AI doesn’t create bias, it inherits it – how do we ensure fairness when it comes to automated decisions?

When artificial intelligence (AI) systems influence decisions that impact people’s lives, they should do so fairly. This should go without saying, considering that potential applications for AI include automated hiring systems, as well as tools for education, finance, and criminal justice.

But ensuring the fairness of AI systems is far more complex than it sounds. Despite years of research, there is still no consensus about what fairness means, how it should be measured, and whether it can ever be fully achieved.

Fairness inherently depends on context. What is considered fair in one area may be inappropriate or even harmful in another area. In the criminal justice system, justice may be primarily about preventing disproportionate harm to particular communities. In education, the focus can be on equity and long-term outcomes.

Finance is often about balancing access to credit with risk assessment. Because AI systems must be formalized mathematically, researchers are translating fairness into…