AI Code of Ethics and Minimum Standards
At Tarleton State University, we are committed to advancing innovation in research, scholarship, and education. As we integrate AI into our academic and operational practices, its use must reflect our core values— excellence, integrity, and respect.
- Texas A&M Ethical Considerations on AI
- TAMUS Regulation 15.99.08 Artificial Intelligence in Research
- TAMUS Regulation 29.01.05 Artificial Intelligence
- IEEE Ethically Aligned Design
- ACM Code of Ethics and Professional Conduct
- Texas DIR AI Templates and Resources
- National Institute for Standards and Technology (NIST) AI Guidance
AI Guidance
When using an AI tool or system, it is important to understand that these platforms may use, collect, and store your personal data, which could lead to privacy risks. When using generative AI, it is important to follow data privacy and security guidelines to protect both personal and institutional data.
- Center of Educational Excellence: AI Resources
- The Provost’s Generative AI Task Force Full Report
- AI Guidance for Syllabi
- AI in Academia: Ethical Use and Practical Guidance
General Information
- Tarleton State University Information Security Controls Catalog
- TAMUS Data Classification Standard
- TAMUS Privacy Policy
- TAMUS Regulation 29.01.05 Artificial Intelligence
- TAMUS Regulation 32.01.02 Complaint and Appeal Process for Nonfaculty Employees
- TSU Academic Integrity
- TSU Student Conduct Code
- What is AI bias? (IBM)
- University Compliance
Quick Guidelines for Responsible AI Use
Teach
Leverage AI to enhance teaching and learning while upholding academic integrity.
Credit AI-generated materials used in course design, instruction, or assessments.
Promote ethical and responsible AI use by modeling best practices and guiding student engagement.
Clearly state expectations for AI use in your course syllabus, including what is allowed, what requires disclosure, and what is not permitted.
Learn
Use AI to support learning and research in ways that align with Tarleton’s academic integrity policies.
Properly cite AI-generated content when it contributes to academic work, just as with any other source.
Understand the challenges and limitations of using AI in academic and research contexts, including issues of accuracy, bias, and ethical use.
Research
Enhance research thoughtfully: Use AI tools to support idea development, content organization, and research design—while maintaining human oversight and critical evaluation of all AI-generated content.
Protect data privacy: Choose AI platforms that uphold strong data privacy standards and do not use inputted data to train publicly accessible models.
Address participant risk: Consider the potential risks of AI-generated content to research participants, and include appropriate disclosures in informed consent documents.
Follow publication standards: Understand and comply with publisher requirements regarding the use and disclosure of AI in submitted work.
Evaluate research integrity: Acknowledge how AI may affect the explanation, reproduction, and validity of your research findings.
Use training data ethically: Acquire and use training data in accordance with consent, privacy laws, and institutional review board (IRB) standards.
Work
Leverage AI to enhance efficiency and decision-making, improving workflows and service delivery across departments.
Prioritize data privacy and security when using AI tools, ensuring compliance with university policies and applicable regulations.
Stay informed about evolving AI technologies, best practices, and ethical considerations to ensure responsible and effective use.