Lindsay Brainard

This paper identifies, explores, and resolves a tension between two common ideas about creativity. The first is that a project is less creative insofar as it adheres to a formula of some kind. The second is that a project’s being carried out within a set of constraints does not necessarily make it less creative. The tension arises from the fact that formulae and constraints operate in the same manner. They reduce the set of options for an agent undertaking some project. How could it be that reducing an agent’s options both does and does not make their project less creative? I resolve this tension by arguing that the first idea is false and should be replaced with the claim that a project is less creative insofar as the decisions that comprise it are dictated by a formula rather than being attributable to the agent. Finally, I employ a case study to demonstrate that there are ways in which formulae and constraints can diminish creativity and ways in which they can have no effect, or perhaps even enhance creativity.

This letter addresses a hypothetical undergraduate student who is on the brink of outsourcing their creative writing assignment to ChatGPT. I argue that the student should not do so for three reasons. They are (1) that creativity is valuable not only because it results in new products, but also because it necessarily involves learning; (2) that creativity offers a path to figuring ourselves out; and (3) that creativity enables meaningful connection with others. As I show, these reasons generalize beyond creative writing assignments. They support the conclusion that students (and the rest of us) should do other creative things instead of outsourcing them to AI as well.

I argue that there is an underappreciated threat posed by the emergence of generative artificial intelligence (AI). I call this the threat of creative obsolescence. The threat is that, given the capabilities of generative AI, humans may gradually abandon our creative pursuits, and in doing so, lose something of significant value. To show why the threat is a realistic possibility, I consider three kinds of value philosophers have attributed to creativity: aesthetic value, epistemic value, and practical value. I then offer examples in which contemporary AI models appear to furnish value of each kind. I argue that the fact that AI appears capable of generating products with the same kinds of value for which human creativity has long been prized raises a question: Should humans continue to strive for creativity in the age of AI? I argue for three reasons to think we should. Each reason identifies a value of creativity that AI appears unable to replicate: imagination, originality, and connectedness. If I am right about any of these reasons, AI cannot fully replace the value of human creativity. But if we fail to recognize this and outsource our creative pursuits to AI, we risk a future in which the distinctive value of human creativity is lost.

There is an underappreciated respect in which the widespread availability of generative artificial intelligence (AI) models poses a threat to human connection. My central contention is that human creativity is especially capable of helping us connect to others in a valuable way, but the widespread availability of generative AI models reduces our incentives to engage in various sorts of creative work in the arts and sciences. I argue that creative endeavors must be motivated by curiosity, and so they must disclose the creative agent’s inquisitive self. It is through self-disclosure, including the disclosure of the inquisitive self, that we put ourselves in a position to be seen by and connect with others through our creative pursuits. Because relying on AI for certain generative tasks is less self-disclosive than the creative work such technologies supplant, this reliance threatens to weaken our connections to one another.

I argue for an account of creativity that unifies creative achievements in the arts, sciences, and other domains and identifies its characteristic value. This account draws upon case studies of creative work in both the arts and sciences to identify creativity as a kind of successful exploration. I argue that if creativity is properly understood in this way, then it is fundamentally a property of processes, something only agents can achieve, something that comes in degrees, subjectively novel, and non-formulaic. As I develop the account, I show how it avoids challenges faced by other accounts of creativity, especially concerning creativity’s value. Hills and Bird (2018, 2019) have together argued that creativity is not necessarily valuable. My account challenges this view. If I am right that creativity is a kind of successful exploration, then creativity does have a characteristic value, specifically epistemic value.

This paper seeks to answer the question: Can contemporary forms of artificial intelligence be creative? To answer this question, I consider three conditions that are commonly taken to be necessary for creativity. These are novelty, value, and agency. I argue that while contemporary AI models may have a claim to novelty and value, they cannot satisfy the kind of agency condition required for creativity. From this discussion, a new condition for creativity emerges. Creativity requires curiosity, a motivation to pursue epistemic goods. I argue that contemporary AI models do not satisfy this new condition. Because they lack both agency and curiosity, it is a mistake to attribute the same sort of creativity to AI that we prize in humans. Finally, I consider the question of whether these AI models stand to make human creativity in the arts and sciences obsolete, despite not being creative themselves. I argue, optimistically, that this is unlikely.

Explaining how something is possible is a familiar and epistemically important achievement in both science and ordinary life. But a satisfactory general account of how-possibly explanation has not yet been given. A crucial desideratum for a successful account is that it must differentiate a demonstration that something is possible from an explanation of how it is possible. In this paper, I offer an account of how-possibly explanation that fully captures this distinction. I motivate my account using two cases, one from ordinary life and one from ornithology. On my account, a how-possibly explanation is a greater achievement than a mere description of how a state of affairs might possibly obtain. In addition to being a potential explanation of why some state of affairs actually obtains, a how-possibly explanation must involve the relief of an imaginative frustration on the part of its recipient. When a recipient’s imaginative frustration is relieved, she does not just know that the state of affairs in question is possible, but is also able to imagine how it could possibly obtain.