There are several reasons to be ethically concerned about the development and use of AI. In this contribution, we focus on one specific theme of concern: moral responsibility. In particular, we consider whether the use of autonomous AI causes a responsibility gap and put forward the thesis is that this is not the case. Our argument proceeds as follows. First, we provide some conceptual background by discussing respectively what autonomous systems are, how the notion of responsibility can be understood, and what the responsibility gap is about. Second, we explore to which extent it could make sense to assign responsibility to artificial systems. Third, we argue that the use of autonomous systems does not necessarily lead to a responsibility gap. In the fourth and last section of this chapter, we set out why the responsibility gap – even if it were to exist – is not necessarily problematic.

This chapter deals with two possible ways of closing the “responsibility gap” that can occur when AI devices cause harm: holding the device itself criminally responsible and punishing the corporation that employs the device. Robots can at present not be subject to criminal liability because they do not fit into the general scheme of criminal law and cannot feel punishment. But the present scope of corporate criminal responsibility could be expanded to cover harm caused by AI devices controlled by corporations and operating for their benefit. Corporate liability for AI devices should, however, at least require an element of negligence in programming, testing, or supervising the robot.

When agents insert technological systems into their decision-making processes, they can obscure moral responsibility for the results. This can give rise to a distinct moral wrong, which we call “agency laundering.” At root, agency laundering involves obfuscating one’s moral responsibility by enlisting a technology or process to take some action and letting it forestall others from demanding an account for bad outcomes that result. We argue that the concept of agency laundering helps in understanding important moral problems in a number of recent cases involving automated, or algorithmic, decision-systems. We apply our conception of agency laundering to a series of examples, including Facebook’s automated advertising suggestions, Uber’s driver interfaces, algorithmic evaluation of K-12 teachers, and risk assessment in criminal sentencing. We distinguish agency laundering from several other critiques of information technology, including the so-called “responsibility gap,” “bias laundering,” and masking.