The student debt debate may be about to end, but it won’t be because of loan forgiveness. Higher education is one of a number of sectors of the economy subject to the economic phenomenon of Baumol’s cost disease. This is a dynamic that explains the difficulty of achieving productivity gains in certain sectors that are labor-intensive and rely heavily on human input. Sectors such as healthcare, law, and education are particularly affected by this phenomenon, which makes it challenging to deliver high-quality services while keeping costs under control.
However, it is possible that the recent innovations in AI offer a path out of this economic trap. By leveraging AI to automate routine tasks and augment human expertise, these sectors could see significant productivity gains that would enable them to deliver high-quality services more efficiently and at lower costs.
In the healthcare sector, for example, AI is already being used to improve patient outcomes and reduce costs. AI-powered medical imaging technologies can help doctors diagnose and treat diseases more accurately and efficiently, while virtual health assistants can provide personalized care and support to patients outside of traditional care settings. People even prefer AI-generated bedside manners. The Journal of American Medicine published a study that found that ChatGPT provided more empathetic and better quality answers to patient questions compared to actual physicians nearly 80% of the time[1]. AI will also lighten administrative costs so health providers can shift investment toward patient care. For every dollar hospitals spend to collect revenue, $0.25 go toward repetitive administrative tasks[2]. AI can eliminate some of those costs that are often passed down to the patient.
Similarly, in the legal sector, AI technologies can be used to improve the speed and accuracy of legal research and analysis, reducing the time and cost required for case preparation and litigation. AI-powered contract review systems can also streamline the contract review process and reduce the risk of errors or oversights. The discovery process within legal cases is subject to simplification as well. AI can efficiently analyze massive amounts of digital documents through a process called “ediscovery.” Firms like Relativity and Everlaw are delivering software to ease the discovery process and find breakthrough evidence without the man-hours.
In the education sector, AI technologies can be used to personalize learning and provide students with more effective feedback and support. AI-powered tutoring systems can adapt to individual student needs and provide targeted interventions, while automated grading systems can reduce the time and effort required for assessment and feedback. Generative AI can also make waves for accessibility as well as costs. AI can provide transcription services for students with disabilities. Start-ups like Verbit already boast Coursera, Harvard University, and Stanford University as customers.
These gains and opportunities obviously raise important questions about change and adaptation in these sectors. As AI technologies continue to improve and become more widely adopted, they are likely to disrupt traditional business models and create new winners and losers.
In healthcare, for example, traditional healthcare providers may find themselves competing with new entrants such as telemedicine providers or AI-powered diagnostics companies. Similarly, in education, traditional institutions may face intensified competition from online learning platforms or AI-powered tutoring systems. In the legal sector, AI technologies may disrupt traditional law firms by enabling new entrants to offer lower-cost legal services or more efficient case preparation and litigation services.
Despite this, AI technologies are unlikely to be able to fully replace human expertise, creativity or innovation. In the near term, we are likely to see the same pattern as with previous technology revolutions: a migration of effort to new fields and new opportunities as productivity increases in areas where it previously lagged.
Citations:
[1] Ayers JW, Poliak A, Dredze M, et al. Comparing Physician and Artificial Intelligence Chatbot Responses to Patient Questions Posted to a Public Social Media Forum. JAMA Intern Med. Published online April 28, 2023. doi:10.1001/jamainternmed.2023.1838
[2] Tseng P, Kaplan RS, Richman BD, Shah MA, Schulman KA. Administrative Costs Associated With Physician Billing and Insurance-Related Activities at an Academic Health Care System. JAMA. 2018;319(7):691–697. doi:10.1001/jama.2017.19148