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Shared theoretical frameworks, research tools, and foundational resources for the field.
Also in Shared Infrastructure
2.1 Governments should foster and facilitate national infrastructures necessary to promote open access to datasets to all elements of society having a vested interest in access to such datasets for research and/or non-commercial use. In this regard, governments should give serious consideration to two-tier access models which would allow for free access for academic and research purposes, and paid-for access for commercialised purposes. 2.2 Governments should support open data initiatives in the public or private sector with guidance and research to share wide understanding of the advantages to be gained from open access data, the structures through which datasets can be shared and exchanged, and the processes by which data can be made suitable for open access (including API standardisation, pseudonymisation, aggregation or other curation, where necessary). 2.3 Governments should ensure that the data held by public sector bodies are accessible and open, where possible and where this does not conflict with a public sector mandate to recover taxpayer investment in the collection and curation of such data. Private sector bodies such as industry organisations and trade associations should similarly support and promote open data within their industry sector, making their own datasets open, where possible. 2.4 Organisations that develop, deploy or use AI systems are encouraged to open up access to, and/or license, their datasets, where possible via chaperoned mechanisms such as Data Trusts. 2.5 Any sharing or licensing of data should be to an extent which is reasonable in the circumstances and should be in compliance with legal, regulatory, contractual and any other obligations or requirements in relation to the data concerned (including privacy, security, freedom of information and other confidentiality considerations).
Reasoning
Governments and organizations facilitate shared open datasets as ecosystem research resources for AI development and safety research.
Ethical Purpose and Societal Benefit
Organisations that develop, deploy or use AI systems and any national laws that regulate such use should require the purposes of such implementation to be identified and ensure that such purposes are consistent with the overall ethical purposes of beneficence and non-maleficence, as well as the other principles of the Policy Framework for Responsible AI.
3.2.2 Technical StandardsEthical Purpose and Societal Benefit > Overarching principles
2.1.3 Policies & ProceduresEthical Purpose and Societal Benefit > Work and automation
2.2.1 Risk AssessmentEthical Purpose and Societal Benefit > Environmental impact
2.2.1 Risk AssessmentEthical Purpose and Societal Benefit > Weaponised AI
3.1.3 International AgreementsEthical Purpose and Societal Benefit > The weaponisation of false or misleading information
1.2.1 Guardrails & FilteringOther (outside lifecycle)
Outside the standard AI system lifecycle
Governance Actor
Regulator, standards body, or oversight entity shaping AI policy
Govern
Policies, processes, and accountability structures for AI risk management