Location via proxy:   [ UP ]  
[Report a bug]   [Manage cookies]                
Skip to main content

Advertisement

AI and society: a virtue ethics approach

  • Open Forum
  • Published:
AI & SOCIETY Aims and scope Submit manuscript

Abstract

Advances in artificial intelligence and robotics stand to change many aspects of our lives, including our values. If trends continue as expected, many industries will undergo automation in the near future, calling into question whether we can still value the sense of identity and security our occupations once provided us with. Likewise, the advent of social robots driven by AI, appears to be shifting the meaning of numerous, long-standing values associated with interpersonal relationships, like friendship. Furthermore, powerful actors’ and institutions’ increasing reliance on AI to make decisions that may affect how people live their lives may have a significant impact on privacy while also raising issues about algorithmic transparency and human control. In this paper, building and expanding on previous works, we will look at how the deployment of Artificial Intelligence technology may lead to changes in identity, security, and other crucial values (such as friendship, fairness, and privacy). We will discuss what challenges we may face in the process, while critically reflecting on whether such changes may be desirable. Finally, drawing on a series of considerations underlying virtue ethics, we will formulate a set of preliminary suggestions, which—we hope—can be used to more carefully guide the future roll out of AI technologies for human flourishing; that is, for social and moral good.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

Explore related subjects

Discover the latest articles, news and stories from top researchers in related subjects.

Data Availability Statement

The manuscript has no associated data.

Notes

  1. https://sitn.hms.harvard.edu/flash/2017/history-artificial-intelligence/ (Last Accessed September 2022).

  2. http://www.gov.cn/zhengce/content/2017-07/20/content5211996.html (Last Accessed September 2022).

  3. https://www.ai.gov/ (Last Accessed September 2022).

  4. http://en.kremlin.ru/events/president/news/57425 (Last Accessed September 2022).

  5. https://ec.europa.eu/futurium/en/ai-alliance-consultation.1.html (Last Accessed September 2022).

  6. An example at: https://github.com/git/git/commit/e194cd1e0e08611462eb9c5a731a7a3d797f9252 (Last Accessed September 2022).

  7. https://www.yegor256.com/2018/03/21/zerocracy-announcement.html (Last Accessed September 2022); https://patents.google.com/patent/US20120023476A1/en (Last Accessed September 2022).

  8. https://slate.com/technology/2016/06/microsoft-ceo-satya-nadella-humans-and-a-i-can-work-together-to-solve-societys-challenges.html (Last Accessed September 2022).

  9. https://www.ibm.com/blogs/think/2017/01/ibm-cognitive-principles/ (Last Accessed September 2022).

  10. https://tadviser.com/index.php/Product:PromobotRobo-C (Last Accessed September 2022).

  11. https://physicstoday.scitation.org/doi/10.1063/1.2731975 (Last Accessed September 2022).

  12. http://publication.pravo.gov.ru/File/GetFile/0001202004240030?type=pdf (Last Accessed September 2022).

References

  • Abeliansky A, Prettner K (2017) Automation and demographic change. Available at SSRN 2959977 518:1–44

  • Acemoglu D, Restrepo P (2020) Robots and jobs: evidence from us labor markets. J Polit Econ 128(6):2188–2244

    Google Scholar 

  • Ahuja AS (2019) The impact of artificial intelligence in medicine on the future role of the physician. PeerJ 7:7702

    Google Scholar 

  • Alemi M, Ghanbarzadeh A, Meghdari A, Moghadam LJ (2016) Clinical application of a humanoid robot in pediatric cancer interventions. Int J Soc Robot 8(5):743–759

    Google Scholar 

  • Altman R (2015) Distribute AI benefits fairly. Nature 521(7553):417–418

    Google Scholar 

  • Alvarado R (2021) Should we replace radiologists with deep learning? Pigeons, error and trust in medical AI. Bioethics 36:121–133

    Google Scholar 

  • Anderson SL, Anderson M (2011) A prima facie duty approach to machine ethics and its application to elder care. In: Workshops at the twenty-fifth AAAI conference on artificial intelligence, pp 2–7

  • Arendt H (1950) The human condition. University of Chicago Press, Chicago

    Google Scholar 

  • Arntz M, Gregory T, Zierahn U (2017) Revisiting the risk of automation. Econ Lett 159:157–160

    Google Scholar 

  • Barrera E (2020) Technology and the virtues: a philosophical guide to a future worth wanting. Glob Med J 12(1):128–131

    MathSciNet  Google Scholar 

  • Bauer WA (2020) Virtuous vs. utilitarian artificial moral agents. AI Soc 35(1):263–271

    Google Scholar 

  • Bench-Capon T, Araszkiewicz M, Ashley K, Atkinson K, Bex F, Borges F, Bourcier D, Bourgine P, Conrad JG, Francesconi E et al (2012) A history of AI and Law in 50 papers: 25 years of the international conference on AI and Law. Artif Intell Law 20(3):215–319

    Google Scholar 

  • Blake W, Bloom H (1982) The complete poetry and prose of William Blake. University of California Press, Berkeley

    Google Scholar 

  • Bostrom N (2017) Superintelligence. Oxford University Press, Oxford

    Google Scholar 

  • Breazeal CL (2002) Designing sociable robots. MIT Press, Cambridge

    Google Scholar 

  • Breazeal C, Dautenhahn K, Kanda T (2016) In: Siciliano B, Khatib O (eds) Social robotics, Cham. Springer, Berlin, pp 1935–1972. https://doi.org/10.1007/978-3-319-32552-1_72

  • Brooks RA (1999) Cambrian intelligence: the early history of the new AI. MIT Press, Cambridge

    Google Scholar 

  • Brynjolfsson E, McAfee A (2014) The second machine age: work, progress, and prosperity in a time of brilliant technologies. WW Norton & Company, New York

    Google Scholar 

  • Brynjolfsson E, Mcafee A (2017) Artificial intelligence, for real. Harvard Business Review, Brighton

    Google Scholar 

  • Buchanan BG (2005) A (very) brief history of artificial intelligence. AI Mag 26(4):53

    Google Scholar 

  • Bugayenko Y, Bakare A, Cheverda A, Farina M, Kruglov A, Plaksin Y, Succi G, Pedrycz W (2022a) Automatically prioritizing and assigning tasks from code repositories in puzzle driven development. In: 2022 IEEE/ACM 19th international conference on mining software repositories (MSR). IEEE, pp 722–723

  • Bugayenko Y, Daniakin K, Farina M, Jolha F, Kruglov A, Succi G, Pedrycz W (2022) Extracting corrective actions from code repositories. In: 2022 IEEE/ACM 19th international conference on mining software repositories (MSR). IEEE, pp 687–688

  • Bush V et al (1945) As we may think. Atl Mon 176(1):101–108

    Google Scholar 

  • Bynum TW (2006) Flourishing ethics. Ethics Inf Technol 8(4):157–173

    Google Scholar 

  • Cath C, Wachter S, Mittelstadt B, Taddeo M, Floridi L (2018) Artificial intelligence and the ‘good society’: the US, EU, and UK approach. Sci Eng Ethics 24(2):505–528

    Google Scholar 

  • Ciancarini P, Farina M, Masyagin S, Succi G, Yermolaieva S, Zagvozkina N (2021a) Non verbal communication in software engineering—an empirical study. IEEE Access 9:71942–71953

    Google Scholar 

  • Ciancarini P, Farina M, Masyagin S, Succi G, Yermolaieva S, Zagvozkina N (2021b) Root causes of interaction issues in agile software development teams: status and perspectives. In: Future of information and communication conference. Springer, Berlin, pp 1017–1036

  • Clarke S, Zohny H, Savulescu J (2021) Rethinking moral status. Oxford University Press, Oxford

    Google Scholar 

  • Coeckelbergh M (2020) AI ethics. MIT Press, Cambridge

    Google Scholar 

  • Constantinescu M, Crisp R (2022) Can robotic AI systems be virtuous and why does this matter? Int J Soc Robot. https://doi.org/10.1007/s12369-022-00887-w

    Article  Google Scholar 

  • Constantinescu M, Voinea C, Uszkai R, Vică C (2021) Understanding responsibility in responsible AI. Dianoetic virtues and the hard problem of context. Ethics Inf Technol 23:803–814

    Google Scholar 

  • Copeland BJ (2000) The turing test. Minds Mach 10(4):519–539

    MathSciNet  Google Scholar 

  • Cowls J, King T, Taddeo M, Floridi L (2019) Designing AI for social good: seven essential factors. https://doi.org/10.2139/ssrn.3388669

  • Danaher J (2019) The philosophical case for robot friendship. J Posthum Stud 3(1):5–24

    Google Scholar 

  • Danziger S, Levav J, Avnaim-Pesso L (2011) Extraneous factors in judicial decisions. Proc Natl Acad Sci 108(17):6889–6892

    Google Scholar 

  • Daugherty PR, Wilson HJ (2018) Human + machine: reimagining work in the age of AI. Harvard Business Press, Brighton

    Google Scholar 

  • Davenport TH, Kirby J (2016) Only humans need apply: winners and losers in the age of smart machines. Harper Business, New York

    Google Scholar 

  • de Fine Licht K, de Fine Licht J (2020) Artificial intelligence, transparency, and public decision-making. AI Soc 35(4):917–926

    Google Scholar 

  • Dean J, Corrado GS, Monga R, Chen K, Devin M, Le QV, Mao MZ, Ranzato M, Senior A, Tucker P et al (2012) Large scale distributed deep networks. NIPs 2012(1):1223–1231

    Google Scholar 

  • Delcker J (2018) Europe’s silver bullet in global AI battle: ethics. https://www.politico.eu/article/europe-silver-bullet-global-ai-battle-ethics/. Accessed 4 Sept 2022

  • Dignum V (2018) Ethics in artificial intelligence: introduction to the special issue. Springer, Berlin

    Google Scholar 

  • Douglas T, Pugh J, Singh I, Savulescu J, Fazel S (2017) Risk assessment tools in criminal justice and forensic psychiatry: the need for better data. Eur Psychiatry 42:134–137

    Google Scholar 

  • Dreyfus H (1976) What computers can’t do. Harper Collins, New York

    Google Scholar 

  • Dreyfus HL, Hubert L et al (1992) What computers still can’t do: a critique of artificial reason. MIT Press, Cambridge

    Google Scholar 

  • Farina M, Lavazza A (2021a) Knowledge prior to belief: is extended better than enacted? Behav Brain Sci 44:e152. https://doi.org/10.1017/S0140525X2000076X

  • Farina M (2021b) Embodiment: dimensions, domains, and applications. Adapt Behav 29(1):73-99. https://doi.org/10.1177/105971232091296

  • Farina M, Lavazza A (2022a) Incorporation, transparency and cognitive extension: why the distinction between embedded and extended might be more important to ethics than to metaphysics. Philos Technol 35(1):1–21

    Google Scholar 

  • Farina M, Lavazza A (2022b) Why there are still moral reasons to prefer extended over embedded: a (short) reply to Cassinadri. Philos Technol. https://doi.org/10.1007/s13347-022-00566-8

    Article  Google Scholar 

  • Felzmann H, Fosch-Villaronga E, Lutz C, Tamò-Larrieux A (2020) Towards transparency by design for artificial intelligence. Sci Eng Ethics 26(6):3333–3361

    Google Scholar 

  • Floridi L (2019) Establishing the rules for building trustworthy AI. Nat Mach Intell 1(6):261–262

    Google Scholar 

  • Floridi L (2020) What the near future of artificial intelligence could be. Philos Technol 32:1–15 https://doi.org/10.1007/s13347-019-00345-y

  • Floridi L, Cowls J (2022) A unified framework of five principles for AI in society. In Carta S (ed) Machine learning and the city: applications in architecture and Urban design. Wiley, Hoboken, NJ, pp 535–545

  • Floridi L, Cowls J, Beltrametti M, Chatila R, Chazerand P, Dignum V, Luetge C, Madelin R, Pagallo U, Rossi F et al (2018) AI4People-an ethical framework for a good AI society: opportunities, risks, principles, and recommendations. Minds Mach 28(4):689–707

    Google Scholar 

  • Fodor JA (1975) The language of thought, vol 5. Harvard University Press, Cambridge

    Google Scholar 

  • Ford M (2017) Rise of the robots: technology and the threat of a jobless future. Basic Books, New York

    Google Scholar 

  • Frey CB, Osborne MA (2017) The future of employment: how susceptible are jobs to computerisation? Technol Forecast Soc Change 114:254–280

    Google Scholar 

  • Frisch M (1959) Homo faber. Abelard-Schuman, London

    Google Scholar 

  • Gabriel I (2020) Artificial intelligence, values, and alignment. Minds Mach 30(3):411–437

    Google Scholar 

  • Glöckner A (2016) The irrational hungry judge effect revisited: simulations reveal that the magnitude of the effect is overestimated. Judgm Decis Mak 11(6):601

    Google Scholar 

  • Guo Z, Liu S, Liu J, Li Y, Chen L, Lu H, Zhou Y (2021) How far have we progressed in identifying self-admitted technical debts? A comprehensive empirical study. ACM Trans Softw Eng Methodol (TOSEM) 30(4):1–56

    Google Scholar 

  • Hallamaa J, Kalliokoski T (2020) How AI systems challenge the conditions of moral agency? In: International conference on human–computer interaction. Springer, Berlin, pp 54–64

  • Heerink M, Vanderborght B, Broekens J, Albó-Canals J (2016) New friends: social robots in therapy and education. Int J Soc Robot 8(4):443–444

    Google Scholar 

  • Hopfield JJ (1982) Neural networks and physical systems with emergent collective computational abilities. Proc Natl Acad Sci 79(8):2554–2558

    MathSciNet  Google Scholar 

  • Isaac WS (2017) Hope, hype, and fear: the promise and potential pitfalls of artificial intelligence in criminal justice. Ohio State J Crim Law 15:543

    Google Scholar 

  • Jobin A, Ienca M, Vayena E (2019) The global landscape of AI ethics guidelines. Nat Mach Intell 1(9):389–399

    Google Scholar 

  • Johal W (2020) Research trends in social robots for learning. Curr Robot Rep 1:75–83

  • Johnson DG, Verdicchio M (2019) AI, agency and responsibility: the VW fraud case and beyond. AI Soc 34(3):639–647

    Google Scholar 

  • Jones SE (2013) Against technology: from the luddites to neo-luddism. Routledge, New York

    Google Scholar 

  • Kahneman D (2011) Thinking, fast and slow. Macmillan Publishers, London

    Google Scholar 

  • Karimov A, Lavazza A, Farina M (2022) Epistemic responsibility, rights, and duties during the Covid-19 pandemic. Soc Epistemol. https://doi.org/10.1080/02691728.2022.2077856

  • Kline R (2010) Cybernetics, automata studies, and the Dartmouth conference on artificial intelligence. IEEE Ann Hist Comput 33(4):5–16

    MathSciNet  Google Scholar 

  • Krakovsky M (2018) Artificial (emotional) intelligence. Commun ACM 61(4):18–19

    Google Scholar 

  • Krizhevsky A, Sutskever I, Hinton GE (2012) Imagenet classification with deep convolutional neural networks. Adv Neural Inf Process Syst 25:1097–1105

    Google Scholar 

  • Kurzweil R (2005) The singularity is near: when humans transcend biology. Penguin Books, London

    Google Scholar 

  • Lalsing V, Kishnah S, Pudaruth S (2012) People factors in agile software development and project management. Int J Softw Eng Appl 3(1):117

    Google Scholar 

  • Lavazza A, Farina M (2021) Experts, naturalism, and democracy. J Theory Soc Behav 52(2):279–297

    Google Scholar 

  • Le Q, Miralles-Pechuán L, Kulkarni S, Su J, Boydell O (2020) An overview of deep learning in industry. In: Liebowitz (ed) Data analytics and AI. CRC Press, Boca Raton, FL, pp 65–98

  • LeCun Y, Haffner P, Bottou L, Bengio Y (1999) Object recognition with gradient-based learning. In: Forsyth D, Mundy J, Gesu V, Cipolla R (eds) Shape, contour and grouping in computer vision, Lecture Notes in Computer Science. Springer, Berlin, Germany, pp 319–345

  • Li O (2021) Problems with “friendly AI’’. Ethics Inf Technol 23(3):543–550

    Google Scholar 

  • MacIntyre A (1981) After Virtue. University of Notre Dame Press, Notre Dame, IN

  • Markoff J (2016) Machines of loving grace: the quest for common ground between humans and robots. Ecco, New York

    Google Scholar 

  • Marti P (2010) Robot companions: towards a new concept of friendship? Interact Stud Soc Behav Commun Biol Artif Syst 11(2):220–226

    Google Scholar 

  • McCarthy J, Minsky M, Rochester N (1956) The Dartmouth summer research project on artificial intelligence. Artif Intell Past Present Future, pp 1–13. http://jmc.stanford.edu/articles/dartmouth/dartmouth.pdf

  • McClelland JL, Rumelhart DE, Hinton GE (1986) The appeal of parallel distributed processing. MIT Press, Cambridge, pp 3–44

    Google Scholar 

  • McCorduck P, Cfe C (2004) Machines who think: a personal inquiry into the history and prospects of artificial intelligence. CRC Press, Boca Raton

    Google Scholar 

  • McKay C (2020) Predicting risk in criminal procedure: actuarial tools, algorithms, AI and judicial decision-making. Curr Issues Crim Justice 32(1):22–39

    Google Scholar 

  • Megha S, Salem H, Ayan E, Mazzara M, Aslam H, Farina M, Bahrami MR, Ahmad M (2021) Survey on blockchain applications for healthcare: reflections and challenges. In: International conference on advanced information networking and applications. Springer, Berlin, pp 310–322

  • Minsky M, Papert S (1969) Perceptrons: an introduction to computational geometry. MIT Press, Cambridge

    Google Scholar 

  • Mitchell RJ (1990) Managing complexity in software engineering. Peter Peregrinus, London

    Google Scholar 

  • Montague PR, Dolan RJ, Friston KJ, Dayan P (2012) Computational psychiatry. Trends Cogn Sci 16(1):72–80

    Google Scholar 

  • Montes GA, Goertzel B (2019) Distributed, decentralized, and democratized artificial intelligence. Technol Forecast Soc Change 141:354–358

    Google Scholar 

  • Newell A, Simon HA et al (1972) Human problem solving. Prentice-Hall, Englewood Cliffs

    Google Scholar 

  • Newell A, Shaw JC, Simon HA (1959) Report on a general problem solving program. In: IFIP congress, vol 256, p 64

  • Norvig PR, Intelligence SA (2002) A modern approach. Prentice Hall, Upper Saddle River

    Google Scholar 

  • Nussbaum MC (1999) Virtue ethics: a misleading category? J Ethics 3(3):163–201

    Google Scholar 

  • Palmer A, Schwan D (2021) Beneficent dehumanization: employing artificial intelligence and carebots to mitigate shame-induced barriers to medical care. Bioethics 36(2):187–193

  • Peeters A, Haselager P (2021) Designing virtuous sex robots. Int J Soc Robot 13(1):55–66

    Google Scholar 

  • Persson I, Savulescu J (2012) Unfit for the future: the need for moral enhancement. Oxford University Press, Oxford

    Google Scholar 

  • Philbeck T, Davis N (2018) The fourth industrial revolution. J Int Aff 72(1):17–22

    Google Scholar 

  • Pietrini P, Lavazza A, Farina M (2022) Covid-19 and biomedical experts: when epistemic authority is (probably) not enough. J Bioeth Inq 19(1):135–142

    Google Scholar 

  • Raisch S, Krakowski S (2021) Artificial intelligence and management: the automation–augmentation paradox. Acad Manag Rev 46(1):192–210

    Google Scholar 

  • Renda A et al (2019) Artificial intelligence. ethics, governance and policy challenges. CEPS Centre for European Policy Studies, Brussels

    Google Scholar 

  • Rosenblatt F (1960) Perceptron simulation experiments. Proc IRE 48(3):301–309

    MathSciNet  Google Scholar 

  • Rumelhart DE, Hinton GE, McClelland JL et al (1986) A general framework for parallel distributed processing. Parallel Distrib Process Explor Microstruct Cogn 1(45–76):26

    Google Scholar 

  • Rumelhart DE, Widrow B, Lehr MA (1994) The basic ideas in neural networks. Commun ACM 37(3):87–93

    Google Scholar 

  • Sand M, Durán JM, Jongsma KR (2021) Responsibility beyond design: physicians’ requirements for ethical medical AI. Bioethics 36(2):162–169. https://doi.org/10.1111/bioe.12887

  • Savulescu J (2009) Moral status of enhances beings: what do we owe the gods? In: Savulescu J, Bostrom N (eds) Human Enhancement. Oxford University Press, Oxford, UK, pp 211–247

  • Savulescu J, Maslen H (2015) Moral enhancement and artificial intelligence: moral AI? In: Romportl J, Zackova E, Kelemen J (eds) Beyond artificial intelligence: the disappearing human-machine divide. Springer, Berlin, pp 79–95

  • Schuller D, Schuller BW (2018) The age of artificial emotional intelligence. Computer 51(9):38–46

    Google Scholar 

  • Schwaber K (1997) Scrum development process. In: Sutherland D, Patel D, Casanave C, Hollowell G, Miller J (eds) Business object design and implementation. Springer, Berlin, pp 117–134

  • Searle JR (1982) The Chinese room revisited. Behav Brain Sci 5(2):345–348

    Google Scholar 

  • Smuha NA (2019) The EU approach to ethics guidelines for trustworthy artificial intelligence. Comput Law Rev Int 20(4):97–106

    Google Scholar 

  • Spiekermann S, Krasnova H, Hinz O, Baumann A, Benlian A, Gimpel H, Heimbach I, Köster A, Maedche A, Niehaves B et al (2022) Values and ethics in information systems. Bus Inf Syst Eng 64(2):247–264

    Google Scholar 

  • Spinellis D (2005) Version control systems. IEEE Softw 22(5):108–109

    Google Scholar 

  • Stahl BC (2021) Concepts of ethics and their application to AI. In: Stahl BC (ed) Artificial Intelligence for a Better Future, Springer Briefs in Research and Innovation Governance. Springer, Cham, pp 19–33

  • Sternberg RJ (1983) Components of human intelligence. Cognition 15(1–3):1–48

    Google Scholar 

  • Storey M-A, Ryall J, Bull RI, Myers D, Singer J (2008) Todo or to bug. In: 2008 ACM/IEEE 30th international conference on software engineering. IEEE, pp 251–260. https://doi.org/10.1145/1368088.1368123

  • Susskind RE, Susskind D (2015) The future of the professions: how technology will transform the work of human experts. Oxford University Press, Oxford

    Google Scholar 

  • Taddeo M, Floridi L (2018) How AI can be a force for good. Science 361(6404):751–752

    MathSciNet  Google Scholar 

  • Trappl, R (2015) A construction manual for robots’ ethical systems. Springer, Berlin

    Google Scholar 

  • Turing AM, Haugeland J (1950) Computing machinery and intelligence. MIT Press, Cambridge

    Google Scholar 

  • Vallor S (2016) Technology and the virtues: a philosophical guide to a future worth wanting. Oxford University Press, Oxford

    Google Scholar 

  • Vallor S (2017) AI and the automation of wisdom. In: Powers T (ed) Philosophy and Computing Essays in Epistemology, Philosophy of Mind, Logic, and Ethics. Springer, Berlin, pp 161–178

  • Wajcman J (2017) Automation: is it really different this time? Br J Sociol 68(1):119–127

    Google Scholar 

  • Wallach W, Vallor S (2020) Moral machine: from value alignment to embodied virtue. In: Liao M (Ed). Ethics of Artificial Intelligence. Oxford University Press, New York, NYC, pp 383–412

  • Walsh T, Levy N, Bell G, Elliott A, Maclaurin J, Mareels I, Wood F (2019) The effective and ethical development of artificial intelligence: an opportunity to improve our wellbeing. Australian Council of Learned Academies, Melbourne

    Google Scholar 

  • Wang R (2020) Legal technology in contemporary USA and China. Comput Law Secur Rev 39:105459

    Google Scholar 

  • Wasserman AI (1996) Toward a discipline of software engineering. IEEE Softw 13(6):23–31

    Google Scholar 

  • Weidong J (2020) The change of judicial power in China in the era of artificial intelligence. Asian J Law Soc 7(3):515–530

    Google Scholar 

  • Weizenbaum J (1976) Computer power and human reason: from judgment to calculation. WH Freeman & Co, New York

    Google Scholar 

  • Wiener N (1988) The human use of human beings: cybernetics and society. Da Capo Press, Boston

    Google Scholar 

  • Wiese W, Friston KJ (2021) Ai ethics in computational psychiatry: from the neuroscience of consciousness to the ethics of consciousness. Behav Brain Res 420:113704

  • Wright SA, Schultz AE (2018) The rising tide of artificial intelligence and business automation: developing an ethical framework. Bus Horiz 61(6):823–832

    Google Scholar 

  • Xia Q, Sifah EB, Asamoah KO, Gao J, Du X, Guizani M (2017) Medshare: trust-less medical data sharing among cloud service providers via blockchain. IEEE Access 5:14757–14767

    Google Scholar 

  • Yang G, Bellingham J, Dupont P, Fischer P, Floridi L, Full R, Jacobstein N et al (2018) The grand challenges of science robotics. Sci Robot 3(14):eaar7650

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Mirko Farina.

Ethics declarations

Conflict of interest

The authors assume all responsibility of the inception, development, writing, editing and final approval of the manuscript in its submitted form and have no conflicts of interest to declare.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Farina, M., Zhdanov, P., Karimov, A. et al. AI and society: a virtue ethics approach. AI & Soc 39, 1127–1140 (2024). https://doi.org/10.1007/s00146-022-01545-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00146-022-01545-5

Keywords