The purpose of this policy is to establish guidelines for the acceptable use of Artificial Intelligence (AI) technologies, as defined within this document. SUNY recognizes that through the responsible use of AI, its institutions can drive innovation, increase operational efficiencies, and better serve New Yorkers while protecting privacy, managing risk, and promoting accountability, safety, and equity.

1. Introduction

The purpose of this policy is to establish guidelines for the acceptable use of Artificial Intelligence (AI) technologies, as defined within this document. SUNY recognizes that through the responsible use of AI, its institutions can drive innovation, increase operational efficiencies, and better serve New Yorkers while protecting privacy, managing risk, and promoting accountability, safety, and equity.
The responsible use of AI, with appropriate guardrails, can advance our research agenda and accelerate groundbreaking research and discovery; achieve operational improvements on behalf of the students we serve; and, consistent with shared governance principles, support faculty in strengthening teaching and learning. AI systems are now customarily embedded across the academic, research, healthcare, and administrative missions of the SUNY system ¿ as is the case in countless workplaces nationwide.
SUNY is proud of our extensive efforts to expand the responsible use of AI to benefit students, faculty, patients, and staff. These include:

• Naming the inaugural SUNY AI for the Public Good Fellows, made up of 20 SUNY faculty and staff across disciplines ranging from health sciences to sustainable resources management. The Fellows serve as a resource to colleagues working to update courses and learning activities to incorporate AI literacy, including the effective and ethical use of AI and teaching students to critically evaluate AI-generated content.
• Updating SUNY’s General Education Framework core competency in information literacy to reflect the use of emerging technologies and AI. As a result of this change, all students will develop skills to evaluate information from a variety of sources, with an awareness of authority, validity, bias, and origin, and demonstrate an understanding of the ethical dimensions of information use, creation, and dissemination.
• Hosting Governor Hochul’s Empire AI consortium, which provides supercomputer access to researchers working to advance the public good. Empire AI is housed at the State University of New York at Buffalo and includes the State University of New York at Albany, Binghamton, and Stony Brook, along with the state’s other leading research institutions.
• Establishing Empire AI campus partnerships between SUNY’s University Centers, university colleges, technology colleges, and community colleges to advance AI research and education for the public good. The partnerships leverage Empire AI to increase research experiences, professional development, and other opportunities for SUNY students and faculty.
• Launching the nation’s first independent AI research center at a public university. The Center for AI Responsibility and Research at the State University of New York at Binghamton will be the nation’s premier academic hub for creating the science and engineering of responsible, repeatable, and transparent artificial intelligence.
• Launching Departments and Centers of AI & Society across eight SUNY institutions ¿ which foster collaboration across disciplines to provide inclusive AI research, address ethical concerns in the use of AI, and advance responsible data use.

The following policy supports SUNY institutions in developing AI policies tailored to their specific circumstances anchored by a common set of systemwide principles. This policy is guided by three overarching philosophies:

• AI policy is most effective when it is woven into the broader fabric of institutional governance. Many of the challenges posed by AI, such as safeguarding data privacy, ensuring information security, maintaining accessibility, preventing discrimination, and ensuring patient safety, are addressed by existing institutional policies. Institutions are encouraged to identify where AI considerations naturally extend existing policy frameworks and to update those policies accordingly, rather than attempting to consolidate all AI-related guidance in one place. A dedicated AI policy may still serve an important coordinating function, but it should complement and cross-reference an institution’s existing policy landscape, not duplicate it.
• Oversight and governance of AI systems should be proportionate to the risk those systems pose. Not every AI application requires the same degree of scrutiny: a tool that recommends library resources, for example, does not carry the same stakes as one that influences admissions decisions. Institutions should calibrate their review processes, approval requirements, and ongoing monitoring to reflect the potential impact of each AI system on the rights, well-being, and safety of students, faculty, staff, and the broader community. This risk-informed approach ensures that institutional resources and attention are directed where they matter most, without imposing unnecessary barriers to the adoption of lower-risk tools that can improve everyday operations.
• AI policies relating to the use of pedagogic, student-facing applications in the classroom should be developed through shared governance and should take care not to limit creativity and experimentation in teaching, research, and learning. These policies should generally reflect a lower-risk approach than policies relating to, for example, student evaluation and grading.

SUNY will supplement this policy with additional subject-specific guidance to institutions, and templates for key documents, and will conduct surveys on a regular basis to better understand AI use throughout the university system.

2. AI System Definition

AI System: A machine-based system that can, for a given set of human-defined objectives, make predictions, recommendations, or decisions influencing real or virtual environments, and that uses machine and human-based inputs to perceive real and virtual environments, abstract such perceptions into models through analysis in an automated manner, and use model inference to formulate options for information or action.
This policy intentionally defines AI systems broadly to provide a common systemwide governance framework across academic, research, and administrative contexts. More specific exclusions, thresholds, or scoping limitations may be adopted in campus policies or in subject-specific guidance where particular operational, legal, or compliance measures require greater precision.

3. Responsible AI Principles

All SUNY institutions will adhere to the following principles for the responsible use of AI. These principles articulate the values that should inform institutional AI adoption. However, the degree to which each principle requires formal processes, documentation, or review will depend on the nature and risk profile of the AI system in question. Not every principle demands the same operational rigor for every system.

1. Accountability and Governance: Establish clear guidelines and accountability frameworks for identified individuals and institutional bodies to responsibly manage AI deployment and usage. The ultimate accountability for work completed and actions made by, or in conjunction with, AI systems must rest with human beings.
2. Ethical Design and Bias Mitigation: Understand, address, and mitigate the risk that AI systems may produce biased, unethical, or discriminatory outcomes, where that risk exists given the AI systems’ purposes and uses.
3. Transparency and Explainability: Use reasonable efforts to enable individuals affected by AI-driven processes to obtain a meaningful understanding of how those processes affect consequential decisions concerning them.
4. Data Privacy and Security: Prioritize user privacy by adhering to data protection regulations and implementing robust security measures to safeguard sensitive information used in, or generated by, AI systems, where appropriate.
5. Education: Develop AI curricula and learning opportunities to allow students to obtain the knowledge and ethical grounding necessary to design, deploy, and govern responsible AI systems. The integration of AI into the General Education Framework information literacy core competency is one among many opportunities to advance this principle.


4. General AI Systems Institutional Requirements

SUNY institutions shall publish AI policies and/or update relevant existing policies no later than December 31, 2026. Upon written request, and for good cause shown, the Chancellor (or designee) may grant a one-time extension of up to two months. These policies must, at minimum, confirm the institution’s commitment to the Responsible AI Principles described above and describe the institution’s approach to:

1. Roles and Responsibilities: Clarifying faculty, staff, and student roles and responsibilities for the management and oversight of AI systems.
2. Procurement: Incorporating language in relevant procurements that will, to the extent possible, protect SUNY data, protect against biased, discriminatory and unethical outcomes, and preserve SUNY’s decision-making authority.
3. Domain-Specific Governance: Reflecting differences in expectations around academic freedom, shared governance, intellectual property, regulatory compliance, and operational risk concerning the use of AI for teaching and learning, research, healthcare, and administrative operations.
4. Training: Ensuring faculty, staff, and students receive the training necessary to allow them to manage AI tools in a non-discriminatory, ethical and non-biased manner.
5. Protecting Fairness, Privacy and Security: Scrutinizing AI tools and implementing appropriate and scalable controls to protect institutional data and operations and prevent bias and discrimination.
6. Risk-Based Governance: Instituting oversight and management mechanisms that reflect the nature and severity of the risks the AI systems present. AI systems that can control or meaningfully influence outcomes affecting the safety, rights, or wellbeing of individuals warrant heightened scrutiny, including more rigorous approval processes, bias reviews, risk assessments, and training requirements.
7. Review Regularly: Re-evaluating policies with AI-related provisions at regular intervals to account for changes in AI technology, the regulatory environment, and campus operational practices.

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