Situating AI on the road from data sharing to societal impact

This talk is part of the AI Lunch series at the Jefferson Lab and was given remotely on 2 September 2020.

Abstract

By its very nature, Artificial Intelligence depends on the availability of data at scale. In this presentation - which shall be available at https://doi.org/10.5281/zenodo.3996019 when it starts - we will look at a range of factors that influence the nature and scale of data sharing, from open science to disasters, from research infrastructures to ethics, from cooperation to competition. We will then delve into how these factors affect the data life cycle and the research cycle and explore how data sharing (or the lack of it) translates into societal impact. On that journey, we will watch out for ways in which AI can and does contribute to or benefit from the sharing of data and associated resources (or not), which will then form the basis of our discussion.

Further notes: https://github.com/Daniel-Mietchen/events/blob/master/JLab-AI-Lunch-Series.md