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Research Ethics and Academic Integrity

Navigating the Ethical Use of Generative AI in Research

The rise of Generative Artificial Intelligence (Gen AI) presents exciting opportunities for researchers, but it also raises important ethical considerations. At the University of Derby, we are committed to fostering responsible and ethical research practices, including the use of AI tools.

Key Ethical Considerations:

  • Accuracy and Bias: Gen AI models can sometimes produce inaccurate or biased information. Researchers must critically evaluate AI-generated content and ensure its accuracy and fairness before incorporating it into their work.
  • Transparency and Acknowledgement: When using Gen AI in research, it's crucial to be transparent about its use. Clearly acknowledge the AI tool's contribution and explain how it was used in your research process.
  • Privacy and Data Protection: Gen AI tools may collect and process data, raising privacy concerns. Researchers must handle data responsibly, ensuring compliance with data protection regulations and obtaining necessary consents.
  • Intellectual Property: Be mindful of copyright and intellectual property rights when using Gen AI. Ensure that you have the right to use any AI-generated content and that you are not infringing on the rights of others.
  • Human Oversight: While Gen AI can be a valuable tool, it should not replace human judgement and critical thinking. Researchers must maintain oversight of the research process and ensure that AI is used ethically and responsibly.

University of Derby Guidance:

The University of Derby provides guidance on the acceptable and responsible use of Gen AI in research. This guidance emphasises the importance of:

  • Research Ethics Approval: If your research involves the use of Gen AI, you must include sufficient detail in your research ethics application to ensure that the approach aligns with ethical principles.
  • Peer Review: Gen AI should not be used to assist in peer review, as it may raise concerns about confidentiality and intellectual property.
  • Authorship: Gen AI does not meet the requirements for authorship, as it lacks accountability. Therefore, it should not be listed as an author on any research publication.

By adhering to these ethical principles and guidelines, researchers at the University of Derby can harness the power of Gen AI while ensuring the integrity, validity, and ethical soundness of their research.

Glossary of Terms

  • Artificial Intelligence (AI): Technology that enables machines to interact with humans in a natural, human-like manner.
  • Bias: Prejudice or favouritism inherent in data or algorithms, leading to discriminatory or unfair outcomes.
  • Conventional AI: AI models trained on large datasets to understand and generate conversational language patterns.
  • Generative AI (Gen AI): Technology that allows machines to create new content, including text, images, video, audio, or code.
  • Large Language Models (LLMs): A type of Gen AI that produces text outputs.
  • Plagiarism: The act of presenting someone else's work or ideas as your own, without giving proper credit.
  • Research Ethics: The moral principles and guidelines that govern the conduct of research to ensure the protection of human subjects, the integrity of data, and the responsible use of research findings.
  • Transparency: Openness and honesty in disclosing information about the use of AI in research, including the methods, data, and limitations of the AI tools.

Universty of Derby Policies:

The following resources provide further guidance on the ethical use of AI in research:

  • The Ethics of Artificial Intelligence: A range of resources on the ethical issues of AI from UNESCO (UN Educational, Scientific and Cultural Organisation).
  • European AI Alliance: A forum and source of resources dedicated to all legal, technical, and economic implications that artificial intelligence (AI) presents to society.
  • Mitigating Bias in Artificial Intelligence: This playbook for business leaders explores issues of bias in AI and strategies for mitigating them. From the Centre for Gender, Equity and Leadership at Berkeley Haas University.
  • JISC National Centre for AI: This site includes a range of resources about AI.
  • Institute for Ethics in AI: A research center at the University of Oxford dedicated to examining the ethical implications of artificial intelligence.