There are a number of ways to read Polanyi. For example, there are some historical and political angles to The Tacit Dimension that relate to the pursuit of science and knowledge and to restrictions on freedom by the state or by other entities to pursue those activities. Polanyi also worked during a period of the 20th century that saw great upheaval, massive wars, and a rise in totalitarianism that in some ways mirrors the kind of nationalism and demagoguery that is showing its face today across the world. It would be interesting to explore these aspects of Polanyi’s work, and especially reasons for some of the influence Polanyi’s ideas have had on some neoliberal thinkers, but for now, let’s simply bracket out those aspects and focus on what the knowledge management (KM) literature has taken off with—the idea that “we can know more than what we can tell.”
Each of us will have our own interests in where KM intersects with our areas of pursuit. For me, it is hard to escape how tacit knowing impacts the pursuit of science and, inclusive of that, scholarly communication and the conduct of scientific discourse. And this is because, unlike some skeptics in the scholarly communication literature, I hold the view that science is only as successful as the scholarly publishing system. That is, our primary way to communicate scientific knowledge is through the written text, the documentation, and if our system for disseminating that documentation is unhealthy, then our pursuit of science, globally and writ-large, suffers.
With this in mind, we can relate the implications attached to tacit knowing to some modern developments. There is an increasing number of researchers, scientists, and librarians who actively pursue a thing called open science. Some of the arguments put forth in favor of a process that opens science includes claims that an open science results in a more efficient and productive system that takes advantage of web and internet technologies, is able to operate with better transparency, is better at re-using other scientists’ data, and is better at attributing other scientists’ work. In some ways, we might say that an open science is the full, or nearly full, realization of the inherent norms of scientific practice.
Within this rhetoric among the proponents of open science lies the idea that an open science results in a science that is more scientific. The key idea here is that science practiced openly will be more available for critique, review, judgment, and so forth and as such, its epistemological claims can more easily be falsified or verified via, usually, reproducibility and replication tests. Thus, and at the very least, there are ideas inherent in the open science movement that imply that science is not science unless it is open and it is not true unless it is reproducible, in a very mechanical sense. But, these are questionable and testable claims, which demand a path for moving forward—a path that requires of us to test the validity of open science and the premises upon which rest our ability to document and codify the processes involved in the conduct of scientific pursuits. That is, to say that open science is better science requires us to test that claim, scientifically.
Thus, there are significant epistemological and also commensurability issues that are simply not acknowledged by the open science community. Pertinent to this is one basic issue: the criterion of demarcation. That is, what criterion do we use to identify science from what is not science (or pseudoscience)? For Polanyi, if “we can know more than we can tell” means there are limits to what we can communicate, and open science is about being better at communicating scientific work, then even under a better model of scholarly and scientific communication there will always be an upper bound limit on what can be falsified, verified, or reproduced via scientific documentation. This means there will never be a complete guarantee that scientific claims can be trusted via the scholarly communication system. There is always something intrinsic in our scientific knowing that is beyond what we can tell.
What is also not fully acknowledged are other ideas about the demarcation of science—issues related to problem-solving (ala Kuhn) and problem-finding (ala Merton). Here we can refer to, I think, one of the best passages (pp. 64-66) of Polanyi’s book, the ending of which he writes:
Thus the scientific interest—or scientific value—of a contribution is formed by three factors: its exactitude, its systematic importance, and the intrinsic interest of its subject matter (p. 66).
In other words, Polanyi argues that science is demarcated not just by its truthfulness, its coherence, but also by whether it is interesting in the right theoretical way. This brings us back to Merton’s statement about the transmission of not just scientific knowing to the next generation of scientists, but also of scientific taste. Let me re-quote Merton:
The role of outstanding scientists in influencing younger associates is repeatedly emphasized in the interviews with [Nobel] laureates. Almost invariably they lay great emphasis on the importance of problem-finding, not only problem-solving. They uniformly express the strong conviction that what matters most in their work is a developing sense of taste, of judgment, in seizing upon problems that are of fundamental importance (p. 453).
I am not a skeptic about scientific documentation, but tacit knowing raises very interesting and serious challenges about the conduct and dissemination of science, and as well as any kind of knowledge that must be taught and passed from one generation to the next, from teacher to student, or from co-worker to co-worker. This is the task that Polanyi has placed before us.