Every step forward in artificial intelligence (AI) challenges assumptions about what machines can do. Myriad opportunities for economic benefit have created a stable flow of investment into AI research and development, but with the opportunities come risks to decision-making, security and governance. Increasingly intelligent systems supplanting both blue- and white-collar employees are exposing the fault lines in our economic and social systems and requiring policy-makers to look for measures that will build resilience to the impact of automation. Leading entrepreneurs and scientists are also concerned about how to engineer intelligent systems as these systems begin implicitly taking on social obligations and responsibilities, and several of them penned an Open Letter on Research Priorities for Robust and Beneficial Artificial Intelligence in late 2015.1 Whether or not we are comfortable with AI may already be moot: more pertinent questions might be whether we can and ought to build trust in systems that can make decisions beyond human oversight that may have irreversible consequences. By providing new information and improving decision-making through data-driven strategies, AI could potentially help to solve some of the complex global challenges of the 21st century, from climate change and resource utilization to the impact of population growth and healthcare issues.