This post was written as part of a hackathon held at the École Normale Supérieure as part of a "Turing Seminar" course in our “Mathematics, Vision, Learning” Master's program. The use of AI was helpful to correct errors, as well as rewriting certain sections to improve clarity.
Authors: Nassim Arifette and Darius Dabert

Introduction

What is Recursive Self-Improvement (RSI)?

RSI is a concept in AI that describes a system capable of continuously improving its own capabilities without needing external help. Essentially, once an AI becomes smart enough, it could start designing and upgrading itself, creating a feedback loop that rapidly boosts its intelligence. In theory, this process could trigger an "intelligence explosion" with the AI quickly surpassing human intelligence by an unimaginable margin^[1].

The Narrative Around RSI

RSI has become a hot topic in both AI research and pop culture, fueled by sci-fi stories and thought experiments. A famous example is the "paperclip maximizer" scenario—a hypothetical AI so focused on its goal (making as many paperclips as possible) that it destroys humanity in the process. The idea here is that even small alignment mistakes in a superintelligent AI could spiral into catastrophic consequences.

These dystopian narratives have driven much of the conversation around AI safety, often painting RSI as an imminent existential threat^[2]. But while it’s a fascinating thought experiment, this framing tends to overlook practical realities, such as the technical, societal, and economic barriers to developing truly self-improving AI.

Our Thesis

We argue that while RSI concerns are intellectually engaging, they’re also highly speculative and often overstated. Modern AI systems face significant practical limitations that make the idea of uncontrolled RSI less urgent than many fear.

Rather than fixating on RSI as an existential risk, we should prioritize addressing more immediate challenges in AI, like bias, misuse, and resource inefficiency. By critically analyzing the assumptions behind RSI and considering real-world constraints, we hope to offer a more grounded perspective on AI safety and the actual challenges we need to tackle.

I. Concerns and Hypotheses of Recursive Self-Improvement (RSI)

Recursive Self-Improvement (RSI) is one of the most captivating—and unsettling—ideas in artificial intelligence (AI) theory. At its core, RSI suggests that ...

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