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IBM Turns to Blockchain To Solve Some of AI's Thorniest Problems
In this episode of the Blockchain Journal podcast, Blockchain Journal editor-in-chief David Berlind interviews Shyam Nagarajan, a global partner with IBM Consulting whose focus is Blockchain and Responsible AI (Artificial Intelligence). Naturally, Nagarajan had a lot to say about the explosive growth of AI, the increasing importance of trusted data in training AI models, and the role that blockchain is uniquely qualified to play when it comes to the responsible, fair, and transparent deployment and governance of AI in the enterprise.
David and Shyam explore the role of blockchain in ensuring data authenticity and provenance in the so-called "supply chain of AI models." But until actual management consoles and applications are put into business decision-makers' hands, the conversation borders on the theoretical instead of the practical. But IBM is looking to change that with some new application layer governance offerings that sit on top of blockchain with an eye towards ease of access and control. But overall, the conversation highlights the value of blockchain in addressing the challenges and risks associated with AI.
Key Takeaways
* The value of blockchain in the world of AI lies in its ability to ensure the trustworthiness and provenance of the data that AI relies on.
* Blockchain can be used to verify the authenticity and integrity of data used to train AI models, reducing the risks associated with data bias and tampering.
* An AI-imbued application layer on top of blockchain can provide additional functionality and governance for ease of AI model and data management as well as third-party auditing.
* Education and awareness about AI governance are crucial for organizations to implement responsible AI practices effectively. Today, the need for AI governance is under-appreciated, and it's unclear who within the enterprise should assume the responsibility. This "don't look at me" attitude is delaying the enterprise AI governance conversation while the effects of shadow IT, where unchecked departmental AI deployments start to take root, could become irreversible at the pace things are heading.
To watch the video version of this podcast or read its full-text transcript, go to:
https://blockchainjournal.com/interview/ibm-turns-blockchain-solve-some-ais-thorniest-problems
The video can also be watched on Blockchain Journal's YouTube Channel at https://www.youtube.com/watch?v=Xwc2pkZ3_FI
View all episodes
By Blockchain JournalIn this episode of the Blockchain Journal podcast, Blockchain Journal editor-in-chief David Berlind interviews Shyam Nagarajan, a global partner with IBM Consulting whose focus is Blockchain and Responsible AI (Artificial Intelligence). Naturally, Nagarajan had a lot to say about the explosive growth of AI, the increasing importance of trusted data in training AI models, and the role that blockchain is uniquely qualified to play when it comes to the responsible, fair, and transparent deployment and governance of AI in the enterprise.
David and Shyam explore the role of blockchain in ensuring data authenticity and provenance in the so-called "supply chain of AI models." But until actual management consoles and applications are put into business decision-makers' hands, the conversation borders on the theoretical instead of the practical. But IBM is looking to change that with some new application layer governance offerings that sit on top of blockchain with an eye towards ease of access and control. But overall, the conversation highlights the value of blockchain in addressing the challenges and risks associated with AI.
Key Takeaways
* The value of blockchain in the world of AI lies in its ability to ensure the trustworthiness and provenance of the data that AI relies on.
* Blockchain can be used to verify the authenticity and integrity of data used to train AI models, reducing the risks associated with data bias and tampering.
* An AI-imbued application layer on top of blockchain can provide additional functionality and governance for ease of AI model and data management as well as third-party auditing.
* Education and awareness about AI governance are crucial for organizations to implement responsible AI practices effectively. Today, the need for AI governance is under-appreciated, and it's unclear who within the enterprise should assume the responsibility. This "don't look at me" attitude is delaying the enterprise AI governance conversation while the effects of shadow IT, where unchecked departmental AI deployments start to take root, could become irreversible at the pace things are heading.
To watch the video version of this podcast or read its full-text transcript, go to:
https://blockchainjournal.com/interview/ibm-turns-blockchain-solve-some-ais-thorniest-problems
The video can also be watched on Blockchain Journal's YouTube Channel at https://www.youtube.com/watch?v=Xwc2pkZ3_FI