When speaking publicly, researchers and entrepreneurs alike tend to present the rosiest possible picture of their work. This often leads to harmful over-claiming (Pitching out corrupts within) and a less personal, more transactional relationship with others. An interesting antidote is to actively practice “anti-marketing”: to make a point of focusing publicly on the least rosy parts of one’s projects—what’s confusing, what’s frustrating, what’s not working.
If you make anti-marketing the goal, then interesting challenges become a positive thing: fodder for public conversation, not something to be swept under the rug. At least most of the time, you should be focused on your project’s biggest challenges, rather than what’s going well. I suspect it also builds a deeper, more authentic relationship with one’s audience (see also Work with the garage door up
This term was coined (as far as I know!) by Michael Nielsen in November, 2019 (in personal conversation).
Q. What’s Michael’s term for focusing public conversation on the least rosy elements of one’s projects?
A. Anti-marketing.
Related is Bret Victor’s term “anti-rhetoric”, as used here in an excerpted email to Nicky Case about Explorable explanations.
I'd like to suggest, as you work on your projects, you keep a couple questions in mind:
- By playing your model, can a reader learn something that you don't already know yourself? - Could a reader potentially use your model to argue *against* your position?If so, then you're enabling independent thought, not just pushing your own beliefs. It's a kind of anti-rhetoric. Sounds scary! But I think you can do it, and you'll be onto something really valuable.
“{anti-rhetoric}”: Bret’s term for {communications which enable independent thought, rather than just pushing the author’s beliefs—e.g. a reader should be able to learn something the author doesn’t know, or argue against the author}
Q. How does Bret Victor want John Cramer to convince him of his QM interpretation?
A. By letting him actively try and fail to refute his interpretation, by making the experience of the book be about engagement with his computational models. (source)