In a recent meeting of the Sawyer Seminar, Dr. Edouard Machery came to discuss the role of data in his work. He is a Distinguished Professor in the History and Philosophy of Science (HPS) Department at the University of Pittsburgh, and Director of the Center for Philosophy of Science.
The HPS department seems to be inherently interdisciplinary, one that brings together apparently diametrically opposed methods, like statistics and philosophy. On their website, it states “Integrating Two Areas of Study: HPS supports the study of science, its nature and fundamentals, its origins, and its place in modern politics, culture, and society.” Though many, seemingly disparate skills are required for such a field, there was still interest in building a new domain, experimental philosophy. Dr. Machery engages in this area in his current research, as he states, “with a special focus on null hypothesis significance testing, external validity, and issues in statistics.”
Engaging in such varied methods, and being interdisciplinary at a personal level is difficult (to say the least). If it is true what Malcolm Gladwell states, that mastery in a subject takes roughly 10,000 hours of practice, there are only so many fields of expertise one can cultivate in a lifetime. Working in a domain in which one has gained expertise also takes time. Is it like a language? Are there polyglot parallels? After acquiring four, does one get faster at accruing expertise?
Many specialists were drawn to their field because of a passion for the subject, and proficiency materialized as advanced degrees, formalized proof of sustained attention towards a research question and expertise gained. It is blatantly impractical to attain such a level in multiple fields, prudence dictates that such in-depth study is not frequently undertaken. Given our limited time on this planet, what are the necessary skills required for the future? Every moment spent learning one skill is less time that can be devoted to other endeavors. Is it worth it to spend 10,000 hours learning to code? As is the case with so many questions, the answer seems to be, “it depends”.
Finding this answer for any person starts with gaining a working familiarity in fields with which they want to engage. Extending the language metaphor, it is valuable to become “conversational” in multiple domains. Exchanging ideas and communicating across fields can be thought of, as is mentioned by Machery in our forthcoming podcast, like “trade zones.” Once one has meaningfully engaged with a new discipline, be it computer science or philosophy, the value of further time investment becomes clearer.
In these areas, one may also find collaborators who are interested in the same questions, seen from the vantage-point of another field.
Terminologies can become locations of tension within these “trade zones”, offering opportunities to explain the limitations and usefulness of concepts within and across disciplines. In moments where it becomes clear that one field uses a term differently, there is the potential to reflect and clarify for oneself and one’s colleague(s) from another field what the value of (or implications within) a given term or concept are. This is a learning opportunity in the moment of conversation across fields, but such moments are also possible while learning about other domains of knowledge.
Many advances in scholarship have been made by critically considering the paradigms under which our own and other fields operate. For individuals and collaborators, generous and scholarly exchanges are the way forward.