# Blockchain-Based Platform to Fight Disinformation Using Crowd Wisdom and Artificial Intelligence
## 2 Background  
### Fighting Disinformation  
In terms of fact-checking [6; 7], there are a couple of current approaches to fighting disinformation, each with its own drawbacks:  
1. Verification is performed by _Professional Fact Checkers_ with accurate results following a standardized methodology for fact checking. This approach is time consuming, has little impact (since it is conducted most of the time in the \"post-mortem\" phase of the misinformation spreading) and it is very difficult to scale.
2. Verification is performed by non-professional communities--_Crowdsourced Fact Checking_, leveraging \"cross wisdom\" with no supporting tools. This approach has good potential to scale, but it is prone to becoming partisan or to be detoured. The level of impact is still low due to the \"post-mortem\" nature of the analysis.
3. Verification is conducted by software tools that utilize statistical algorithms mimicking the critical thinking process--_Non-assisted Automated Verification_. This approach has huge scaling and impact potential, but it cannot achieve the same level of accuracy as 1 and 2.  
In the approaches mentioned above, the system must choose between scalability and accuracy. In any completely distributed system, consensus is considered one of the key properties when talking about a system that is considered reliable. The first blockchain has run on a public network since 2009 and opened the door to a new type of architecture, but at the same time, the technology offers just an infrastructure that must be combined with other techniques to offer solutions for today's problems.  
The approaches for blockchain-based solutions to address the challenges of online disinformation are:  
* _Verifying provenance._ This approach tracks and verifies the sources of online digital content. Examples of projects employing this approach are:
* New York Times' News Provenance Project ([[https://newsprovenanceproject.com](https://newsprovenanceproject.com)]([https://newsprovenanceproject.com](https://newsprovenanceproject.com)), accessed on 8 May 2023; [[https://www.nytimes.com/2020/07/06/insider/could-we-fight-misinformation-with-blockchain-technology.html](https://www.nytimes.com/2020/07/06/insider/could-we-fight-misinformation-with-blockchain-technology.html)]([https://www.nytimes.com/2020/07/06/insider/could-we-fight-misinformation-with-blockchain-technology.html](https://www.nytimes.com/2020/07/06/insider/could-we-fight-misinformation-with-blockchain-technology.html)), accessed on 8 May 2023)
* Truepic ([[https://truepic.com/](https://truepic.com/)]([https://truepic.com/](https://truepic.com/)), accessed on 8 May 2023) notarizes content on the Bitcoin and Ethereum blockchains to establish a chain of custody from capture to storage
* _Assessing identity and reputation._ Blockchain-based solutions can track and verify the reputation of content creators in a transparent and decentralized way, thus eliminating the need for a trusted and centralized institution. Smart contracts built on blockchain offer the necessary mechanisms to achieve these goals.
* _Incentivizing high quality content and content assessment._ The blockchain generated cryptocurrency can be used to reward/penalize the actors that are responsible with trust assessment of both content and content creators. The trust score will be reflected upon content creators which will be incentivized to create high quality content. Pressland ([[https://pressland.com/](https://pressland.com/)]([https://pressland.com/](https://pressland.com/)), accessed on 5 August 2022) is another example of a system that stores online data on blockchain after it was analyzed using machine learning algorithms.