1. Creating a Cooperative AI Policymaking Platform through Open Source Collaboration
- Author
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Lewington, Aiden, Vittalam, Alekhya, Singh, Anshumaan, Uppuluri, Anuja, Ashok, Arjun, Athmaram, Ashrith Mandayam, Milt, Austin, Smith, Benjamin, Weinberger, Charlie, Sarin, Chatanya, Bergmeir, Christoph, Chang, Cliff, Patel, Daivik, Li, Daniel, Bell, David, Cao, Defu, Shin, Donghwa, Kang, Edward, Zhang, Edwin, Li, Enhui, Chen, Felix, Smithline, Gabe, Chen, Haipeng, Gasztowtt, Henry, Shin, Hoon, Zhang, Jiayun, Gray, Joshua, Low, Khai Hern, Patel, Kishan, Cooke, Lauren Hannah, Burstein, Marco, Kalapatapu, Maya, Mittal, Mitali, Chen, Raymond, Zhao, Rosie, Majid, Sameen, Potlapalli, Samya, Wang, Shang, Patel, Shrenik, Li, Shuheng, Komaragiri, Siva, Lu, Song, Siangjaeo, Sorawit, Jung, Sunghoo, Zhang, Tianyu, Mao, Valery, Krishnakumar, Vikram, Zhu, Vincent, Kam, Wesley, Li, Xingzhe, and Liu, Yumeng
- Subjects
Computer Science - Computers and Society ,Computer Science - Artificial Intelligence ,Computer Science - Machine Learning - Abstract
Advances in artificial intelligence (AI) present significant risks and opportunities, requiring improved governance to mitigate societal harms and promote equitable benefits. Current incentive structures and regulatory delays may hinder responsible AI development and deployment, particularly in light of the transformative potential of large language models (LLMs). To address these challenges, we propose developing the following three contributions: (1) a large multimodal text and economic-timeseries foundation model that integrates economic and natural language policy data for enhanced forecasting and decision-making, (2) algorithmic mechanisms for eliciting diverse and representative perspectives, enabling the creation of data-driven public policy recommendations, and (3) an AI-driven web platform for supporting transparent, inclusive, and data-driven policymaking.
- Published
- 2024