New kinds of problems, Part I
The Edelman Trust Barometer 2022 is out. If you have the time, I definitely recommend to check it out. It’s free and available for download. Edelman is a global communications firm that has been studying trust in detail for over 20 years, with interesting reports about trends in various types of government, media, businesses and NGOs and the public’s perception thereof, with breakdowns per type, sector, country and so forth. I’ll share the one-pager top 10 conclusions as it lines up perfectly with what I want to write about:
I suppose this confirms what many people feel on a daily basis, in a variety of personal ways, regardless of where they think these issues started or how to solve them. Why I personally find it interesting it because it lines up with an important aspect of the crypto-ethos, precisely aiming to restore trust: don’t trust, verify. A starting point for a potential solution for this growing distrust, and the accompanying polarization that goes with it is not, *checks notes*, to keep calm and trust more, or to continue to give benefit of the doubt to opaque actors, a large part of which now advocate for increased censorship or at least more speech control. It hasn’t really been working well so far and seems to be ‘fueling the fire’ in a sense. The decay of mainstream media and government’s reputations has been going on for a while now. The take that this will self-correct is unfortunately aging badly - and we absolutely should correct this, as it would ultimately be better for everyone to have a robust shared reality.
In fact, trust may be one of the things that is so important for the world that it could find actual application on a blockchain or Web3, without it being a VC cash grab driven meme with no real use case. As a very quick introduction, what is Web3?
Web3 is the combination of the decentralized and community-governed aspects of Web 1 (1990-2005) and the much more advanced functionalities and usability of Web 2 (2005-2020), made possible by blockchain technology.
An easy to understand example of a Web3 application is Stepn.
Stepn is an application that tracks your steps when you walk, trajectory, and calories, one like many that exist in Web2. But the difference is that, in exchange for using Stepn (and thereby letting them access and monetize your data), you can earn tokens. You get paid in a sort of in-’game’ currency, if you will. You can choose to swap the tokens you earn for dollars, every day, getting rewarded as a user by receiving anywhere from $5 to $40 per day (at the peak), for your daily exercise. Or, you can also keep the tokens, and use them to vote in the governance of the project, somewhat like becoming a shareholder with a vote.
So you have the user-friendliness of a modern Web2 app, with the open-source, community aspect of the early days of the internet. On the blockchain, you can track how many tokens the Stepn team has allocated to itself, whether they are selling the tokens (they are..) or saving them, what changes are being made to the project roadmap, and how they were voted on. This explanation is a little simplified, but it is fundamentally correct.
It shows how Web3 projects don’t only reward their founders, but also its early adopters/users in general, in a structured way. It also underlines that governance is not only controlled by the founding team, but also in part by the community, in a transparent and traceable fashion. A semi-decentralized governance obviously also has downsides in terms of speed and efficiency, but as an example of what Web3 stands for, this is a reasonably good one, if you hadn’t heard of Web3 yet.
As I have hinted at in previous posts, I think improved fact-checking may be a perfect usecase for a ‘Web3’ (buzzword) project on the blockchain. When they invented Bitcoin and the blockchain, Satoshi didn’t only invent a transactional system. He also invented (a starting point for) a decentralized truth or shared reality. Russians and Ukrainians, Israelis and Palestinians, Chinese and Taiwanese can argue about many things, but not about how many Bitcoin are held by an address on the blockchain. This may sound really trivial, but it is quite a powerful concept if you let it sink in. The first decentralized truth. When taken to its logical outcome, it can have far-reaching consequences if utilized appropriately. It can’t solve disagreements, but it can technologically support the beginning of a model of truth that doesn’t need to be believed by appealing to authority, but can be verified by everyone that would like to do so, thereby creating a decentralized way of checking facts. Solid read:
TL;DR, we can start to imagine a Uber-like rating system, in which the news source, the fact checker, and the reviewer all receive a rating, to increase overall reliability of all three elements of a sustainable verification system.
I’m just spitballing, but I think a good way to start thinking about what this could look like, is to start at the best-expected outcome and then work our way back from there to specify the reviewing system's parameters (and close most back doors of possible manipulation). The outcome should be very simple: a news source would have a 'reliability score'. If for example they have posted 100 articles over the years and it turns out that 70 of them have been proven truthful, 25 have yet to become verifiable and 5 turned out to be completely wrong, that should reflect in a careful positive and easily visible reputation 'score'. The more articles are posted, per topic, and the more time has passed allowing the content to be proven reliable, false, or unverifiable, the more the scoring can be weighed accordingly. The title of expert is not earned once, but continuously. A Uber driver is rated for every trip as a control mechanism, and I believe news sources should be as well. They are much more important for society as a whole.
It could for example look like a market mechanism for accountability, reputation, and conviction. Categories of content can be fact, grey zone, prediction, opinion, or current public narrative. Rules can be put on the blockchain. Fact checkers can remain pseudonymous but accountable thanks to track changes and, over time, a hit-rate that can be reviewed. Same for the reviewers, that should potentially get rewarded somehow for their accuracy, even if it would just be by earning battle-tested credibility and status. The identity of participants can potentially remain hidden, but reputation and historical track record can be shown. I believe this is a game changer.
For the sake of the discussion, in my opinion, Twitter is the ideal platform to run a trial like this, because 1) all three groups of participants are already on the platform 2) from their founder Jack Dorsey until now, Twitter has some crypto-implementations already in place and are open to more 3) Elon Musk, but also the current board, have said that authentication to stop misinformation is an important step, but that it does not necessarily need to mean that one cannot hide their identity if they want to (NFTs could actually work). This seems like the perfect combination to run a rating system with three groups.
On-chain fact-checking can also be more accessible for voices from overseas, and unbiased experts in their respective fields. It would be easier to get tangible input from a Cambodian Nutrition expert, or whatever floats your boat. This new-found accountability and skin in the game for those that perhaps often get it wrong can help protect society against group think, and most certainly avoid people being censored about things that later turn out to be true. The ‘is this hindsight or suppressed foresight’ issue that sometimes censors people who did in fact predict the ‘new insight’ without hindsight could elegantly be solved, as both sides of any debate about what consensus is would be tracked and reviewed over time.
Some best practices from the (very interesting, check out the dashboard) Good Judgment organization, launched by IARPA – a part of the US intelligence community - in 2011, focused on cutting-edge methods of tracking, adjusting and reviewing forecasts could be implemented. For what it’s worth, anyone can join their initiative and the forecasts made by people that actively hone their forecasting skills become increasingly valuable and accurate.
I didn’t want to write a very long post so here is the continuation. Although I don’t know if that’s any better:)