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The Future Impact of Artificial Intelligence on Humans and Human Rights

Published online by Cambridge University Press:  07 June 2019


What are the implications of artificial intelligence (AI) on human rights in the next three decades? Precise answers to this question are made difficult by the rapid rate of innovation in AI research and by the effects of human practices on the adaption of new technologies. Precise answers are also challenged by imprecise usages of the term “AI.” There are several types of research that all fall under this general term. We begin by clarifying what we mean by AI. Most of our attention is then focused on the implications of artificial general intelligence (AGI), which entail that an algorithm or group of algorithms will achieve something like superintelligence. While acknowledging that the feasibility of superintelligence is contested, we consider the moral and ethical implications of such a potential development. What do machines owe humans and what do humans owe superintelligent machines?

Roundtable: Artificial Intelligence and the Future of Global Affairs
Copyright © Carnegie Council for Ethics in International Affairs 2019 

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1 For the nexus between human rights and AI, see Risse, Mathias, “Human Rights and Artificial Intelligence: An Urgently Needed Agenda,” Human Rights Quarterly 41, no. 1 (February 2019), pp. 116CrossRefGoogle Scholar.

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6 Regarding state surveillance, see Deibert, Ronald J., “The Road to Digital Unfreedom: Three Painful Truths about Social Media,” Journal of Democracy 30, no. 1 (January 2019), pp. 2539CrossRefGoogle Scholar; regarding corporate surveillance, see Zuboff, Age of Surveillance Capitalism; regarding open-source investigations by nonstate actors, see Steven Livingston and Sushma Raman, “Human Rights Documentation in Limited Access Areas: The Use of Technology in War Crimes and Human Rights Abuse Investigations” (Cambridge, Mass.: Carr Center for Human Rights Policy, May 2018),

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20 For a right-by-right discussion of the impact of AI on human rights, see Filippo A. Raso, Hannah Hilligoss, Vivek Krishnamurthy, Christopher Bavitz, and Levin Kim, “Artificial Intelligence & Human Rights: Opportunities & Risks,” Berkman Klein Center for Internet & Society at Harvard University, September 25, 2018, One topic we have not touched on here but should acknowledge because it is widely discussed is that of algorithmic fairness, which involves the responsible use of big data and machine learning in many domains of life; see, for instance, Barocas, Solon and Selbst, Andrew D., “Big Data's Disparate Impact,” California Law Review 104 (2016)Google Scholar.

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25 At the core of reinforcement learning is backpropogation and the Monte Carlo Tree Search. “Backpropagation” is shorthand for “the backward propagation of errors.” An error is computed at the output and distributed backward throughout the neural network's layers. For more on backpropagation, see the “Backpropogation” page on the DeepAI website: For the Monte Carlo Tree Search, see Martin Müller (2010), “Challenges in Monte Carlo Tree Search,”

26 Silver et al., “Mastering the Game of Go.”

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30 Ian Sample, “Google's DeepMind Predicts 3D Shapes of Proteins,” Guardian, December 2, 2018,

31 Oren Etzioni, quoted in Larry Greenemeier, “AI versus AI: Self-Taught AlphaGo Zero Vanquishes Its Predecessor,” Scientific American, October 18, 2017,; emphasis added.

32 Razvan Pascanu, Theophane Weber, Peter Battaglia, Yujia Li, Sébastien Recaniere, and David Reichert, “Agents That Imagine and Plan,” DeepMind, July 20, 2017,

33 AlphaStar team, “AlphaStar: Mastering the Real-Time Strategy Game Star-Craft II,” DeepMind, January 24, 2019,

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37 Isobel Asher Hamilton, “Elon Musk Believes AI Could Turn Humans into an Endangered Species like the Mountain Gorilla,” Business Insider, November 26, 2018,

38 Kurt Schlosser, “MIT Student Wows ‘60 Minutes’ by Surfing the Internet and Ordering Pizza — with His Mind,” GeekWire, April 23, 2018,

39 For explorations of such a blended world, see Marx Tegmark, Life 3.0: Being Human in the Age of Artificial Intelligence (New York: Knopf, 2017).

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46 Dennett, From Bacteria to Bach and Back, p. 400.

47 For the functionalist take on the mind, see Heil, Philosophy of Mind, ch. 6; for an early formulation of functionalism, see Putnam, Hilary, “Minds and Machines,” ch. 18 in Mind, Language, and Reality: Philosophical Papers, vol. 2 (Cambridge, U.K.: Cambridge University Press, 1975), pp. 362385CrossRefGoogle Scholar; for influential critical discussion, see Block, Ned, “Troubles with Functionalism,” in Block, Ned, ed., Readings in the Philosophy of Psychology, vols. 1 (Cambridge, Mass: Harvard University Press, 1980), pp. 268305Google Scholar.

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51 Elizabeth Glasure, “Artificial Intelligence Is the Next Big Player in Genomics,” Biospace, December 11, 2018,; Himanshu Goenka, “Bioterrorism and Gene Editing: Can Crispr Tool Be Used as Biological Weapon in War?,” International Business Times, December 14, 2016,; see also Antonio Regalado, “Top U.S. Intelligence Official Calls Gene Editing a WMD Threat,” MIT Technology Review, February 9, 2016, The H5N1 flu strain, for example, kills 60 percent of those it infects. Yet, among humans, it is not highly contagious. In 2011, researchers in the United States and Holland altered the H5N1 genome in a way that made its level of contagion high. A strain like this could “change world history if it were ever set free” by triggering a pandemic, “quite possibly with many millions of deaths.” Martin Enserink, “Scientists Brace for Media Storm around Controversial Flu Studies,” Science, November 23, 2011,

52 Stephen Hsu, “Super-Intelligent Humans Are Coming,” Nautilus, October 16, 2014,

53 Harari, Homo Deus, p. 4; emphasis added

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61 Page, Benjamin I., Seawright, Jason, and Lacombe, Mathew J., Billionaires and Stealth Politics (Chicago: University of Chicago Press, 2018)CrossRefGoogle Scholar; Mayer, Jane, Dark Money: The Hidden History of the Billionaires behind the Rise of the Radical Right (New York: Doubleday Press, 2016)Google Scholar.

62 The following paragraphs draw on Risse, “Human Rights and Artificial Intelligence.”

63 Hume, David, An Enquiry concerning the Principles of Morals, ed. by Schneewind, J. B. (London: Hackett Publishing, 1983)Google Scholar.

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65 Another way of thinking about the categorical imperative is that it requires us to always act in ways that would pass a generalization test. Certain actions would be rendered impermissible because they would not hold up if everybody were to take them, as, for instance, stealing and lying would not: there would be no property to begin with if everybody stole, and no communication if everybody reserved the right to lie.

66 Petersen, Steve, “Superintelligence as Superethical,” in Lin, Patrick, Abney, Keith, and Jenkins, Ryan, eds., Robot Ethics 2.0 (New York: Oxford University Press, 2017), pp. 332–7Google Scholar; Chalmers, David, “The Singularity: A Philosophical Analysis,” Journal of Consciousness Studies 17, nos. 9–10Google Scholar; see also “What Makes People Happy? / Daniel Kahneman,” YouTube video, 9:47, from a discussion with Professor Kahneman at the 2017 Asilomar conference, posted by the Future of Life Institute, January 30, 2017,

67 Scanlon, T. M., “What is Morality?” in The Harvard Sampler: Liberal Education in the Twenty-First Century, Shephard, Jennifer M., Kosslyn, Stephen M., Hammonds, Evelynn M., eds. (Cambridge, Mass.: Harvard University Press, 2011), pp. 243266Google Scholar

68 For speculation on what such mixed societies could be like, see Tegmark, Life 3.0, ch. 5.

69 For the point about Hobbes, see “Prof. Peter Railton — Machine Morality: Building or Learning?,” YouTube video, 33:56, posted by the Artificial Intelligence Channel, September 11, 2017,

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