Higher Education Must Take the Lead in Making AI Socially Beneficial
- Donald Norris
- Apr 7
- 3 min read
In my recent blog, I discussed achieving socially beneficial outcomes through analytics and AI-driven change. Amir Husain, in his forthcoming book, The Cybernetic Society, emphasizes the urgent need for transformative actions within the next five years. These actions are crucial to build trust, develop governance, and shape the practices of emerging AI platforms to avoid a dystopian future, which would be characterized by:
Intensified inequality
Unhealthy concentration of power in tech oligarchies
Job displacement across all sectors
Economic stagnation
Societal unrest and disruption
Feedback from my previous blogs has raised two pivotal questions:
1. What socially and economically beneficial outcomes should we pursue?
2. How can higher education reclaim its leadership role in promoting societal well-being?
Advancing Social and Economic Well-Being Through Ethical AI Principles
A societal movement is emerging around principles of ethical and socially beneficial AI governance. These principles could guide the responsible use of AI at institutional levels and across broader ecosystems, from multi-institutional collaborations to national and international policy frameworks.
These principles of Ethical AI Governance include:
AI Should be Human-Centric and Socially Beneficial: AI should enhance collaborative intelligence between humans and machines centered on human values. There is a significant leadership opportunity for higher education in collaboration with government and industry to define and promote the functional and socio-economic benefits of AI.
AI Should Be Fair: AI must use data and knowledge fairly, safeguarding intellectual contributions from all professional sectors, including academia.
AI Should Be Accountable: Users and creators of AI systems must ensure transparency in both performance and impact.
AI Should Be Secure and Safe: Both technology providers and institutional users must be responsible for the security and integrity of AI systems.
AI Should Be Explainable and Transparent: AI processes should be clear and understandable to all stakeholders, avoiding "black box" scenarios.
Figure 1: Principles of Ethical AI Governance
Currently, the engagement of higher education with AI displays the characteristics of an experimental, reactive venture. It is driven by the technology sector (vendors and investors), which furnishes funding, sets the pace of product innovation, and teases the market with accelerating visions/predictions of rapid, inevitable transformation. As a result, AI innovation is moving too quickly in some ways, and its potential negative outcomes are given short shrift. Moreover, the tech sector demonstrates little comprehension of the full implications of the economic, social, and ethical transformations that data, predictive analytics, and AI will drive for AGI and automation. This understanding can be provided by leaders and AI practitioners in higher education.
Higher Education Must Reclaim Its Voice
Higher education leadership must become involved in the quest for understanding and achieving social, economic, and ethical well-being through transformative AI. Despite its vast potential, many in higher education and the public remain unaware of the challenges and opportunities presented by AI and AGI. Moreover, U.S. higher education, unfortunately, is currently preoccupied with urgent challenges such as:
Declining enrollment and public support,
Authoritarian attacks on scientific research,
Efforts to dismantle the U.S. Department of Education,
Politically motivated attacks on elite institutions,
Uncertainty and financial distress caused by turbulent times and Trump's economics,
The threats and opportunities AI poses to core teaching, research, and public service functions.
Many of these existing challenges can be addressed by AI. Higher education leaders must adopt
bolder leadership and fresh perspectives in deploying AI to address the challenges of turbulent
times and Trump programs. They should step forward, not as defenders of privilege or the status
quo, but as active agents of social and economic well-being, achieved through:
Embracing and promoting ethical AI and advocating for positive social and economic outcomes.
Leveraging AI to build resiliency and institutional adaptability to turbulence.
Championing human-centric innovation, addressing many vexing social and economic problems, and offering new solutions appropriate to the times.
Using AI to reinvent general education and career planning for continuous learner upskilling.
Achieving better, more personalized student outcomes, including reduced costs.
Promoting commercialization of university-produced intellectual property to stimulate new solutions, jobs, and enterprises.
By embracing these expanded roles, higher education can rediscover its voice and its essential role in shaping a prosperous and beneficial future during transformative, turbulent times.
Resources
1. Donald M. Norris, “How to Avoid AI-Driven Dystopia: Starting Now,” Blog, February
2025.
Together, Forbes Innovation, January 10, 2025.
3. Jasleen Kaur Sindhu, “AI Ethics: Enable AI Innovation with Governance Platforms,”
Gartner Group, October 14, 2024.
4. Joshua Rothman, “Are We Taking AI Seriously Enough?” The New Yorker, April 1,
2025.
Inside Higher Education, April 2, 2025.