Generative AI and Society
Welcome! Our role will be to examine the histories, theories, and social impact of artificial intelligence.
Today, we take it as almost natural that everywhere we go we can access “information” and interact with the environment. Shopping. Financial Transactions. Work. Are all mediated (in many places in the world) by machines. Increasingly, we assume ourselves (for better or worse) to be part of large, interconnected, and constantly evolving and learning networks. We expect our search engines to change their recommendations according to our searches, we assume that our consumer behaviors will be immediately responded to and fulfilled in ever faster and more accelerated manners, we expect fast fashion, fast downloads, and increased personalization. We have even come to believe that “smart” cities and grids, and AI infrastructures will help us better respond to catastrophes and manage large agglomerations of populations under rapidly changing security, economic, and environmental conditions. AI is seen as integral to our imagined extra-terrestrial future, and to our fantasies of a geoengineering that will save us from climate change. Whether we believe AI is the next step in “disaster capitalism” and extreme neo-liberalism and neo-colonialism, or whether we believe AI will finally set the market free and permit endless prosperity, health, and eternal growth, both points of view share in the faith that computing is ubiquitous, that the future of computation will no longer be about planning or representation, and that systems can autonomously evolve through constant reflexive analysis of data.
How did we come to believe these things? How has human survival come to be equated with increased computational penetration into the environment? How have technological and natural evolution become co-extensive? And how and why and for whom does the dream of governance without representation, or even programming (as in computer programming), serve?
This course will engage these questions. To get to better understanding of these issues, we will actually study many things that you may not consider “artificial” intelligence. We will examine histories of cybernetics, the social and human sciences, and the biological and natural sciences in order to understand how we came to see the computational management of the planet as a necessary and natural thing. The narrative of this course is that concepts of environment and ecology merged with those of computation and cognition to produce our contemporary discourse of AI. The course is roughly partitioned into three sections: Evolution, Intelligence, and Ecology. These categories are of course all contested, and quite slippery. But this is part of the challenge of this course. Collectively we will struggle to develop theories, narratives, and methods by which to engage contemporary discourses of AI, and to challenge them with alternative histories, vocabularies, and practices. We will also engage with lab visits at AI research centers and actual play with Large Language Models, in order to better understand the technology and its impacts on society.