Intention Is All You Need

TL;DR

This paper critically examines the optimistic view that generative AI can simply translate natural language intentions into software, highlighting issues of homogenisation and the complexity of forming genuine intentions.

Contribution

It challenges the notion of intention as neutral in generative AI and explores the complexities and constraints involved in forming true intentions for programming.

Findings

Generative AI tends to homogenise intentions, reducing diversity.

Forming genuine intentions in AI is complex due to constraints and materiality.

Existentialist perspectives offer new insights into intentional programming practices.

Abstract

Among the many narratives of the transformative power of Generative AI is one that sees in the world a latent nation of programmers who need to wield nothing but intentions and natural language to render their ideas in software. In this paper, this outlook is problematised in two ways. First, it is observed that generative AI is not a neutral vehicle of intention. Multiple recent studies paint a picture of the "mechanised convergence" phenomenon, namely, that generative AI has a homogenising effect on intention. Second, it is observed that the formation of intention itself is immensely challenging. Constraints, materiality, and resistance can offer paths to design metaphors for intentional tools. Finally, existentialist approaches to intention are discussed and possible implications for programming are proposed in the form of a speculative, illustrative set of intentional programming practices.