New MIT Sloan research suggests that AI is more likely to complement, not replace, human workers.
Cambridge, MA, March 17, 2025 (GLOBE NEWSWIRE) — While much public discourse centers on concerns of advanced technologies substituting for and displacing human workers, new research from the MIT Sloan School of Management presents a different perspective — moving beyond simply identifying jobs at risk from AI and highlighting areas where human expertise will remain important and complementary to technological advancements.
The paper, “The EPOCH of AI: Human-Machine Complementarities at Work” offers a framework of human-intensive capabilities and a set of metrics to evaluate tasks across all occupations and better understand the effects of AI on the labor market. Authors are Roberto Rigobon, the Society of Sloan Fellows Professor of Management at MIT Sloan, and postdoctoral associate Isabella Loaiza.
“There tends to be a prevailing narrative that robots are coming for jobs,” said Rigobon. “We think it’s important to ask different questions — looking more at human capabilities than AI capabilities and shifting toward what technology can give us rather than what it might take away.”
The researchers studied the statistical limitations of AI tools. AI is based on universal approximation functions and it is known that those tools perform badly when data are biased or small, when extrapolation far from the training data is needed, and when moral dilemmas emerge. From these deficiencies, the authors concentrated on how humans have dealt with these problems, which creates the foundation for skills that are complementary to AI.
The paper evaluates tasks across a variety of occupations using three key metrics: the EPOCH index (encompassing five groups of human capabilities), a risk-of-substitution score, and a potential-for-augmentation score. The acronym EPOCH stands for:
- Empathy and Emotional Intelligence
- Presence, Networking, and Connectedness
- Opinion, Judgment, and Ethics
- Creativity and Imagination
- Hope, Vision, and Leadership.
Each of these categories include uniquely human capabilities that enable humans to do work in areas where machines are limited.
The metrics are used to evaluate how human-intensive a task is, and whether an occupation can likely be automated or augmented by technology. While automation involves a direct transfer of a task from humans to machines, augmentation occurs when using a machine in a task increases worker productivity in that task or other tasks, thus enhancing overall labor productivity. Augmentation, therefore, requires considering the interactions among tasks, whether in pairs, clusters, or networks. Rather than just serving as “partial automation,” augmentation allows humans to do things that they couldn’t do before. For example, the introduction of advanced microscope tools has augmented humans’ ability to work within micro and nano worlds.
“A lot of the research done in this area tends to look more generally at detailed work activities — using scores from there and extrapolating it down,” said Loaiza. “We focused specifically on tasks and, most importantly, the structure of tasks within a job or occupation to measure augmentation.”
The findings suggest that there are many critical human-intensive tasks — tasks that cannot be done effectively entirely by machines — and an increase in the amount of human-intensive tasks, and in the frequency with which workers performed these tasks between 2016 and 2024. In addition, tasks that were newly added to the O*NET data set — one of the largest datasets used to study labor in the United States, maintained by the Bureau of Labor Statistics — in 2024 have higher levels of EPOCH capabilities than the tasks that previously existed (prior to 2024) and the tasks that disappeared in 2024.
Examples of tasks with high EPOCH levels involve direct recruitment, placement, training and evaluation of architecture or engineering project staff. Such tasks include determining scientific or technical goals within broad outlines provided by top management and developing detailed plans to accomplish these goals. Examples of jobs that often include high levels of EPOCH skills, such as creativity or empathy, include emergency management directors, clinical and counseling psychologists, childcare providers, public relations specialists, and film directors.
The research points to the need to invest in the development of workers’ EPOCH capabilities to gain the benefits from helping workers become complementary to — and not replaced by — AI and new technologies.
“We deliberately don’t call these [human skills] ‘soft’ skills,” said Rigobon. “A ‘hard’ skill, like solving a math problem, is comparatively easy to teach. It is much harder to teach a person these critical human skills and capabilities—such as hope, empathy, and creativity.”
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CONTACT: Matthew Aliberti MIT Sloan School of Management 7815583436 malib@mit.edu
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