Automation & Higher Ed

I was delighted to see this thoughtful review of my new book The Equality Machine in Inside Higher Ed focused on some of the questions nearest and dearest to prawfs' hearts: the future of the professor and higher education as AI becomes more and more part of our learning and teaching. In The Equality Machine, I have a chapter that considers robots and automation in education but does not delve into universities and higher ed. Here's the review:

If the dream of creating high-quality/low-cost scaled online programs is ever to be realized, artificial intelligence—AI—will likely be the key enabling technology. The job of the AI in a scaled (high-enrollment) online course will be to optimally connect the instructor to the learner. The AI will determine when the human instructor should coach, encourage and engage with the learner—and when to hold back. The professor and the AI will collaborate to scale the relational model of learning that is the secret sauce of effective instructional practices.

Integrating faculty and AI to scale quality online learning is, to my knowledge, today more an idea than a reality. After reading The Equality Machine, however, I’m more hopeful than ever that this vision will come to fruition. While not focusing on higher education, the book provides enough examples of the transformative powers of digital technology to enhance human flourishing that some level of academic techno-optimism may be warranted.

Lobel, a law professor at U of San Diego, sets out to counter the conventional wisdom that technologies like AI offer more threats than benefits. The book traces a range of examples where the principled and ethical use of big data analysis and AI are being utilized for progressive aims. Examples include using digital technologies to expose and correct discrimination in hiring, promotion and compensation. Gender and racial pay and position gaps can be more effectively addressed with good data, enabling employers and employees visibility into the persistent labor market inequities.

Some of the most powerful examples of the potential for digital technologies to improve well-being described in The Equality Machine come from the domain of health and health care. Lobel describes the efforts of pioneering physicians and researchers to pair clinicians with algorithms for earlier diagnosis and individualized treatments. Soon, AI-enabled medical devices such as insulin pumps will dynamically adjust dosage levels to avoid health crises for diabetics before they occur.

Likely the most controversial parts of The Equality Machine will be Lobel’s thinking on the future of sex robots. As with the entire book, Lobel’s thinking on technologically enabled intimacy bots is nuanced, balanced and complicated. She examines the negatives of reinforcing existing sexist and racist stereotypes of the sex-tech industry but ultimately comes down on the side of optimism. Smart sex robots have the potential to relieve loneliness and enhance happiness, and their creation should be met with less fear and more thought, debate and discussion.

While The Equality Machine seeks to offer a positive vision for technology in advancing social justice, equality and happiness—the book is by no means a defense of big tech. Lobel is highly skeptical that the tech industry will prioritize inclusive and pro-social applications and systems in the absence of scrutiny, regulation and advocacy. The book offers ideas about how to engage with the tech industry to shift incentives toward promoting equitable design.

In reading The Equality Machine, I kept wishing for Lobel to turn her analytical lens to issues of tech, companies and higher education. What might we envision as the role of platform companies, big data and AI in creating accessible, affordable and high-quality online degree programs? Where are the artificial intelligence and university leadership communities coming together? How might we extend the idea of creating equality machines to the working of higher education?