Exploring the synergy between AI and Blockchain for transparency and trust in data governance | Jon Derbyster
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Blockchain’s potential to increase accountability and transparency in AI decision-making
Artificial intelligence (AI) has the ability to quickly process large amounts of input and simulate human reasoning, but the decisions are often not transparent. This lack of transparency has become a challenge for AI, as it can lead to trust and ethical issues.
Blockchain technology, with its key features such as immutable digital records and decentralized data storage, can potentially help provide insight into a typically centralized and opaque AI, and provide trust, privacy and accountability to AI.
The challenge of accountability is one of the main problems facing AI today. It affects the confidence people have in the results.
To trust AI, its algorithms must be explainable. Blockchain’s immutable digital record can help better understand the framework behind AI and the source of the data it uses, solving the challenge of explainable AI.
This can improve confidence in AI’s data integrity and, by extension, in the recommendations that AI makes.
Also, blockchain’s decentralized data storage can act as an audit trail to show users how their data is being used by companies and other centralized organizations.
If AI models are stored and distributed on blockchains, their decisions can become more decentralized, accountable and transparent.
Blockchain can also help AI expand by providing access to an organization’s internal and external data, allowing for more actionable insights, better management of data consumption, and model sharing. This can create a more reliable and transparent data market.
The synergy between AI and Blockchain: Improving business processes and improving efficiency
The combination of AI and blockchain can add value to business processes involving multiple parties by reducing the need for human intervention.
Blockchain technology can remove potentially unnecessary third parties from multi-party transactions, which in theory can accelerate transaction speed and increase efficiency across transactions.
Reducing friction between transactions can empower individuals to own their data, while blockchain ensures the security of the transaction process.
AI can also bring benefits to blockchains. For example, AI can improve the intelligence of blockchain-based business networks and give them a competitive advantage, as it can quickly and comprehensively read, analyze and find links between data.
AI models incorporated into smart contracts implemented on a blockchain can suggest expired products to recall and perform transactions such as reorders, payments or item purchases based on predetermined thresholds and events.
Furthermore, AI algorithms can potentially help detect fraudulent activity on the blockchain.
There are many examples of how blockchain and AI can potentially work together in various industries such as healthcare, life sciences, financial services and supply chain.
For example, in healthcare, blockchain and AI can be used to track clinical trials, manage patient records and develop personalized treatments.
In conclusion, while AI can simulate human reasoning and quickly respond to large amounts of input, the lack of transparency can lead to trust and ethical issues.
However, blockchain’s key features, such as immutable digital records and decentralized data storage, can provide insight into typically centralized and opaque AI, bringing trust, privacy and accountability to AI.
AI and blockchain can work together to further scale and automate transaction evaluation processes.
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