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Establishing Trust in AI with Scott Zoldi at the London Blockchain Conference

Scott Zoldi is Chief Analytics Officer at FICO, so he knows a thing or two about AI. At the London Blockchain Conference 2024, he gave a keynote speech about why it’s imperative to establish trust and governance in AI.

FICO monitors about two thirds of the world’s payment card transactions for fraud on a continuous basis, and it’s also involved in credit scoring. Therefore, FICO’s AI has a huge impact on people, and Zoldi takes the responsibility that comes with this extremely seriously. As a result, he and his team have been focused on responsible AI, not tolerating the flaws seen in many generative AI models today.

Looking at some stats, Zoldi explained that 61% of people are wary of trusting AI, and 73% perceive it to have very significant risks. Clearly, people have trust issues around the technology, and Zoldi is working to change that by building transparent models.

The 4 Pillars of Responsible AI

Part of the solution is standards, but the industry does not have them. Few can even define responsible AI, let alone what it should look like.

Zoldi used the analogy of four pillars when talking about responsible AI: robust, interpretable, ethical, and auditable AI.

Robustness involves testing AI models in every way possible, making sure they are secure and robust.

Interpretable AI is about transparency. It’s about making it obvious what the relationships between decisions are and how they are made.

Ethical AI is about data. All data is biased, Zoldi says, and this can lead to unfair outcomes. However, the biases aren’t always obvious, so developers need to test and figure them out.

Auditability provides a source of truth: what decisions were made, who made them, and how can we create accountability? This is a relatively new concept in AI, but it’s an important one for building trust.

In order to come up with standards, everyone needs to get around the table: legal, business, customer service, and others. Right now, 43% of stakeholders say they don’t know how to meet regulatory requirements. Interestingly, another emerging technology can help…

The Role of the Blockchain

Creating responsible AI is the perfect application for blockchain technology, Zoldi told the London Blockchain Conference attendees. Blockchain allows developers to enforce criteria like model expectations and success metrics. These will be decided up-front, leaving no room to wiggle out of them later.

Having an immutable record of every decision that got made is the key. The records can be public or private, and while FICO’s are private, Zoldi assured the audience he can open the records to anyone who needs to see them, e.g., regulators. Everyone makes mistakes, but being able to reflect on and correct them is what creates trust, he explained.

The second element in creating trust is “humans in the loop.” This means people are involved at every step in creating, testing, and verifying the models. Each model will have its own blockchain, creating accountability and integrity through transparency.

These aren’t just pie in the sky ideas, either. Zoldi and his team have been using the Hyperledger Fabric blockchain for eight years now. He gave a detailed breakdown of how each step in the model creation process is recorded on the blockchain.

“This is the killer app,” he finished. There is a trust issue with AI, it’s justified, and blockchain technology plays a key role in fixing it. Scott Zoldi and his team are showing us how it can be done.

A Heavyweight Endorsement of Blockchain Technology

Critics of blockchain tech often claim it is a solution in search of a problem. Clearly, one of the world’s top data analytics experts disagrees. Blockchain isn’t just a hypothetical solution for one of the biggest problems facing humanity: it’s actively being used to solve it.

With use cases like this being promoted by heavyweights like Scott Zoldi, perhaps the world will begin to wake up to the reality of what blockchain technology is: a distributed, immutable ledger which can be used to prove anything, and which can create hitherto unforeseen levels of transparency in AI and endless other industries.

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