Artificial intelligence (AI) creates significant opportunities to enhance learning, productivity, research, and innovation, while also introducing risks such as inaccurate information, bias, privacy concerns, and overreliance on automated systems.
Spark! takes a critical embrace approach to AI: we encourage thoughtful experimentation while developing the judgment needed to use AI responsibly. Our goal is to equip students and the broader Spark! community to understand when and how AI adds value, critically evaluate its outputs and impacts, and remain accountable for the work they produce.
This policy applies to students and those supporting student work at Spark!, including affiliated staff, faculty, researchers, mentors, and partners. It applies to coursework, research, experiential learning, projects, and other academic or professional work conducted through Spark! For purposes of this policy, AI includes generative AI and other AI systems used to create, analyze, recommend, predict, or support decisions.
Spark! follows six principles for responsible AI use.
| Guiding Principle | What This Means in Practice |
|---|---|
| 1. Use AI to enhance human processes, judgment, and innovation — not replace them. | Use AI to support learning, research, creativity, problem-solving, and productivity while maintaining meaningful human involvement. Determine when AI adds value and when human expertise or judgment is required. |
| 2. Take responsibility for AI-assisted work and its outcomes. | Review and verify AI-generated outputs before relying on them. Fact-check claims, test code and technical outputs, identify errors or hallucinations, and ensure work meets applicable academic, technical, and professional standards. Be prepared to explain and defend your work and the decisions you make. |
| 3. Identify and be transparent about who your work could harm or exclude. | Consider potential bias, exclusion, misuse, and other harms created or amplified by AI, including those arising from data and design choices. Apply greater scrutiny and safeguards as the potential stakes and consequences increase, particularly when work involves sensitive data, consequential decisions, human participants, or potential impacts on individuals or communities. Address identified risks to the best of your ability and seek guidance when needed. |
| 4. Disclose AI use transparently. | Appropriately acknowledge meaningful AI assistance in research, assignments, code, projects, and professional work. At a minimum, disclosure should identify the AI tool used and how it contributed to the work. Follow any additional instructor, program, publication, or institutional requirements for disclosure and citation. |
| Resources: | |
| • Cornell AI Attribution Guidelines; | |
| • Purdue University Libraries, How to Cite AI-Generated Content. | |
| 5. Protect sensitive information while advancing AI innovation. | Do not provide confidential, personal, proprietary, sensitive research, or otherwise protected information to AI systems unless the tool and use are authorized for that information. Follow applicable university privacy, security, research, and data-management requirements. |
| 6. Use AI only when it adds meaningful value. | Consider whether AI is necessary or beneficial for the task rather than using it by default. Minimize unnecessary AI use and consider its environmental impact when choosing tools and approaches. |