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AI Language Models: Risks and Opportunities in Marine Policymaking


Centrala begrepp
AI language models pose risks of bias in marine policymaking but also offer opportunities for capacity building and efficiency.
Sammanfattning

AI language models like ChatGPT are increasingly used in marine policy processes, aiding with tasks such as drafting statements and conducting background research. While they have the potential to assist developing countries with capacity constraints, there are concerns about biases favoring Western economic perspectives. The article explores the risks and benefits of AI language models in marine policymaking, focusing on the BBNJ Agreement case study. It highlights biases in foundational language models, document databases, and prompt engineering. Additionally, it discusses misplaced trust, overreliance on AI, and the displacement of real capacity building. Despite these challenges, there are opportunities for LLMs to improve equity by assisting with understanding legal documents, aiding in public consultation processes, and enhancing technical capacity building.

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Statistik
AI Large Language Models like ChatGPT are reshaping policymaking processes. Developing countries face capacity constraints that put them at a disadvantage in negotiations. LLMs can assist with analyzing legal documents and aiding public consultation processes. Concerns exist regarding biases favoring Western economic perspectives. Overreliance on AI could lead to displacement of real capacity building efforts.
Citat
AI tools relying on official documents could further sweep key structural issues "under the rug." Developing countries may overrely on AI tools due to lack of access to legal resources. Misplaced trust in AI could lead policymakers to make errors or inappropriate decisions.

Djupare frågor

開発途上国がAIツールによる先進国を有利にするバイアスを持続させないようにする方法は何ですか?

開発途上国がAIツールによるバイアスを軽減し、公正な政策形成プロセスを確保するためのいくつかの方法があります。まず第一に、開発途上国は自身のニーズや文化的背景を考慮したカスタマイズされたAIツールの開発や導入を促進すべきです。これにより、先進国中心の視点ではなく、包括的で多元的な意見が反映される可能性が高まります。また、トレーニングデータやプロンプト設計など、AIシステム内部で生じるバイアスを定期的に監視し修正することも重要です。さらに、開発途上国間で情報共有や協力体制を強化し、互いの立場や関心事項を理解しあうことも不可欠です。
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