AI is one of the most exclusive trends in the modern technology world. But in most cases, businesses aren’t able to implement more explainable AI apps. The growing demand and use of the AI and blockchain in business-critical scenarios are leading companies to think about trust issues. This situation appears more frequently when AI /ML applications are seen legging in making several decisions.
There are certain problems with AI / ML applications, such as:
- Often time, AI / ML applications fail at natural language processing and understating it. It has been one of the biggest challenges so far.
- Machine understanding an image has been solved to some extent. By categorizing images, machines can learn what an image is all about. But AI and ML systems aren’t very successful at understanding what actually is going on in an image.
- The GANs (Generative Adversarial Networks) are certainly the biggest invention so far, but it has still to be figured out that how to stably train GANs.
And there are tens of other issues which are still to be resolved.
There are several situations in which humans are trusting machines to make decisions. Wrongly taken decisions can put lives at risk or can have potentially harmful outcomes. Although the decision-making capabilities of AI/ML systems are becoming unquestionably opaque, the blend of blockchain and AI can make machine learning systems further interpretable.
Here Are Some Use Cases:
- The National Institution for Transforming India, also known as NITI Ayog, is working on a strategy paper for applications of AI and blockchain in India. It will outline the use cases that how AI, Machine Learning, and Blockchain can be implemented.
- Blockchain has emerged from Bitcoin. Dexter Hadley, a physician and computational biologist at the University of California, San Francisco, has the thought of using this Bitcoin technology and AI to share medical data. For example, the blend could do far better jobs at detecting breast cancer in women than doctors.
- The merger of AI, Blockchain, and other technologies like AR can bring in interesting transformation in the real estate industry. This merger will help in creating virtual assistants that will provide the best fit property options to clients along with automating marketing. It will also provide image-based property valuation and searches, and hyper-local content curation. With several others, Blockchain can help in improving property records, decreasing the cost for all parties, and trimming down risks in real estate transactions.
- Where, there is need of the infallible decision-making capability, the blend of AI/ML, and blockchain can really create the most reliable solutions.
- Blockchain can make AI/ML systems tamper-proof and regulate them. The blockchain is essentially a distributed system in which nodes aren’t fail-safe, but AI is able to find out patterns and then predict final outcomes. The blend will help blockchain to distribute the data that a blockchain really needs to hold.
- Blockchain can also provide an instrument for the regulation of autonomous AI entities, according to CoinTelegraphi.com
- Blockchain works fine for its transactional and bookkeeping advantages, according to SingularityNET, which is a decentralized protocol for accessing a network of Artificial Intelligence algorithms and agents.
Three major advantages of blending AI and Blockchain
AI and blockchain encrypted can work well together
AI has plenty to implement in terms of security. Building an AI system with algorithms working in an encrypted state is still a big challenge for AI and machine learning application developers. A part of the process that involves unencrypted data may present several security risks, but blockchain databases hold information in an encrypted form only. An AI or ML system based on the blend of Blockchain uses data which are kept safe with private keys.
AIs’ decision can be tracked, understood and explained by blockchain.
Many decisions made by AIs can be sometimes hard for humans to understand. Now decisions can be recorded on a blockchain, on the basis of data-point-by-data-point; they can easily be audited with the assurance that no one tempered records.
AI can help in managing blockchain more efficiently than humans.
Traditional computers cannot get things done without explicit instructions on how they have to perform a task. When the blockchain data, which is encrypted by nature, is operated on traditional computers then they require a large amount of process power. When blending AI with Blockchain, the task can be performed intelligently and thoughtfully as AI can organize the entire processing more efficiently.