The Pentagon has committed to combating bias in artificial intelligence but may not be asking the right questions of industry partners to be successful. AI has become a bedrock of 21st century military strategy, and the Defense Department argues that machine learning is integral to the U.S. military's competitive edge. But traditional AI models are "brittle" and "not ready for deployment," Nisheeth Vishnoi, a Yale professor of computer science, said. Wrong results on the battlefield include incorrect identification of human and environmental targets. The department has spent billions of dollars on AI development, including establishment of a Joint Artificial Intelligence ...

I've also come to realise that this code could have unintended consequences on the employment prospects, loan approvals and health outcomes of a complete stratum of society. This realisation prompted me to delve deeper into the notion of bias in artificial intelligence and its unintended consequences in real world scenarios. It's possible to build AI systems that are more robust against bias and discrimination. Furthermore, a partnership between human and machines could actually lead to improvements in the fairness of human decision making. My intention in this blog is to focus explicitly on the ways in which a biased system directly affects a minority group and steps we can take to fix it.