Description:

Recent years have seen profound developments in the ability of machines to generate natural language. Trained on massive bodies of existing linguistic data, large language models (LLMs) like those behind OpenAI's ChatGPT, Google's Bard, Meta's LlamaChat, or Anthropic's Claude have astonished the public with their general-purpose ability to generate naturalistic text: to write poems and recipes; social media posts and term papers; legal briefs and instruction manuals; reference letters and manifestos. They have also raised urgent questions about the risks and potentials that this technology holds for our lives, including our political lives. How will LLMs amplify the threats of mis- and dis-information? How can they avoid replicating the biases found in the datasets they were trained on? How will they interfere with mechanisms of both institutional and grassroots political action? Whose labor will they replace, and to whose benefit? Who gets to control them, and how? And how might they enhance the creativity that we bring to devising political strategies and theorizing our political lives?

This online event brings together scholars from computer science, political theory and philosophy to examine these and other questions about large language models and politics from a variety of angles.

Panelists:

Emma Rodman (Political Science, UMass Lowell)

Amy Zhang (Computer Science, University of Washington)

Annette Zimmerman (Philosophy, University of Wisconsin-Madison)

Register for the event HERE