Social vs Science Experiments

Summary:

• Science experiments come out as ‘products’ and once they’re out, they’re out.
• Social experiments haven’t been tested in human-prod until they’re released and continue to rely on people.
• Once social products establish ‘network effects’, it’s really hard to kill them.
• The ‘network’ is built by establishing a solid core - a small group of true believers - then propagating the idea outward.
• Forming this ‘network’ is hard when half the people using your product are here for the coins.
• That’s partly why great products are built during crypto-bear.

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Types of Products / Experiments

• There are two types of products:

  • A product useful on its own. Eg: the world doesn’t need to use GPT-3 for it to be useful to you.
  • A product that needs a ‘network’ of users to be actually useful. Eg: unless the world uses Twitter, it’s not gonna be useful to me. Here the network is half the product.

• The production environment of the ‘science products’ can be simulated in a lab, enabling them to tinker, mess up, and iterate in the relative obscurity of the lab.

• For the ‘network products’, since people are part of the product, the real usage conditions are hard to simulate without users.

  • People come in when things look good, and run when it starts crumbling. But since people part of the experience, the product was objectively better when it was at the peak of the hype cycle.

• A science product is developed away from the real world. So when it is released, it comes out as a fully formed butterfly.

Network Effects

Social experiments live and die by network effects.

• That’s the prize for dealing with the messiness of building a social product.
• Sometimes the network effect can be so strong that even a shit product survives (Facebook).

Establishing network effects

1. Start with a small niche
2. Grow the density and connections among participants
3. And then start adding on adjacent networks.

• Ethereum and bitcoin exactly this: both took off in a much quieter market environment, in the very small first and second crypto cycles, starting with cores of true believers and expanding outwards.

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 permissionless.

Science-ifying social experiments

• The best of both worlds.
• Farcaster:
  • Doing a bunch of really smart technical things.
  • But still a social product.
  • So: limiting who can use the product to a tight core of like-minded people.
  • 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.

Building in bear market

• One of the reasons that big crypto projects are built in bear markets is that only the people who really care stick around and there’s less noise and competition.
• There’s also the total lack of interest from the outside world lets social experiments mirror science experiments as closely as possible.

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Metadata

• People:: Packy McCormick
• Related:: Blockchains, Products, Economics
• References:: https://www.notboring.co/p/social-vs-science-experiments
• Status::understood
• Created:: 24th Nov 2022
• Updated:: $=dv.el('t', dv.current().file.mday)