AI 2030
Jason Chandra, FRM, currently serves as a Senior Consultant in Data Science & Analytics at Peregrine Economics and as a Graduate Research Assistant at the University of Chicago, focusing on time series and statistical analysis related to demolitions and demographic issues. As a Data Scientist Consultant for The Chicago Low-Income Housing Trust Fund, Jason leads data integration projects and employs NLP and sentiment analysis for property inspection data. Jason's past experience includes working as an NLP Data Scientist on a capstone project at the Federal Reserve Bank of New York, where Jason developed an NLP-based economic dashboard. Prior roles encompass a Portfolio Management Analyst position at Milliman, where Jason developed financial strategies, and a DJ/EDM Producer role at Loch Recordings. Jason holds a Master of Science in Applied Data Science from the University of Chicago and a Bachelor of Arts in Physics and Economics from Northwestern University.
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AI 2030
AI 2030 is an initiative aimed at harnessing the transformative power of AI to benefit humanity while minimizing its potential negative impact. By bringing together leading experts from government agencies, academia, industry, and various sectors, AI2030 seeks to shape global AI agendas and foster public-private collaboration in the responsible development and use of AI. The initiative addresses various aspects of responsible AI, including governance, regulations, industry-specific frameworks, principles, best practices, and cutting-edge tools and solutions.