Responsible Artificial Intelligence
We are an independent, nonprofit research institute that works to build ethics, accountability and transparency into AI systems: developing new algorithms, training organisations operating AI systems and providing technical guidance for AI policy development.
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 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…
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.
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.
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.
Gradient Institute is developing new techniques and tools for machine learning based causal inference and working with the ACT Education Directorate to apply them to better understand the factors behind school student outcomes.
Gradient Institute is working with the central bank and financial regulatory body of Singapore, the Monetary Authority of Singapore, to develop methodology, metrics and tools that enable the country’s financial institutions to evaluate their AI and data analytics solutions to ensure they are being…
Gradient Institute worked with the Australian Human Rights Commission (AHRC), the Consumer Policy Research Centre, CHOICE and CSIRO’s Data61 to develop a report on algorithmic bias.
Emerging technologies are shaping Australian society at an unprecedented scale. We believe in the power of students to tackle issues such as the future of work, automated decision-making and Industry 4.0. As such, we are excited to be collaborating with Tech for Social Good…
This instructor-led and guided one-day course (18 May 2021) is designed for professionals who use, or interact closely, with machine learning or statistical modelling, as well as the technical teams building them. It provides practical insights to AI uses in business in an interactive…
This two-day course (25-26 May 2021) develops the technical skills required to build systems that use machine learning to make automated decisions whilst also accounting for ethical objectives. It includes presentations, discussions, a group project, and hands-on interactive exercise modules.