A Movement for Meaning
So, how do we spread meaning-articulacy? How do we switch from being consumers to being meaning agents? How do we make a movement out of this?
Ellie is the person to ask. She has a deck you can read. But I’ll highlight some activities.
- In Berlin, San Francisco, and Austin Texas, there are already local chapters, where people support each other in becoming values articulate.
- The first part of our course also helps with this.
We want to make this possible for many more people.
- We want chapters in more cities and better event structures.
- We want our course materials to work for more people.
- Ideally the course should be unnecessary.
- One of us, Ivan, has a large language model approach to guessing people’s sources of meaning.
- Another, Ryan, has a journal for getting clear on sources of meaning.
- I’ve made several different app experiments to find sources of meaning from games you’ve played, practices you love, people you admire, or your emotions.
There should be many ways to get clear on your values. Some of them are already emerging:
More experiments are needed.
We want this community to be able to advocate for spaces. In the near future, any scientist should be able to stand up and say “hey, my research lab used to be a space but this policy has turned it into a funnel”. And people should understand, and look into it.
To do this, values-articulacy must follow in the footsteps of feminism, climate justice, NVC, Effective Altruism—many other social movements that spread new vocabularies.
We can learn from these groups, and we can also give something to them. We can help people use meaning to connect, instead of ideology. If we can do that in a big way, we’ll decrease political polarization, strengthen the social fabric, and increase resilience.
We can also build a bridge to academia. Values cards and spaces can be integrated into microeconomics, transaction cost economics, and cognitive science. We can spell out what a meaning agent is in political theory, and game theory, etc.
Spacemakers
Column 2 is a maker community. Something like Y Combinator, Organic, Zebras Unite, or On Deck, but for spacemakers.
Sam, Ben, and I train spacemakers at the School for Social Design. This video has touched on most of our curriculum. We teach people to break designs into funnels, tubes, and spaces. interview people about their sources of meaning. To build success metrics for spaces, to design for hard steps, and to make space trains.
We already have a free textbook online. I, personally, administer tests when people go through it.
But the school is just a start. We could have accelerators, incubators, and funds for spacemakers. We need connections with other entrepreneurial movements. We’ll need business infrastructure, like software as a service for spacemakers.
How shall we build all of this? That’s a questions for people like Sam, Ben, and Anne. They'd love to talk!
Meaning Profiles
Next, there’s the challenge of replacing the profiles in operating systems and ad networks. There are startups to be made here! There are machine learning projects! There's open data and web standards!
I hope we can create a cross-industry working group. Kind of like the W3C, which makes standards for web browsers. Call it the M3C. For drafting the protocols and APIs of a meaning-driven world.
There’s at least one startup I’d like to be part of. Once people have become values-articulate, I’d like to make a service that helps them make their lives meaningful. Something that, for a fee, hooks them up with the right events, communities, local people, etc, to suit their sources of meaning.
I’m also excited to use values cards for AI alignment.
For more detail about any of this, talk to me or Ivan.
Space Trains
Finally, there’s the final boss, of replacing markets, recommenders, and structures that tend towards Piles & Transactions—replacing those with space train structures.
Part of this is economics research
.
Part of what a market does is structure resource flows, based on value-added. So, to replace markets with space trains means solving problems of attribution and payments — or more broadly, of resource allocation at the margin of meaning. Resources need to flow through space trains right. I have some ideas about that. But I wouldn't be surprised if someone else, with a stronger background in linear algebra and econ, did the work first. I hope I get to be on that team.
Ultimately, I hope space trains, and other meaning-articulate structures, won’t just replace markets and recommender feeds, but also voting structures, org structures, many other things.
I’m excited about that, and putting a team together.
To help you find your part, I’ll try to map some of the work to be done.
First, let me summarize some changes to be made.
- We want to switch from people being only aware of their goals, to being aware of their sources of meaning.
- We want to switch from designers and entrepreneurs focusing on funnels and tubes to understanding which parts of their projects are spaces and focusing just as much on them, and on the sources of meaning they're about.
- We also want designers to learn about the hard steps they’d have to make easier for those spaces to be good for those sources of meaning.
- We want the profiles kept by big corporations to center as much on our sources of meaning as they do our vulnerabilities, and ultimately to be accountable to our sources of meaning.
- Finally, we want to transition as much of the creator economy and the broader economy as possible from organizing piles and transactions, to organizing space trains.
And you might have an important part to play, in this pivotal moment.
Strategy
So these are all solutions, but I haven’t talked at all about strategy. I haven’t talked about getting these design methods adopted, getting big companies to change their profiles, anything like that.
But strategy is important. But it isn’t mine to do.
So far, the talk’s been my own work and research.
I’ll help of course, but this is a team effort, and I’m thankfully a small part of it.
So here are some of the initiatives:
On the right are large-scale systems, which only a few can change. On the left are things we all can work on.
I’ll go through each column, from left to right.
And as I step through them, I’ll mention the rest of the team. Ellie, Ben, Ivan, Sam, Anne, Ryan, Lily, Shelby, David, and Jason — and many more to come.