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Developing Automated Deceptions and the Impact on Trust

Philosophy & Technology volume 28, pages 91–105 (2015)Cite this article

Abstract

As software developers design artificial agents (AAs), they often have to wrestle with complex issues, issues that have philosophical and ethical importance. This paper addresses two key questions at the intersection of philosophy and technology: What is deception? And when is it permissible for the developer of a computer artifact to be deceptive in the artifact’s development? While exploring these questions from the perspective of a software developer, we examine the relationship of deception and trust. Are developers using deception to gain our trust? Is trust generated through technological “enchantment” warranted? Next, we investigate more complex questions of how deception that involves AAs differs from deception that only involves humans. Finally, we analyze the role and responsibility of developers in trust situations that involve both humans and AAs.

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Notes

  1. For Floridi, a LoA qualifies the level at which a system is considered and informs the discussion of such a system. When we analyze a system, we do so from a particular perspective or level of abstraction. This often results in a model or prototype that identifies the system at the “given LoA.” Floridi refers to this as the “system-level-model-structure (or SLMS) scheme:” “Thus, introducing an explicit reference to the LoA makes it clear that the model of a system is a function of the available observables, and that it is reasonable to rank different LoAs and to compare and assess the corresponding models.” (Floridi 2008) from (Wolf et al. 2012, p. 24).

  2. Some philosophers disagree with the claim that trust is (simply) a relation; for example, some argue that it is a “disposition.” Others argue that it can be an attitude (affective) as well as cognitive (see, for example, Baier 1986). Also, see McLeod (2011) for a description of some alternative philosophical models of trust that have been advanced in the literature.

  3. See Buechner et al. (2013) for a discussion of trustworthiness.

  4. We thank Luciano Floridi for this example.

  5. We thank Herman Tavani for this clarification.

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Acknowledgments

The authors thank Herman Tavani, Mariarosaria Taddeo, and Luciano Floridi for their insightful comments that strengthened the paper.

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Authors and Affiliations

  1. Sacred Heart University, 5151 Park Avenue, Fairfield, CT, 06825, USA

    Frances S. Grodzinsky

  2. University of Missouri—St. Louis, 1 University Blvd, St. Louis, MO, 63121, USA

    Keith W. Miller

  3. Bemidji State University, 1500 Birchmont Drive, #23, Bemidji, MN, 56601, USA

    Marty J. Wolf

Authors
  1. Frances S. Grodzinsky
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  2. Keith W. Miller
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  3. Marty J. Wolf
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Correspondence to Frances S. Grodzinsky.

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Grodzinsky, F.S., Miller, K.W. & Wolf, M.J. Developing Automated Deceptions and the Impact on Trust. Philos. Technol. 28, 91–105 (2015). https://doi.org/10.1007/s13347-014-0158-7

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Keywords

  • Deception
  • Trust
  • Artificial agents