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DTSTAMP:20260512T081212Z
DTSTART;TZID=Europe/Berlin:20240524T234500
DTEND;TZID=Europe/Berlin:20240524T234500
SUMMARY:Philosophy of Science Meets Machine Learning conference (PhilML‘24)
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TZID:Europe/Berlin
LOCATION:Maria von der Linden Strasse 6\, Tübingen\, Germany\, 72076
DESCRIPTION:<p>The organizers of the fourth Philosophy of Science Meets Machine Learning conference (PhilML&lsquo\;24)\, taking place on September 11-13\, 2024 at the University of T&uuml\;bingen\, would like to invite the submission of extended abstracts. Submissions\, due May 24\, should consist of an anonymised extended abstract (750 words\, not including references)\, along with a cover sheet with your name\, email-address and institutional affiliation. It should be sent as an attachment to philml2024@gmail.com .&nbsp\;</p>\n<p>Since 2021\, PhilML has brought together scientifically-engaged philosophers with machine learners to address foundational issues raised by developments in ML research. Submissions are invited from all philosophical subfields\, including philosophy of science\, mind\, ethics\, epistemology and political philosophy\, as well as foundational and philosophical submissions from machine learners.&nbsp\;</p>\n<p>The workshop&rsquo\;s central topics include:</p>\n<p>(i) Reflections on key topics such as learning\, reliability\, causal inference\, robustness\, explanation\, trust\, transparency and understanding.&nbsp\;&nbsp\;</p>\n<p>(ii) Implications of machine learning for the sciences\, e.g. physics\, cognitive science\, biology\, psychology\, social science or medicine.&nbsp\;</p>\n<p>(iii) Implications of machine learning for scientific methodology\, e.g. model-building and model selection\, design of experiments\, conceptual engineering.&nbsp\;</p>\n<p>(iii) Issues arising at the intersection of machine learning and public policy\, e.g. risk assessment\, resource allocation\, climate and energy policy\, the provision of public services.&nbsp\;</p>\n<p>(iv) Novel considerations raised by foundation models e.g.\, authorship\, latent representation\, or nativism/empiricism.&nbsp\;</p>\n<p>Each abstract will be reviewed by multiple philosophers/ML researchers working in or around the University of T&uuml\;bingen. Selection criteria are research quality\, novelty\, and topical diversity. The workshop is organized by the Cluster of Excellence &lsquo\;Machine Learning: New Perspectives for Science.&rsquo\; Decisions will be announced by mid-June.</p>\n<p>As in the last years\, we again have an amazing line-up of invited speakers:</p>\n<p>- Stefan Buijsman (Delft)<br> - Molly Crockett (Princeton)<br> - Julia Haas (DeepMind)<br> - Dominik Janzing (Amazon)<br> - Gabbrielle Johnson (Claremont)<br> - Brent Mittelstadt (Oxford)<br> - Alexander Tolbert (Emory)<br> - Ana-Andreea Stoica (MPI-IS)</p>\n\n<p>For participation in the workshop we have to charge a registration fee of (tentatively) 100 Euro for senior academics\, respectively 50 Euros for graduate students\, covering beverages\, lunch and snacks\, and the conference dinner.&nbsp\;</p>\n<p>If you have questions\, please email: thomas.grote@uni-tuebingen.de</p>
ORGANIZER;CN=Thomas Grote;CN=Konstantin Genin;CN=Timo Freiesleben;CN=Sebastian Zezulka;CN=Markus Ahlers;CN=Raysa Benatti:
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