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Hi all, looking forward to 4S in Toronto in the Fall! </div>
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If you are interested in looking at <b>methodologies of research in language, AI, and the social sciences</b>, please consider submitting our abstract for this panel.
<b>"Leaning into Language: Ordinary Language Philosophy and Artificial Intelligence.”</b> We’re really interested in brainstorming ideas for cross-disciplinary research: methods, challenges, opportunities, labs etc. A practical bent. </div>
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Blurb:</div>
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Ordinary language philosophers had a lot to say about mid-century artificial intelligence (Ryle 1949; Shanker 1998; Button et al. 1995). Often, when discussing vague concepts such as trust, thinking, consciousness, or intelligence in AI, interlocuters invoke
different referents with the same signs. Wittgenstein (1953) suggests that there might not even be a stable semantic ground upon which discussions can be formed, that the meaning of such terms can be found right there in the very arguments that are assumed
to distract from the truth (Wittgenstein 1953). </div>
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Anthropology, often called “philosophy with people in it,” (Ingold 1992) provides an ideal means by which we can test the theories of ordinary language philosophy. Linguistic anthropology, in particular, seeks to show how people’s linguistic and semiotic expressions
both shape, and are shaped by, cultural norms (Agha 2006; Nakassis 2018). When interacting with technology, for example, language allows users to make sense of their experiences and to communicate them to others; they situate their experiences within a web
of familiar concepts and tropes (Bucher 2015): other people, previous experiences with technology, representations of AI in popular culture, political affiliations, culturally sanctioned expressions of emotions etc.</div>
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These culturally-approved stances and narratives are mobilized to make sense of new experiences with new technologies (Suchman 2007; Szymanski & Whalen 2011). In this latest wave of interest in (generative) AI technologies,
<b>how can we analyze the language of both engineers and lay people as they talk about AI as an entry point into understanding the cultural, social, and affective ground upon which such descriptions are formed?</b>
<b>What qualitative and quantitative evidence can we gather that allows us to understand more fully what people talk about when they talk about AI? </b></div>
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Looking forward,</div>
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Joseph Wilson,</div>
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<a href="mailto:Joseph.wilson@utoronto.ca" data-outlook-id="a8d8005e-797d-4b48-8444-e2f235f658c1" style="color: rgb(5, 99, 193); margin-top: 0px; margin-bottom: 0px;"><u>Joseph.wilson@utoronto.ca</u></a></div>
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PhD Candidate,</div>
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Dept. of Anthropology, University of Toronto</div>
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<a href="http://www.josephwilson.ca/" title="http://www.josephwilson.ca/" data-outlook-id="e4f67a5d-958c-4bc7-8379-8f8dd069b0e6" style="color: rgb(5, 99, 193); margin-top: 0px; margin-bottom: 0px;"><u>www.josephwilson.ca</u></a></div>
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<a href="https://www.linkedin.com/in/joseph-wilson-1191659/" data-outlook-id="3cd9602c-0f7a-417c-b3c0-c7ddc42a7898" style="color: rgb(5, 99, 193); margin-top: 0px; margin-bottom: 0px;"><u>LinkedIn</u></a></div>
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Out now: <i>Humans of AI: Understanding the People Behind the Machines</i>. <a href="https://utppublishing.com/doi/book/10.3138/9781487561659" data-outlook-id="9865717b-a114-4a12-8123-2a84688088ef" style="margin-top: 0px; margin-bottom: 0px;">
University of Toronto Press Aevo</a>.</div>
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