Balancing Responsibility and Innovation: Education Experts Outline an Ethical Path for AI Adoption

It’s been a recurring question in our conversations with clients over the last 12 months: what does ethical AI adoption in education involve, and what are the requirements for institutional policies to get there? We will be delving deep into this area at next month’s Anthology Together ’24 conference in Orlando, with sessions spanning new product innovation, our Trustworthy AI Approach, AI plagiarism, the role of AI in promoting accessibility, insights we’ve taken from the AI Design Assistant, and more.

In the meantime, we’re delighted to announce the release of Enhancing Higher Education With Generative AI: A Responsible Approach, a strategy guide developed by MIT SMR Connections and sponsored by Anthology. This brings together views from leaders at the MIT Sloan School of Management, the University of Michigan, Arizona State University, Emory University, Texas A&M, Microsoft, and Anthology to provide a helpful playbook on the risks and benefits of generative AI and how policies can be shaped to balance them.

"Generative AI is fundamentally transforming how we approach education," says Nicolaas Matthijs, chief product officer at Anthology. "With the release of our comprehensive strategy guide alongside our robust AI Policy Framework, we underscore our dedication to guiding this innovation responsibly, ensuring that it leads to ethical and substantial advancements in higher education."

Some quick takeaways include:

• Ongoing training and education are important for all stakeholders: With generative AI evolving quickly, ensuring that both students and staff have a strong familiarity with these technologies—and with the institution’s related policies—is crucial. “From Monday through Thursday, we have training sessions at noon, and they’re completely full. Sometimes we have as many as 150 people,” says Ravi Pendse, vice president for information technology and CIO at the University of Michigan. Because instructors are the gatekeepers of education, it’s particularly important to provide them with training and clear guidelines.
• The potential benefits of generative AI extend beyond efficiency: While generative AI is showing impressive results in streamlining administrative tasks, it’s important to also recognize the opportunities to improve the effectiveness of teaching and learning practices as well. This includes, for example, expediting the adoption of authentic assessment tasks: “I tell professors to take their assignment and throw it on GPT. If it gives a satisfactory answer back, then you know your assignment needs to be changed a little bit,” says Sunay Palsole, assistant vice chancellor for engineering remote education at Texas A&M.
• User oversight remains crucial for responsible adoption: Valid concerns remain around the use of generative AI, including the potential for hallucinations and biases, and these are likely to persist. As a result, it’s important to ensure user oversight, and a learning environment where all stakeholders maintain accountability for their work. “Technology should facilitate connection between instructors and learners, not replace it,” notes Nicolaas Matthijs in Anthology’s Sponsor’s Viewpoint. 

Don’t miss this great opportunity to inform AI policy conversations at your institution. Download Enhancing Higher Education With Generative AI: A Responsible Approach for free today!