# The Dual Imperative: Innovation and Regulation in the AI Era

arXiv: https://arxiv.org/abs/2407.12690 · HTML: https://mlsanity.com/paper/2407.12690/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 6 of its 27 references that are in the map.
- First posted on arXiv 23 May 2024.

## Builds on (most cited first, 6 of 6)

- [The Alignment Problem from a Deep Learning Perspective](https://mlsanity.com/paper/2209.00626/) (2022)
- [An Overview of Catastrophic AI Risks](https://mlsanity.com/paper/2306.12001/) (2023)
- [Harms from Increasingly Agentic Algorithmic Systems](https://mlsanity.com/paper/2302.10329/) (2023)
- [Generative Flow Networks for Discrete Probabilistic Modeling](https://mlsanity.com/paper/2202.01361/) (2022)
- [Is Power-Seeking AI an Existential Risk?](https://mlsanity.com/paper/2206.13353/) (2022)
- [Liquid Time-constant Recurrent Neural Networks as Universal Approximators](https://mlsanity.com/paper/1811.00321/) (2018)

## Built on by (most cited first, 1 of 1)

- [An Instrument to Evaluate Governance Proposals: AI Policy Analysis at Scale](https://mlsanity.com/paper/2607.28094/) (2026)

## Abstract (arXiv)

This article addresses the societal costs associated with the lack of regulation in Artificial Intelligence and proposes a framework combining innovation and regulation. Over fifty years of AI research, catalyzed by declining computing costs and the proliferation of data, have propelled AI into the mainstream, promising significant economic benefits. Yet, this rapid adoption underscores risks, from bias amplification and labor disruptions to existential threats posed by autonomous systems. The discourse is polarized between accelerationists, advocating for unfettered technological advancement, and doomers, calling for a slowdown to prevent dystopian outcomes. This piece advocates for a middle path that leverages technical innovation and smart regulation to maximize the benefits of AI while minimizing its risks, offering a pragmatic approach to the responsible progress of AI technology. Technical invention beyond the most capable foundation models is needed to contain catastrophic risks. Regulation is required to create incentives for this research while addressing current issues.