Who’s Been Regulating My AI?: Goldilocks and The House Of Lords Report on LLMs and Generative AI

By: Parman Dhillon, Gareth Stokes & Mark O’Conor (DLA Piper)

Amidst the recent finalization of the EU’s AI Act, significant advancements in AI persist at a rapid pace. On February 2nd, 2024, the House of Lords Communications and Digital Committee (HoL) issued its findings on large language models (LLMs) and generative AI.

The report delved into various subjects, notably focusing on two key areas:

1. The ‘Goldilocks problem,’ as termed by the HoL, which revolves around striking the right balance between investment and risk, particularly in the realm of open and closed AI models.
2. Copyright and liability concerns stemming from the development, training, and utilization of LLMs.

This article marks the first installment of a two-part series. In this segment, we’ll explore the ‘Goldilocks problem,’ analyze open and closed access models, and assess the UK government’s strategy for managing AI systems in comparison to global practices. The second part will delve into the HoL’s discussions on liability and copyright.

The ‘Goldilocks Problem’

The HoL report aimed to forecast the probable trajectories of LLMs over the next three years and propose strategies for the UK to seize opportunities while mitigating risks. It acknowledged the pivotal role of governments in steering the success of AI companies, given developers’ dependence on access to energy, computing resources, and consumer markets—factors heavily influenced by government policies and investments. However, the HoL also acknowledged the inherent challenge faced by governments, termed the ‘Goldilocks’ problem, in finding the optimal balance between fostering innovation and managing risks, often with limited foresight into market dynamics.

Similarly, the EU grappled with this dilemma in its regulation of foundation models, or ‘general-purpose AI,’ as defined in its latest text. While the EU aimed for stringent regulation, determining the appropriate boundaries proved challenging, compounded by resistance from Member States concerned about stifling their domestic AI innovation…

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