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Developing artificial agents worthy of trust: “Would you buy a used car from this artificial agent?”

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Abstract

There is a growing literature on the concept of e-trust and on the feasibility and advisability of “trusting” artificial agents. In this paper we present an object-oriented model for thinking about trust in both face-to-face and digitally mediated environments. We review important recent contributions to this literature regarding e-trust in conjunction with presenting our model. We identify three important types of trust interactions and examine trust from the perspective of a software developer. Too often, the primary focus of research in this area has been on the artificial agents and the humans they may encounter after they are deployed. We contend that the humans who design, implement, and deploy the artificial agents are crucial to any discussion of e-trust and to understanding the distinctions among the concepts of trust, e-trust and face-to-face trust.

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Notes

  1. See the overview article by Benbasat et al. (2008) for a list of influences and reflections on state of the art research in this area.

  2. We will not replay the arguments behind this analysis here; interested readers should see Taddeo’s paper, as well as ideas she criticizes in Luhmann (1979), Gambetta (1998), Nissenbaum (2001), Tuomela and Hofmann (2003), Weckert (2005).

  3. In the information systems literature this type of risk is referred to as channel, web, or Internet risk.

  4. See Floridi and Sanders (2004).

  5. See Grodzinsky et al. (2008).

  6. The idea that AAs “make decisions” is philosophically controversial; we are not claiming here that AAs make decisions in a way that is identical or comparable to the way humans make decisions. Instead, we are only positing that the program running inside an AA will take different courses of actions based on decision control structures and the state of the computation at a given moment. Although such issues as whether AAs have free will are fascinating and are related to trust, we explicitly are not exploring those issues in this paper.

  7. See Castelfranchi and Falcone and the work of the Unit of AI Cognitive Modelling and Interaction, National Research Council Institute of Psychology, Rome, Italy (2001).

  8. See Kloth (2009).

  9. There are both theoretical and practical reasons why neural net decisions are unlikely to be easily explained to humans. For example, systems that can give a comprehensible explanation to a human of why a decision was reached are far more resource intensive than systems that are less expressive about their reasoning (Greiner et al. 2001).

  10. The learning that can take place studying AA trust decisions will be facilitated if that software is available widely. Thus, source code available software (including Free Software) will be of particular interest.

  11. See Miller et al. (2009).

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Authors and Affiliations

  1. Sacred Heart University, 5151 Park Avenue, Fairfield, CT, USA

    F. S. Grodzinsky

  2. University of Illinois Springfield, One University Plaza, Springfield, IL, USA

    K. W. Miller

  3. Bemidji State University, 1500 Birchmont Drive NE, #23, Bemidji, MN, USA

    M. J. Wolf

Authors
  1. F. S. Grodzinsky
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  2. K. W. Miller
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  3. M. J. Wolf
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Correspondence to M. J. Wolf.

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Grodzinsky, F.S., Miller, K.W. & Wolf, M.J. Developing artificial agents worthy of trust: “Would you buy a used car from this artificial agent?”. Ethics Inf Technol 13, 17–27 (2011). https://doi.org/10.1007/s10676-010-9255-1

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