Artificial Intelligence (AI) is reshaping higher education and has the potential to completely change how students study, how teachers share their knowledge, and how institutions operate. However, there are challenges, too. Universities must integrate AI technologies while balancing innovation with ethical implications and security concerns to ensure that academic integrity and personal privacy are not compromised.
Unfortunately, there are currently gaping holes in universities’ AI-related policies and guidelines. A recent study from EDUCAUSE revealed that less than a quarter (23%) of the 900 higher education technology professionals surveyed claimed their institution has any AI-related acceptable use policies already in place. Another 48% said they “disagreed” or “strongly disagreed” that their organization has appropriate policies and guidelines in place to facilitate “ethical and effective decision-making about AI use.”
To successfully address these challenges, universities need to act and develop comprehensive AI policies that factor in the needs and concerns of all stakeholders, including students, faculty, researchers, and administrators.
| Potential Danger | Description |
| Loss of human connection | AI-driven learning may lack empathy and personal touch, affecting student engagement and emotional well-being. |
| Data privacy and security concerns | AI systems collect vast amounts of data, raising issues about protecting sensitive information from unauthorized access or breaches. |
| Bias and fairness problems | AI algorithms may perpetuate existing biases, potentially discriminating against certain student populations. |
| Overdependence on AI | Overreliance on AI tools could hinder students’ critical thinking and problem-solving skills. |
| Cheating and academic integrity issues | GenAI tools make it easier for students to generate content that can be presented as their own work. |
| Challenges in detecting AI use | Current AI detection tools have limitations in accurately identifying AI-generated content, complicating efforts to maintain academic integrity. |
| Equity concerns | Unequal access to AI technologies could widen achievement gaps between students from different socioeconomic backgrounds. |
| “Blind spots” in implementation | Focusing too narrowly on certain AI applications may cause universities to miss other important impacts and opportunities of AI in education. |
| Potential for misuse | Without proper guidelines, there is a risk of students misusing AI in ways that hinder their learning and development of essential skills. |
Why Should Universities Develop an AI Policy?
Universities, as centers of knowledge and innovation, have a responsibility to see that AI technologies are integrated responsibly. This is why they need an AI policy to provide the framework to guide the ethical and effective use of AI amongst its different constituents (faculty, research, administration, students). Here’s why developing such a policy is crucial:
Mitigating Ethical Risks: AI can inadvertently perpetuate biases, leading to unfair outcomes. For instance, AI-driven grading systems could reinforce existing inequalities if not carefully designed and monitored. A clear policy can help prevent these ethical pitfalls by setting standards for AI use.
Ensuring Academic Integrity: AI tools can be excellent tools for teaching and learning but also come with risks, such as facilitating cheating or plagiarism. Tertiary education entities, such as universities and colleges, need policies to maintain academic integrity in the face of increasing AI use to prevent cheating, ensure fair assessment, preserve learning outcomes, and maintain credibility.
Protecting Privacy and Data Security: AI systems depend on vast amounts of data, including sensitive and confidential information. This data could be exposed to breaches, abuse, or misuse without proper guardrails. A robust AI policy needs to factor this in to prioritize and protect data privacy and security.
Fueling Innovation and Equity: While managing risks, a robust AI policy can drive innovation by laying out a clear framework for its ethical use. Policies must ensure that AI benefits all students, irrespective of their background or chosen field of study, by facilitating fair access to AI resources and tools.
Research Integrity: AI policies are crucial for maintaining research integrity. They help establish clear guidelines on how AI can be used ethically in research processes without compromising academic standards or scientific rigor. AI policies can also help mitigate the information asymmetry problem in AI use. By setting clear expectations and requirements, policies can ensure that researchers have a better understanding of the AI tools they’re using, their limitations, and potential biases.
Regulatory Compliance: As AI use grows, so does the regulatory landscape surrounding it. Universities must comply with evolving legal requirements, such as the White House Executive Order on the Safe, Secure, and Trustworthy Development and Use of Artificial Intelligence and the EU’s AI Act, by developing policies that anticipate and address compliance challenges.
The Core Components of an AI Policy for Universities
Developing a comprehensive AI policy requires addressing several crucial areas. Below are the core elements that should be included in such a policy:
Institutional Alignment and Governance
Universities must establish a clear position on AI’s acceptable use and role within their institution. This means aligning AI use with the university’s mission, values, and long-term goals. The deployment of AI must support the university’s broader educational objectives.
A dedicated governance framework is key to overseeing AI implementation. This should include regular audits to manage risks and ensure ethical use. Universities should appoint a committee or task force to keep an eye on AI practices, evaluate new AI applications, and recommend and oversee updates to the policy as needed.
Effective policy development requires input from all key stakeholders, including administrators, faculty, staff, and students. The right conversations and perspectives will factor in diverse views, giving the policy a better chance of a broader buy-in. This process can also help identify potential issues early on in the initiatives and build a culture of responsible AI use.
Pedagogical Integration
AI has the potential to revolutionize education by driving personalized learning experiences and mechanisms for adaptive feedback. Policies must encourage the use of AI to improve teaching and learning yet still ensure that these tools are used ethically and do not undermine the educator’s role.
Unambiguous guidelines must also be established to address the use and role of AI in academic assessments. For example, universities might set policies on the use of AI tools in assignments, exams, and grading to prevent misuse. Fairness and maintaining academic integrity need to be at the heart of these guidelines.
Operational Considerations
To implement AI successfully, the right infrastructure and training are needed across campuses. Universities must ensure that all departments have fair and equal access to AI tools and resources. Moreover, faculty and staff must be trained to use AI technologies in their work fairly and responsibly.
AI tools often handle sensitive data, which must be kept private and secured accordingly. Policies must establish protocols for protecting this data, including negotiating security agreements with AI vendors and educating users about best practices for handling data.
Ethical and Responsible Use
Tertiary institutions need to clearly define what constitutes the appropriate or inappropriate use of AI tools. Any policy should be tailored to the institution’s specific needs, and the ethical implications of AI use should be considered in different contexts.
Addressing potential biases in AI systems needs to be a priority. Policies need to ensure that AI applications promote fairness and do not perpetuate inequalities. Regularly auditing AI systems for bias and implementing corrective measures when necessary can address this challenge.
Continuous Review and Adaption
The speed at which AI is developing requires policies to be regularly reviewed and updated. Universities should establish controls for the ongoing monitoring of AI trends and technologies to keep their policies relevant and effective.
Maintaining transparency around AI use helps to build trust and understanding. Universities need to document new AI use cases and applications and share their data with stakeholders to fuel an open and informed culture and environment.
Harnessing the Benefits, Mitigating the Risks
Universities can only harness the benefits of AI if they have a comprehensive AI policy to mitigate its risks. By addressing these challenges and downsides, universities can deploy AI in a way that aligns with their mission and values.
Elevate can assist Universities and other tertiary institutions in developing their comprehensive AI policies tailored to their settings. Contact us to schedule a consultation on how to build your AI policies, AI Center of Excellence, or conduct an AI Risk Assessment or AI Audit.