Kicking off month two of the Co.Lab Fellowship, if I had to sum it up in a word, it'd be "overwhelmed." But not in a bad way. It's just that it's been no small feat to dive deep into my research and try to sift through the mountain of information, categorize it, and then explain it in plain English.

For context, I’m building TrustLevel here, working on reputation protocols that aim to ensure reliability of information and contributions. This grant specifically has me zooming in on how trustworthy reviews of proposals can make or break the funding success of decentralized innovation funds.

In this second article, I'll zoom out to the core reasons information often falls short in the digital and decentralized worlds.

And hey, if you skipped my first article, no stress—catch up here:

Innovating Trust in Web3: Pioneering the Future of Decentralized Fundraising

Two key learnings that bring subtle but decisive change

Since I already had a solution in mind for developing a reputation system to improve the reliability of information, my fellowship adventure started with finding my niche in a field full of opportunities and use cases.

And during the first month two major things happened:

1. I identified ‘Decentralized Innovation Funds’ as an ideal entry market where I could find everything I needed to implement a reputation system:
   • Active Communities: It is their activities that make it possible to build reputation in the first place, and in return they can benefit from such a system.
   • Rich Data: Uncountable community contributions and interactions generate rich data sets that form the basis to build a reputation system and make it possible to test with real data whether or not the system is able to identify people with high-quality contributions.
   • Easier Metrics: Depending on the use case, the metrics for a good reputation are more or less difficult to measure. With clearly defined proposal outcomes, this is much easier than validating the reliability of news sources, for example.
   • Strong Need: The strong need for a solution to improve the decision-making processes for voters (especially in very open systems with almost no entry barriers for proposers, reviewers and voters).
   • Market Entry: I already have active projects and partners in that field which should make it easier to enter the market.
2. I have come to the realization that the term reputation is associated with too many different concepts. Also, my pitch 'Reputation system for reliable information' is too abstract and therefore needs additional explanation. As a result, I then decided to look at the big picture with the many potential use cases and look for common patterns to determine what kind of information is not reliable and how a reputation system can improve this. You can find out how that turned out at the end…

Redrawing the Map - The Context Revisited

So what exactly do we mean when we talk about "information" in these different digital domains? It can be broadly defined as any content that helps to form a perception about a particular thing and to make a decision or take an action about it. In short, any kind of presentation on a subject (be it project, research, news, product, person or work). In short, any kind of presentation on a subject, be it a idea, project, research, news, product or person.

Let's take a quick look at few different industries and what kind of unreliable information we are dealing with and what impact it has:

• Innovation Funding: Especially in a decentralized environment, unreliable evaluations of proposals can lead to a misallocation of resources and thus stifle the very innovation they are supposed to promote. The same applies to the assessment of project outcomes. Without this, the impact and therefore the effectiveness of the funding allocations remain unclear.
• Academic Research: The peer review process is essential to ensure the reliability of published work. However, biased peer reviews and often non-transparent review processes jeopardize the foundation of scientific work, as studies cannot be independently verified, leading to the dissemination of unreliable or erroneous research results.
• News Media: The reliability of news and reports is under constant threat from misinformation, biased reporting, and sensationalism, fueled by the race to attract viewers which undermines public trust and the fundamental role of journalism in democracy.
• E-commerce: Fake reviews and dubious sellers undermine consumer trust.
• DeFi: Unreliable assessments of borrowers and lending protocols can cause lenders to lose significant investments or prevent new borrowers from entering the sector.
• DAO Governance: In the unique ecosystem of DAOs, where governance is decentralized and decisions are made collectively based on voting, the accuracy and credibility of information is critical. Misleading data or flawed verification processes can skew voting results, distort the evaluation of proposals and inaccurately represent members' contributions.