Linking Trust to Trustworthiness
By O. O’neill. 2018
169 citations recorded by the source corpus.
Abstract Trust is valuable when placed in trustworthy agents and activities, but damaging or costly when (mis)placed in untrustworthy agents and activities. So it is puzzling that much contemporary work on trust – such as that based on polling evidence – studies generic attitudes of trust in types of agent, institution or activity in complete abstraction from any account of trustworthiness. Information about others’ generic attitudes of trust or mistrust that take no account of evidence whether those attitudes are well or ill placed can offer little or no help for those who aim to place or refuse trust well. Information about attitudes is evidently useful to those who aim to influence those who hold them, which explains why polls about attitudes are popular with political parties, advertisers and other campaigning organisations. But where we aim not to influence others, but to place and refuse trust intelligently we must link trust to trustworthiness, and must focus on evidence of honesty, competence and reliability.
Subfields: Cognitive Neuroscience, Philosophy
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Citations in the corpus
- Explainable machine learning in deployment (2019, background): “By providing an explanation for how the model made a decision, explainability techniques seek to provide transparency directly targeted to human users, often aiming to increase trustworthiness [44].”
- Uncertainty as a Form of Transparency: Measuring, Communicating, and Using Uncertainty (2020, background): “Transparency is one way for an artificial intelligence (AI) system to show stakeholders that the system is trustworthy [140, 183].”
- Tackling threats to informed decision-making in democratic societies: Promoting epistemic security in a technologically-advanced world (2020, background): “Regina Rini (2019) makes a similar point with regard to our reliance on photographic media.”