Managing algorithmic risks--safeguarding the use of complex algorithms and machine learning

The rise of advanced data analytics and cognitive technologies has led to an explosion in the use of algorithms across a range of purposes, industries, and business functions. Decisions that have a profound impact on individuals are being influenced by these algorithms--including what information individuals are exposed to, what jobs they're offered, whether their loan applications are approved, what medical treatment their doctors recommend, and even their treatment in the judicial system. What's more, dramatically increasing complexity is fundamentally turning algorithms into inscrutable black boxes of decision making. An aura of objectivity and infallibility may be ascribed to algorithms. But these black boxes are vulnerable to risks, such as accidental or intentional biases, errors, and frauds--raising the question of how to "trust" algorithmic systems.