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Key AI Ethics

According to the Living Guidelines on the Responsible Use of Generative AI in Research, researchers should ensure responsible use of generative AI by:

1. Remain ultimately responsible for scientific output

  • Researchers are responsible for the integrity of AI-generated or AI-supported content
  • Researchers must recognize AI's limitations, including bias, hallucinations, and inaccuracies.
  • AI systems are neither authors nor co-authors. Authorship implies agency and responsibility, so it lies with human researchers.
  • No fabricated AI material: Researchers must not falsify, alter, or manipulate **original research data using AI.

2. Use generative AI transparently

  • Transparency: Researchers disclose generative AI tools used (name, version, date, usage, impact) and, if relevant, share input and output per open science principles.
  • Account for randomness: Recognize AI's stochastic nature and ensure reproducibility and robustness.
  • Acknowledge limitations: Discuss AI tool biases, limitations, and mitigation measures.

3. Focus on Privacy, Confidentiality, and intellectual property

  • Protect sensitive work: Avoid uploading unpublished or sensitive content into AI systems unless data reuse is assured.
  • Respect personal data: Only input personal data with clear consent and a specific purpose, ensuring compliance with EU data protection rules.
  • Understand implications: Be aware of privacy, confidentiality, and intellectual property concerns. Verify privacy settings, tool ownership, hosting environment, and data security measures.
  • ❗ Note: We recommended to use BlaBlaDor for you research in terms of its privacy focus (Blablador hosts both open-source models and those created by the Helmholtz Association).

4. Comply with Laws and Regulations

  • Intellectual property and data sensitivity: Generative AI outputs may pose risks to intellectual property rights and personal data protection.
  • Avoid plagiarism: Ensure proper citation and respect for others’ authorship; AI outputs may draw on existing works.
  • Handle personal data responsibly: Address any personal data in AI outputs in line with EU data protection rules.

5. Learn and Train for Effective AI Use

  • Stay informed: Researchers keep up with evolving generative AI tools and share best practices with colleagues and stakeholders.

6. Avoid AI in Sensitive Activities

  • Mitigate risks: Avoiding generative AI prevents unfair treatment or assessment caused by hallucinations and biases.
  • Protect unpublished work: It ensures the confidentiality of original research, shielding it from unintended exposure or AI model inclusion.