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Hum.-Robot Interact."],"published-print":{"date-parts":[[2021,9,30]]},"abstract":"<jats:p>Explainability has emerged as a critical AI research objective, but the breadth of proposed methods and application domains suggest that criteria for explanation vary greatly. In particular, what counts as a good explanation, and what kinds of explanation are computationally feasible, has become trickier in light of oqaque \u201cblack box\u201d systems such as deep neural networks. Explanation in such cases has drifted from what many philosophers stipulated as having to involve deductive and causal principles to mere \u201cinterpretation,\u201d which approximates what happened in the target system to varying degrees. However, such post hoc constructed rationalizations are highly problematic for social robots that operate interactively in spaces shared with humans. For in such social contexts, explanations of behavior, and, in particular, justifications for violations of expected behavior, should make reference to socially accepted principles and norms.<\/jats:p>\n          <jats:p>\n            In this article, we show how a social robot\u2019s actions can face explanatory demands for how it came to act on its decision, what goals, tasks, or purposes its design had those actions pursue and what norms or social constraints the system recognizes in the course of its action. As a result, we argue that explanations for social robots will need to be accurate representations of the system\u2019s operation along causal, purposive, and justificatory lines. These explanations will need to generate appropriate references to principles and norms\u2014explanations based on mere \u201cinterpretability\u201d will ultimately fail to connect the robot\u2019s behaviors to its appropriate determinants. We then lay out the foundations for a cognitive robotic architecture for HRI, together with particular component algorithms, for generating explanations and engaging in justificatory dialogues with human interactants. Such explanations track the robot\u2019s\n            <jats:italic>actual<\/jats:italic>\n            decision-making and behavior, which themselves are determined by normative principles the robot can describe and use for justifications.\n          <\/jats:p>","DOI":"10.1145\/3457183","type":"journal-article","created":{"date-parts":[[2021,7,12]],"date-time":"2021-07-12T00:21:25Z","timestamp":1626049285000},"page":"1-23","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":17,"title":["Explaining in Time"],"prefix":"10.1145","volume":"10","author":[{"given":"Thomas","family":"Arnold","sequence":"first","affiliation":[{"name":"Tufts University, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Daniel","family":"Kasenberg","sequence":"additional","affiliation":[{"name":"Tufts University, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Matthias","family":"Scheutz","sequence":"additional","affiliation":[{"name":"Tufts University, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2021,7,11]]},"reference":[{"key":"e_1_2_1_1_1","unstructured":"Dario Amodei Chris Olah Jacob Steinhardt Paul Christiano John Schulman and Dan Man\u00e9. 2016. 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