Tasks often vary along a dimension where some tasks matter more, yet are also harder to judge for quality of performance. This spectrum appears in org management, where it is harder to judge the quality of higher level more important decisions. It also appears in academia, where STEM tasks tend to be less important but easier to judge, compared to those in humanities.
In management, the usual strategy is to first test people at lower level, less important, easier to judge tasks. Then as some folks prove themselves, slowly move those folks up the ladder to similar but more important but harder to judge tasks. Somewhat emphasize looking at the easier to judge tasks that each person does wherever they are, and moving them from orgs and divisions where it was easier to judge similar-level performance. And supplement all this with ratings of potential by people at similar levels.
It would be possible instead to place people in high org positions on the basis of their having been a good executive assistant, or having been a good biographer or historian of top executives, or having made popular books, podcasts, or videos on top management. But such moves are pretty rare.
In academia, the analogous strategy would be first have people do relatively unimportant but easier to judge tasks, and slowly move them up to the more important but harder to judge tasks. So first have them do many simple homework problems, then fewer harder problems, then replicate prior actual research, then do original research.
First work in topic areas with more math, faster feedback, easier replication, easier measurement, more data to test against, better organized concepts, lower dimensionality of concepts, more causal identifiability, more stationarity, less observer dependence, more decomposability, less interpretive dependence, less value dependence, weaker desires of funders and researchers to believe particular claims, and less adversarial sources with incentives to deceive researchers. Then more to harder topics. Supplement with ratings of potential by nearby folks.
Within disciplines, we do often follow similar strategies, starting with easier to judge tasks, emphasizing easier to judge aspects like writing quality, and relying on adjacent ratings of potential. But this tendency mostly stops at disciplinary boundaries. People who end up doing the most important hardest to judge tasks in the humanities didn’t start by proving themselves in STEM and then slowly moving to harder disciplines. They instead start with the easier to judge tasks in the humanities. Which often consist of the history of, commentary on, interpretation of, and popularization of famous prior writers in those same humanities areas.
While it is possible that this just happens to be the best way to train and select people for such roles, the usual tendencies of academic disciplines to create and protect their “turf” seems to me a more likely explanation. The top people in the humanities want to feel more in charge of choosing their successors, and to teach more classes on their topics, both of which are threatened by the STEM to humanities career pathway I outline above.
The intellectuals that I’ve been most impressed by have often trained and proven themselves first on easier to judge problems, and then gradually took on harder problems. So I suspect academia is making a big mistake here.
To be clear, while a big % of humanities scholars should start elsewhere, most scholars who start elsewhere need not end up in humanities.
I think everyone needs either STEM training, or practice in some real-world domain with feedback such as auto repair, farming, plumbing, or business management, not because it's easy, but because:
- it introduces people to the idea that some questions have correct and incorrect answers which can be found and distinguished from each other, and to how to know whether your question is one which might have an answer, or is even a question
- it teaches them to seek trade-offs and optimizations rather than perfection
- it is the only way people can ever recognize how sloppily they reason in the absence of empirical feedback
- it is the only way people can grasp how feedback within a system, and interactions with other systems, and noise within the system, will interfere with analytic reasoning. STEM isn't best characterized as analytical reasoning; it's best characterized as those disciplines in which physical feedback hits analytical reasoning.
As I explained below, I do appreciate the STEM-to-Humanities pipeline idea, but first, consider this drawback of the idea: These broad discipline categories align with fundamentally different cognitive processing styles.
STEM disciplines fit a brain optimized for rule-governed, algorithmic ("fine-grained") information. A major advantage of STEM is domain modularity: you can rigorously analyze problems without needing reference to vast, disparate external fields. In contrast, the humanities attract and reward brains wired for long-distance associations, quasi-regularities, and diffuse pattern recognition across broad, interconnected domains of human experience.
This difference explains why STEM fields regularly support child prodigies and early-career breakthroughs, with math, physics, and computer science being the stand-out cases. We seldom see child prodigies in diplomacy, history, or literature. These disciplines require a breadth of contextual knowledge and human experience that can typically only be hard-won through decades of lived wisdom.
For these reasons, a general pipeline from STEM to the humanities won't work for most people. However, a one-way late-career transition from narrow/rule-governed fields to broad/integrative questions is a recognized pattern. Scholars can exploit early-life advantages in algorithmic domains, then pivot toward broad synthesis as their life experience and domain breadth accumulate.
Examples of this arc that I noticed as I was evolving as a young scientist.
Herb Simon: Moved from formal economics and decision models to broad questions of human cognition, artificial intelligence, and organizational behavior.
Christof Koch: Shifted from quantitative biophysics and cellular neurobiology to the expansive, integrative question of consciousness.
Steven Pinker: Began in technical psycholinguistics and visual cognition before expanding into broad historical, societal, and humanistic syntheses.
Alan Turing: Started in foundational logic and computation before pivoting to morphogenesis, artificial intelligence, and philosophy of mind.
Isaac Newton: Mastered formal physics and mathematics early, then devoted much of his later life to theology, history, and alchemy.
E.O. Wilson (Ant biology/sociobiology --> broad human nature, ethics, and biodiversity synthesis like Consilience).
Michael Polanyi (Physical chemistry --> philosophy of science, social theory, epistemological tacit knowledge).
(Personal note: E.O. Wilson was my sociobiology professor in 1981 and Steven Pinker wrote me letters of recommendation for graduate school.)
I'd be interested to hear what other examples of people transitioning from narrow/rule-governed domains to broad, integrative humanistic questions stand out to others here.