Advertisement

Explainable Argumentation for Wellness Consultation

  • Isabel SassoonEmail author
  • Nadin Kökciyan
  • Elizabeth Sklar
  • Simon Parsons
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11763)

Abstract

There has been a recent resurgence in the area of explainable artificial intelligence as researchers and practitioners seek to provide more transparency to their algorithms. Much of this research is focused on explicitly explaining decisions or actions to a human observer, and it should not be controversial to say that looking at how humans explain to each other can serve as a useful starting point for explanation in artificial intelligence. However, it is fair to say that most work in explainable artificial intelligence uses only the researchers’ intuition of what constitutes a ‘good’ explanation. There exist vast and valuable bodies of research in philosophy, psychology, and cognitive science of how people define, generate, select, evaluate, and present explanations, which argues that people employ certain cognitive biases and social expectations to the explanation process. This paper argues that the field of explainable artificial intelligence can build on this existing research, and reviews relevant papers from philosophy, cognitive psychology/science, and social psychology, which study these topics. It draws out some important findings, and discusses ways that these can be infused with work on explainable artificial intelligence.

Keywords

Explanation Explainability Interpretability Explainable AI Transparency 

Notes

Acknowledgements

This work was funded by EPSRC grant EP/P010105/1 CONSULT: Collaborative Mobile Decision Support for Managing Multiple Morbidities.

References

  1. 1.
    Atkinson, K., Bench-Capon, T.: Practical reasoning as presumptive argumentation using action based alternating transition systems. Artif. Intell. 171(10–15), 855–874 (2007)MathSciNetCrossRefGoogle Scholar
  2. 2.
    Atkinson, K., Bench-Capon, T.J.M., Modgil, S.: Argumentation for decision support. In: Database and Expert Systems Applications (DEXA), pp. 822–831 (2006)Google Scholar
  3. 3.
    Bex, F., Walton, D.: Combining explanation and argumentation in dialogue. Argument Comput. 7(1), 55–68 (2016)Google Scholar
  4. 4.
    Cerutti, F., Norman, T.J., Toniolo, A., Middleton, S.E.: CISpaces.org: from fact extraction to report generation. In: Proceedings of COMMA 2018 Computational Models of Argument, pp. 269–280 (2018)Google Scholar
  5. 5.
    Cogan, E., Parsons, S., McBurney, P.: What kind of argument are we going to have today? In: Proceedings of the 4th International Joint Conference on Autonomous Agents and Multiagent Systems, pp. 544–551. ACM (2005)Google Scholar
  6. 6.
    Coulson, A., Glasspool, D., Fox, J., Emery, J.: RAGs: a novel approach to computerized genetic risk assessment and decision support from pedigrees. Methods Inf. Med. 40(4), 315–322 (2001)CrossRefGoogle Scholar
  7. 7.
    Dung, P.M.: On the acceptability of arguments and its fundamental role in nonmonotonic reasoning, logic programming and \(n\)-person games. Artif. Intell. 77(2), 321–357 (1995)MathSciNetCrossRefGoogle Scholar
  8. 8.
    Fox, J.: Will it happen? can it happen? a new approach to formal risk analysis. Risk Decis. Policy 4(2), 117–128 (1999)MathSciNetCrossRefGoogle Scholar
  9. 9.
    Girle, R.A.: Commands in dialogue logic. In: Gabbay, D.M., Ohlbach, H.J. (eds.) FAPR 1996. LNCS, vol. 1085, pp. 246–260. Springer, Heidelberg (1996).  https://doi.org/10.1007/3-540-61313-7_77CrossRefGoogle Scholar
  10. 10.
    Gunning, D.: Explainable Artificial Intelligence (XAI). Defense Advanced Research Projects Agency (DARPA) (2017)Google Scholar
  11. 11.
    Kokciyan, N., et al.: Towards an argumentation system for supporting patients in self-managing their chronic conditions. In: Proceedings of the AAAI Joint Workshop on Health Intelligence (2018)Google Scholar
  12. 12.
    Krause, P., Fox, J., Judson, P., Patel, M.: Qualitative risk assessment fulfils a need. In: Hunter, A., Parsons, S. (eds.) Applications of Uncertainty Formalisms. LNCS (LNAI), vol. 1455, pp. 138–156. Springer, Heidelberg (1998).  https://doi.org/10.1007/3-540-49426-X_7CrossRefGoogle Scholar
  13. 13.
    McBurney, P., Parsons, S.: Chance discovery using dialectical argumentation. In: Proceedings of the Workshop on Chance Discovery, Fifteenth Annual Conference of the Japanese Society for Artificial Intelligence. Matsue, Japan (2001)CrossRefGoogle Scholar
  14. 14.
    McBurney, P., Hitchcock, D., Parsons, S.: The eightfold way of deliberation dialogue. Int. J. Intell. Syst. 22(1), 95–132 (2007)CrossRefGoogle Scholar
  15. 15.
    McBurney, P., Parsons, S.: Representing epistemic uncertainty by means of dialectical argumentation. Ann. Math. Artif. Intell. 32(1–4), 125–169 (2001)MathSciNetCrossRefGoogle Scholar
  16. 16.
    McBurney, P., Parsons, S.: Games that agents play: a formal framework for dialogues between autonomous agents. J. Logic Lang. Inf. 11(3), 315–334 (2002)MathSciNetCrossRefGoogle Scholar
  17. 17.
    McBurney, P., Parsons, S.: A denotational semantics for deliberation dialogues. In: Proceedings of the 3rd International Conference on Autonomous Agents and Multi-Agent Systems. IEEE Press (2004)Google Scholar
  18. 18.
    Miller, T.: Explanation in artificial intelligence: Insights from the social sciences. Artif. Intell. 267, 1–38 (2018). ISSN 0004-3702.  https://doi.org/10.1016/j.artint.2018.07.007. http://www.sciencedirect.com/science/article/pii/S0004370218305988 MathSciNetCrossRefGoogle Scholar
  19. 19.
    Miller, T., Howe, P., Sonenberg, L.: Explainable AI: beware of inmates running the asylum. In: Proceedings of the IJACI Workshop on Explainable AI (2017)Google Scholar
  20. 20.
    Parsons, S., et al.: Argument schemes for reasoning about trust. Argument Comput Spec. Issue Trust Argum. Technol. 5(2–3), 160–190 (2014)Google Scholar
  21. 21.
    Parsons, S., McBurney, P., Sklar, E., Wooldridge, M.: On the relevance of utterances in formal inter-agent dialogues. In: Proceedings of the 6th International Conference on Autonomous Agents and Multiagent Systems (2007)Google Scholar
  22. 22.
    Parsons, S., Wooldridge, M., Amgoud, L.: Properties and complexity of some formal inter-agent dialogues. J. Log. Comput. 13(3), 347–376 (2003)MathSciNetCrossRefGoogle Scholar
  23. 23.
    Parsons, S., Wooldridge, M., Amgoud, L.: On the outcomes of formal inter-agent dialogues. In: Proceedings of the 2nd International Conference on Autonomous Agents and Multi-Agent Systems. ACM Press, New York (2003)Google Scholar
  24. 24.
    Prakken, H.: Formal systems for persuasion dialogue. Knowl. Eng. Rev. 21(02), 163–188 (2006)CrossRefGoogle Scholar
  25. 25.
    Rago, A., Cocarascu, O., Toni, F.: Argumentation-based recommendations: Fantastic explanations and how to find them. In: Proceedings of the 27th International Joint Conference on Artificial Intelligence, pp. 1949–1955 (2018)Google Scholar
  26. 26.
    Rahwan, I., Ramchurn, S.D., Jennings, N.R., Mcburney, P., Parsons, S., Sonenberg, L.: Argumentation-based negotiation. Knowl. Eng. Rev. 18(4), 343–375 (2003)CrossRefGoogle Scholar
  27. 27.
    Rahwan, I., Simari, G.R.: Argumentation in Artificial Intelligence, vol. 47. Springer, Heidelberg (2009)Google Scholar
  28. 28.
    Rajendran, P.: Aggregating and Analysing Opinions for Argument-based Relations. Ph.D. thesis, University of Liverpool, Liverpool, June 2019Google Scholar
  29. 29.
    Shortliffe, E.H., Davis, R., Axline, S.G., Buchanan, B.G., Green, C.C., Cohen, S.N.: Computer-based consultations in clinical therapeutics: explanation and rule acquisition capabilities of the MYCIN system. Comput. Biomed. Res. 8(4), 303–320 (1975)CrossRefGoogle Scholar
  30. 30.
    Sklar, E.I., Azhar, M.Q.: Argumentation-based dialogue games for shared control in human-robot systems. J. Hum. Robot Interact. 4(3), 120–148 (2015)CrossRefGoogle Scholar
  31. 31.
    Tolchinsky, P., Cortes, U., Modgil, S., Caballero, F., Lopez-Navidad, A.: Increasing human-organ transplant availability: argumentation-based agent deliberation. IEEE Intell. Syst. 21(6), 30–37 (2006)CrossRefGoogle Scholar
  32. 32.
    Walton, D., Krabbe, E.C.W.: Commitment in Dialogue: Basic Concepts of Interpersonal Reasoning. State University of New York Press, Albany (1995)Google Scholar
  33. 33.
    Walton, D., Reed, C., Macagno, F.: Argumentation Schemes. Cambridge University Press, Cambridge (2008)CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Isabel Sassoon
    • 1
    Email author
  • Nadin Kökciyan
    • 1
  • Elizabeth Sklar
    • 1
  • Simon Parsons
    • 1
  1. 1.Department of InformaticsKing’s College LondonLondonUK

Personalised recommendations