The Challenge
The rise of generative artificial intelligence (AI) in research communities is making the research pipeline more efficient but also risks a credibility rupture. AI can support valuable work for researchers, but it also enables the rapid production of credible-sounding content that can be misleading or false. At a time of declining trust and growing misinformation, this raises a fundamental question for think tanks: How can audiences identify credible research?
As think tanks incorporate AI into research and dissemination workflows, the absence of clear norms creates risk for both producers and users of research. It becomes harder to assess what is evidence based, what has been responsibly produced, and what deserves trust from policy makers and publics alike.
CIGI’s Human Analysis Standard
CIGI has developed a standard to establish a common baseline for responsible use of generative AI in policy research, support more consistent practice around AI use, and provide a practical standard for think tanks and other knowledge-producing organizations.
The Human Analysis Standard (HAS) can guide and communicate a think tank’s commitment to the responsible use of AI in research and policy engagement. The proposed standard has a three-pronged approach to ensure that human oversight and analysis remain at the forefront of policy research.
HAS Principles
- Human in the lead: Human guidance, review and sign-off on research content where AI was involved.
- Transparency: Disclosure of AI use on research products and public access to the organization’s internal AI use policy.
- Responsible analysis: AI-assisted content anchored in credible sources and fact-checking.
Trust Signals
Visual elements accompany HAS on a publication or content page to communicate CIGI’s standard and commitment to responsible AI use.
