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Social choice ethics in artificial intelligence

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Abstract

A major approach to the ethics of artificial intelligence (AI) is to use social choice, in which the AI is designed to act according to the aggregate views of society. This is found in the AI ethics of “coherent extrapolated volition” and “bottom–up ethics”. This paper shows that the normative basis of AI social choice ethics is weak due to the fact that there is no one single aggregate ethical view of society. Instead, the design of social choice AI faces three sets of decisions: standing, concerning whose ethics views are included; measurement, concerning how their views are identified; and aggregation, concerning how individual views are combined to a single view that will guide AI behavior. These decisions must be made up front in the initial AI design—designers cannot “let the AI figure it out”. Each set of decisions poses difficult ethical dilemmas with major consequences for AI behavior, with some decision options yielding pathological or even catastrophic results. Furthermore, non-social choice ethics face similar issues, such as whether to count future generations or the AI itself. These issues can be more important than the question of whether or not to use social choice ethics. Attention should focus on these issues, not on social choice.

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Notes

  1. Note that while consciousness may play a role in ethics learning among human children, it is not essential for AI. The essential feature is that ethics is learned via interaction with the environment, regardless of whether that interaction involves consciousness.

  2. One exception, in which social choice is (briefly) discussed in the context of CEV, is Tarleton (2010). Keyword searches in Google Scholar identified no other discussions of social choice in CEV or bottom-up ethics. There is a more extensive study of “computational social choice” relating aspects of social choice theory and computer science (Brandt et al. 2015).

  3. This is similar to the “boundary problem” in democracy (Arrhenius 2005).

  4. Martin (2017) also considers having AIs set their own ethics or the ethics of other AIs; more on this below.

  5. Tay was programmed to learn from (and thus give standing to) Twitter users who interact with it, which quickly devolved into deviance and obscenity as Twitter users taught it to misbehave. Microsoft has since been wrestling with the question of how to give standing to a more appropriate mix of people.

  6. There is a certain irony that some proponents of CEV speak in terms of giving standing only to humanity but also favor a transition to posthumanity (e.g., Bostrom 2008).

  7. For an argument against Benatar’s views, see Baum (2008).

  8. This happened in 2000 and 2016, when Al Gore and Hillary Clinton, respectively, received more votes from individual voters, but George W. Bush and Donald Trump, respectively, received more votes in the electoral college.

  9. There is no indication that Tay was designed with bottom–up ethics in mind, but the net result is the same in that Tay acquired its principles for behavior via input from the people it interacted with.

References

  • Adams FC (2008) Long-term astrophysical processes. In: Bostrom N, Ćirković MM (eds) Global catastrophic risks. Oxford University Press, Oxford, pp 33–47

    Google Scholar 

  • Allen C, Varner G, Zinser J (2000) Prolegomena to any future artificial moral agent. J Exp Theor Artif Intell 12:251–261

    MATH  Google Scholar 

  • Allen C, Smit I, Wallach W (2005) Artificial morality: top-down, bottom-up, and hybrid approaches. Ethics Inf Technol 7(3):149–155

    Google Scholar 

  • Anomaly J (2015) What’s wrong with factory farming? Public Health Ethics 8(3):246–254

    Google Scholar 

  • Arrhenius G (2005) The boundary problem in democratic theory. In: Tersman F (ed) Democracy unbound: basic explorations I. Filosofiska Institutionen, Stockholm, pp 14–29

    Google Scholar 

  • Arrhenius G (2011) The impossibility of a satisfactory population ethics. In: Dzhafarov E, Lacey P (eds) Descriptive and normative approaches to human behavior. World Scientific, Singapore, pp 1–26

    Google Scholar 

  • Arrhenius G, Rabinowicz W (2015) The value of existence. In: Hirose I, Olson J (eds) The Oxford handbook of value theory. Oxford University Press, Oxford, pp 424–443

    Google Scholar 

  • Arrow KJ (1951) Social choice and individual values. Wiley, New York

    MATH  Google Scholar 

  • Balliet D, Wu J, De Dreu CKW (2014) Ingroup favoritism in cooperation: a meta-analysis. Psychol Bull 140(6):1556–1581

    Google Scholar 

  • Baron RS (2005) So right it’s wrong: groupthink and the ubiquitous nature of polarized group decision making. Adv Exp Soc Psychol 37:219–253

    Google Scholar 

  • Baum SD (2008) Better to exist: a reply to Benatar. J Med Ethics 34(12):875–876

    Google Scholar 

  • Baum SD (2009) Description, prescription and the choice of discount rates. Ecol Econ 69(1):197–205

    Google Scholar 

  • Benatar D (2006) Better never to have been: the harm of coming into existence. Oxford University Press, Oxford

    Google Scholar 

  • Bohannon J (2015) Fears of an AI pioneer. Science 349(6245):252

    MathSciNet  MATH  Google Scholar 

  • Borenstein J, Arkin R (2016) Robotic nudges: the ethics of engineering a more socially just human being. Sci Eng Ethics 22(1):31–46

    Google Scholar 

  • Bostrom N (2008) Why I want to be a posthuman when I grow up. In: Gordijn B, Chadwick R (eds) Medical enhancement and posthumanity. Springer, Berlin, pp 107–136

    Google Scholar 

  • Bostrom N (2014) Superintelligence: paths, dangers, strategies. Oxford University Press, Oxford

    Google Scholar 

  • Brandt F, Conitzer V, Endriss U, Lang J, Procaccia AD (2015) Handbook of computational social choice. Cambridge University Press, Cambridge

    MATH  Google Scholar 

  • Buchanan A (2009) Moral status and human enhancement. Philos Public Aff 37(4):346–381

    Google Scholar 

  • Clark J (2016) Artificial intelligence has a ‘sea of dudes’ problem. Bloomberg, New York

    Google Scholar 

  • Cockell CS (2007) Originism: ethics and extraterrestrial life. J Br Interplanet Soc 60:147–153

    Google Scholar 

  • de Condorcet M (1785) Essai sur l’Application de l’Analyse à la Probabilité des Décisions Rendues à la Pluralité des Voix. L’imprimerie Royale, Paris

    Google Scholar 

  • Fossat P, Bacqué-Cazenave J, De Deurwaerdère P, Delbecque JP, Cattaert D (2014) Anxiety-like behavior in crayfish is controlled by serotonin. Science 344(6189):1293–1297

    Google Scholar 

  • Foucault M (1961) Folie et Déraison: Histoire de la Folie à l’âge Classique. Plon, Paris

    Google Scholar 

  • Frederick S, Loewenstein G, O’donoghue T (2002) Time discounting and time preference: a critical review. J Econ Lit 40(2):351–401

    Google Scholar 

  • Funk C, Kennedy B, Podrebarac Sciupac E (2016) U.S. public wary of biomedical technologies to ‘enhance’ human abilities. Pew Research Center

  • Gibbs S (2016) Microsoft’s racist chatbot returns with drug-smoking Twitter meltdown. The Guardian

  • Ginges J, Atran S, Medin D, Shikaki K (2007) Sacred bounds on rational resolution of violent political conflict. Proc Natl Acad Sci 104(18):7357–7360

    Google Scholar 

  • Goertzel B (2016) Infusing advanced AGIs with human-like value systems: two theses. J Evol Technol 26(1):50–72

    Google Scholar 

  • Hannon B (1998) How might nature value man? Ecol Econ 25:265–279

    Google Scholar 

  • Harsanyi JC (1996) Utilities, preferences, and substantive goods. Soc Choice Welf 14(1):129–145

    MathSciNet  MATH  Google Scholar 

  • Holbrook D (1997) The consequentialistic side of environmental ethics. Environ Values 6:87–96

    Google Scholar 

  • Hubbard FP (2011) ‘Do androids dream?’: Personhood and intelligent artifacts. Temple Law Rev 83:405–441

    Google Scholar 

  • Klein A (2016) Robot ranchers monitor animals on giant Australian farms. New Scientist

  • Lin P (2016) Why ethics matters for autonomous cars. In: Maurer M, Gerdes JC, Lenz B, Winner H (eds) Autonomous driving: technical, legal and social aspects. Springer, Berlin, pp 69–85

    Google Scholar 

  • Marglin SA (1963) The social rate of discount and the optimal rate of investment. Q J Econ 77(1):95–111

    Google Scholar 

  • Martin D (2017) Who should decide how machines make morally laden decisions? Sci Eng Ethics 23(4):951–967

    Google Scholar 

  • Mersky AC, Samaras C (2016) Fuel economy testing of autonomous vehicles. Transp Res Part C Emerg Technol 65:31–48

    Google Scholar 

  • Metz R (2014) Startup Knightscope is preparing to roll out human-size robot patrols. MIT Technol Rev

  • Muehlhauser L, Helm L (2012) Intelligence explosion and machine ethics. In: Eden A, Søraker J, Moor JH, Steinhart E (eds) Singularity hypotheses: a scientific and philosophical assessment. Springer, Berlin, pp 101–126

    Google Scholar 

  • Ng YK (1990) Welfarism and utilitarianism: a rehabilitation. Utilitas 2(2):171–193

    Google Scholar 

  • Ng YK (1999) Utility, informed preference, or happiness: following Harsanyi’s argument to its logical conclusion. Soc Choice Welf 16(2):197–216

    MATH  Google Scholar 

  • O’Malley-James JT, Cockell CS, Greaves JS, Raven JA (2014) Swansong biospheres II: the final signs of life on terrestrial planets near the end of their habitable lifetimes. Int J Astrobiol 13:229–243

    Google Scholar 

  • Openshaw S (1983) The modifiable areal unit problem. Geo Books, Norwich

    Google Scholar 

  • Pew Research Center (2017) Changing attitudes on gay marriage

  • Picard R (1997) Affective computing. MIT Press, Cambridge

    Google Scholar 

  • Ritov I, Baron J (1999) Protected values and omission bias. Organ Behav Hum Decis Process 79(2):79–94

    Google Scholar 

  • Rolston H III (1986) The preservation of natural value in the solar system. In: Hargrove EC (ed) Beyond spaceship Earth: environmental ethics and the solar system. Sierra Club Books, San Francisco, pp 140–182

    Google Scholar 

  • Rose JD, Arlinghaus R, Cooke SJ, Diggles BK, Sawynok W, Stevens ED, Wynne CDL (2014) Can fish really feel pain? Fish Fish 15(1):97–133

    Google Scholar 

  • Schienke EW, Tuana N, Brown DA, Davis KJ, Keller K, Shortle JS, Stickler M, Baum SD (2009) The role of the NSF Broader Impacts Criterion in enhancing research ethics pedagogy. Soc Epistemol 23(3–4):317–336

    Google Scholar 

  • Schienke EW, Baum SD, Tuana N, Davis KJ, Keller K (2011) Intrinsic ethics regarding integrated assessment models for climate management. Sci Eng Ethics 17(3):503–523

    Google Scholar 

  • Stone C (1972) Should trees have standing? Toward legal rights for natural objects. South Calif Law Rev 45:450–501

    Google Scholar 

  • Stone J, Fernandez NC (2008) To practice what we preach: the use of hypocrisy and cognitive dissonance to motivate behavior change. Soc Personal Psychol Compass 2(2):1024–1051

    Google Scholar 

  • Sunstein CR (2000) Standing for animals. UCLA Law Rev 47(5):1333–1368

    Google Scholar 

  • Tarleton N (2010) Coherent extrapolated volition: a meta-level approach to machine ethics. The Singularity Institute, Berkeley, CA

    Google Scholar 

  • Thaler R, Sunstein C (2008) Nudge: improving decisions about health, wealth, and happiness. Yale University Press, New Haven

    Google Scholar 

  • Tonn B (1996) A design for future-oriented government. Futures 28(5):413–431

    Google Scholar 

  • Wallach W, Allen C (2008) Moral machines: teaching robots right from wrong. Oxford University Press, Oxford

    Google Scholar 

  • Wallach W, Allen C, Smit I (2008) Machine morality: bottom-up and top-down approaches for modelling human moral faculties. AI & Soc 22(4):565–582

    Google Scholar 

  • Yampolskiy RV (2013) Artificial intelligence safety engineering: why machine ethics is a wrong approach. In: Müller VC (ed) Philosophy and theory of artificial intelligence. Springer, Berlin, pp 389–396

    Google Scholar 

  • Yazawa M (2016) Contested conventions: the struggle to establish the constitution and save the union, 1787–1789. Johns Hopkins University Press, Baltimore

    Google Scholar 

  • Yudkowsky E (2004) Coherent extrapolated volition. The Singularity Institute, San Francisco

    Google Scholar 

Download references

Acknowledgements

Anders Sandberg provided helpful discussion for the development of this paper. Tony Barrett and two anonymous reviewers provided helpful feedback on earlier drafts. Any errors or shortcomings in the paper are the author’s alone. Work on this paper was funded in part by Future of Life Institute Grant Number 2015-143911. The views in this paper are the author’s and are not necessarily the views of the Future of Life Institute or the Global Catastrophic Risk Institute.

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  1. Global Catastrophic Risk Institute, PO Box 40364, Washington, DC, 20016, USA

    Seth D. Baum

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Baum, S.D. Social choice ethics in artificial intelligence. AI & Soc 35, 165–176 (2020). https://doi.org/10.1007/s00146-017-0760-1

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