘Sandy,’ … Wellman, M. (2019). Machine behaviour. Nature, 568(7753), 477–486. https://doi.org/10.1038/s41586-019-113⁠8⁠-⁠yeng Open Google Scholar doi.org/10.5771/9783748929451
  469. Ramiller, N. C., & Chiasson, M. (2008). The service behind the service: Sensegiving in the service economy. In M. Barrett, E. Davidson, E. Middleton, & J. DeGross (Eds.), Information Technology in the Service Economy: Challenges and Possibilities for the 21st Century (pp. 117–126). Springer. Open Google Scholar doi.org/10.5771/9783748929451
  470. Reid, E. M. (1991). Electropolis: Communication and community on internet relay chat [Honours Thesis, University of Melbourne, Department of History]. http://www.aluluei.com/electropolis.htm Open Google Scholar doi.org/10.5771/9783748929451
  471. Reisman, D., Schultz, J., Crawford, K., & Whittaker, M. (2018). Algorithmic impact assessments: A practical framework for public agency accountability. AI Now Institute. https://ainowinstitute.org/aiareport2018.pdf Open Google Scholar doi.org/10.5771/9783748929451
  472. H.R. 7356: Facial Recognition and Biometric Technology Moratorium Act of 2020, U.S. Congress (2020) (testimony of Pramila Rep. Jayapal). https://www.govtrack.us/congress/bills/116/hr7356 Open Google Scholar doi.org/10.5771/9783748929451
  473. Reynolds, D. A. (2009). Gaussian Mixture Models. In S.Z. Li (Ed.), Encyclopedia of Biometrics (pp. 659–663). Springer. Open Google Scholar doi.org/10.5771/9783748929451
  474. Ribeiro, M. H., Ottoni, R., West, R., Almeida, V. A., & Meira Jr, W. (2020). Auditing radicalization pathways on YouTube. Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency, 131–141. Open Google Scholar doi.org/10.5771/9783748929451
  475. Rich, E., Knight, K., & Nair, S. B. (2009). Artificial intelligence third edition. McGraw-Hill. Open Google Scholar doi.org/10.5771/9783748929451
  476. Richardson, L. (2015). Performing the sharing economy. Geoforum, 67, 121–129. Open Google Scholar doi.org/10.5771/9783748929451
  477. Ringrose, K. (2019). Law Enforcement’s Pairing of Facial Recognition Technology with Body-Worn Cameras Escalates Privacy Concerns. Va. L. Rev. Online, 105, 57. Open Google Scholar doi.org/10.5771/9783748929451
  478. Ritzer, G. (2015). Prosumer capitalism. The Sociological Quarterly, 56(3), 413–445. Open Google Scholar doi.org/10.5771/9783748929451
  479. Ritzer, G., Dean, P., & Jurgenson, N. (2012). The coming of age of the prosumer. American Behavioral Scientist, 56(4), 379–398. Open Google Scholar doi.org/10.5771/9783748929451
  480. Robertson, R. E., Jiang, S., Lazer, D., & Wilson, C. (2019). Auditing autocomplete: Suggestion networks and recursive algorithm interrogation. Proceedings of the 10th ACM Conference on Web Science, 235–244. Open Google Scholar doi.org/10.5771/9783748929451
  481. Rogers, B. (2016). Employment rights in the platform economy: Getting back to basics. Harv. L. & Pol’y Rev., 10, 479. Open Google Scholar doi.org/10.5771/9783748929451
  482. Rolls Royce. (2020, December). The Aletheia Framework. Rolls Royce. https://www.rolls-royce.com/sustainability/ethics-and-compliance/the-aletheia-framework.aspx Open Google Scholar doi.org/10.5771/9783748929451
  483. Romer, P. M. (1990). Endogenous Technological Change. Journal of Political Economy, 98(5, Part 2), S71–S102. https://doi.org/10.1086/261725 Open Google Scholar doi.org/10.5771/9783748929451
  484. Roscher, W. (1870). Die romantische Schule der Nationalökonomik in Deutschland. Zeitschrift Für Die Gesamte Staatswissenschaft / Journal of Institutional and Theoretical Economics, 57–105. Open Google Scholar doi.org/10.5771/9783748929451
  485. Rowley, H. A., Baluja, S., & Kanade, T. (1998). Neural network-based face detection. IEEE Transactions on Pattern Analysis and Machine Intelligence, 20(1), 23–38. Open Google Scholar doi.org/10.5771/9783748929451
  486. Rudin, C., Waltz, D., Anderson, R. N., Boulanger, A., Salleb-Aouissi, A., Chow, M., Dutta, H., Gross, P. N., Huang, B., & Ierome, S. (2011). Machine learning for the New York City power grid. IEEE Transactions on Pattern Analysis and Machine Intelligence, 34(2), 328–345. Open Google Scholar doi.org/10.5771/9783748929451
  487. Russell, S. (2019, October 8). How to Stop Superhuman A.I. Before It Stops Us. The New York Times. https://www.nytimes.com/2019/10/08/opinion/artificial-intelligence.html Open Google Scholar doi.org/10.5771/9783748929451
  488. Russell, S., & Norvig, P. (2010). Artificial Intelligence: A modern approach (3rd edition). Pearson Education. Open Google Scholar doi.org/10.5771/9783748929451
  489. Sadowski, J. (2019). When data is capital: Datafication, accumulation, and extraction. Big Data & Society, 6(1), 1–12. Open Google Scholar doi.org/10.5771/9783748929451
  490. Sætra, H. S. (2020). A shallow defence of a technocracy of artificial intelligence: Examining the political harms of algorithmic governance in the domain of government. Technology in Society, 62(101283), 1–10. Open Google Scholar doi.org/10.5771/9783748929451
  491. Salin, E. D., & Winston, P. H. (1992). Machine learning and artificial intelligence: An introduction. Analytical Chemistry, 64(1), 49A-60A. Open Google Scholar doi.org/10.5771/9783748929451
  492. Samatas, M. (2005). Studying surveillance in Greece: Methodological and other problems related to an authoritarian surveillance culture. Surveillance & Society, 3(2), 181–197. Open Google Scholar doi.org/10.5771/9783748929451
  493. Sambasivan, N., & Holbrook, J. (2018). Toward responsible AI for the next billion users. Interactions, 26(1), 68–71. Open Google Scholar doi.org/10.5771/9783748929451
  494. Sandberg, S., & Pedersen, W. (2011). Street capital: Black cannabis dealers in a white welfare state. The Policy Press. Open Google Scholar doi.org/10.5771/9783748929451
  495. Sandler, M., & Howard, A. (2018, April 3). MobileNetV2: The Next Generation of On-Device Computer Vision Networks. Google AI Blog. http://ai.googleblog.com/2018/04/mobilenetv2-next-generation-of-on.html Open Google Scholar doi.org/10.5771/9783748929451
  496. Sandler, M., Howard, A., Zhu, M., Zhmoginov, A., & Chen, L.-C. (2018). Mobilenetv2: Inverted residuals and linear bottlenecks. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 4510–4520. Open Google Scholar doi.org/10.5771/9783748929451
  497. Satariano, A. (2019, September 4). Police Use of Facial Recognition Is Accepted by British Court. The New York Times. https://www.nytimes.com/2019/09/04/business/facial-recognition-uk-court.html Open Google Scholar doi.org/10.5771/9783748929451
  498. Saygin, A. P., Cicekli, I., & Akman, V. (2000). Turing test: 50 years later. Minds and Machines, 10(4), 463–518. Open Google Scholar doi.org/10.5771/9783748929451
  499. Scassa, T. (2018). Information Law in the Platform Economy: Ownership, Control, and Reuse of Platform Data. In D. McKee, F. Makela, & T. Scassa (Eds.), Law and the «Sharing Economy»: Regulating Online Market Platforms (pp. 321–356). University of Ottawa Press. Open Google Scholar doi.org/10.5771/9783748929451
  500. Schermer, B. W. (2011). The limits of privacy in automated profiling and data mining. Computer Law & Security Review, 27(1), 45–52. Open Google Scholar doi.org/10.5771/9783748929451
  501. Scheuerman, M. K., Paul, J. M., & Brubaker, J. (2019). How Computers See Gender: An Evaluation of Gender Classification in Commercial Facial Analysis and Image Labeling Services. Proceedings of the ACM on Human-Computer Interaction, 3, 1–33. Open Google Scholar doi.org/10.5771/9783748929451
  502. Scheuerman, M. K., Wade, K., Lustig, C., & Brubaker, J. R. (2020). How We’ve Taught Algorithms to See Identity: Constructing Race and Gender in Image Databases for Facial Analysis. Proceedings of the ACM on Human-Computer Interaction, 4(CSCW1), 1–35. Open Google Scholar doi.org/10.5771/9783748929451
  503. Schiller, D. (2000). Digital capitalism: Networking the global market system. MIT Press. Open Google Scholar doi.org/10.5771/9783748929451
  504. Schiller, D., & Mosco, V. (2001). Continental Order? Integrating North America for Cybercapitalism. Rowman and Littlefield. Open Google Scholar doi.org/10.5771/9783748929451
  505. Schmidt, E., Work, B., Catz, S., Chien, S., Darby, C., Ford, K., Griffiths, J.-M., Horvitz, E., Jassy, A., & Mark, W. (2021). National Security Commission on Artificial Intelligence (AI). National Security Commission on Artificial Intelligence. https://www.nscai.gov/wp-content/uploads/2021/03/Full-Report-Digital-1.pdf Open Google Scholar doi.org/10.5771/9783748929451
  506. Schor, J. (2016). Debating the sharing economy. Journal of Self-Governance and Management Economics, 4(3), 7–22. Open Google Scholar doi.org/10.5771/9783748929451
  507. Schor, J. B., & Attwood-Charles, W. (2017). The “sharing” economy: Labor, inequality, and social connection on for-profit platforms. Sociology Compass, 11(8), e12493. Open Google Scholar doi.org/10.5771/9783748929451
  508. Schultz, T. W. (1961). Investment in Human Capital. The American Economic Review, 51(1), 1–17. Open Google Scholar doi.org/10.5771/9783748929451
  509. Schumpeter, J. (1954). History of Economic Analysis (E. B. Schumpeter, Ed.). Routledge. Open Google Scholar doi.org/10.5771/9783748929451
  510. Schwartz, O. (2018, September 26). Love in the time of AI: Meet the people falling for scripted robots. The Guardian. https://www.theguardian.com/technology/2018/sep/26/mystic-messenger-dating-simulations-sims-digital-intimacy Open Google Scholar doi.org/10.5771/9783748929451
  511. Seeger, A.-M., & Heinzl, A. (2018). Human versus machine: Contingency factors of anthropomorphism as a trust-inducing design strategy for conversational agents. In F. D. Davis, R. Riedl, P. vom Brocke, P. Léger, & A. B. Randolph (Eds.), Information systems and neuroscience (pp. 129–139). Springer. Open Google Scholar doi.org/10.5771/9783748929451
  512. Seelman, K. D. (1993). Assistive technology policy: A road to independence for individuals with disabilities. Journal of Social Issues, 49(2), 115–136. Open Google Scholar doi.org/10.5771/9783748929451
  513. Segura, M. S., & Waisbord, S. (2019). Between data capitalism and data citizenship. Television & New Media, 20(4), 412–419. Open Google Scholar doi.org/10.5771/9783748929451
  514. Sengupta, A. (2020, November 16). Election polls were a disaster this year. Here’s how AI could help. Fast Company. https://www.fastcompany.com/90575531/ai-election-polling Open Google Scholar doi.org/10.5771/9783748929451
  515. Senior, A. W., Evans, R., Jumper, J., Kirkpatrick, J., Sifre, L., Green, T., Qin, C., Žídek, A., Nelson, A. W., & Bridgland, A. (2020). Improved protein structure prediction using potentials from deep learning. Nature, 577(7792), 706–710. Open Google Scholar doi.org/10.5771/9783748929451
  516. Shaw, W. H. (1979). “The Handmill Gives You the Feudal Lord”: Marx’s Technological Determinism. History and Theory, 18(2), 155–176. JSTOR. https://doi.org/10.2307/2504754 Open Google Scholar doi.org/10.5771/9783748929451
  517. Shelley, M. W. (1869). Frankenstein, or, The Modern Prometheus. Sever, Francis, & Company. Open Google Scholar doi.org/10.5771/9783748929451
  518. Shen, J., Pang, R., Weiss, R. J., Schuster, M., Jaitly, N., Yang, Z., Chen, Z., Zhang, Y., Wang, Y., & Skerrv-Ryan, R. (2018). Natural tts synthesis by conditioning wavenet on mel spectrogram predictions. 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 4779–4783. Open Google Scholar doi.org/10.5771/9783748929451
  519. Shergill, G. S., Sarrafzadeh, A., Diegel, O., & Shekar, A. (2008). Computerized Sales Assistants: The application of computer technology to measure consumer interest-a conceptual framework. Journal of Electronic Commerce Research, 9(2), 176–191. Open Google Scholar doi.org/10.5771/9783748929451
  520. Sherif, M. (1936). The psychology of social norms. Harper. Open Google Scholar doi.org/10.5771/9783748929451
  521. Shilton, K. (2015). “ That’s Not An Architecture Problem!”: Techniques and Challenges for Practicing Anticipatory Technology Ethics. IConference 2015 Proceedings. Open Google Scholar doi.org/10.5771/9783748929451
  522. Shilton, K. (2018). Engaging values despite neutrality: Challenges and approaches to values reflection during the design of internet infrastructure. Science, Technology, & Human Values, 43(2), 247–269. Open Google Scholar doi.org/10.5771/9783748929451
  523. Siau, K., & Wang, W. (2020). Artificial intelligence (AI) ethics: Ethics of AI and ethical AI. Journal of Database Management (JDM), 31(2), 74–87. Open Google Scholar doi.org/10.5771/9783748929451
  524. Siegel, E. (2013). Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die. Wiley. Open Google Scholar doi.org/10.5771/9783748929451
  525. Silverman, C. (2016, November 16). This Analysis Shows How Viral Fake Election News Stories Outperformed Real News On Facebook. BuzzFeed News. https://www.buzzfeednews.com/article/craigsilverman/viral-fake-election-news-outperformed-real-news-on-facebook Open Google Scholar doi.org/10.5771/9783748929451
  526. Similar companies to VocaliD. (2021). Venture Radar. https://www.ventureradar.com/similar/VocaliD/34420c6a-e53f-46ae-870b-cef6bc01008a Open Google Scholar doi.org/10.5771/9783748929451
  527. Simonite, T. (2019, September 3). Behind the Rise of China’s Facial-Recognition Giants. Wired. https://www.wired.com/story/behind-rise-chinas-facial-recognition-giants/ Open Google Scholar doi.org/10.5771/9783748929451
  528. Simonite, T. (2020, July 22). AI Text Generator GPT-3 Is Learning Our Language—Fitfully. WIRED. https://www.wired.com/story/ai-text-generator-gpt-3-learning-language-fitfully/ Open Google Scholar doi.org/10.5771/9783748929451
  529. Simonite, T. (2021, March 16). The Departure of 2 Google AI Researchers Spurs More Fallout. WIRED. https://www.wired.com/story/departures-2-google-ai-researchers-spur-fallout/ Open Google Scholar doi.org/10.5771/9783748929451
  530. Sinha, N., Bhowmick, A., & Kishore, B. (2015). Encrypted information hiding using audio steganography and audio cryptography. International Journal of Computer Applications, 112(5), 49–53. Open Google Scholar doi.org/10.5771/9783748929451
  531. Sismondo, S. (2009). An Introduction to Science and Technology Studies (2nd ed.). Wiley-Blackwell. Open Google Scholar doi.org/10.5771/9783748929451
  532. Skitka, L. J., Mosier, K. L., & Burdick, M. (1999). Does automation bias decision-making? International Journal of Human-Computer Studies, 51(5), 991–1006. Open Google Scholar doi.org/10.5771/9783748929451
  533. Slaney, M., & Casey, M. (2008). Locality-sensitive hashing for finding nearest neighbors [lecture notes]. IEEE Signal Processing Magazine, 25(2), 128–131. Open Google Scholar doi.org/10.5771/9783748929451
  534. Slater, D. (2013). Love in times of algorithms: What technology does to meeting and mating. Current. Open Google Scholar doi.org/10.5771/9783748929451
  535. Smaradottir, B. F., Haaland, J. A., & Martinez, S. G. (2018). User evaluation of the smartphone screen reader VoiceOver with visually disabled participants. Mobile Information Systems, 2018. https://doi.org/10.1155/2018/6941631 Open Google Scholar doi.org/10.5771/9783748929451
  536. Smith, Aaron. (2019, September 5). More Than Half of U.S. Adults Trust Law Enforcement to Use Facial Recognition Responsibly. Pew Research Center: Internet, Science & Tech. https://www.pewinternet.org/2019/09/05/more-than-half-of-u-s-adults-trust-law-enforcement-to-use-facial-recognition-responsibly/ Open Google Scholar doi.org/10.5771/9783748929451
  537. Smith, Adam. (1804). An Inquiry Into the Nature and Causes of the Wealth of Nations, Volume 1 (Vol. 1). Oliver D Cooke. Open Google Scholar doi.org/10.5771/9783748929451
  538. Solow, R. M. (2017). Thomas Piketty Is Right. In H. Boushey, J. B. DeLong, & M. Steinbaum (Eds.), After Piketty (pp. 48–59). Harvard University Press. https://doi.org/10.4159/9780674978195-003 Open Google Scholar doi.org/10.5771/9783748929451
  539. Sotala, K. (2020, July 18). Collection of GPT-3 results. LESSWRONG. https://www.lesswrong.com/posts/6Hee7w2paEzHsD6mn/collection-of-gpt-3-results Open Google Scholar doi.org/10.5771/9783748929451
  540. Sovacool, B. K., & Hess, D. J. (2017). Ordering theories: Typologies and conceptual frameworks for sociotechnical change. Social Studies of Science, 47(5), 703–750. https://doi.org/10.1177/0306312717709363 Open Google Scholar doi.org/10.5771/9783748929451
  541. Srnicek, N. (2017). Platform capitalism. John Wiley & Sons. Open Google Scholar doi.org/10.5771/9783748929451
  542. St. Vincent, S. (2019, June 21). Facial Recognition Technology in US Schools Threatens Rights. Human Rights Watch. https://www.hrw.org/news/2019/06/21/facial-recognition-technology-us-schools-threatens-rights Open Google Scholar doi.org/10.5771/9783748929451
  543. Star, S. L. (1999). The ethnography of infrastructure. American Behavioral Scientist, 43(3), 377–391. Open Google Scholar doi.org/10.5771/9783748929451
  544. Statista. (2018). Nachrichteninhalte—Aufmerksamkeitsquellen in Deutschland 2016. Statista. https://de.statista.com/statistik/daten/studie/550868/umfrage/aufmerksamkeitsquellen-fuer-nachrichteninhalte/ Open Google Scholar doi.org/10.5771/9783748929451
  545. Statista. (2021, January). Search engines: Market share of desktop and mobile search in Germany 2021. Statista. https://www.statista.com/statistics/445974/search-engines-market-share-of-desktop-and-mobile-search-germany/ Open Google Scholar doi.org/10.5771/9783748929451
  546. Statt, N. (2018, May 10). Google now says controversial AI voice calling system will identify itself to humans. The Verge. https://www.theverge.com/2018/5/10/17342414/google-duplex-ai-assistant-voice-calling-identify-itself-update Open Google Scholar doi.org/10.5771/9783748929451
  547. Steinacker, L., Kostka, G., Meckel, M., Guo, D., & Suter, V. (2020, May). Facing the public: A cross-national analysis of social norms and communication about facial recognition technologies. International Communication Association 2020, Australia. https://www.alexandria.unisg.ch/259127/ Open Google Scholar doi.org/10.5771/9783748929451
  548. Steinacker, L., Meckel, M., Kostka, G., & Borth, D. (2020). Facial Recognition: A cross-national Survey on Public Acceptance, Privacy, and Discrimination. ArXiv Preprint ArXiv:2008.07275. Open Google Scholar doi.org/10.5771/9783748929451
  549. Steinbicker, J. (2001). Zur Theorie der Informationsgesellschaft. Springer. Open Google Scholar doi.org/10.5771/9783748929451
  550. Steiner, C. (2013). Automate This: How algorithms took over markets, our jobs, and the world. Penguin Random House. Open Google Scholar doi.org/10.5771/9783748929451
  551. Stern, S. E., Dumont, M., Mullennix, J. W., & Winters, M. L. (2007). Positive prejudice toward disabled persons using synthesized speech: Does the effect persist across contexts? Journal of Language and Social Psychology, 26(4), 363–380. Open Google Scholar doi.org/10.5771/9783748929451
  552. Stern, S. E., Mullennix, J. W., & Wilson, S. J. (2002). Effects of perceived disability on persuasiveness of computer-synthesized speech. Journal of Applied Psychology, 87(2), 411–417. Open Google Scholar doi.org/10.5771/9783748929451
  553. Stöcker, C., & Preuss, M. (2020). Riding the Wave of Misclassification: How We End up with Extreme YouTube Content. International Conference on Human-Computer Interaction, 359–375. Open Google Scholar doi.org/10.5771/9783748929451
  554. Stone, D., Jarrett, C., Woodroffe, M., & Minocha, S. (2005). User interface design and evaluation. Elsevier. Open Google Scholar doi.org/10.5771/9783748929451
  555. Stone, P., Brooks, R., Brynjolfsson, E., Calo, R., Etzioni, O., Hager, G., Hirschberg, J., Kalyanakrishnan, S., Kamar, E., Kraus, S., Leyton-Brown, K., Parkes, D. C., Press, W., Saxenian, A., Shah, J., Tambe, M., & Teller, A. (2016). One hundred year study on Artificial Intelligence: AI and life in 2030. Stanford University. ai100.standford.edu Open Google Scholar doi.org/10.5771/9783748929451
  556. Strauss, A., & Corbin, J. (1998). Basics of qualitative research techniques. Citeseer. Open Google Scholar doi.org/10.5771/9783748929451
  557. Striphas, T. (2015). Algorithmic culture. European Journal of Cultural Studies, 18(4–5), 395–412. https://doi.org/10.1177/1367549415577392 Open Google Scholar doi.org/10.5771/9783748929451
  558. Strubell, E., Ganesh, A., & McCallum, A. (2019). Energy and policy considerations for deep learning in NLP. ArXiv Preprint ArXiv:1906.02243. Open Google Scholar doi.org/10.5771/9783748929451
  559. Suarez-Villa, L. (2000). Invention and the Rise of Technocapitalism. Rowman & Littlefield. Open Google Scholar doi.org/10.5771/9783748929451
  560. Suarez-Villa, L. (2013). Technocapitalism. http://www.technocapitalism.com/Introduction.htm Open Google Scholar doi.org/10.5771/9783748929451
  561. Suchman, L. (1987). Plans and Situated Actions: The Problem of Human-Machine Communication. Cambridge University Press. Open Google Scholar doi.org/10.5771/9783748929451
  562. Suchman, L. (2007). Human-machine reconfigurations: Plans and situated actions (2nd Edition). Cambridge University Press. Open Google Scholar doi.org/10.5771/9783748929451
  563. Svenmarck, P., Luotsinen, L., Nilsson, M., & Schubert, J. (2018). Possibilities and challenges for artificial intelligence in military applications. Proceedings of the 2018 NATO Big Data and Artificial Intelligence for Military Decision Making Specialists’ Meeting, 1–15. Open Google Scholar doi.org/10.5771/9783748929451
  564. Sweeney, L. (2013). Discrimination in online ad delivery. ArXiv Preprint ArXiv:1301.6822. Open Google Scholar doi.org/10.5771/9783748929451
  565. Taigman, Y., Yang, M., Ranzato, M., & Wolf, L. (2014). DeepFace: Closing the Gap to Human-Level Performance in Face Verification. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 1701–1708. https://www.cv-foundation.org/openaccess/content_cvpr_2014/html/Taigman_DeepFace_Closing_the_2014_CVPR_paper.html Open Google Scholar doi.org/10.5771/9783748929451
  566. Takeishi, A., & Lee, K.-J. (2005). Mobile music business in Japan and Korea: Copyright management institutions as a reverse salient. The Journal of Strategic Information Systems, 14(3), 291–306. https://doi.org/10.1016/j.jsis.2005.07.005 Open Google Scholar doi.org/10.5771/9783748929451
  567. Tan, B., Shen, X., & Zhai, C. (2006). Mining long-term search history to improve search accuracy. Proceedings of the 12th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 718–723. Open Google Scholar doi.org/10.5771/9783748929451
  568. Tandoc, E. C., Lim, Z. W., & Ling, R. (2018). Defining “Fake News”: A typology of scholarly definitions. Digital Journalism, 6(2), 137–153. https://doi.org/10.1080/21670811.2017.1360143 Open Google Scholar doi.org/10.5771/9783748929451
  569. Tankard, M. E., & Paluck, E. L. (2016). Norm Perception as a Vehicle for Social Change: Vehicle for Social Change. Social Issues and Policy Review, 10(1), 181–211. https://doi.org/10.1111/sipr.12022 Open Google Scholar doi.org/10.5771/9783748929451
  570. Tankard, M. E., & Paluck, E. L. (2017). The Effect of a Supreme Court Decision Regarding Gay Marriage on Social Norms and Personal Attitudes. Psychological Science, 28(9), 1334–1344. https://doi.org/10.1177/0956797617709594 Open Google Scholar doi.org/10.5771/9783748929451
  571. Tans, G. (2018, October 11). For Businesses Big and Small, AI is the Great Equalizer. Linkedin. https://www.linkedin.com/pulse/businesses-big-small-ai-great-equalizer-gillian-tans Open Google Scholar doi.org/10.5771/9783748929451
  572. Tao, Q., & Veldhuis, R. (2010). Biometric authentication system on mobile personal devices. IEEE Transactions on Instrumentation and Measurement, 59(4), 763–773. Open Google Scholar doi.org/10.5771/9783748929451
  573. Tariq, S., Jeon, S., & Woo, S. S. (2021). Am I a Real or Fake Celebrity? Measuring Commercial Face Recognition Web APIs under Deepfake Impersonation Attack. ArXiv Preprint ArXiv:2103.00847. Open Google Scholar doi.org/10.5771/9783748929451
  574. Taylor, L. (2017). What is data justice? The case for connecting digital rights and freedoms globally. Big Data & Society, 4(2), 1–14. Open Google Scholar doi.org/10.5771/9783748929451
  575. Taylor, P. (2009). Text-to-speech synthesis. Cambridge University Press. Open Google Scholar doi.org/10.5771/9783748929451
  576. Tene, O., & Polonetsky, J. (2013). Big data for all: Privacy and user control in the age of analytics. Nw. J. Tech. & Intell. Prop., 11(5), 240–272. Open Google Scholar doi.org/10.5771/9783748929451
  577. Thaler, R. H., Sunstein, C. R., & Balz, J. P. (2013). Choice architecture. In E. Shafir (Ed.), The behavioral foundations of public policy (pp. 428–439). Princeton University Press. Open Google Scholar doi.org/10.5771/9783748929451
  578. The Royal Society. (2017). Machine learning: The power and promise of computers that learn by example. The Royal Society. https://royalsociety.org/-/media/policy/projects/machine-learning/publications/machine-learning-report.pdf Open Google Scholar doi.org/10.5771/9783748929451
  579. The State of Responsible AI: 2021. (2021). FICO. https://www.fico.com/en/resource-access/download/36776?access_token_9f4fd=3a3e8333dc8922948bee98cd1fd89cb11e2585415f725da6adf63342cb6e18d0 Open Google Scholar doi.org/10.5771/9783748929451
  580. Thelen, K. A. (2018). Regulating Uber: The politics of the platform economy in Europe and the United States. Perspectives on Politics, 16(4), 938–953. Open Google Scholar doi.org/10.5771/9783748929451
  581. Thompson, C. (2014). Smarter Than You Think: How Technology is Changing Our Minds for the Better. Harper Collins Australia. Open Google Scholar doi.org/10.5771/9783748929451
  582. Thompson, C. (2019). Coders: The making of a new tribe and the remaking of the world. Penguin Press. Open Google Scholar doi.org/10.5771/9783748929451
  583. Thrift, N. (1998). Virtual Capitalism: The Globalisation of Reflexive Business Knowledge. In J. Carrier & D. Miller (Eds.), Virtualism: A New Political Economy (pp. 161–186). Berg Publishers. Open Google Scholar doi.org/10.5771/9783748929451
  584. Tiernan, E. (2021, February 17). Massachusetts’ New Police Reform Law Misses First Deadline. Governing. https://www.governing.com/now/Massachusetts-New-Police-Reform-Law-Misses-First-Deadline.html Open Google Scholar doi.org/10.5771/9783748929451
  585. TradeCNBC. (2021, January 25). I wish @CNN cared as much about the riots that happened all summer. This #FacesOfTheRiot show is scary, like a McCarthy hearing, or Russian dissenter hunt [Tweet]. @TradeCNBC. https://twitter.com/TradeCNBC/status/1353549611638652929 Open Google Scholar doi.org/10.5771/9783748929451
  586. Tréguer, P. (2018, May 30). Meaning andOorigin of ‘to be unable to run a whelk stall.’ Word Histories. https://wordhistories.net/2018/05/30/unable-run-whelkstall/ Open Google Scholar doi.org/10.5771/9783748929451
  587. Trouvain, J., & Brackhane, F. (2011). Wolfgang von Kempelen’s speaking machine as an instrument for demonstration and research. Proceedings of the 17th International Conference of Phonetic Sciences, 164–167. Open Google Scholar doi.org/10.5771/9783748929451
  588. Tufekci, Z. (2014). Engineering the public: Big data, surveillance and computational politics. First Monday, 19(7). https://doi.org/10.5210/fm.v19i7.4901 Open Google Scholar doi.org/10.5771/9783748929451
  589. Tufekci, Z. (2018). YouTube, the great radicalizer. The New York Times. https://www.nytimes.com/2018/03/10/opinion/sunday/youtube-politics-radical.html Open Google Scholar doi.org/10.5771/9783748929451
  590. Turing, A. M. (1950). Computing Machinery and Intelligence. Mind, LIX(236), 433–460. https://doi.org/10.1093/mind/LIX.236.433 Open Google Scholar doi.org/10.5771/9783748929451
  591. Tutt, A. (2017). An FDA for algorithms. Admin. L. Rev., 69, 83–123. Open Google Scholar doi.org/10.5771/9783748929451
  592. UBI Hologram. (2021, January 24). Any #Facesoftheriot bounty hunters out there? We’re looking for a guy that owes us some money ... What the hell: I’ll toss another $100 on the pile. [Tweet]. @hologram_stan. https://twitter.com/hologram_stan/status/1353420876662755329 Open Google Scholar doi.org/10.5771/9783748929451
  593. United Nations Environment Programme. (2020). Principles for Responsible Investment Report 2020. PRI. https://www.unpri.org/download?ac=10948 Open Google Scholar doi.org/10.5771/9783748929451
  594. U.S. Federal Trade Commission. (2021, April 19). Aiming for truth, fairness, and equity in your company’s use of AI. Federal Trade Commission. https://www.ftc.gov/news-events/blogs/business-blog/2021/04/aiming-truth-fairness-equity-your-companys-use-ai Open Google Scholar doi.org/10.5771/9783748929451
  595. U.S. podcast advertising revenue 2019. (2020, July). Statista. https://www.statista.com/statistics/760791/us-podcast-advertising-revenue/ Open Google Scholar doi.org/10.5771/9783748929451
  596. Vaccari, C., & Chadwick, A. (2020). Deepfakes and disinformation: Exploring the impact of synthetic political video on deception, uncertainty, and trust in news. Social Media + Society, 6(1), 1–13. Open Google Scholar doi.org/10.5771/9783748929451
  597. Vallas, S. P. (2019). Platform capitalism: What’s at stake for workers? New Labor Forum, 28(1), 48–59. Open Google Scholar doi.org/10.5771/9783748929451
  598. van Heek, J., Arning, K., & Ziefle, M. (2016). The Surveillance Society: Which Factors Form Public Acceptance of Surveillance Technologies? In M. Helfert, C. Klein, B. Donnellan, & O. Gusikhin (Eds.), Smart Cities, Green Technologies, and Intelligent Transport Systems (pp. 170–191). Springer. Open Google Scholar doi.org/10.5771/9783748929451
  599. Van Hoof, J., Kort, H. S., Markopoulos, P., & Soede, M. (2007). Ambient intelligence, ethics and privacy. Gerontechnology, 6(3), 155–163. Open Google Scholar doi.org/10.5771/9783748929451
  600. Veblen, T. (1908a). On the nature of capital. Quarterly Journal of Economics, 23(1), 104–136. Open Google Scholar doi.org/10.5771/9783748929451
  601. Veblen, T. (1908b). Professor Clark’s economics. Quarterly Journal of Economics, 22(2), 147–195. Open Google Scholar doi.org/10.5771/9783748929451
  602. Venkatesh, Morris, Davis, & Davis. (2003). User Acceptance of Information Technology: Toward a Unified View. MIS Quarterly, 27(3), 425. https://doi.org/10.2307/30036540 Open Google Scholar doi.org/10.5771/9783748929451
  603. Venkatesh, V., Thong, J. Y. L., & Xu, X. (2012). Consumer Acceptance and Use of Information Technology: Extending the Unified Theory of Acceptance and Use of Technology. MIS Quarterly, 36(1), 157–178. https://doi.org/10.2307/41410412 Open Google Scholar doi.org/10.5771/9783748929451
  604. Vincent, J. (2016, June 29). Satya Nadella’s rules for AI are more boring (and relevant) than Asimov’s Three Laws. The Verge. https://www.theverge.com/2016/6/29/12057516/satya-nadella-ai-robot-laws Open Google Scholar doi.org/10.5771/9783748929451
  605. Vincent, J. (2020, July 27). This is what a deepfake voice clone used in a failed fraud attempt sounds like. The Verge. https://www.theverge.com/2020/7/27/21339898/deepfake-audio-voice-clone-scam-attempt-nisos Open Google Scholar doi.org/10.5771/9783748929451
  606. Vincent, J. (2021a, April 14). The EU is considering a ban on AI for mass surveillance and social credit scores. The Verge. https://www.theverge.com/2021/4/14/22383301/eu-ai-regulation-draft-leak-surveillance-social-credit Open Google Scholar doi.org/10.5771/9783748929451
  607. Vincent, J. (2021b, April 21). FBI used facial recognition to identify a Capitol rioter from his girlfriend’s Instagram posts. The Verge. https://www.theverge.com/2021/4/21/22395323/fbi-facial-recognition-us-capital-riots-tracked-down-suspect Open Google Scholar doi.org/10.5771/9783748929451
  608. Viola, P., & Jones, M. (2001). Rapid object detection using a boosted cascade of simple features. Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 1, I–I. Open Google Scholar doi.org/10.5771/9783748929451
  609. Viola, P., & Jones, M. J. (2004). Robust Real-Time Face Detection. International Journal of Computer Vision, 57(2), 137–154. Open Google Scholar doi.org/10.5771/9783748929451
  610. Vocally Yours (Round 5). (2018). Digital News Initiative. https://newsinitiative.withgoogle.com//dnifund/dni-projects/vocally-yours-round-5/ Open Google Scholar doi.org/10.5771/9783748929451
  611. Voiceitt: Home. (2021). Voiceitt. https://voiceitt.com/ Open Google Scholar doi.org/10.5771/9783748929451
  612. Von Kempelen, W. (1791). Mechanismus der menschlichen Sprache nebst der Beschreibung einer sprechenden Machine. Degen. Open Google Scholar doi.org/10.5771/9783748929451
  613. Wagner, E. L., Newell, S., & Piccoli, G. (2010). Understanding project survival in an ES environment: A sociomaterial practice perspective. Journal of the Association for Information Systems, 11(5), 276–297. Open Google Scholar doi.org/10.5771/9783748929451
  614. Wajcman, J. (2002). Addressing Technological Change: The Challenge to Social Theory. Current Sociology, 50(3), 347–363. https://doi.org/10.1177/0011392102050003004 Open Google Scholar doi.org/10.5771/9783748929451
  615. Walther, J. B. (1996). Computer-mediated communication: Impersonal, interpersonal, and hyperpersonal interaction. Communication Research, 23(1), 3–43. Open Google Scholar doi.org/10.5771/9783748929451
  616. Walther, J. B. (2007). Selective self-presentation in computer-mediated communication: Hyperpersonal dimensions of technology, language, and cognition. Computers in Human Behavior, 23(5), 2538–2557. Open Google Scholar doi.org/10.5771/9783748929451
  617. Walther, J. B., Van Der Heide, B., Ramirez, A., Burgoon, J. K., & Peña, J. (2015). Interpersonal and hyperpersonal dimensions of computer-mediated communication. In S. S. Sundar (Ed.), The handbook of the psychology of communication technology (pp. 1–22). Wiley & Sons. Open Google Scholar doi.org/10.5771/9783748929451
  618. Wang, Yilun, & Kosinski, M. (2018). Deep neural networks are more accurate than humans at detecting sexual orientation from facial images. Journal of Personality and Social Psychology, 114(2), 246. Open Google Scholar doi.org/10.5771/9783748929451
  619. Wang, Yuxuan, Skerry-Ryan, R. J., Stanton, D., Wu, Y., Weiss, R. J., Jaitly, N., Yang, Z., Xiao, Y., Chen, Z., Bengio, S., Le, Q., Agiomyrgiannakis, Y., Clark, R., & Saurous, R. A. (2017). Tacotron: Towards End-to-End Speech Synthesis. ArXiv:1703.10135 [Cs]. http://arxiv.org/abs/1703.10135 Open Google Scholar doi.org/10.5771/9783748929451
  620. Wardle, C., & Derakhshan, H. (2017). Information disorder: Toward an interdisciplinary framework for research and policy making. Council of Europe. https://rm.coe.int/information-disorder-toward-an-interdisciplinary-framework-for-researc/168076277c Open Google Scholar doi.org/10.5771/9783748929451
  621. Waytz, A., Heafner, J., & Epley, N. (2014). The mind in the machine: Anthropomorphism increases trust in an autonomous vehicle. Journal of Experimental Social Psychology, 52, 113–117. Open Google Scholar doi.org/10.5771/9783748929451
  622. Weber, M. (1968). Economy and Society: An outline of interpretive sociology. University of California Press. Open Google Scholar doi.org/10.5771/9783748929451
  623. Weber, S., & Stanton, C. (2019, October 2). The World Isn’t Ready for AI to Upend the Global Economy. Carnegie Endowment for International Peace. https://carnegieendowment.org/2019/10/02/world-isn-t-ready-for-ai-to-upend-global-economy-pub-79961 Open Google Scholar doi.org/10.5771/9783748929451
  624. Webster, F. (2014). Theories of the information society. Routledge. Open Google Scholar doi.org/10.5771/9783748929451
  625. Weick, K. E., Sutcliffe, K. M., & Obstfeld, D. (2005). Organizing and the process of sensemaking. Organization Science, 16(4), 409–421. Open Google Scholar doi.org/10.5771/9783748929451
  626. West, S. M. (2019). Data capitalism: Redefining the logics of surveillance and privacy. Business & Society, 58(1), 20–41. Open Google Scholar doi.org/10.5771/9783748929451
  627. Wiener, N. (1988). The human use of human beings: Cybernetics and society. Da Capo Press. Open Google Scholar doi.org/10.5771/9783748929451
  628. Wiener, N. (2019). Cybernetics or Control and Communication in the Animal and the Machine. MIT Press. Open Google Scholar doi.org/10.5771/9783748929451
  629. Wing, J. M. (2020). Trustworthy AI. ArXiv Preprint ArXiv:2002.06276. Open Google Scholar doi.org/10.5771/9783748929451
  630. Winner, L. (1977). Autonomous technology: Technics-out-of-control as a theme in political thought (9. printing). MIT Press. Open Google Scholar doi.org/10.5771/9783748929451
  631. Wood, A. J., Graham, M., Lehdonvirta, V., & Hjorth, I. (2019). Good gig, bad gig: Autonomy and algorithmic control in the global gig economy. Work, Employment and Society, 33(1), 56–75. Open Google Scholar doi.org/10.5771/9783748929451
  632. Wood, S. G., Moxley, J. H., Tighe, E. L., & Wagner, R. K. (2018). Does Use of Text-to-Speech and Related Read-Aloud Tools Improve Reading Comprehension for Students With Reading Disabilities? A Meta-Analysis. Journal of Learning Disabilities, 51(1), 73–84. https://doi.org/10.1177/0022219416688170 Open Google Scholar doi.org/10.5771/9783748929451
  633. Woodward, J. D., Horn, C., Gatune, J., & Thomas, A. (2003). Biometrics: A look at facial recognition. RAND. Open Google Scholar doi.org/10.5771/9783748929451
  634. Woolgar, S. (1991). The Turn to Technology in Social Studies of Science. Science, Technology, & Human Values, 16(1), 20–50. JSTOR. https://doi.org/10.1177/016224399101600102 Open Google Scholar doi.org/10.5771/9783748929451
  635. Woolley, B. (2015). The Bride of Science: Romance, reason and Byron’s daughter. Pan Macmillan. Open Google Scholar doi.org/10.5771/9783748929451
  636. Wu, X., & Zhang, X. (2016). Responses to Critiques on Machine Learning of Criminality Perceptions (Addendum of arXiv: 1611.04135). ArXiv Preprint ArXiv:1611.04135. Open Google Scholar doi.org/10.5771/9783748929451
  637. Yamamoto, R., Song, E., & Kim, J.-M. (2020). Parallel WaveGAN: A fast waveform generation model based on generative adversarial networks with multi-resolution spectrogram. ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 6199–6203. Open Google Scholar doi.org/10.5771/9783748929451
  638. Yong, S. (2013). Panopticism Technique in Crime Prevention Through Environmental Design (SSRN Scholarly Paper ID 3001563). Social Science Research Network. https://papers.ssrn.com/abstract=3001563 Open Google Scholar doi.org/10.5771/9783748929451
  639. Young, A. (1998). Towards an Interim Statistical Framework: Selecting the Core Components of Intangible Investment. OECD Secretariat. Open Google Scholar doi.org/10.5771/9783748929451
  640. Zarkadakis, G. (2015). In Our Own Image: Will artificial intelligence save or destroy us? Random House. Open Google Scholar doi.org/10.5771/9783748929451
  641. Zhang, D., Mishra, S., Brynjolfsson, E., Etchemendy, J., Ganguli, D., Grosz, B., Lyons, T., Manyika, J., Niebles, J. C., & Sellitto, M. (2021). The AI Index 2021 Annual Report. Human-Centered AI Institute, Stanford University. https://arxiv.org/pdf/2103.06312.pdf Open Google Scholar doi.org/10.5771/9783748929451
  642. Zhang, J.-X., Ling, Z.-H., & Dai, L.-R. (2018). Forward attention in sequence-to-sequence acoustic modeling for speech synthesis. 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 4789–4793. Open Google Scholar doi.org/10.5771/9783748929451
  643. Zielke, T., & Wolfer, R. C. (2008). Facing up to gambling addicts. Biometric Technology Today, 16(3), 10–11. Open Google Scholar doi.org/10.5771/9783748929451
  644. Zimmer, M. (2010). “But the data is already public”: On the ethics of research in Facebook. Ethics and Information Technology, 12(4), 313–325. Open Google Scholar doi.org/10.5771/9783748929451
  645. Zou, J., & Schiebinger, L. (2018). AI can be sexist and racist—It’s time to make it fair. Nature Publishing Group. Open Google Scholar doi.org/10.5771/9783748929451
  646. Zuboff, S. (1988). In the age of the smart machine: The future of work and power. Basic Books. Open Google Scholar doi.org/10.5771/9783748929451
  647. Zuboff, S. (2015). Big other: Surveillance capitalism and the prospects of an information civilization. Journal of Information Technology, 30(1), 75–89. https://doi.org/10.1057/jit.2015.5 Open Google Scholar doi.org/10.5771/9783748929451
  648. Zuboff, S. (2016, March 5). Google as a Fortune Teller: The Secrets of Surveillance Capitalism. Frankfurter Allgemeine Zeitung. https://www.faz.net/1.4103616 Open Google Scholar doi.org/10.5771/9783748929451
  649. Zuboff, S. (2019). The age of surveillance capitalism: The fight for a human future at the new frontier of power. Profile Books. Open Google Scholar doi.org/10.5771/9783748929451

Similar publications

from the topics "Computer and Internet", "Sociology General", "Cultural Sociology & Sociology of Knowledge", "Media Science, Communication Research"
Cover of book: Ethik der Kryptographie
Book Titles Full access
Laurence Lerch
Ethik der Kryptographie
Cover of book: Systemtheorie und Erzählen
Book Titles No access
Ralf Kellermann
Systemtheorie und Erzählen
Cover of book: Hinter der Lage
Book Titles No access
David Czudnochowski
Hinter der Lage
Cover of book: Konstruktiver Journalismus
Book Titles Full access
Julia Faltermeier
Konstruktiver Journalismus
Cover of book: Secular Humanism in Sweden
Book Titles No access
Susanne Kind
Secular Humanism in Sweden

Notice

This work is protected by copyright and may only be used in accordance with the provisions of the Terms of Use and License Agreement. Any use of the work beyond this is expressly prohibited and will be prosecuted.

Give feedback

We welcome your feedback on content and features. Your message helps us to continuously improve our service.

Rating
Attach images
or drag and drop
PNG or JPG (max. 3 MB)

Login

Forgotten your password?
Login via Open Athens
Don't have an account yet?
Register now

Cite publication

Download: RIS BibTex