From pen to algorithm: optimizing legislation for the future with artificial intelligence

This research poses the question of whether it is possible to optimize modern legislative drafting by integrating LLM-based systems into the lawmaking process to address the pervasive challenge of misinformation and disinformation in the age of AI. While misinformation is not a novel phenomenon, wit...

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Veröffentlicht in:AI & society 2024-09
Hauptverfasser: Hill, Guzyal, Waddington, Matthew, Qiu, Leon
Format: Artikel
Sprache:eng
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Zusammenfassung:This research poses the question of whether it is possible to optimize modern legislative drafting by integrating LLM-based systems into the lawmaking process to address the pervasive challenge of misinformation and disinformation in the age of AI. While misinformation is not a novel phenomenon, with the proliferation of social media and AI, disseminating false or misleading information has become a pressing societal concern, undermining democratic processes, public trust, and social cohesion. AI can be used to proliferate disinformation and misinformation through fake news and deepfakes; can AI also be used for beneficial purposes to develop the antidote legislation combatting these challenges? Leveraging the capabilities of LLMS, such as ChatGPT and others, can present a promising direction for optimizing legislative drafting. By proposing the methodological approach of an AI bun, this article explores an important approach in which LLMS can support lawmakers and policy experts in crafting legislation. The article contributes to the discourse through a nuanced understanding of the opportunities and challenges in harnessing LLM-powered tools for legislative innovation. Ultimately, it underscores the transformative potential of LLMs as a potential resource for lawmakers seeking to navigate decision-making while developing legislation on an example of navigating the intricate landscape of misinformation and disinformation regulation in the age of AI.
ISSN:0951-5666
1435-5655
DOI:10.1007/s00146-024-02062-3