Here's how we teach machines to be fair

As we empower machines to make critical decisions about who can access vital opportunities, we need to prevent discriminatory outcomes. After all, machine learning is only a tool. The responsibility falls on people use it wisely – especially the people leading the way in its advancement, from corporate leaders down to system engineers. In other words, we need to design and use ML applications in a way that not only improves business efficiency but also promotes and protects human rights. But the nature of ML technology – its ubiquitousness, complexity, exclusiveness and opaqueness – can amplify longstanding problems related to unequal access to opportunities.