Advertisement

Accountability for Practical Reasoning Agents

  • Stephen CranefieldEmail author
  • Nir OrenEmail author
  • Wamberto W. VasconcelosEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11327)

Abstract

Artificial intelligence has been increasing the autonomy of man-made artefacts such as software agents, self-driving vehicles and military drones. This increase in autonomy together with the ubiquity and impact of such artefacts in our daily lives have raised many concerns in society. Initiatives such as transparent and ethical AI aim to allay fears of a “free for all” future where amoral technology (or technology amorally designed) will replace humans with terrible consequences. We discuss the notion of accountable autonomy, and explore this concept within the context of practical reasoning agents. We survey literature from distinct fields such as management, healthcare, policy-making, and others, and differentiate and relate concepts connected to accountability. We present a list of justified requirements for accountable software agents and discuss research questions stemming from these requirements. We also propose a preliminary formalisation of one core aspect of accountability: responsibility.

References

  1. 1.
    Dubnick, M.J.: Accountability as a cultural keyword. In: Bovens et al. [56]Google Scholar
  2. 2.
    Billingham, P., Colin, A.: The democratisation of accountability in the digital age: promise and pitfalls. In: Winner of Robert Davies Essay Competition 2016, Skoll Centre for Social Entrepreneurship, Saïd Business School, The University of Oxford, U.K. (2016). https://www.sbs.ox.ac.uk/sites/default/files/Skoll_Centre/Docs/Accountability_BillinghamColin-Jones.pdf
  3. 3.
    Wachter, S.: Towards accountable A.I. in Europe? The Alan Turing Institute, U.K. https://www.turing.ac.uk/blog/towards-accountable-ai-europe. Accessed 25 July 2018
  4. 4.
    Bostrom, N., Yudkowsky, E.: The ethics of artificial intelligence. In: Frankish, K., Ramsey, W.M. (eds.) The Cambridge Handbook of Artificial Intelligence, pp. 316–334. Cambridge University Press (2014)Google Scholar
  5. 5.
    Dignum, V.: Ethics in artificial intelligence: introduction to the special issue. Ethics Inf. Technol. 20(1), 1–3 (2018)MathSciNetCrossRefGoogle Scholar
  6. 6.
    Simonite, T.: Tech firms move to put ethical guard rails around AI. Wired, May 2018. https://www.wired.com/story/tech-firms-move-to-put-ethical-guard-rails-around-ai/. Accessed 29 July 2018
  7. 7.
    Zou, J., Schiebinger, L.: AI can be sexist and racist – it’s time to make it fair. Nature 559, 324–326 (2018)CrossRefGoogle Scholar
  8. 8.
    Georgeff, M., Pell, B., Pollack, M., Tambe, M., Wooldridge, M.: The belief-desire-intention model of agency. In: Müller, J.P., Rao, A.S., Singh, M.P. (eds.) ATAL 1998. LNCS, vol. 1555, pp. 1–10. Springer, Heidelberg (1999).  https://doi.org/10.1007/3-540-49057-4_1CrossRefGoogle Scholar
  9. 9.
    Meneguzzi, F.R., Zorzo, A.F., da Costa Móra, M.: Propositional planning in BDI agents. In: Proceedings of the ACM Symposium on Applied Computing, pp. 58–63. ACM, New York (2004)Google Scholar
  10. 10.
    Rao, A.S., Georgeff, M.P.: BDI agents: from theory to practice. In: Proceedings of the 1st International Conference on Multi-Agent Systems (ICMAS 1995), pp. 312–319. AAAI (1995). https://www.aaai.org/Papers/ICMAS/1995/ICMAS95-042.pdf
  11. 11.
    Chopra, A.K., Singh, M.P.: The thing itself speaks: accountability as a foundation for requirements in sociotechnical systems. In: 2014 IEEE 7th International Workshop on Requirements Engineering and Law, p. 22. IEEE (2014)Google Scholar
  12. 12.
    Dastani, M., van der Torre, L., Yorke-Smith, N.: Commitments and interaction norms in organisations. Auton. Agent. Multi-Agent Syst. 31(2), 207–249 (2017)CrossRefGoogle Scholar
  13. 13.
    Fornara, N., Colombetti, M.: Representation and monitoring of commitments and norms using OWL. AI Commun. 23(4), 341–356 (2010)MathSciNetzbMATHGoogle Scholar
  14. 14.
    Baldoni, M., Baroglio, C., May, K.M., Micalizio, R., Tedeschi, S.: Computational accountability. In: Proceedings of the AI*IA Workshop on Deep Understanding and Reasoning: A Challenge for Next-generation Intelligent Agents, volume 1802 of CEUR Workshop Proceedings, pp. 56–62. CEUR-WS.org (2017)Google Scholar
  15. 15.
    Baldoni, M., Baroglio, C., May, K.M., Micalizio, R., Tedeschi, S.: ADOPT JaCaMo: accountability-driven organization programming technique for JaCaMo. In: An, B., Bazzan, A., Leite, J., Villata, S., van der Torre, L. (eds.) PRIMA 2017. LNCS (LNAI), vol. 10621, pp. 295–312. Springer, Cham (2017).  https://doi.org/10.1007/978-3-319-69131-2_18CrossRefGoogle Scholar
  16. 16.
    Baldoni, M., Baroglio, C., Micalizio, R.: The AThOS project: first steps towards computational accountability. In: Proceedings of the 1st Workshop on Computational Accountability and Responsibility in Multiagent Systems, volume 2051 of CEUR Workshop Proceedings, pp. 3–19. CEUR-WS.org (2018)Google Scholar
  17. 17.
    Bovens, M., Schillemans, T., Goodin, R.E.: Public accountability. In: Bovens et al. [56]Google Scholar
  18. 18.
    Dignum, V.: Responsible artificial intelligence: designing AI for human values. ITU J. ICT Discov. 1(1), 1–8 (2018)Google Scholar
  19. 19.
    Fox, J.: The uncertain relationship between transparency and accountability. Dev. Pract. 17(4–5), 663–671 (2007)CrossRefGoogle Scholar
  20. 20.
    Schillemans, T.: The public accountability review: a meta-analysis of public accountability research in six academic disciplines. Working paper, Utrecht University School of Governance (2013). https://dspace.library.uu.nl/handle/1874/275784
  21. 21.
    Emanuel, E.J., Emanuel, L.L.: What is accountability in health care? Ann. Intern. Med. 124(2), 229–239 (1996)CrossRefGoogle Scholar
  22. 22.
    Eshleman, A.: Moral responsibility. In: Zalta, E.N. (ed.) The Stanford Encyclopedia of Philosophy. Metaphysics Research Lab, Stanford University, winter 2016 edn. (2016)Google Scholar
  23. 23.
    PMI: Guide to the Project Management Body of Knowledge (PMBOK®Guide), 5th edn. Project Management Institute (2013)Google Scholar
  24. 24.
    Jacka, J.M., Keller, P.J.: Business Process Mapping: Improving Customer Satisfaction, 2nd edn. Wiley, Hoboken (2009)Google Scholar
  25. 25.
    Grossi, D., Dignum, F., Royakkers, L.M.M., Meyer, J.-J.C.: Collective obligations and agents: who gets the blame? In: Lomuscio, A., Nute, D. (eds.) DEON 2004. LNCS (LNAI), vol. 3065, pp. 129–145. Springer, Heidelberg (2004).  https://doi.org/10.1007/978-3-540-25927-5_9CrossRefGoogle Scholar
  26. 26.
    Micalizio, R., Torasso, P., Torta, G.: On-line monitoring and diagnosis of multi-agent systems: a model based approach. In: Proceedings of the 16th European Conference on Artificial Intelligence, pp. 848–852. IOS Press (2004)Google Scholar
  27. 27.
    Witteveen, C., Roos, N., van der Krogt, R., de Weerdt, M.: Diagnosis of single and multi-agent plans. In: Proceedings of the Fourth International Joint Conference on Autonomous Agents and Multiagent Systems, pp. 805–812. ACM (2005)Google Scholar
  28. 28.
    Grossi, D., Royakkers, L., Dignum, F.: Organizational structure and responsibility. Artif. Intell. Law 15(3), 223–249 (2007)CrossRefGoogle Scholar
  29. 29.
    de Jonge, F., Roos, N., Witteveen, C.: Primary and secondary diagnosis of multi-agent plan execution. Auton. Agent. Multi-Agent Syst. 18(2), 267–294 (2009)CrossRefGoogle Scholar
  30. 30.
    Mastop, R.: Characterising responsibility in organisational structures: the problem of many hands. In: Governatori, G., Sartor, G. (eds.) DEON 2010. LNCS (LNAI), vol. 6181, pp. 274–287. Springer, Heidelberg (2010).  https://doi.org/10.1007/978-3-642-14183-6_20CrossRefzbMATHGoogle Scholar
  31. 31.
    De Lima, T., Royakkers, L.M.M., Dignum, F.: Modeling the problem of many hands in organisations. In: Proceedings of the 19th European Conference on Artificial Intelligence, volume 215 of Frontiers in Artificial Intelligence and Applications, pp. 79–84. IOS Press (2010)Google Scholar
  32. 32.
    Bulling, N., Dastani, M.: Coalitional responsibility in strategic settings. In: Leite, J., Son, T.C., Torroni, P., van der Torre, L., Woltran, S. (eds.) CLIMA 2013. LNCS (LNAI), vol. 8143, pp. 172–189. Springer, Heidelberg (2013).  https://doi.org/10.1007/978-3-642-40624-9_11CrossRefzbMATHGoogle Scholar
  33. 33.
    Micalizio, R., Torasso, P.: Cooperative monitoring to diagnose multiagent plans. J. Artif. Intell. Res. 51, 1–70 (2014)MathSciNetCrossRefGoogle Scholar
  34. 34.
    Lorini, E., Longin, D., Mayor, E.: A logical analysis of responsibility attribution: emotions, individuals and collectives. J. Log. Comput. 24(6), 1313–1339 (2014)MathSciNetCrossRefGoogle Scholar
  35. 35.
    Aldewereld, H., Dignum, V., Vasconcelos, W.W.: Group norms for multi-agent organisations. ACM Trans. Auton. Adapt. Syst. 11(2), 15:1–15:31 (2016)CrossRefGoogle Scholar
  36. 36.
    Alechina, N., Halpern, J.Y., Logan,B.: Causality, responsibility and blame in team plans. In: Proceedings of the 16th International Conference on Autonomous Agents and Multiagent Systems, pp. 1091–1099. IFAAMAS (2017)Google Scholar
  37. 37.
    Winikoff, M.: Towards trusting autonomous systems. In: El Fallah-Seghrouchni, A., Ricci, A., Son, T.C. (eds.) EMAS 2017. LNCS (LNAI), vol. 10738, pp. 3–20. Springer, Cham (2018).  https://doi.org/10.1007/978-3-319-91899-0_1CrossRefGoogle Scholar
  38. 38.
    Bovens, M.: Analysing and assessing accountability: a conceptual framework. Eur. Law J. 13(4), 447–468 (2007)MathSciNetCrossRefGoogle Scholar
  39. 39.
    Richard, M.: ‘accountability’: An ever-expanding concept? Public Adm. 78(3), 555–573 (2000)CrossRefGoogle Scholar
  40. 40.
    Anderson, M.L., Perlis, D.R.: Logic, self-awareness and self-improvement: the metacognitive loop and the problem of brittleness. J. Log. Comput. 15(1), 21–40 (2005)MathSciNetCrossRefGoogle Scholar
  41. 41.
    Cranefield, S., Winikoff, M., Dignum, V., Dignum, F.: No pizza for you: Value-based plan selection in BDI agents. In: Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, pp. 178–184. ijcai.org (2017)Google Scholar
  42. 42.
    Meneguzzi, F., Rodrigues, O., Oren, N., Vasconcelos, W.W., Luck, M.: BDI reasoning with normative considerations. Eng. Appl. Artif. Intell. 43, 127–146 (2015)CrossRefGoogle Scholar
  43. 43.
    Gatt, A., et al.: From data to text in the neonatal intensive care unit: using NLG technology for decision support and information management. AI Commun. 22(3), 153–186 (2009)MathSciNetGoogle Scholar
  44. 44.
    Mulwa, C., Lawless, S., Sharp, M., Wade, V.: The evaluation of adaptive and personalised information retrieval systems: a review. Int. J. Knowl. Web Intell. 2(2/3), 138–156 (2011)CrossRefGoogle Scholar
  45. 45.
    Bex, F., Grasso, F., Green, N., Paglieri, F., Reed, C.: Argument Technologies: Theory, Analysis, and Applications. Studies in Logic and Argumentation. College Publications (2017)Google Scholar
  46. 46.
    Alechina, N., Dastani, M., Logan, B., Meyer, J.-J.C.: Reasoning about plan revision in BDI agent programs. Theoret. Comput. Sci. 412(44), 6115–6134 (2011)MathSciNetCrossRefGoogle Scholar
  47. 47.
    Ma, J., Liu, W., Hong, J., Godo, L., Sierra, C.: Plan selection for probabilistic BDI agents. In: 2014 IEEE 26th International Conference on Tools with Artificial Intelligence, pp. 83–90, November 2014Google Scholar
  48. 48.
    Winikoff, M.: An AgentSpeak meta-interpreter and its applications. In: Bordini, R.H., Dastani, M.M., Dix, J., El Fallah Seghrouchni, A. (eds.) ProMAS 2005. LNCS (LNAI), vol. 3862, pp. 123–138. Springer, Heidelberg (2006).  https://doi.org/10.1007/11678823_8CrossRefGoogle Scholar
  49. 49.
    Winikoff, M.: Debugging agent programs with “why?” questions. In: Proceedings of the 16th International Conference on Autonomous Agents and Multiagent Systems, pp. 251–259. IFAAMAS (2017)Google Scholar
  50. 50.
    Atkinson, K., Bench-Capon, T.J.M.: Practical reasoning as presumptive argumentation using action based alternating transition systems. Artifi. Intell. 171(10–15), 855–874 (2007)MathSciNetCrossRefGoogle Scholar
  51. 51.
    Andrighetto, G., Governatori, G., Noriega, P., van der Torre, L.W.N. (eds.) Normative Multi-Agent Systems, volume 4 of Dagstuhl Follow-Ups. Schloss Dagstuhl - Leibniz-Zentrum für Informatik (2013)Google Scholar
  52. 52.
    Mallya, A.U., Singh, M.P.: An algebra for commitment protocols. Auton. Agent. Multi-Agent Syst. 14(2), 143–163 (2007)CrossRefGoogle Scholar
  53. 53.
    Dignum, F., Weigand, H., Verharen, E.: Meeting the deadline: on the formal specification of temporal deontic constraints. In: Raś, Z.W., Michalewicz, M. (eds.) ISMIS 1996. LNCS, vol. 1079, pp. 243–252. Springer, Heidelberg (1996).  https://doi.org/10.1007/3-540-61286-6_149CrossRefGoogle Scholar
  54. 54.
    Searle, J.R.: The Construction of Social Reality. Free Press, New York (1995)Google Scholar
  55. 55.
    Finkel, A., Iyer, S.P., Sutre, G.: Well-abstracted transition systems: application to FIFO automata. Inf. Comput. 181(1), 1–31 (2003)MathSciNetCrossRefGoogle Scholar
  56. 56.
    Bovens, M., Goodin, R.E., Schillemans, T. (eds.): The Oxford Handbook of Public Accountability. Oxford University Press, Oxford (2014)Google Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.University of OtagoDunedinNew Zealand
  2. 2.University of AberdeenAberdeenUK

Personalised recommendations