Social vs. Science Experiments

After a bunch of tedious, incredibly difficult work in relative privacy, these products are so obviously useful that adopting them is becoming a no-brainer. That’s one of the benefits of quietly doing science experiments in the lab before commercializing.

Start with a small niche, grow the density and connections among participants, and only then start adding on adjacent networks. That’s really hard to do in a bull market, when a bunch of people rush anything that looks even remotely promising, diluting and even poisoning the niche, particularly when web3 products are designed to be open and permiss... See more

People building social experiments have no such luxury. While technology plays an important role – blockchains, token standards, zero-knowledge proofs, and the like are all major technical innovations – people are a necessary component of the product itself. And people are messy, flighty, scammy, fickle, excitable, and all of the other wonderful th... See more

[in bear markets] I think the bigger thing is that the total lack of interest from the outside world lets social experiments mirror science experiments as closely as possible.

This is not meant to excuse the actual scams as fun experiments. Au contraire, the actual scams are doubly-destructive, because they harm their own users and they cast a shadow over the well-intentioned projects. Fuck the scammers.

Metcalfe’s Law, which states that the value of a network is proportional to the number of people using it, cuts both ways for social experiments that need to establish network effects. It’s really hard to get the right people to use the right product in the earliest stages, and most network businesses fail because of this Cold Start Problem.

That gives the product the chance to be as much like a science experiment as it’s possible for a social experiment to be, making and fixing mistakes in private with the collective input of people who care about the product. It will be big one day, and maybe there will be a token, but by building in a semi-closed lab, it should have a strong enough ... See more

Social experiments live and die by Network Effects, the prize for dealing with all of the human messiness upfront for the few social experiments that make it to the other side. Network effects can become so strong that it doesn’t matter how bad the bits a company produces are, people will stick around (ahem, Facebook).

That’s not to say that Hype doesn’t impact public perception of science experiments. AI was famously always “ten years away” and “just linear regressions with a fancy name”... until it wasn’t. But AI’s success didn’t depend on getting a lot of people to use not-yet-good-enough chatbots; it depended on keeping a relatively small number of nerds exci... See more