AI Governance

Laying the Foundation for AI

To implement responsible AI in higher education, New York Tech has developed core principles to guide our decisions, policies, and deployment, ensuring ethical standards and effective integration. These principles form the cornerstone for all AI activities at New York Tech, ensuring that AI integration prioritizes ethical considerations and upholds institutional integrity.

Our Core AI Principles

Fairness and Reliability: AI systems should be developed to minimize bias and guarantee outcomes that are consistent, valid, and equitable.

Human Oversight and Value Alignment: AI should support—not replace—human judgment, especially in legal or ethical contexts, and must reflect New York Tech’s values.

Transparency and Explainability: Users must be informed when AI is utilized, understand its mechanisms, and interpret its results clearly.

Privacy, Security, and Safety: AI systems must protect user data, ensure security, and mitigate risks that could compromise institutional or personal safety.

Accountability: Institutions and AI providers must set clear frameworks to ensure ethical oversight and responsible use.

AI Policies and Guidelines

Employee Guidelines for Use of GenAI

New York Tech has established the following guidelines to help employees use Generative AI tools responsibly and ethically, while protecting our intellectual property and institutional data. 

Learn More

Academic Integrity Policy: U.S. Campuses

New York Tech’s Academic Integrity Policy includes a section on unauthorized uses of Generative AI, such as ChatGPT, Sudowrite, Gemini, and more.

Learn More

AI Leadership at New York Tech

Our task force, composed of experts and enthusiasts, is dedicated to creating a vibrant environment that supports cutting-edge research and promotes interdisciplinary collaboration. We are excited to embark on this journey and look forward to the future advancements that AI will bring to our institution and beyond.

Chair

Tiffani Hinds

Members

  • Robert Gallagher
  • Jennifer Griffiths
  • Xueqing Huang
  • Sandra Manninger
  • Rakesh Mittal
  • Helene Schorr
  • Joanne West

Task

Develop comprehensive policies on ethical AI use for students, ensuring alignment with institutional standards.

Chair

Lise McCoy

Members

  • Carl Abraham
  • Blake Bearden
  • Johnathan Berman
  • John Carter
  • Joanne Donoghue
  • Michael Hayek
  • Mihir Matalia
  • Quinyatta Mumford
  • Tyler Pham
  • Viswanathan Rajagopalan
  • Randy Stout
  • Mary Claire Swaim

Task

Focus on the potential applications of generative AI in medical education and its potential to improve teaching and learning methods in medical education.

Chair

Babak Dastgheib-Beheshti

Members

  • Francesca Fiore
  • Lori Hochman
  • Frank Lee
  • Alessandro Melis
  • John Misak
  • Rakesh Mittal

Task

Create accessible interdisciplinary AI courses and programs, including a universal minor and potential concentrations and majors.

Chair

  • Laurie Harvey

Members

  • Becky Frieden
  • Millie Gonzalez
  • Sheri Kelleher
  • Dost Khalique
  • Sebastien Marion
  • Rajendram Rajnarayanan
  • Pennie Turgeon

Task

Provide ongoing AI education and training for faculty, staff, and students.

Chair

Becky Frieden

Members

  • Joel Acevedo
  • Monika Rohde
  • Raquel Romanick
  • Stephen Stallone
  • Ian White
  • Katherine Zuliani

Task

Develop guidelines for AI adoption that enhance productivity and decision-making in administrative operations and services.

Co-Chairs

Francine Glazer and John Misak

Members

  • Jessica Boudrouris
  • Minaz Fazal
  • Mindy Haar
  • Cathrine Hartup
  • Laurie Harvey
  • Maya Kroumova
  • Lise McCoy
  • Noreen O’Brien
  • Clarke Snell
  • Anand Santhanakrishnan

Task

Outline pedagogies and supports for integrating AI tools into our diverse learning environments.

Chair

Tom Vallario

Members

  • Jean Marie Finnerty
  • Cheryl Monticciolo
  • Rajendram Rajnarayanan
  • Monika Rhode

Task

Develop institutional policies and guidelines for ethical and responsible AI use.

Chair

Jared Littman

Members

  • Houwei Cao
  • Chris Egan
  • Vidita Gawade
  • Shinu Kuriakose
  • Kevin Park
  • Mihir Matalia
  • Jerry Zhou

Task

Expand the scope to pioneer new frontiers in AI research and ensure our institution remains an AI leader.

Chair

Jeunelle Sanabria

Members

  • Shlomie Garcia
  • T’ron Strapp

Task

Provide a platform for student insights on AI initiatives and include student reps on key committees.