In my mind, the raison d'etre for democracies is to make good decisions, a way to harness the wisdom of the crowd in the pre-Internet age. Which is not to say that it's perfect, but anyway...
There are several problems that seriously distort the US's ability to make good decisions.
The first is that the US's political system has some significant anti-democratic features, and so does not accurately represent the will of the voters. As Chief Justice Earl Warren said in Reynolds v. Sims (1964), "Legislators represent people, not trees or acres. Legislators are elected by voters, not farms or cities or economic interests."
The second is that, starting with Trump in 2016, the Republican party and conservative news started pushing overtly counter-factual information. President Trump alone made many thousands of false or misleading claims, and Fox News has been important in the mainstreaming of various conspiracy theories.
Without an informed citizenry and equal representation, it is impossible to make good decisions. This can negatively affect everything from national defense to the economy to medicine to utility oversight.
(I'm not being utopian about this. I understand that voters may always prefer to base decisions at least partly on personality, in addition to policy. But in the age of Trump, it seems like we've swung completely away from policy and entirely towards personality, and that's bound to cause significant missteps on the international stage. Also, misinformation has always been a problem   and always will be, but the level of misinformation seems to have gotten noticeably worse lately.)
If we were to have a "United States 2.0", how would we organize it? Advances in decision-making software and social science research into group decision-making may offer the opportunity to do things very differently the next time.
Wikipedia pages about group decision-making offline:
Wikipedia pages about political group decision-making offline:
Wikipedia pages that have a more social science bent:
Wikipedia pages about decision-making software:
Wikipedia pages about the combination of all of the above::
Other Wikipedia pages:
Do current social media websites surface the most useful content? (Granted, there's a difference between "usefulness" and "engagement", but let's put that aside for the moment.) I would say no, they do not:
But on Twitter, if you tweet something out and one lone person out there—it moves them, it changes them, it changes their world—that’s not going to register. What that’s going to look like is your tweet got one lonely like and you’re going to feel like a failure. And one of the interesting things about this experience is the process of quantification of Twitter peels off all that richness.
There’s all the stuff that you don’t see. All you see is the number going up. And the number going up picks up on some really simple things. It doesn’t pick up on how deeply someone cared about what you said. It picks up on whether they clicked like. And a lot of times people click like because something made them laugh for a second, not because it moved them two weeks later.
So the basic thing that I keep thinking about is that point systems are really narrow, and really clear, and really simple. And in games—in real games—when the point systems aren’t attached to, I don’t know, the political life of our nation, that’s great. It’s beautiful. And we can talk about why that enables all these kinds of beauties. But when you attach that to something in your life, like, I don’t know, Fitbit, or Twitter, or grades, or, probably for you, the number of downloads on your podcast, that thins out so much of the richness and the plurality and the different ways that we could value things.
... I’ve been trying to figure out exactly this question, why we’re seeing this increase of points everywhere, not just inside formal games? And the answer seems to be that quantified measures are extremely good tools for large-scale bureaucracies to organize themselves.
... [T]he reason is because this information needs to travel. In a large-scale bureaucracy, there are lots of people that need access to the same information. And they won’t have the same background. They won’t have the same contextual richness. And so he says that what an institutional quantification does is it concentrates on this little nugget that’s invariant and this lets the information travel easily between context and it lets it aggregate easily.
... So again, for me, in education, the easiest example is grade point average. You could actually imagine a university without any letter grades in it, right? You could have this rich qualitative feedback. I could tell one student who wanted to be a journalist, we could work on their writing and the clarity of their writing. And I could tell another student who wanted to be a philosopher, we could work on exactly getting the right kind of logical formalisms. And another student who was in my ethics class who is there because they’re going into medicine—they’re never going to write anything, but they really want to understand these ideas—I could work with them on what the ideas meant and how it could inform their lives.
I don’t actually need in any of these cases, for their educational growth, to assign them a letter grade that’s on a scale that could compare one student to the other. But information— the kind of information that this generates, these rich, qualitative reports, they’re not going to travel well. They don’t aggregate easily. A dean from the business school isn’t going to understand them.
So in order to make that information travel well, I need to create this neat little informational packet where I strip off all of the weird context-sensitive stuff and just create something simple. In this case, I rank each student inside a pre-established spectrum— F to A. And that information, right, is totally comprehensible to anyone. It aggregates easily. Everyone collects it in the same way. It’s been standardized. It mounts up.
So if you have large-scale bureaucracies that need to be organized and function coherently, then you need these kind of simple, nuance-free packets of information. And I think that’s one of the reasons we’ve seen this constant rise of simplified metrical analysis.
But the thing about these instantly debatable questions is they tend to avoid nuance and complexity. Like, there is a spectrum of foods that involve some combination of processed wheat with meat and/or cheese and/or vegetables. And within that spectrum, there is another spectrum that we call sandwich. And both of those spectra have fuzzy edges because that's the nature of spectra. But that is a boring take that does not demand engagement, whereas a question like "Is butt legs?" does demand engagement.
And engagement is sort of the fuel that runs the social Internet. Videos with higher engagement-to-view ratios on YouTube or TikTok are shown to more people than videos with low engagement-to-view ratios. The same is true, for example, on my Twitter. ...
But I see this everywhere I make stuff online. When I make something that allows people to agree or disagree with it in a straightforward dichotomous way, it gets a larger audience than when I don't do that. And this is true even when I'm sharing something that almost everyone would be happy about. ...
... And for me, that's the real lesson: The way to get simple engagement, likes, views, and comments is not necessarily the way to get actual engagement, the kind of volunteering and fundraising and lobbying that helps bring about real change. Of course, none of this is to delegitimize having fun on the Internet and engaging with instantly debatable questions. And I think even politically charged, instantly debatable questions can be hugely helpful in getting us angry, because we should be pissed off about injustice. And sometimes those instantly debatable questions can be a way into a new or deeper understanding of it.
The year I graduated from high school, 11 million children under the age of five died. This year, fewer than 5 million will. That is still way too high, but there was nothing inevitable about that progress — it happened because people worked together to make it happen. Activists, health care workers, governments, charities, all worked together to make that progress. And it was messy, hard, complicated work. But that is real engagement, not stopping at mere despair.