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Welcome to the Ethical AI team

We are excited to announce that Gradient Institute and Ethical AI Advisory have joined together! We have been working together as partners for the last year and realised how complementary we were – with Gradient working on the technical aspects of ensuring AI is used responsibly and Ethical AI Advisory working on the organisational and

Machine learning as a tool for evidence-based policy

In this article, Gradient's Dan Steinberg and Finn Lattimore show how machine learning can be used for evidence-based policy. They show how it can capture complex relationships in data, helping mitigate bias from model mis-specification and how regularisation can lead to better causal estimates.

AI-LEAP Call for Papers

AI-LEAP is a new Australia-based conference aiming at exploring Artificial Intelligence (AI) from a multitude of perspectives: Legal, Ethical, Algorithmic and Political (LEAP). It draws broadly on computer science, social sciences and humanities to provide an exciting intellectual forum for a genuinely interdisciplinary exchange of ideas on what’s one of the most pressing issues of our times. The first edition will take place in Canberra in December 2021.

Gradient provides AI Primer for National AI Summit

At the request of the Australian Government's Department of Industry, Science, Energy and Resources, Gradient Institute provided an interactive "Artificial Intelligence Primer" training session for attendees at the National AI Summit.

Explainer on Causal Inference with Bayes Rule

In this article, Finn Lattimore and David Rohde show how a Bayesian approach to inferring the impact of interventions or actions representing causality softens the boundary between tractable and impossible queries, and opens up potential new approaches to causal inference.

Practical fairness assessments for AI systems in finance

Gradient Institute's Chief Practitioner, Lachlan McCalman, describes our collaborative work with the Monetary Authority of Singapore and industry partners to develop a practical AI Fairness assessment methodology.

Next-best-action for social good

Gradient's Chief Scientist, Tiberio Caetano, explains how next-best-action systems are often used to optimise business metrics and individual customer outcomes, but questions whether they could also become a vehicle for promoting social good.

New tools for fairer AI

A new technical paper for the Australian Human Rights Commission produced by Gradient Institiute with the Consumer Policy Research Centre, CHOICE and CSIRO's Data61 shows how businesses can identify algorithmic bias in artificial intelligence systems, and proposes steps they can take to address the problem.