Democratic Governance of AI Systems and Datasets
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Democratic Governance of AI Systems and Datasets

Dr. Anselm Küsters, LL.M.
Dr. Anselm Küsters, LL.M.
Dr. Eleonora Poli
Dr. Eleonora Poli

Progress in AI’s capabilities has highlighted a significant concern: the uneven allocation of AI’s benefits among and within societies and economies, worsening both domestic and global inequalities. In addition to limiting market competition and innovation, this concentration of power also translates into social challenges: global inequalities, risks of bias and disinformation, replacement of jobs, and lack of democratic control.

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The Hiroshima AI Process G7 Digital & Tech Ministers statement of 1 December 2023 states that one of the key goals of the process is “to maximize and share the benefits of this technology for the common good worldwide with partners beyond G7”. The policy interventions outlined in this brief serve this purpose, by supporting democratization of AI technologies. Ensuring democratic governance of AI can lead to greater oversight and control of AI technologies and systems, levelling the playing field and making AI technologies more accessible, and ensuring that AI deployment respects human rights and democratic values. And at global scale, ensuring democratic governance of AI means addressing concerns for global digital divide and inclusivity, building local capacity and engaging stakeholders in the global majority countries. The brief outlines a set of policy interventions focused on the provision of resources necessary to democratize AI development and use, through digital public infrastructures and digital public goods provided by G7 member states. This includes computing power, training datasets and open-source AI solutions. Additional recommendations concern managing AI-induced labour market changes and ensuring a framework for international and multilateral cooperation.

Originial publication at Think7

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Democratic Governance of AI Systems and Datasets (publ. 05.15.2024) PDF 1 MB Download
Democratic Governance of AI Systems and Datasets