For example, but not limited to:The decentralization aspect eliminates a single point of attack, increasing the resilience of AI models against breaches. The immutability of blockchain ensures that the data used in training AI models and the models themselves cannot be illicitly altered, maintaining the integrity of the models. Every alteration or decision made by the AI model can be audibly traced through blockchain, providing unparalleled transparency and accountability. Smart contracts automate the enforcement of data access and usage rules, preventing unauthorized or unethical use of AI models. Smart contracts can ensure that data is only used for training and testing and by authorized personnel, locking the option to be used for other purposes.
Incorporating rules via smart contracts enables users to have control over their autonomous workers/assistants, enabling a shutdown or even a “kill switch,” if necessary, when AI agents start behaving dangerously. If Goldman Sachs wants to create AI agents that think and act like a seasoned employee in a highly regulated industry and with imperative risk to financial systems and at the extreme financial markets’ stability, it would be vital, not optional, to have these AI agents controlled by programmable tokens.
These areas are where blockchain shines and can support AI weaknesses to facilitate the scaling and evolution of this vision. Blockchain strengths support AI weaknessesBlockchain technology can significantly bolster the security of AI models by leveraging its key features such as decentralization, immutability, traceability, smart contracts, data privacy and identity verification.
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Author / Journalist: Cointelegraph by Dr. Merav Ozair
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