Artificial Intelligence

Digital orb in a person's hand

Exploring the Future of AI

At the Division of Digital Transformation & Technology, we are dedicated to pioneering the integration of artificial intelligence (AI) in higher education. Our commitment extends beyond mere implementation; we aim to foster a vibrant ecosystem where AI serves as a catalyst for academic excellence and innovation. Recognizing the transformative potential of AI, we strive to empower faculty, students, and staff to harness these cutting-edge technologies, thereby enhancing the learning experience and driving forward-thinking outcomes.

We invite you to join us on this journey of discovery and innovation. By participating in these offerings, you will not only enhance your own understanding of AI but also contribute to a collective effort to advance education through technology.

Key Focus Areas

Education

Research

Operations

Policy Adherence

Our AI policies are designed to ensure that AI is implemented responsibly, ethically, and effectively to enhance the educational experience while safeguarding the rights and interests of all stakeholders. These policies cover the development, deployment, and use of AI technologies within our institution.

By adhering to these policies, the Division of Digital Transformation & Technology aims to foster a responsible and innovative environment for AI in higher education, enhancing the learning experience while maintaining the highest standards of ethics and integrity.

Guiding Principles

  • Transparency: All AI systems must be transparent in their operations, with clear explanations available to users about how decisions are made and data is processed.
  • Fairness: AI applications must be designed and tested to avoid biases and ensure equitable treatment of all users, regardless of race, gender, age, or other personal characteristics.
  • Accountability: Developers and operators of AI systems are responsible for the outcomes of those systems. Mechanisms must be in place for addressing any issues or grievances related to AI use.
  • Data Protection: Personal data used by AI systems must be securely stored and protected against unauthorized access, breaches, and misuse.
  • Informed Consent: Users must be informed about how their data will be used by AI systems and must provide consent before their data is collected and processed.
  • Anonymization: Where possible, data should be anonymized to protect individual privacy while still allowing for effective AI analysis and use.
  • Research and Testing: AI systems should undergo rigorous testing and validation before deployment to ensure they meet performance standards and ethical guidelines.
  • Continuous Monitoring: Deployed AI systems must be continuously monitored to identify and rectify any issues or unintended consequences that arise.
  • User Training: Faculty, staff, and students should receive appropriate training on the use and implications of AI technologies to ensure effective and informed usage.
  • Plagiarism Detection: AI tools used for plagiarism detection must be accurate, fair, and transparent, providing clear feedback to students and educators.
  • Assessment and Grading: AI systems used in student assessment must complement, not replace, human judgment. Educators must have the final say in grading and evaluations.
  • Supportive Technologies: AI applications designed to support learning, such as tutoring systems or adaptive learning platforms, should enhance the educational experience without undermining academic integrity.
  • Interdisciplinary Research: Encourage collaboration across disciplines to explore innovative AI applications and address complex challenges in education.
  • Faculty Engagement: Actively involve faculty in the development and implementation of AI initiatives, ensuring their expertise and insights shape the use of AI in education.
  • Student Involvement: Provide opportunities for students to engage with AI technologies, including research projects, internships, and coursework focused on AI development and ethics.
  • Regulatory Compliance: All AI initiatives must comply with relevant local, national, and international laws and regulations regarding data protection, privacy, and ethical standards.
  • Governance Structure: Establish a governance structure to oversee AI initiatives, including a committee responsible for reviewing AI policies, addressing ethical concerns, and ensuring alignment with institutional goals.
  • Policy Review: Regularly review and update AI policies to reflect technological advancements, emerging ethical considerations, and feedback from the academic community.

  • Transparency: All AI systems must be transparent in their operations, with clear explanations available to users about how decisions are made and data is processed.
  • Fairness: AI applications must be designed and tested to avoid biases and ensure equitable treatment of all users, regardless of race, gender, age, or other personal characteristics.
  • Accountability: Developers and operators of AI systems are responsible for the outcomes of those systems. Mechanisms must be in place for addressing any issues or grievances related to AI use.

  • Data Protection: Personal data used by AI systems must be securely stored and protected against unauthorized access, breaches, and misuse.
  • Informed Consent: Users must be informed about how their data will be used by AI systems and must provide consent before their data is collected and processed.
  • Anonymization: Where possible, data should be anonymized to protect individual privacy while still allowing for effective AI analysis and use.

  • Research and Testing: AI systems should undergo rigorous testing and validation before deployment to ensure they meet performance standards and ethical guidelines.
  • Continuous Monitoring: Deployed AI systems must be continuously monitored to identify and rectify any issues or unintended consequences that arise.
  • User Training: Faculty, staff, and students should receive appropriate training on the use and implications of AI technologies to ensure effective and informed usage.

  • Plagiarism Detection: AI tools used for plagiarism detection must be accurate, fair, and transparent, providing clear feedback to students and educators.
  • Assessment and Grading: AI systems used in student assessment must complement, not replace, human judgment. Educators must have the final say in grading and evaluations.
  • Supportive Technologies: AI applications designed to support learning, such as tutoring systems or adaptive learning platforms, should enhance the educational experience without undermining academic integrity.

  • Interdisciplinary Research: Encourage collaboration across disciplines to explore innovative AI applications and address complex challenges in education.
  • Faculty Engagement: Actively involve faculty in the development and implementation of AI initiatives, ensuring their expertise and insights shape the use of AI in education.
  • Student Involvement: Provide opportunities for students to engage with AI technologies, including research projects, internships, and coursework focused on AI development and ethics.

  • Regulatory Compliance: All AI initiatives must comply with relevant local, national, and international laws and regulations regarding data protection, privacy, and ethical standards.
  • Governance Structure: Establish a governance structure to oversee AI initiatives, including a committee responsible for reviewing AI policies, addressing ethical concerns, and ensuring alignment with institutional goals.
  • Policy Review: Regularly review and update AI policies to reflect technological advancements, emerging ethical considerations, and feedback from the academic community.

Teaching & Learning with AI

Asynchronous
ODU faculty can explore the domain of Teaching and Learning with AI in this interactive asynchronous journey, diving into its basics, impacts, and ethical dimensions while promoting safe and effective usage.

Upcoming Resources

AI Toolkit Series

A series of short modules introducing various artificial intelligence tools and technologies for educators to explore at their own pace.

Faculty Showcase: AI Success Stories

Faculty members share their experiences and achievements using artificial intelligence in various disciplines.

AI Research Projects Showcase

Faculty and student researchers showcase their AI-focused projects and findings. 

Guest Speaker Series

Engage with experts discussing the role of AI in shaping the future of higher education. 

Stay Connected and Engage with Us

Stay updated on our future AI offerings!

Visit the links below to submit your interest in presenting, offering workshops, or request for an AI topic to be researched.