Talk details:

AI Seminar: Painful Intelligence: What AI Can Tell Us About Human Suffering

Speaker: Dr. Aapo Hyvärinen, Professor of Computer Science, University of Helsinki

Location: KEC 1001 and Zoom

Zoom link: https://oregonstate.zoom.us/s/98357211915

Talk Abstract:

This talk introduces my recent e-book with the same title, freely available on Arxiv. The book uses the modern theory of artificial intelligence (AI) to understand human suffering or mental pain. Both humans and sophisticated AI agents process information about the world in order to achieve goals and obtain rewards, which is why AI can be used as a model of the human brain and mind. The book starts with the assumption that suffering is mainly caused by frustration. Frustration means the failure of an agent (whether AI or human) to achieve a goal or a reward it wanted or expected. Frustration is inevitable because of the overwhelming complexity of the world, limited computational resources, and scarcity of good data. In particular, such limitations imply that an agent acting in the real world must cope with uncontrollability, unpredictability, and uncertainty, which all lead to frustration. Such computational theory is finally used to derive various interventions or training methods that will reduce suffering in humans. The ensuing interventions are very similar to those proposed by Buddhist and Stoic philosophy, and include mindfulness meditation.

Speaker Bio:

Aapo Hyvärinen studied undergraduate mathematics at the universities of Helsinki (Finland), Vienna (Austria), and Paris (France), and obtained a Ph.D. degree in Information Science at the Helsinki University of Technology in 1997. After post-doctoral work at the Helsinki University of Technology, he moved to the University of Helsinki in 2003, where he was appointed Professor in 2008, at the Department of Computer Science. From 2016 to 2019, he was Professor of Machine Learning at the Gatsby Computational Neuroscience Unit, University College London, UK. Aapo Hyvarinen is the main author of the books "Independent Component Analysis" (2001), "Natural Image Statistics" (2009), and "Painful Intelligence" (2022). He is Action Editor at the Journal of Machine Learning Research and Neural Computation, and has worked as Area Chair at ICML, ICLR, AISTATS, UAI, ACML and NeurIPS. He is a Fellow at the European Laboratory for Learning and Intelligent Systems (ELLIS). His research focuses on the probabilistic theory of machine learning and its applications in neuroscience.

If you would like to meet with the speakers one-on-one, please email tadepall@oregonstate.edu by Tuesday.

For future AI seminars, please visit: https://engineering.oregonstate.edu/EECS/research/AI-seminars.

Best,

Christian Abou Mrad 

Graduate Student 

Oregon State University