Socrates’ close association of madness and philosophy from the Phaedrus’ Palinode has puzzled interpreters. How can philosophy be equated to irrationality? In this paper I argue against interpretations that either deny that the association of madness and philosophy ought to be taken seriously or downplay this association by considering madness as akin to the unreflective inspiration characterizing only the first stages of philosophizing but subsequently overcome by the mature philosopher. I show that the association of madness and philosophy is an integral part of Socrates’ polemics against what he calls “human moderation”, characterized by a cold calculation of costs and benefits. And, moreover, that madness is an ongoing feature of philosophy and of the philosopher, who is never fully in possession of all his rational and cognitive processes but has to constantly work on them in an effort of self-clarification.
External visitors must comply with the university’s guest policy as outlined here: https://www.newschool.edu/covid-19/campus-access/?open=visitors.
Audience members must show proof of a full COVID-19 vaccination series (and booster if eligible), ID, and remain masked at all times.
Professor Williamson will give 3 lectures: September 19, 21, and 23. All will take place in AB-2400 [East Wing] from 4:30-6:30pm.
The lectures will discuss problems in the methodology of contemporary philosophy. Although philosophy without use of counterexamples would be a disaster, the way they are currently handled is naïve. In particular, it is too vulnerable to fake counterexamples generated by more or less universal human heuristics.
Lecture One: Heuristics [9/19]
Human cognition, from sense perception to abstract reflection, frequently employs heuristics, quick, easy, efficient, and imperfectly reliable ways of solving problems. To a neglected extent, philosophical problems and paradoxes from reliance on the outputs of fallible heuristics. This will be illustrated with examples involving vagueness, conditionals, belief ascription, truth and falsity, and reasons aggregation. Potential lessons for philosophical method will be discussed.
Lecture Two: Overfitting [9/21]
Overfitting is a well-recognized methodological problem in natural science, where use of models with too many degrees of freedom leads to unstable theorizing and failure to detect errors in the data. Overfitting is also a major but ill-recognized methodological problem in philosophy, exacerbated by its reliance on heuristics. General intellectual tendencies conducive to overfitting in philosophy will be discussed.
Lecture Three: Hyperintensionality [9/23]
The ‘hyperintensional revolution’ proclaims that central metaphysical distinctions cannot be captured in modal terms since they are sensitive to differences between necessary equivalents. Such hyperintensionalism fits the profile of overfitting. It is motivated by case judgments that are explicable as results of a fallible heuristic and it leads to models with too many degrees of freedom.
Professor Williamson will give 3 lectures: September 19, 21, and 23. All will take place in AB-2400 [East Wing] from 4:30-6:30pm.
The lectures will discuss problems in the methodology of contemporary philosophy. Although philosophy without use of counterexamples would be a disaster, the way they are currently handled is naïve. In particular, it is too vulnerable to fake counterexamples generated by more or less universal human heuristics.
Lecture One: Heuristics [9/19]
Human cognition, from sense perception to abstract reflection, frequently employs heuristics, quick, easy, efficient, and imperfectly reliable ways of solving problems. To a neglected extent, philosophical problems and paradoxes from reliance on the outputs of fallible heuristics. This will be illustrated with examples involving vagueness, conditionals, belief ascription, truth and falsity, and reasons aggregation. Potential lessons for philosophical method will be discussed.
Lecture Two: Overfitting [9/21]
Overfitting is a well-recognized methodological problem in natural science, where use of models with too many degrees of freedom leads to unstable theorizing and failure to detect errors in the data. Overfitting is also a major but ill-recognized methodological problem in philosophy, exacerbated by its reliance on heuristics. General intellectual tendencies conducive to overfitting in philosophy will be discussed.
Lecture Three: Hyperintensionality [9/23]
The ‘hyperintensional revolution’ proclaims that central metaphysical distinctions cannot be captured in modal terms since they are sensitive to differences between necessary equivalents. Such hyperintensionalism fits the profile of overfitting. It is motivated by case judgments that are explicable as results of a fallible heuristic and it leads to models with too many degrees of freedom.
Professor Williamson will give 3 lectures: September 19, 21, and 23. All will take place in AB-2400 [East Wing] from 4:30-6:30pm.
The lectures will discuss problems in the methodology of contemporary philosophy. Although philosophy without use of counterexamples would be a disaster, the way they are currently handled is naïve. In particular, it is too vulnerable to fake counterexamples generated by more or less universal human heuristics.
Lecture One: Heuristics [9/19]
Human cognition, from sense perception to abstract reflection, frequently employs heuristics, quick, easy, efficient, and imperfectly reliable ways of solving problems. To a neglected extent, philosophical problems and paradoxes from reliance on the outputs of fallible heuristics. This will be illustrated with examples involving vagueness, conditionals, belief ascription, truth and falsity, and reasons aggregation. Potential lessons for philosophical method will be discussed.
Lecture Two: Overfitting [9/21]
Overfitting is a well-recognized methodological problem in natural science, where use of models with too many degrees of freedom leads to unstable theorizing and failure to detect errors in the data. Overfitting is also a major but ill-recognized methodological problem in philosophy, exacerbated by its reliance on heuristics. General intellectual tendencies conducive to overfitting in philosophy will be discussed.
Lecture Three: Hyperintensionality [9/23]
The ‘hyperintensional revolution’ proclaims that central metaphysical distinctions cannot be captured in modal terms since they are sensitive to differences between necessary equivalents. Such hyperintensionalism fits the profile of overfitting. It is motivated by case judgments that are explicable as results of a fallible heuristic and it leads to models with too many degrees of freedom.
Generative art made with algorithms has existed since the early days of computing in the 1960s. In recent years, a new strand of generative art has emerged: AI-generated art, which leverages the recent progress of artificial intelligence to create artworks. Unlike old-fashioned generative art, AI-generated art is not produced with an explicit set of programming instructions provided by human artists; instead, it involves training an algorithm on a dataset so that it can later produce artworks (images, music, or video clips) using its own internal parameters that have not been explicitly defined by a human. This process raises fascinating questions at the intersection of computer science, art history, and the philosophy of art. At a superficial level of analysis, AI-generated art seems to offload much of the creative impetus of art production to the machine, requiring minimal intervention from the artist. On closer inspection, however, it involves a novel process of curation at two key stages: upstream in the selection of the dataset on which the algorithm is trained, and downstream in the selection of the outputs that should qualify as artworks. Instead of replacing human artists with computers, AI-generated art can be understood as a new kind of collaboration between mind and machine, both of which contribute to the aesthetic value of the final artwork.
This seminar will bring together AI artists and philosophers to explore the significance of this new mode of art production. It will discuss the implications of AI-generated art for the definition of art, the nature of the relationship between artists and tools, the process of digital curation, and whether AI systems can be as creative as humans.
Event Speakers
- Sougwen Chung, artist and researcher
- Helena Sarin, visual artist
- Anne Spalter, digital mixed-media artist
- Katherine Thomson-Jones, Professor of Philosophy at Oberlin College
- Moderated by Raphaël Millière, Presidential Scholar in Society and Neuroscience at Columbia University
Event Information
Free and open to the public. Registration is required via Eventbrite. Registered attendees will receive an event link shortly before the seminar begins.
This event is hosted by the Presidential Scholars in Society and Neuroscience as part of the Seminars in Society and Neuroscience series.
The Center for Science and Society makes every reasonable effort to accommodate individuals with disabilities. If you require disability accommodations to attend a Center for Science and Society event, please contact us at scienceandsociety@columbia.edu or (212) 853-1612 at least 10 days in advance of the event. For more information, please visit the campus accessibility webpage.
A prominent logician Melvin Fitting has turned 80. This hybrid conference is a special event in his honor.
Melvin Fitting was in the departments of Computer Science, Philosophy, and Mathematics at the CUNY Graduate Center and in the department of Mathematics and Computer Science at Lehman College. He is now Professor Emeritus. He has authored 11 books and over a hundred research papers with staggering citation figures. In 2012, Melvin Fitting was given the Herbrand Award by the Conference on Automated Deduction (CADE) for distinguished contributions to the field. In 2019, Professor Fitting received a Doctor Honoris Causa (an Honorary Doctorate) from the University of Bucharest.
Greetings, congratulations, photos for posting, and ZOOM link requests could be sent to Sergei Artemov by sartemov@gmail.com or sartemov@gc.cuny.edu.
Conference website https://sartemov.ws.gc.cuny.edu/fitting-at-80/
Program (the times are given in the Eastern Day Time zone EST). In-person location: CUNY Graduate Center, rm. 3310-B.
January 28, Saturday
8:00-8:45 am Arnon Avron (Tel Aviv), “Breaking the Tie: Benacerraf’s Identification Argument Revisited”
8:45-9:30 am Junhua Yu (Beijing), “Exploring Operators on Neighborhood Models”
9:30-9:45 am Break
9:45-10:30 am Sara Negri (Genoa), “Faithful Modal Embedding: From Gödel to Labelled Calculi”
10:30-11:15 am Heinrich Wansing (Bochum), “Remarks on Semantic Information and Logic. From Semantic Tetralateralism to the Pentalattice 65536_5”
11:15-11:30 am Break
11:30 am -12:15 pm Roman Kuznets (Vienna), “On Interpolation”
12:15-1:00 pm Walter Carnielli (Campinas), “Combining KX4 and S4: A logic that encompasses factive and non-factive evidence“
1:00-1:15 pm Break
1:15-2:00 pm Eduardo Barrio and Federico Pailos (Buenos Aires), “Meta-classical Non-classical Logics”
2:00-2:45 pm Graham Priest (New York), “Jaśkowski and the Jains: a Fitting Tribute”
2:45-4:00 pm Session of memories and congratulations featuring Sergei Artemov, Anil Nerode, Hiroakira Ono, Melvin Fitting, and others.