Business

92% of Executives Still See AI as Risky. Could Blockchain Be the Answer?

Dan Nicholson

AI’s rapid evolution has been fraught with ethical questions, but blockchain may hold the answer to some of these. From eliminating AI bias to building transparency and accountability, blockchain has the potential to address many of the stumbling blocks in AI’s development. A synergistic relationship between the two technologies could determine how we address some of the most pressing challenges in AI. 

AI’s Trust Issue

AI is poised to reshape the business landscape in the coming years, but there are still major issues to iron out. According to the 2023 KPMG Generative AI Survey, 71% of companies plan to implement their first generative AI solution within two years. Yet, 92% of leaders surveyed think generative AI implementation is a moderate- to high-risk endeavor. This points to the urgent need for solutions to AI’s trust problems.

Generative and predictive AI models like ChatGPT and DALL-E have shown immense potential in a wide variety of applications. However, AI's decision-making process, often perceived as a "black box," raises concerns about bias, ethical use, and intellectual property (IP) rights. 

Crypto.com explains: “The complexity of the AI decision-making process is often not transparent. Complex machine learning models in AI, such as deep neural networks, are often black boxes.” This is what leads generative models to produce biased answers or infringe on IP rights.

Enhancing AI Transparency and Accountability

Some solutions may be found in blockchain technology, known for its foundational role in cryptocurrencies. Its core features—immutability, decentralized data storage, and transparent digital records—can provide a much-needed layer of clarity and trustworthiness to AI operations. Here’s how:

1. Immutable Record for AI Decision-Making: By recording the data and processes used in AI models on a blockchain, companies can create a tamper-proof audit trail. This not only enhances the explainability of AI decisions but also bolsters trust among users and stakeholders. For instance, blockchain's role in tracking AI's training data can shed light on the sources and nature of the data, addressing concerns around data integrity and bias.

2. Decentralization for Data Security and Integrity: Blockchain's decentralized nature can transform how AI models are stored and distributed. This setup not only ensures data security but also promotes a more accountable and transparent decision-making process. The decentralized storage of data on blockchains can act as an audit trail, showcasing how data is being used and mitigating risks of centralized control and manipulation.

3. Legal and IP Protection: In the context of generative AI, blockchain can safeguard intellectual property rights. By storing and tagging IP on a blockchain, companies can significantly reduce the risk of IP infringement. Furthermore, transforming IP into non-fungible tokens (NFTs) with embedded smart contracts enables precise management of usage rights and royalty payments.

Real-World Applications

The integration of blockchain and AI is not just theoretical but is finding practical applications across industries. Sheila Warren, CEO of the Crypto Council for Innovation, stated in a CNBC panel discussion, “I do think that the verification of AI and the checks and balances within AI systems are going to be blockchain driven and blockchain-backed.”

Casper Labs and IBM are currently developing blockchain-based tools for AI governance. These tools offer “version control” for AI models, allowing businesses to revert to earlier versions if biases or inaccuracies are detected. This application underscores blockchain's potential to provide a responsible framework for AI deployment, addressing both ethical concerns and operational challenges.

Other tech companies like FICO are exploring blockchain to track the construction and training of AI algorithms. This approach promises better records management and a higher degree of confidence in AI outputs, according to FICO’s chief analytics officer, Scott Zoldi. “We find that the blockchain can break things down into bite-sized little mini-contracts,” he explained to the Wall Street Journal. “There’s a level of transparency and honesty in having that immutability.”

Conclusion

Blockchain technology is emerging as a powerful ally in addressing some of AI's most significant challenges, particularly in terms of transparency, data integrity, and IP protection. As companies navigate the complexities of AI deployment, blockchain offers a path to more ethical, accountable, and trustworthy AI systems. The potential for blockchain to revolutionize AI is immense, but realizing this potential will require collaborative efforts, innovative thinking, and a commitment to responsible technology deployment.

Sources

2023 KPMG Generative AI Survey

Crypto.com

CNBC

IBM

Wall Street Journal

Dan Nicholson is the author of “Rigging the Game: How to Achieve Financial Certainty, Navigate Risk and Make Money on Your Own Terms,” deemed a best-seller by USA Today and The Wall Street Journal. In addition to founding the award-winning accounting and financial consulting firm Nth Degree CPAs, Dan has created and run multiple small businesses, including Certainty U and the Certified Certainty Advisor program.

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