I was asked a while ago to speak to graduate students about interdisciplinary collaboration, so I put together some notes about the pitfalls and benefits of working with people from different intellectual backgrounds. Such collaboration is essential for understanding the nature of mind, which requires the participation of philosophers, neuroscientists, linguists, anthropologists, and computer modelers as well as psychologists. I haven’t gotten around to writing this up in more detail, so I’d like to present the outline as cryptic advice. A more discursive discussion of collaboration in cognitive science is here.
A. Reasons NOT To Collaborate Across Disciplines
1. Collaboration and interdisciplinary work waste time.
2. Your home discipline won’t respect you.
3. Other disciplines will consider you a meddling interloper.
4. You’ll find it harder to publish.
5. You’ll find it harder to get grants.
6. You’ll find it harder to get a job.
B. Reasons To Collaborate Across Disciplines
1. Many important problems (e.g. the nature of mind) are too complex to be pursued using the ideas and methods of a single discipline.
2. Collaboration and interdisciplinary work can be fun and exciting.
3. Interdisciplinary collaboration can be creative.
4. Interdisciplinary collaboration can be productive.
5. Interdisciplinary collaboration can reach a broader audience.
6. Interdisciplinary collaboration can be socially useful.
7. Interdisciplinary collaboration can lead to interesting jobs.
C. How To Be Interdisciplinary
1. Find exciting problems: explore and exploit coincidences.
2. Read and socialize widely.
3. Be better than disciplinary.
4. Learn multiple methods.
5. Communicate broadly.
6. Use helpful tools like Wikipedia and Google Scholar.
7. Evaluate feasibility and productivity.
D. How To Collaborate
1. Find a mentor.
2. Find a partner.
3. Build a team.
4. Avoid jerks and freeloaders.
5. Check your ego at the door.
6. Be flexible and open to change.
7. Find a productive and congenial division of labor.
8. Be generous about credit.
9. Evaluate feasibility and productivity.