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Provenance to Combat AI-Driven Misinformation

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Provenance to Combat AI-Driven Misinformation

In the last decade, our lives have moved more online by the day, which has in turn made misinformation a greater threat to both society and individuals. News media, traditionally seen as the fourth state, a reliable pillar of truth, now has found itself undermined by AI-driven misinformation.

This article looks at how integrity and trust can be returned to news media through the latest technology that ensures provenance. Drawing on insights from initiatives like the Taiwan election project, in which  Numbers Protocol utilized blockchain to provide transparent media records through the election period, the article will also explore the transformative potential of provenance in preserving the authenticity of news content. 

Understanding Digital Provenance in News Media 

Provenance refers to the history of ownership, custody, or location of a historical object.

Digital provenance can secure trust in news media by providing a transparent record of a story's origin, evolution, and ownership. In creating a verifiable trail of authenticity, provenance strengthens the credibility of news content and protects it from misinformation threats.

A provenance record for news content illuminates the source's identity and reputation, the nature and quality of the information, as well as the time, place, process, and purpose of its creation and distribution. This understanding enables news consumers to assess the reliability and validity of the content, empowering them to make decisions based on facts, not fiction.

Challenges Faced by News Media in the Age of AI-Driven Misinformation 

The spread of AI-driven misinformation has created formidable challenges to news media, eroding public trust and distorting the flow of information. This has been amplified on a nearly monthly basis by technological advancements in areas such as deep fakes. 

Examples of AI-driven misinformation include: 

  • Fake news: AI algorithms can generate coherent and plausible news articles that are entirely fabricated or based on false premises. These articles can be designed to influence public opinion, sway elections, or incite violence. 
  • Deepfakes: AI algorithms can create realistic videos or audio recordings that show or say things that never happened or were never said. These videos or audio recordings can be used to impersonate or defame public figures or to deceive or manipulate audiences. 
  • Manipulated content: AI algorithms can alter or edit existing content, such as photos, videos, or audio recordings, to change or remove certain details or elements. These alterations or edits can be used to misrepresent or distort the truth, or to create false impressions or associations. 

We have seen over the last few years how misinformation can polarize people, fuel social conflicts and divisions, and threaten the stability and security of democratic institutions. 


The Intersection of Provenance and AI in News Media 

How Provenance Can Be Harnessed to Combat Misinformation 

By leveraging provenance platforms like Numbers Protocol, news media can authenticate sources, track the lineage of information, and validate the accuracy of news stories. Numbers Protocol utilizes blockchain technology to preserve the provenance of digital media and ensure transparency and trust. 

Numbers Protocol's provenance platform, Capture, allows news media to upload their digital content and create Asset Contracts that store the provenance data on the blockchain. These Asset Contracts can be used to set up royalties or create License NFTs, which can be sold off in marketplaces, allowing news media to earn revenue from their digital content. Capture also makes it easy to track and manage the use of assets, providing a transparent record of the origin and ownership of digital content. 

By using Numbers Protocol's provenance platform, news media can benefit from the following advantages: 

  • Authentication: News media can verify the identity and reputation of the source, the nature and quality of the information, and the time and place of the creation and distribution of the digital content. This can help them to avoid or expose fake news, deepfakes, and manipulated content. 
  • Traceability: News media can track the lineage and history of the digital content, from its creation to its current state. This can help them to monitor and control the use and distribution of their digital content, and to prevent or detect unauthorized or malicious alterations or edits. 
  • Validation: News media can confirm the accuracy and validity of the digital content, by comparing it with other sources of information or evidence. This can help them to corroborate or refute the claims or assertions made by the digital content, and to provide factual and objective news stories. 

The Role of AI in Enhancing Provenance Solutions 

AI technologies play a dual role in the quest for media authenticity: they are both the perpetrators and the solution to AI-driven misinformation. While AI algorithms can generate deceptive content, they also empower provenance platforms to deploy sophisticated detection mechanisms for identifying and mitigating misinformation. 

AI technologies can enhance provenance solutions in the following ways: 

  • Detection: AI technologies can help provenance platforms to detect and flag fake news, deepfakes, and manipulated content, by using natural language processing, computer vision, or audio analysis techniques. These techniques can analyze the content and identify inconsistencies, anomalies, or discrepancies that indicate the presence of misinformation. 
  • Attribution: AI technologies can help provenance platforms to attribute and credit the source and creator of the digital content, by using digital watermarking, hashing, or fingerprinting techniques. These techniques can embed or extract unique identifiers or signatures that link the content to its provenance data. 
  • Verification: AI technologies can help provenance platforms to verify and cross-check the provenance data of the digital content, by using blockchain technology, smart contracts, or consensus algorithms. These technologies can store, secure, and validate the provenance data on a distributed ledger, ensuring its immutability and transparency. 


Case Studies: Provenance in Action  

The Numbers Protocol Taiwan Election Project   

The Taiwan election project was a collaborative effort between Numbers Protocol and leading Taiwanese news media outlets. The project aimed to document key historical moments of the 2024 Taiwanese presidential election, covering 66 days from candidate registration to issuing certificates to the elected president, vice president, and lawmakers. The goal was to ensure that every critical moment of this pivotal election was recorded accurately and authentically.  


The project involved the following steps:  

  • Capture: Starting November 20, 2023, as the presidential candidates began their registration, Numbers Protocol equipped its news media partners with blockchain tools and technology to help them collect and document election-related images. Each image collected was given a unique blockchain ID and securely stored using Starling Lab’s authentication technology.  
  • Verify: The public could verify the provenance of an image they stumbled upon on social media by using AI for verification. They could upload the image and initiate a search to see if the image has a blockchain registration. If the image wasn't registered, they could also browse through similar registered images.  
  • Publish: These images were continuously updated on the official project website in real-time and, following the election, were permanently archived on the Filecoin decentralized network. This strategy not only boosted digital resilience but also ensured that these crucial images remain accessible and unaffected by external factors in the future.  

By tracing the data lineage of media related to the Taiwan election, the project was successful in combating election integrity threats.


Future Directions: Advancing the Provenance Paradigm 

Emerging Trends and Innovations 

As the battle against AI-driven misinformation evolves, news media must adapt and innovate to stay ahead of the curve. Future developments in provenance technologies, coupled with AI advancements, hold the promise of creating more resilient defenses against misinformation. 

Some of the emerging trends and innovations in the provenance space include: 

  • New types of digital assets: Provenance technologies can enable the creation of new types of digital assets, such as fractional ownership NFTs, that allow multiple investors to own a fraction of a digital asset. This could make high-value digital assets more accessible to a wider audience, while also providing a new way for news media to monetize their digital content. 
  • New marketplaces and platforms: Provenance technologies can facilitate the emergence of new marketplaces and platforms that are built on blockchain technology, such as the type provided by Capture. These marketplaces allow news media to sell their digital content directly to consumers without the need for intermediaries. It can also provide a more transparent and fair system for pricing, licensing, and distributing digital content.

  • New forms of media consumption and interaction: Provenance technologies can enable the creation of new forms of media consumption and interaction, such as immersive virtual reality experiences, interactive storytelling, or AI collaborations. These forms of media consumption and interaction can enhance the engagement and enjoyment of news consumers, while also providing new opportunities for news media to showcase their digital content. 


Collaborative Efforts and Industry Partnerships 

Collaboration between news media organizations, technology firms, and regulatory bodies is vital, as in this way they can work together to fortify the resilience of news ecosystems against misinformation.

Some of the collaborative efforts and industry partnerships in the provenance space include: 

  • Standards and frameworks: Stakeholders can work together to develop and implement common standards and frameworks for provenance data, such as metadata schemas, data models, or protocols. These standards and frameworks can help to ensure the interoperability, compatibility, and consistency of provenance data across different platforms and devices.

  • Initiatives and projects: Stakeholders can collaborate on various initiatives and projects that aim to promote and demonstrate the value of provenance in news media, such as the Taiwan election project by Numbers Protocol, or the Content Authenticity Initiative by Adobe, Twitter, and The New York Times. These initiatives and projects can help to raise awareness and educate the public about the importance and benefits of provenance in news media.

  • Policies and regulations: Stakeholders can cooperate on developing and enforcing policies and regulations that support and incentivize the use of provenance in news media, such as laws, guidelines, or codes of conduct. These policies and regulations can help to create a conducive and conducive environment for provenance adoption and innovation, while also protecting the rights and interests of news media and news consumers.



The battle against AI-driven misinformation is a pressing issue in today's digital age. The integrity of news media, once considered the bastion of truth, is under threat. However, the use of provenance, particularly when combined with advanced technologies like AI and blockchain, presents a promising solution. 

Providing a transparent record of a story's origin, evolution, and ownership, can strengthen the credibility of news content and protect it from misinformation. This type of digital provenance empowers news consumers to evaluate the reliability and validity of news content, enabling them to make informed decisions based on facts rather than fiction. 

The successful implementation of provenance in the Taiwan election project by Numbers Protocol demonstrates the transformative potential of provenance in preserving the authenticity of news content. The project achieved transparency, trust, and truth, combating misinformation and fostering public trust. 

The Taiwan election project also demonstrated the importance of collaboration between media organizations, technology firms, and regulatory bodies if trust in the media is to be returned.

*This article is created with the help of our Ambassador and Professional Journalist we're partnering with.

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