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{ "pk": 28765, "title": "AI and Cognitive Testing: A New Conceptual Framework and Roadmap", "subtitle": null, "abstract": "Understanding how a person thinks, i.e., measuring a singleindividual’s cognitive characteristics, is challenging becausecognition is not directly observable. Practically speaking, stan-dardized cognitive tests (tests of IQ, memory, attention, etc.),with results interpreted by expert clinicians, represent the stateof the art in measuring a person’s cognition. Three areas ofAI show particular promise for improving the effectiveness ofthis kind of cognitive testing: 1) behavioral sensing, to morerobustly quantify individual test-taker behaviors, 2) data min-ing, to identify and extract meaningful patterns from behav-ioral datasets; and 3) cognitive modeling, to help map ob-served behaviors onto hypothesized cognitive strategies. Webring these three areas of AI research together in a unified con-ceptual framework and provide a sampling of recent work ineach area. Continued research at the nexus of AI and cogni-tive testing has potentially far-reaching implications for soci-ety in virtually every context in which measuring cognition isimportant, including research across many disciplines of cog-nitive science as well as applications in clinical, educational,and workforce settings.", "language": "eng", "license": { "name": "", "short_name": "", "text": null, "url": "" }, "keywords": [ { "word": "artificial intelligence; behavioral sensing; cogni-tive modeling; computational psychiatry; neuropsychology" } ], "section": "Papers with Poster Presentations", "is_remote": true, "remote_url": "https://escholarship.org/uc/item/7g2327r9", "frozenauthors": [], "date_submitted": null, "date_accepted": null, "date_published": "2019-01-01T18:00:00Z", "render_galley": null, "galleys": [ { "label": "PDF", "type": "pdf", "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/28765/galley/18636/download/" } ] }