Job at HKU
The school of humanities at HKU is inviting applications for a professor of philosophy, who works in the area of philosophy of AI or philosophy of technology. The ad, including whom to contact for more information, is here.
Special Issue in Inquiry
Inquiry is accepting submissions for an upcoming special issue on new work in the philosophy of artificial intelligence. The deadline is 1 May 2023. Details can be found here.
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Sharadin Fellowship
Lab member Nate Sharadin has been awarded a CAIS philosophy fellowship. More information is here.
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OUP Volume
Lab leaders Herman Cappelen and Rachel Sterken are editing a book about communicating with AI, with many leading philosophers.
Upcoming conference in Oslo
Ai&Humanity@HKU, in conjunction with the University of Oslo’s New Frontiers In Speech project, is arranging a two day workshop on communicating with AI. The schedule is below; check back soon for abstracts. The conference website is here. Sunday, June 19th, 2022 9:00-10:30 Rachel Sterken, Eliot Michaelson and Jessica Pepp. The Alignment Problem in Human-AI Communication
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Can AI Transform Philosophy?
Herman Cappelen’s paper “Can AI Transform Philosophy” will be published in the Asian Journal Of Philosophy. It will feature a reply by David Chalmers (NYU).
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Cameron Bruckner Talk
On 6 May 2022, at 10am HK, Philosophy@HKU, in an event co-sponsored by AI&Humanity, will be hosting Cameron Bruckner (University of Houston), who will give a talk entitled Ideational Preparation Is All You Need–Deep Learning Meets the Faculty Empiricism Of William James. The event will be held on Zoom. More details, including the Zoom link,
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Sterken on Manipulation, Retweets
Rachel Sterken’s project has produced the following research outputs, which are completed and soon to be published:
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Zoom Roundtable
Introducing the Hong Kong Philosophy of AI group (see here for more details), we’re holding a roundtable on Zoom with Herman Cappelen, Janet Hiao, and Jiji Zhang. Topic. What is meant by “Explainable and Interpretable AI”? When is it important that AI be interpretable and explainable? What are the methods of achieving and measuring explainability?