Artificial Intelligence in Research
Researchers should not enter information into AI systems merely because the technology can process it. Learn how to identify prohibited or restricted inputs, assess confidentiality and reidentification risks, and distinguish public AI services from appropriately authorized research environments.
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Artificial Intelligence in Research
Researchers may have legitimate access to information without permission to share it with an AI provider. Learn how to assess consent, confidentiality, institutional authorization, contractual restrictions, and provider processing arrangements before submitting research data to AI systems.
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Artificial Intelligence in Research
Researchers may need to explain their AI use to stakeholders with different responsibilities and expectations. Learn what each stakeholder needs to know, how to substantiate AI-assisted procedures, and why being comfortable with disclosure is a useful reflection exercise but not a substitute for compliance or scientific validity.
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Artificial Intelligence in Research
Researchers remain accountable for the scientific work they submit, even when AI contributes to writing, code, analysis, or interpretation. Learn what full responsibility means, what cannot be delegated to AI, and how researchers should respond when they cannot adequately verify or defend the final output.
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