三度目の正直：分散型台帳技術（DLT）の新たな機会

The rise of generative AI (GenAI) has made it easier than ever to create fake assets and deep fakes. These can range from fake images and videos to fake audio recordings and even fake text.

The implications of this are far-reaching, as fake assets can be used to spread misinformation, manipulate public opinion, and even commit fraud. This is where the importance of provenance and transparency comes in.

Provenance refers to the origin and history of an asset, while transparency refers to the ability to trace and verify the authenticity of an asset. By ensuring that assets have a clear and verifiable provenance, and by making this information transparent and accessible, we can help to prevent the spread of fake assets and deep fakes.

The Importance of Provenance and Transparency

The importance of provenance and transparency cannot be overstated in today's digital age. With the rise of generative AI and the increasing prevalence of fake assets and deep fakes, it is more important than ever to ensure that digital assets have a clear and verifiable provenance and that this information is transparent and accessible.

The importance of provenance and transparency is becoming increasingly important in industries such as finance, insurance, and healthcare. In these industries, the authenticity and provenance of digital assets can have significant implications for regulatory compliance and legal liability. By ensuring that assets have a clear and verifiable provenance, and by making this information transparent and accessible, companies can help to mitigate these risks and ensure compliance with regulations.

Fake assets and deep fakes pose significant risks to individuals, organizations, and society as a whole. These risks include:

• Misinformation: Fake assets and deep fakes can be used to spread misinformation and manipulate public opinion. This can have significant implications for elections, public policy, and social issues.
• Fraud: Fake assets can be used to commit fraud, such as creating fake documents, videos, or receipts.
• Reputation Damage: Fake assets and deep fakes can damage the reputation of individuals and organizations, leading to a loss of trust and credibility.

Distributed Ledger Technology (DLT) Comes to the Rescue

This is where technology such as DLT can come in handy for companies and individuals to ensure that their digital assets are authentic and have a clear provenance. DLT is particularly well-suited for this use case, as it provides a tamper-proof record of the asset's origin and history. Once an asset is recorded on the blockchain, it cannot be altered or deleted (or if done, it can be easily verified), ensuring that the asset's provenance is clear and verifiable. Each block contains a hash (a digital fingerprint or unique identifier), timestamped batches of recent valid transactions, and the hash of the previous block. The previous block hash links the blocks together and prevents any block from being altered or a block being inserted between two existing blocks. This can help to prevent the spread of fake assets and deep fakes, as well as provide a way to verify the authenticity of assets in cases of fraud or other illegal activities.

Companies such as Truepic specialize in providing tools and services that help to ensure the provenance and transparency of digital assets. These companies use a combination of blockchain technology, machine learning, and other advanced technologies to capture and verify the authenticity of digital assets. Truepic's platform allows users to capture and verify the authenticity of photos and videos in real time. The platform uses blockchain technology to create a tamper-proof record of the asset's origin and history, ensuring that it has a clear and verifiable provenance. Machine learning algorithms are used to analyze the asset and detect any signs of manipulation or tampering. This video shows a good example of how this works.

Truepic offers specific solutions for insurance and financial services. Insurance companies often rely on photos and videos to assess claims, such as damage to a car or property. However, these assets can be easily manipulated or faked, leading to fraudulent claims. By using solutions such as the ones provided by Truepic's platform, insurance companies can ensure that the photos and videos submitted as part of a claim are authentic and have a clear provenance. This can help to prevent fraudulent claims and ensure that legitimate claims are processed quickly and accurately. Another use case for Truepic's platform in the insurance industry is in the area of risk assessment. Insurance companies can use the platform to capture and verify the authenticity of photos and videos of potential risks, such as a property that is being considered for insurance coverage. This can help to ensure that the insurance company has an accurate understanding of the risk and can price the policy accordingly.

From Indemnity to Loss Avoidance

Risk transfer continues to be an option, despite GenAI being a new and increasing risk. For example, Vouch is a company that specializes in risk transfer for tech companies and works with top AI companies to minimize emerging risks, including issues of privacy, IP, and bias. By offering well-known coverages such as D&O, E&O, and EPL, Vouch provides peace of mind to tech-based companies, including those specializing in AI.

While Vouch and other companies are introducing specific coverages to the market to address the risks of generative AI, there is also a case for Distributed Ledger Technology (DLT) to be adopted by insurer's clients to avoid the inherited risks of GenAI. Why focus only on transferring the risk and paying a claim if there are mechanisms to avoid the loss in the first place? Insurers might want to take a closer look (again) into DLT.

GenAI has paved the way for DLT to regain momentum. Will this time be the charm?