Sep 23–26, 2019

Alejandro Saucedo
Chairman, The Institute for Ethical AI & Machine Learning

Alejandro is the Chief Scientist at the Institute for Ethical AI & Machine Learning, where he leads highly technical research on machine learning explainability, bias evaluation, reproducibility and responsible design. With over 10 years of software development experience, Alejandro has held technical leadership positions across hyper-growth scale-ups and tech giants including Eigen Tchnologies, Bloomberg LP and Hack Partners. He has a strong track record building departments of machine learning engineers from scratch, and leading the delivery of large-scale machine learning system across the financial, insurance, legal, transport, manufacturing and construction sectors (in Europe, US and Latin America).

Sessions

11:20am–12:00pm Thursday, September 26, 2019

Location: 1A 12/14

A practical guide to algorithmic bias and explainability in machine learning

Data Science, Machine Learning, & AI

Secondary topics: Ethics

Alejandro Saucedo (The Institute for Ethical AI & Machine Learning)

Alejandro Saucedo demystifies AI explainability through a hands-on case study, where the objective is to automate a loan-approval process by building and evaluating a deep learning model. He introduces motivations through the practical risks that arise with undesired bias and black box models and shows you how to tackle these challenges using tools from the latest research and domain knowledge. Read more.