25 min
Choosing effective causes in a radically uncertain world | Eva Vivalt EA Talks
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- Non-Profit
Eva discusses the challenges to choosing the most cost-effective causes that are due to uncertainty or lack of knowledge. After describing the problem, Eva presents some possible ways forward.
Eva Vivalt is an Assistant Professor in the Department of Economics at the University of Toronto. Dr. Vivalt’s main research interests are in investigating stumbling blocks to evidence-based policy decisions, including methodological issues, how evidence is interpreted, and the use of forecasting. Dr. Vivalt is also a PI on Y Combinator Research’s basic income RCT and has other interests in labor economics, development, and global priorities research. Dr. Vivalt is the Founder of AidGrade, a research institute that generates and synthesizes evidence in international development, and Co-Founder of the Social Science Prediction Platform, a platform to coordinate the collection of forecasts of research results.
Dr. Vivalt holds a Ph.D. in Economics and an M.A. in Mathematics from the University of California, Berkeley and previously worked with the Development Economics Research Group at the World Bank. Prior to the Ph.D., Dr. Vivalt completed an M.Phil. in Development Studies at the University of Oxford on a Commonwealth Scholarship. Dr. Vivalt has visited the Department of Economics at Yale University and Stanford University and was previously a Senior Lecturer (Australian for Assistant Professor) at the Australian National University. Dr. Vivalt has also visited, and is a Research Collaborator at, the Global Priorities Institute at the University of Oxford.
This talk was taken from EA Global Asia and Pacific 2020. Click here to watch the talk with the PowerPoint presentation.
Effective Altruism is a social movement dedicated to finding ways to do the most good possible, whether through charitable donations, career choices, or volunteer projects. EA Global conferences are gatherings for EAs to meet. You can also listen to this talk along with its accompanying video on YouTube.
Eva discusses the challenges to choosing the most cost-effective causes that are due to uncertainty or lack of knowledge. After describing the problem, Eva presents some possible ways forward.
Eva Vivalt is an Assistant Professor in the Department of Economics at the University of Toronto. Dr. Vivalt’s main research interests are in investigating stumbling blocks to evidence-based policy decisions, including methodological issues, how evidence is interpreted, and the use of forecasting. Dr. Vivalt is also a PI on Y Combinator Research’s basic income RCT and has other interests in labor economics, development, and global priorities research. Dr. Vivalt is the Founder of AidGrade, a research institute that generates and synthesizes evidence in international development, and Co-Founder of the Social Science Prediction Platform, a platform to coordinate the collection of forecasts of research results.
Dr. Vivalt holds a Ph.D. in Economics and an M.A. in Mathematics from the University of California, Berkeley and previously worked with the Development Economics Research Group at the World Bank. Prior to the Ph.D., Dr. Vivalt completed an M.Phil. in Development Studies at the University of Oxford on a Commonwealth Scholarship. Dr. Vivalt has visited the Department of Economics at Yale University and Stanford University and was previously a Senior Lecturer (Australian for Assistant Professor) at the Australian National University. Dr. Vivalt has also visited, and is a Research Collaborator at, the Global Priorities Institute at the University of Oxford.
This talk was taken from EA Global Asia and Pacific 2020. Click here to watch the talk with the PowerPoint presentation.
Effective Altruism is a social movement dedicated to finding ways to do the most good possible, whether through charitable donations, career choices, or volunteer projects. EA Global conferences are gatherings for EAs to meet. You can also listen to this talk along with its accompanying video on YouTube.
25 min