A little after 2 a.m. on February 11, 2013, Michael Vang sat in a stolen car and fired a shotgun twice into a house in La Crosse, Wisconsin. Shortly afterward, Vang and Eric Loomis crashed the car into a snowbank and fled on foot. They were soon caught, and police recovered spent shell casings, live ammunition, and the shotgun from the stolen and abandoned car. Vang pleaded no contest to operating a motor vehicle without the owner’s consent, attempting to flee or elude a traffic officer, and possession of methamphetamine. He was sentenced to ten years in prison.

One important criticism of algorithmic systems is that they lack transparency, either because they are complex, protected by intellectual property, or deliberately obscure. There is a debate about whether the EU’s General Data Protection Regulation (GDPR) contains a “right to explanation” This chapter addresses the informational component of algorithmic systems. We argue that information access is integral for respecting autonomy, and transparency policies should be tailored to advance autonomy. We distinguish two facets of agency (i.e., capacity to act). The first is “practical agency,” or the ability to act effectively according to one’s values. The second is “cognitive agency,” which is the ability to exercise what Pamela Hieronymi calls “evaluative control”. We argue that respecting autonomy requires providing persons sufficient information to exercise evaluative control and properly interpret the world and one’s place in it. We draw this distinction out by considering algorithmic systems used in background checks, and we apply the view to key cases involving risk assessment in criminal justice decisions and K-12 teacher evaluation.