Title: “Machine learning: from research, application to downstream societal impacts”
Abstract: AI has come to exert an outsized influence and impact on the world, particularly on marginalised communities. Yet, research in machine learning tends to develop in a siloed manner from the downstream societal impacts, where the kind of applications that are built upon research and their uses, the underlying values of the field, as well as uneven distribution of harm and benefit have largely been ignored. In this talk, I discuss the underlying values of machine learning research as well as downstream impact of AI research in general and Computer Vision in particular. I present quantitative and qualitative analysis showing 1) predominant values driving the field of machine learning and the concentration of power in the hands of the few and 2) how computer vision research is powering mass surveillance. I highlight the ethical and societal implications of such work and the role machine learning researchers might play in disrupting the ‘Computer Vision, surveillance’ pipeline.
Bio: Abeba Birhane is a cognitive scientist, currently a Senior Advisor in AI Accountability at Mozilla Foundation and an Adjunct Assistant Professor at the School of Computer Science and Statistics at Trinity College Dublin, Ireland. Her research focuses on AI accountability, with a particular focus on audits of AI models and training datasets – work for which she was featured in Wired UK and TIME on the TIME100 Most Influential People in AI list. Birhane also serves on the United Nations Secretary-General’s AI Advisory Body and the newly-convened AI Advisory Council in Ireland.
Zoom: https://jhuapl.zoomgov.com/j/1615644606?pwd=N83DHG4pIXb6M4IZVa0x7CDycjzSEP.1
Meeting ID: 161 564 4606
Passcode: 173018