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AI systems, like self-driving cars, healthcare robots, or Autonomous Weapon Systems, already play an increasingly important role in our lives and will do so to an even greater extent in the near future. This raises a fundamental philosophical question: who is morally responsible when such systems cause unjustified harm? In the paper, we argue for the admittedly surprising claim that some of these systems can themselves be morally responsible for their conduct in an important and everyday sense of the term—the attributability sense. More specifically, relying on work by Nomy Arpaly and Timothy Schroeder (In Praise of Desire, OUP 2014), we propose that the behavior of these systems can manifest their ‘quality of will’ and thus be regarded as something they can be blameworthy for. We develop this position in detail, justify some of its crucial presuppositions, and defend it against potential objections.

It is a standard assumption in philosophy of mind and cognitive science that many animals are representational systems: they possess states that represent the world as being a certain way, and that can thus be true or false, correct or incorrect, satisfied or unsatisfied. This raises an interesting question that has recently attracted considerable attention: do some plants qualify as representational systems, too? This chapter will begin by arguing that we should adopt a thoroughly gradualist picture of representation, where an organism's degree of “representationality” is determined (roughly speaking) by the complexity of the information processing underlying its cognitive and behavioral capacities. On this basis, the chapter examines some prominent empirical arguments that have recently been advanced in favor of the thesis that plants are representational systems and argues that they are unsuccessful. However, it will also be suggested that there are some studies that might actually provide support for ascribing a certain degree of representationality to plants, albeit one that is well below the degree that would justify characterizing them as representational systems simpliciter.