skip to main content
10.1145/3514094.3534146acmconferencesArticle/Chapter ViewAbstractPublication PagesaiesConference Proceedingsconference-collections
research-article
Open Access

Current and Near-Term AI as a Potential Existential Risk Factor

Published:27 July 2022Publication History

ABSTRACT

There is a substantial and ever-growing corpus of evidence and literature exploring the impacts of Artificial intelligence (AI) technologies on society, politics, and humanity as a whole. A separate, parallel body of work has explored existential risks to humanity, including but not limited to that stemming from unaligned Artificial General Intelligence (AGI). In this paper, we problematise the notion that current and near-term artificial intelligence technologies have the potential to contribute to existential risk by acting as intermediate risk factors, and that this potential is not limited to the unaligned AGI scenario. We propose the hypothesis that certain already-documented effects of AI can act as existential risk factors, magnifying the likelihood of previously identified sources of existential risk. Moreover, future developments in the coming decade hold the potential to significantly exacerbate these risk factors, even in the absence of artificial general intelligence. Our main contribution is a (non-exhaustive) exposition of potential AI risk factors and the causal relationships between them, focusing on how AI can affect power dynamics and information security. This exposition demonstrates that there exist causal pathways from AI systems to existential risks that do not presuppose hypothetical future AI capabilities.

Skip Supplemental Material Section

Supplemental Material

aies22_065.mp4

mp4

18.9 MB

References

  1. James M Acton. 2020. Cyber Warfare & Inadvertent Escalation. Dædalus, Vol. 149, 2 (2020), 133--149.Google ScholarGoogle ScholarCross RefCross Ref
  2. Dario Amodei, Chris Olah, Jacob Steinhardt, Paul Christiano, John Schulman, and Dan Mané. 2016. Concrete Problems in AI Safety. arxiv: 1606.06565 [cs.AI]Google ScholarGoogle Scholar
  3. Shahar Avin, Bonnie C. Wintle, Julius Weitzdörfer, Seán S. Ó hÉigeartaigh, William J. Sutherland, and Martin J. Rees. 2018. Classifying global catastrophic risks. Futures, Vol. 102 (2018), 20--26. https://doi.org/10.1016/j.futures.2018.02.001Google ScholarGoogle ScholarCross RefCross Ref
  4. Joseph B. Bak-Coleman, Mark Alfano, Wolfram Barfuss, Carl T. Bergstrom, Miguel A. Centeno, Iain D. Couzin, Jonathan F. Donges, Mirta Galesic, Andrew S. Gersick, Jennifer Jacquet, Albert B. Kao, Rachel E. Moran, Pawel Romanczuk, Daniel I. Rubenstein, Kaia J. Tombak, Jay J. Van Bavel, and Elke U. Weber. 2021. Stewardship of global collective behavior. Proceedings of the National Academy of Sciences, Vol. 118, 27 (2021). https://doi.org/10.1073/pnas.2025764118Google ScholarGoogle Scholar
  5. Seth D. Baum. 2020. Medium-Term Artificial Intelligence and Society. Information, Vol. 11, 6 (2020). https://doi.org/10.3390/info11060290Google ScholarGoogle Scholar
  6. Seth D. Baum, Stuart Armstrong, Timoteus Ekenstedt, Olle Häggström, Robin Hanson, Karin Kuhlemann, Matthijs M. Maas, James D. Miller, Markus Salmela, Anders Sandberg, Kaj Sotala, Phil Torres, Alexey Turchin, and Roman V. Yampolskiy. 2019. Long-term trajectories of human civilization. Foresight, Vol. 21, 1 (2019), 53--83. https://doi.org/10.1108/FS-04-2018-0037Google ScholarGoogle ScholarCross RefCross Ref
  7. BBC News. 2021. Australia News Code: What's this row with Facebook and Google all about? https://www.bbc.com/news/world-australia-56107028. Accessed: 2021-08-26.Google ScholarGoogle Scholar
  8. Lotfi Belkhir and Ahmed Elmeligi. 2018. Assessing ICT global emissions footprint: Trends to 2040 & recommendations. Journal of Cleaner Production, Vol. 177 (2018), 448--463. https://doi.org/10.1016/j.jclepro.2017.12.239Google ScholarGoogle ScholarCross RefCross Ref
  9. Max Born, Percy W. Bridgman, Albert Einstein, Leopold Infeld, Frederic Joliot-Curie, Herman J. Muller, Linus Pauling, Cecil F. Powell, Joseph Rotblat, Bertrand Russell, and Hideki Yukawa. 1955. Russell-Einstein Manifesto. Available at https://www.atomicheritage.org/key-documents/russell-einstein-manifesto. Accessed: 2022-03-01.Google ScholarGoogle Scholar
  10. Nick Bostrom. 2002. Existential Risks: Analyzing Human Extinction Scenarios and Related Hazards. Journal of Evolution and Technology, Vol. 9 (2002). https://www.nickbostrom.com/existential/risks.pdfGoogle ScholarGoogle Scholar
  11. Nick Bostrom. 2014. Superintelligence: Paths, Dangers, Strategies. Oxford University Press.Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. Nick Bostrom and Milan M. Ćirković. 2008. Global Catastrophic Risks. Oxford University Press.Google ScholarGoogle Scholar
  13. Vincent Boulanin, Shahar Avin, Frank Sauer, John Borrie, Dimitri Scheftelowitsch, Justin Bronk, Page O. Stoutland, Martin Hagström, Petr Topychkanov, Michael C. Horowitz, Anja Kaspersen, Chris King, S.M. Amadae, and Jean-Marc Rickli. 2019. The Impact of Artificial Intelligence on Strategic Stability and Nuclear Risk, Volume I, Euro-Atlantic Perspectives. Technical Report. SIPRI.Google ScholarGoogle Scholar
  14. Miles Brundage, Shahar Avin, Jack Clark, Helen Toner, Peter Eckersley, Ben Garfinkel, Allan Dafoe, Paul Scharre, Thomas Zeitzoff, Bobby Filar, Hyrum Anderson, Heather Roff, Gregory C. Allen, Jacob Steinhardt, Carrick Flynn, Seán ÓhÉigeartaigh, Simon Beard, Haydn Belfield, Sebastian Farquhar, Clare Lyle, Rebecca Crootof, Owain Evans, Michael Page, Joanna Bryson, Roman Yampolskiy, and Dario Amodei. 2018. The Malicious Use of Artificial Intelligence: Forecasting, Prevention, and Mitigation. Technical Report. https://maliciousaireport.com/Google ScholarGoogle Scholar
  15. Ben Buchanan and Andrew Imbrie. 2022. The New Fire: War, Peace, and Democracy in the Age of AI. MIT Press.Google ScholarGoogle Scholar
  16. Toon Calders, Eirini Ntoutsi, Mykola Pechenizkiy, Bodo Rosenhahn, and Salvatore Ruggieri. 2021. Introduction to The Special Section on Bias and Fairness in AI. ACM SIGKDD Explorations Newsletter, Vol. 23, 1 (2021), 1--3.Google ScholarGoogle ScholarDigital LibraryDigital Library
  17. Ewen Callaway. 2021. DeepMind's AI predicts structures for a vast trove of proteins. Nature, Vol. 595 (Jul 2021), 635. https://doi.org/10.1038/d41586-021-02025-4Google ScholarGoogle Scholar
  18. Joseph Carlsmith. 2021. Is power-seeking AI an existential risk? Technical Report. Open Philanthropy. Draft report available at https://www.lesswrong.com/posts/HduCjmXTBD4xYTegv/draft-report-on-existential-risk-from-power-seeking-ai.Google ScholarGoogle Scholar
  19. Bobby Chesney and Danielle Citron. 2019. Deep fakes: A looming challenge for privacy, democracy, and national security. Calif. L. Rev., Vol. 107 (2019), 1753.Google ScholarGoogle Scholar
  20. Brian Christian. 2021. The Alignment Problem: How Can Machines Learn Human Values? Atlantic Books Ltd.Google ScholarGoogle Scholar
  21. Paul Christiano. 2019. What Failure Looks Like. https://www.lesswrong.com/posts/HBxe6wdjxK239zajf/what-failure-looks-like. Accessed: 2022-03-02.Google ScholarGoogle Scholar
  22. Wendy Hui Kyong Chun. 2021. Discriminating Data: Correlation, Neighborhoods, and the New Politics of Recognition. MIT Press.Google ScholarGoogle ScholarCross RefCross Ref
  23. Matteo Cinelli, Gianmarco De Francisci Morales, Alessandro Galeazzi, Walter Quattrociocchi, and Michele Starnini. 2021. The echo chamber effect on social media. Proceedings of the National Academy of Sciences, Vol. 118, 9 (2021). https://doi.org/10.1073/pnas.2023301118Google ScholarGoogle Scholar
  24. Owen Cotton-Barratt, Max Daniel, and Anders Sandberg. 2020. Defence in Depth Against Human Extinction: Prevention, Response, Resilience, and Why They All Matter. Global Policy, Vol. 11, 3 (2020), 271--282. https://doi.org/10.1111/1758--5899.12786Google ScholarGoogle ScholarCross RefCross Ref
  25. Joshua Coupe, Charles G. Bardeen, Alan Robock, and Owen B. Toon. 2019. Nuclear Winter Responses to Nuclear War Between the United States and Russia in the Whole Atmosphere Community Climate Model Version 4 and the Goddard Institute for Space Studies ModelE. Journal of Geophysical Research: Atmospheres, Vol. 124, 15 (2019), 8522--8543. https://doi.org/10.1029/2019JD030509Google ScholarGoogle ScholarCross RefCross Ref
  26. Kate Crawford. 2021. The Atlas of AI. Yale University Press.Google ScholarGoogle Scholar
  27. Kate Crawford, Roel Dobbe, Theodora Dryer, Genevieve Fried, Ben Green, Elizabeth Kaziunas, Amba Kak, Varoon Mathur, Erin McElroy, Andrea Nill Sánchez, Deborah Raji, Joy Lisi Rankin, Rashida Richardson, Jason Schultz, Sarah Myers West, and Meredith Whittaker. 2019. AI Now 2019 Report. Technical Report. New York: AI Now Institute. https://ainowinstitute.org/AI_Now_2019_Report.htmlGoogle ScholarGoogle Scholar
  28. Allan Dafoe. 2020. AI Governance: Oppotunity and Theory of Impact. https://www.andafoe.com/opportunity. Accessed: 2021-08--26.Google ScholarGoogle Scholar
  29. Shiri Dori-Hacohen, Keen Sung, Jengyu Chou, and Julian Lustig-Gonzalez. 2021. Restoring Healthy Online Discourse by Detecting and Reducing Controversy, Misinformation, and Toxicity Online. Association for Computing Machinery, New York, NY, USA, 2627--2628.Google ScholarGoogle ScholarDigital LibraryDigital Library
  30. K. Eric Drexler. 2019. Reframing Superintelligence: Comprehensive AI Services as General Intelligence. Technical Report. Future of Humanity Institute.Google ScholarGoogle Scholar
  31. Vasisht Duddu. 2018. A survey of adversarial machine learning in cyber warfare. Defence Science Journal, Vol. 68, 4 (2018), 356.Google ScholarGoogle ScholarCross RefCross Ref
  32. Tom Everitt, Gary Lea, and Marcus Hutter. 2018. AGI Safety Literature Review. arxiv: 1805.01109 [cs.AI]Google ScholarGoogle Scholar
  33. Marina Favaro. 2021. Weapons of Mass Distortion: A new approach to emerging technologies, risk reduction, and the global nuclear order. Technical Report. Centre for Science and Security Studies. https://www.kcl.ac.uk/csss/assets/weapons-of-mass-distortion.pdfGoogle ScholarGoogle Scholar
  34. Steven Feldstein. 2019. The Global Expansion of AI Surveillance. https://carnegieendowment.org/files/WP-Feldstein-AISurveillance_final1.html. Accessed: 2021-08--26.Google ScholarGoogle Scholar
  35. Center for Humane Technology. 2021. Ledger of Harms. https://ledger.humanetech.com/.Google ScholarGoogle Scholar
  36. Ben Garfinkel and Allan Dafoe. 2019. How does the offense-defense balance scale? Journal of Strategic Studies, Vol. 42, 6 (2019), 736--763. https://doi.org/10.1080/01402390.2019.1631810Google ScholarGoogle ScholarCross RefCross Ref
  37. Peter Giger. 2020. COVID-19 could distract the world from even greater threats. https://www.weforum.org/agenda/2020/10/covid-19-distract-world-greater-threats/. Accessed: 2021-08-26.Google ScholarGoogle Scholar
  38. Kristina Gligorić, Ashton Anderson, and Robert West. 2019. Causal Effects of Brevity on Style and Success in Social Media. Proc. ACM Hum.-Comput. Interact., Vol. 3, CSCW, Article 45 (2019), 23 pages. https://doi.org/10.1145/3359147Google ScholarGoogle ScholarDigital LibraryDigital Library
  39. Ross Gruetzemacher and Jess Whittlestone. 2022. The transformative potential of artificial intelligence. Futures, Vol. 135 (2022). https://www.sciencedirect.com/science/article/pii/S0016328721001932Google ScholarGoogle Scholar
  40. Caroline Haskins. 2019. Amazon Is Coaching Cops on How to Obtain Surveillance Footage Without a Warrant. https://www.vice.com/en/article/43kga3/amazon-is-coaching-cops-on-how-to-obtain-surveillance-footage-without-a-warrant. Accessed: 2021-08-26.Google ScholarGoogle Scholar
  41. Dan Hendrycks, Nicholas Carlini, John Schulman, and Jacob Steinhardt. 2021. Unsolved Problems in ML Safety. arxiv: 2109.13916 [cs.LG]Google ScholarGoogle Scholar
  42. Tim Hwang. 2020. Subprime Attention Crisis: Advertising and the Time Bomb at the Heart of the Internet. FSG originals.Google ScholarGoogle Scholar
  43. Thomas V. Ingelsby and Amesh A. Adalja. 2019. Global Catastrophic Biological Risks. Springer.Google ScholarGoogle Scholar
  44. Kokil Jaidka, Alvin Zhou, and Yphtach Lelkes. 2019. Brevity is the Soul of Twitter: The Constraint Affordance and Political Discussion. Journal of Communication, Vol. 69, 4 (2019), 345--372. https://doi.org/10.1093/joc/jqz023Google ScholarGoogle ScholarCross RefCross Ref
  45. Shagun Jhaver, Sucheta Ghoshal, Amy Bruckman, and Eric Gilbert. 2018. Online Harassment and Content Moderation: The Case of Blocklists. ACM Trans. Comput.-Hum. Interact., Vol. 25, 2 (2018), 1--33. https://doi.org/10.1145/3185593Google ScholarGoogle ScholarDigital LibraryDigital Library
  46. James Johnson. 2019. Artificial intelligence & future warfare: implications for international security. Defense & Security Analysis, Vol. 35, 2 (2019), 147--169. https://doi.org/10.1080/14751798.2019.1600800Google ScholarGoogle ScholarCross RefCross Ref
  47. Lynn Kaack, Priya Donti, Emma Strubell, George Kamiya, Felix Creutzig, and David Rolnick. 2021. Aligning artificial intelligence with climate change mitigation. (2021). hal-03368037.Google ScholarGoogle Scholar
  48. Lynn Kaack, Priya Donti, Emma Strubell, and David Rolnick. 2020. Artificial Intelligence and Climate Change: Opportunities, considerations, and policy levers to align AI with climate change goals. https://eu.boell.org/en/2020/12/03/artificial-intelligence-and-climate-change Heinrich-Böll-Stiftung, Ecology.Google ScholarGoogle Scholar
  49. Dimitris Kalimeris, Smriti Bhagat, Shankar Kalyanaraman, and Udi Weinsberg. 2021. Preference Amplification in Recommender Systems. In Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining (Virtual Event, Singapore) (KDD '21). Association for Computing Machinery, New York, NY, USA, 805--815. https://doi.org/10.1145/3447548.3467298Google ScholarGoogle ScholarDigital LibraryDigital Library
  50. Mark Kaufman. 2020. The carbon footprint sham. https://mashable.com/feature/carbon-footprint-pr-campaign-sham. Accessed: 2021-08--26.Google ScholarGoogle Scholar
  51. Parag Khanna. 2019. The Future is Asian: Commerce, Conflict, and Culture in the 21st Century. Simon & Schuster.Google ScholarGoogle Scholar
  52. David Krueger, Tegan Maharaj, Shane Legg, and Jan Leike. 2019. Misleading Meta-Objectives and Hidden Incentives for Distributional Shift. Workshop on Safe Machine Learning at the 7th International Conference on Learning Representations (ICLR 2019) (2019), 1--7.Google ScholarGoogle Scholar
  53. John Leslie. 1996. The End of the World: The Science and Ethics of Human Extinction. Routledge.Google ScholarGoogle Scholar
  54. Herbert Lin. 2019. The existential threat from cyber-enabled information warfare. Bulletin of the Atomic Scientists, Vol. 75, 4 (2019), 187--196. https://doi.org/10.1080/00963402.2019.1629574Google ScholarGoogle ScholarCross RefCross Ref
  55. Hin-Yan Liu, Kristian Cedervall Lauta, and Matthijs Michiel Maas. 2018. Governing Boring Apocalypses: A new typology of existential vulnerabilities and exposures for existential risk research. Futures, Vol. 102 (2018), 6--19.Google ScholarGoogle ScholarCross RefCross Ref
  56. Amanda Lotz. 2019. Amazon, Google and Facebook warrant antitrust scrutiny for many reasons -- not just because they're large. https://theconversation.com/amazon-google-and-facebook-warrant-antitrust-scrutiny-for-many-reasons-not-just-because-theyre-large-118370Google ScholarGoogle Scholar
  57. Kim Lyons. 2021. Amazon's Ring now reportedly partners with more than 2,000 US police and fire departments. https://www.theverge.com/2021/1/31/22258856/amazon-ring-partners-police-fire-security-privacy-cameras. Accessed: 2021-08--26.Google ScholarGoogle Scholar
  58. Matthijs M. Maas, Kayla Matteuci, and Di Cooke. 2022. Military Artificial Intelligence as Contributor to Global Catastrophic Risk. In Cambridge Conference on Catastrophic Risks 2020. Draft available at https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4115010.Google ScholarGoogle ScholarCross RefCross Ref
  59. Markets & Markets. 2019. AI in Cybersecurity Market. https://www.marketsandmarkets.com/market-reports/ai-in-cybersecurity-market-224437074.html. Accessed: 2021-08--26.Google ScholarGoogle Scholar
  60. Wayne M. Morrison. 2019. China's Economic Rise: History, Trends, Challenges, and Implications for the United States. Technical Report. Congressional Research Service.Google ScholarGoogle Scholar
  61. Robert S Mueller. 2019. The Mueller report: Report on the investigation into Russian interference in the 2016 presidential election. WSBLD.Google ScholarGoogle Scholar
  62. OECD. 2021. 130 countries and jurisdictions join bold new framework for international tax reform. https://www.oecd.org/newsroom/130-countries-and-jurisdictions-join-bold-new-framework-for-international-tax-reform.htm. Accessed: 2021-08-26.Google ScholarGoogle Scholar
  63. Jonathan Corpus Ong and Jason Vincent A. Caba nes. 2018. Architects of networked disinformation: Behind the scenes of troll accounts and fake news production in the Philippines. https://doi.org/10.7275/2cq4-5396Google ScholarGoogle Scholar
  64. Toby Ord. 2020. The Precipice: Existential Risk and the Future of Humanity. Hachette Books.Google ScholarGoogle Scholar
  65. Naomi Oreskes and Erik M. Conway. 2010. Merchants of Doubt: How a Handful of Scientists Obscured the Truth on Issues from Tobacco Smoke to Global Warming. Bloomsbury Publishing.Google ScholarGoogle Scholar
  66. Eli Pariser. 2011. The Filter Bubble: How the New Personalized Web Is Changing What We Read and How We Think. Penguin.Google ScholarGoogle ScholarDigital LibraryDigital Library
  67. Richard Posner. 2004. Catastrophe: Risk and Response. Oxford University Press.Google ScholarGoogle ScholarCross RefCross Ref
  68. Carina Prunkl and Jess Whittlestone. 2020. Beyond Near- and Long-Term: Towards a Clearer Account of Research Priorities in AI Ethics and Society. In Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society. Association for Computing Machinery, New York, NY, USA, 138--143. https://doi.org/10.1145/3375627.3375803Google ScholarGoogle ScholarDigital LibraryDigital Library
  69. Martin Rees. 2003. Our Final Century: Will the Human Race Survive the Twenty-First Century? William Heinemann.Google ScholarGoogle Scholar
  70. Cheerala Rohith and Ranbir Singh Batth. 2019. Cyber Warfare: Nations Cyber Conflicts, Cyber Cold War Between Nations and its Repercussion. In 2019 International Conference on Computational Intelligence and Knowledge Economy (ICCIKE). IEEE, 640--645.Google ScholarGoogle ScholarCross RefCross Ref
  71. David Rolnick, Priya L. Donti, Lynn H. Kaack, Kelly Kochanski, Alexandre Lacoste, Kris Sankaran, Andrew Slavin Ross, Nikola Milojevic-Dupont, Natasha Jaques, Anna Waldman-Brown, Alexandra Sasha Luccioni, Tegan Maharaj, Evan D. Sherwin, S. Karthik Mukkavilli, Konrad P. Kording, Carla P. Gomes, Andrew Y. Ng, Demis Hassabis, John C. Platt, Felix Creutzig, Jennifer Chayes, and Yoshua Bengio. 2022. Tackling Climate Change with Machine Learning. ACM Comput. Surv., Vol. 55, 2 (2022), 96 pages. https://doi.org/10.1145/3485128Google ScholarGoogle ScholarDigital LibraryDigital Library
  72. Stuart Russell. 2019 a. Human Compatible: Artificial Intelligence and the Problem of Control. Viking Books.Google ScholarGoogle Scholar
  73. Stuart J. Russell. 2019 b. Stuart J. Russell on Filter Bubbles and the Future of Artificial Intelligence. https://www.youtube.com/watch?v=ZkV7anCPfaY&ab_channel=LongNowFoundation. Accessed: 2021-08-26.Google ScholarGoogle Scholar
  74. Lora Saalman, Hwang Ji-Hwan, Su Fei, Jiang Tianjiao, Vasily Kashin, Kim Ji-Sun, Vadim Kozyulin, Arie Koichi, Li Xiang, Cai Cuihong, Liu Yangyue, Hwang Il-Soon, and Nishida Michiru. 2019. The Impact of Artificial Intelligence on Strategic Stability and Nuclear Risk, Volume II, East Asian Perspectives. Technical Report. SIPRI.Google ScholarGoogle Scholar
  75. Kaylyn Jackson Schiff, Daniel S. Schiff, and Natália S Bueno. 2021. The Liar's Dividend: The Impact of Deepfakes and Fake News on Trust in Political Discourse. (2021). https://doi.org/10.17605/OSF.IO/QPXR8.Google ScholarGoogle Scholar
  76. Eric Schmidt, Robert Work, Safra Catz, Eric Horvitz, Steve Chien, Andrew Jassy, Clyburn Mignon, Gilman Louie, Chris Darby, Willian Mark, Kenneth Ford, Jason Matheny, José-Marie Griffiths, Katharina McFarland, and Andrew Moore. 2021. Final Report. Technical Report. National Security Commission on Artificial Intelligence. https://www.nscai.gov/wp-content/uploads/2021/03/Full-Report-Digital-1.pdfGoogle ScholarGoogle Scholar
  77. Bruce Schneier. 2018. Click Here to Kill Everybody: Security and Survival in a Hyper-connected World. W. W. Norton & Company.Google ScholarGoogle Scholar
  78. Elizabeth Seger, Shahar Avin, Gavin Pearson, Mark Briers, Seán Ó hÉigeartaigh, and Helena Bacon. 2020. Tackling threats to informed decision-making in democratic societies: Promoting epistemic security in a technologicall-advanced world. Technical Report. The Alan Turing Institute, Defence and Security Programme. https://www.cser.ac.uk/resources/epistemic-security/Google ScholarGoogle Scholar
  79. Bhakti Sharma, Susanna S. Lee, and Benjamin K. Johnson. 2022. The Dark at the End of the Tunnel: Doomscrolling on Social Media Newsfeeds. Technology, Mind, and Behavior, Vol. 3, 1 (2022). https://tmb.apaopen.org/pub/nn9uaqsz.Google ScholarGoogle Scholar
  80. Emma Strubell, Ananya Ganesh, and Andrew McCallum. 2019. Energy and Policy Considerations for Deep Learning in NLP. arxiv: 1906.02243 [cs.CL]Google ScholarGoogle Scholar
  81. Cass R. Sunstein. 2018. # Republic: Divided Democracy in the Age of Social Media. Princeton University Press.Google ScholarGoogle Scholar
  82. Mariarosaria Taddeo, Tom McCutcheon, and Luciano Floridi. 2019. Trusting Artificial Intelligence in Cybersecurity is a Double-Edged Sword. Nat Mach Intell, Vol. 1 (2019), 557--560. https://doi.org/10.1038/s42256-019-0109--1Google ScholarGoogle ScholarCross RefCross Ref
  83. Petr Topychkanov, Kritika Roy, Saima Aman Sial, Dmitry Stefanovich, Maaike Verbruggen, Sanatan Kulshrestha, Yanitra Kumaraguru, and Malinda Meegoda. 2030. The Impact of Artificial Intelligence on Strategic Stability and Nuclear Risk, Volume III, South Asian Perspectives. Technical Report. SIPRI.Google ScholarGoogle Scholar
  84. Fabio Urbina, Filippa Lentzos, Cédric Invernizzi, and Sean Ekins. 2022. Dual use of artificial-intelligence-powered drug discovery. Nature Machine Intelligence, Vol. 4 (2022), 189--191. https://doi.org/10.1038/s42256-022-00465-9Google ScholarGoogle ScholarCross RefCross Ref
  85. Michela Del Vicario, Alessandro Bessi, Fabiana Zollo, Fabio Petroni, Antonio Scala, Guido Caldarelli, H. Eugene Stanley, and Walter Quattrociocchi. 2016. The spreading of misinformation online. Proceedings of the National Academy of Sciences, Vol. 113, 3 (2016), 554--559. https://doi.org/10.1073/pnas.1517441113Google ScholarGoogle ScholarCross RefCross Ref
  86. Graham Webster, Rogier Creemers, Paul Triolo, and Elsa Kania. 2017. Full Translation: China's `New Generation Artificial Intelligence Development Plan' (2017). https://www.newamerica.org/cybersecurity-initiative/digichina/blog/full-translation-chinas-new-generation-artificial-intelligence-development-plan-2017/. Accessed: 2021-08-26.Google ScholarGoogle Scholar
  87. Meredith Whittaker, Kate Crawford, Roel Dobbe, Genevieve Fried, Elizabeth Kaziunas, Varoon Mathur, Sarah Myers West, Rashida Richardson, Jason Schultz, and Oscar Schwartz. 2018. AI Now 2018 Report. Technical Report. New York: AI Now Institute. https://ainowinstitute.org/AI_Now_2018_Report.htmlGoogle ScholarGoogle Scholar
  88. Jess Whittlestone, Kai Arulkumaran, and Matthew Crosby. 2021. The Societal Implications of Deep Reinforcement Learning. J. Artif. Int. Res., Vol. 70 (2021), 1003--1030. https://doi.org/10.1613/jair.1.12360Google ScholarGoogle ScholarDigital LibraryDigital Library
  89. Nadine Wirkuttis and Hadas Klein. 2017. Artificial intelligence in cybersecurity. Cyber, Intelligence, and Security, Vol. 1, 1 (2017), 103--119.Google ScholarGoogle Scholar
  90. Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Hachette UK.Google ScholarGoogle Scholar
  91. Remco Zwetsloot and Allan Dafoe. 2019. Thinking About Risks From AI: Accidents, Misuse and Structure. Lawfare (2019). https://www.lawfareblog.com/thinking-about-risks-ai-accidents-misuse-and-structure.Google ScholarGoogle Scholar

Index Terms

  1. Current and Near-Term AI as a Potential Existential Risk Factor

              Recommendations

              Comments

              Login options

              Check if you have access through your login credentials or your institution to get full access on this article.

              Sign in
              • Published in

                cover image ACM Conferences
                AIES '22: Proceedings of the 2022 AAAI/ACM Conference on AI, Ethics, and Society
                July 2022
                939 pages
                ISBN:9781450392471
                DOI:10.1145/3514094

                Copyright © 2022 Owner/Author

                Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

                Publisher

                Association for Computing Machinery

                New York, NY, United States

                Publication History

                • Published: 27 July 2022

                Check for updates

                Qualifiers

                • research-article

                Acceptance Rates

                Overall Acceptance Rate61of162submissions,38%

              PDF Format

              View or Download as a PDF file.

              PDF

              eReader

              View online with eReader.

              eReader