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.
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 AI Events
- Integrating AI in Classroom: Practical Strategies and Student Engagement (Workshop): February 27, 2024 Enhance your classroom dynamics with our Integrating AI in Classroom Workshop, where you'll master practical strategies and ignite student engagement providing an opportunity to maximize interactivity.
- Assess Students and Not ChatGPT: Strategies to avoid cheating: March 14, 2024 Discover how to harness Generative AI (GenAI) while safeguarding the authenticity of student assessment.
- AI-Powered Research: Enhance research with AI methodologies (Workshop): March 19, 2024 Enhance your research skills through the AI-Powered Research Workshop, discovering how AI revolutionizes scholarly exploration.
- AI-Driven Assessment Techniques: Innovative assessment methods with AI (Workshop): March 28, 2024 Dive deeper into alternative assessments utilizing AI-driven techniques that promote and enhance student learning.
- AI in Media Production: Hands-on AI media creation tools (Demo): April 2, 2024 Experience the future in AI Media Production Demo, with hands-on AI tools for captivating media creation.
- Prompt Engineering: Unlocking the potential of generative AI: April 4, 2024 Join us for an exploration into how prompt engineering can optimize the educational landscape. This presentation will offer a strategic framework that can be implemented to get the most out of Generative AI
- Integrating AI in the Classroom: Practical Strategies and Student Engagement (Workshop): September 10, 2024 Enhance your classroom dynamics with our Integrating AI in Classroom Workshop, where you'll master practical strategies and ignite student engagement providing an opportunity to maximize interactivity.
- Transforming Teaching with AI: Tools to Lighten the Workload (Workshop): September 17, 2024 Discover AI tools for automating tasks that will free up time for educators to focus on what truly matters—teaching and engaging with students. Registration for this event is open to the public.
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.