Can blockchain truly enhance trust in AI through ‘moral responsibility’?

Experts are still divided on the real impact blockchain tech can have on solving some of the problems that ail AI. Here are the most important things to know about this topic:

1. Blockchain can improve data privacy and security in AI: One of the main challenges in AI is ensuring the privacy and security of sensitive data. Blockchain technology offers a decentralized and secure way to store and share data, which could help address this issue. However, some experts argue that blockchain’s complexity and high energy consumption may limit its practicality for AI applications.

2. Blockchain can enhance transparency and accountability in AI: Another challenge in AI is ensuring that algorithms are fair, unbiased, and accountable. Blockchain technology can provide a transparent and immutable record of how data is collected, processed, and used in AI systems. This could help prevent algorithmic bias and increase trust in AI. However, some experts caution that blockchain’s transparency may not always be desirable or feasible, especially in sensitive or confidential applications.

3. Blockchain can enable decentralized AI networks: A promising application of blockchain in AI is the creation of decentralized networks of AI agents that can collaborate and learn from each other without relying on a central authority. This could lead to more robust and scalable AI systems that are less vulnerable to single points of failure or malicious attacks. However, some experts argue that the technical and governance challenges of building such networks are still significant and require further research.

In summary, while blockchain technology holds great potential for addressing some of the problems that ail AI, experts are still divided on its real impact. Further research and experimentation are needed to fully understand the benefits and limitations of blockchain in AI applications.