Hyvärinen Aapo. Painful intelligence: What AI can tell us about human suffering

Helsinki: University of Helsinki, 2022. — 231 p.This 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 to achieve goals and obtain rewards, which is why AI can be used as a model of the human brain and mind. This book intends to make the theory accessible to a relatively general audience, requiring only some relevant scientific background. 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. Fundamental in such modeling is the idea of learning, or adaptation to the environment. While AI uses machine learning, humans and animals adapt by a combination of evolutionary mechanisms and ordinary learning. Even frustration is fundamentally an error signal that the system uses for learning. This book explores various aspects and limitations of learning algorithms and their implications regarding suffering. At the end of the book, computational theory is used to derive various interventions or training methods that will reduce suffering in humans. The amount of frustration is expressed by a simple equation that indicates how it can be reduced. The ensuing interventions are very similar to those proposed by Buddhist and Stoic philosophy and include mindfulness meditation. Therefore, this book can be interpreted as an exposition of a computational theory justifying why such philosophies and meditation reduce human suffering.Suffering as error signalingDefining suffering.
Frustration due to failed plan.
Machine learning as minimization of errors.
Frustration due to reward prediction error.
Suffering due to self-needs.
Fast and slow intelligence and their problems.Origins of suffering: uncontrollability and uncertaintyEmotions and desires as interrupts.
Thoughts wandering by default.
Perception as construction of the world.
Distributed processing and no-self philosophy.
Consciousness is the ultimate illusion.Liberation from sufferingOverview of the causes and mechanisms.
Reprogramming the brain to reduce suffering.
Retraining neural networks by meditation.Epilogue.