Fairness and Biases in AI
with Emily Denton, Laura Alonso Alemany, Luciana Benotti, and Shakir Mohamed
Followed by a practical session on diagnosing and mitigating bias in word embeddings, with Laura Alonso and Luciana Benotti. The session is based on the responsibly.ai toolkit, and if you want to warm up for it and learn about the magic and wonder of word embeddings, they recommend Jay Alammar’s material.
Please join our Khipu 2021 Event Series Slack Workspace, to post questions to the panelists before the event and interact with other Khipu community members.
We hope to see you there!
Wednesday June 16th
17hs Brasilia (UTC-3)
16hs Santiago (UTC-4)
15hs Mexico DF (UTC-5)
Emily Denton is a Research Scientist on Google’s Ethical AI team where they examine the societal impacts of AI technology. Their recent research centers on critically examining the norms, values, and work practices that structure the development and use of machine learning datasets. Prior to joining Google, Emily received their PhD in machine learning from the Courant Institute of Mathematical Sciences at New York University, where they focused on unsupervised learning and generative modeling of images and video.
Laura Alonso Alemany is a linguist working on natural language processing applications. She works to facilitate understanding of language technologies in particular and data sciences in general. She is interested in machine learning as an instrument to explore language. She aims to apply the understanding of language into the shaping of solutions and applications. Lately, she is broadening this aim to also apply the understanding of society and ethical principles.
Luciana Benotti investigates dialogue systems and their social impact, including misunderstandings, grounding, and educational applications. She received an IBM and two Google awards for outreach efforts developing AI-based technology for education. She is a researcher at the Universidad Nacional de Córdoba and at CONICET in Argentina. Recently, she was an invited scholar at Stanford University and the University of Trento. She is an elected member of the NAACL executive board, representing fellow Latin-Americans working on natural language processing.
Dr Shakir Mohamed works on technical and sociotechnical questions in machine learning and artificial intelligence research, aspiring to make contributions to machine learning principles, applied problems in healthcare and environment, and ethics and diversity. Shakir is a research scientist and lead at DeepMind in London, an Associate Fellow at the Leverhulme Centre for the Future of Intelligence, and a Honorary Professor of University College London. Shakir is also a founder and trustee of the Deep Learning Indaba, a grassroots organisation aiming to build pan-African capacity and leadership in AI. Shakir was the General Chair for the 2021 International conference on Learning Representations, and a member of the Royal Society Diversity Committee.
About Khipu 2021 Event Series:
A series of monthly online meetings geared towards supporting the advancement of AI talent in Latinamerica.
The events will take place on a monthly basis with different topics every time.
Learn more about Khipu at khipu.ai.