Alejandro Saucedo
Chief Scientist, The Institute for Ethical AI & Machine Learning

Alejandro Saucedo 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. Previously, Alejandro held technical leadership positions across hypergrowth scale-ups and tech giants including Eigen Technologies, Bloomberg LP, and Hack Partners. He has a strong track record of 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, the US, and Latin America).

Sessions

2:35pm–3:15pm Thursday, September 12, 2019

Location: LL21 C/D

A practical guide toward explainability and bias evaluation in AI and machine learning

Models and Methods

Secondary topics: Ethics, Security, and Privacy, Machine Learning

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

Average rating:

(4.00, 3 ratings)

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.