The popularity of Artificial intelligence (AI) technology is gaining steam with its widespread adoption across various industry verticals. Companies are implementing AI to improve the efficiency of their processes and applications. However, of late AI solutions have hit some roadblocks which have hindered the development and adoption of the technology. Blockchain technology can be the game changer in addressing many of the issues that are holding back AI adoption.
Acknowledging the issues of AI technology is the first step towards mitigating the blockades. For instance, the AI chatbot of Microsoft, Tay, failed miserably as it turned racist almost immediately after its release. Another example of AI failure is the crash of the autonomous car of Tesla that could not recognize a parked fire truck in its way. Blockchain technology can help AI developers to overcome many of these challenges. The technology offers an immutable, distributed, and decentralized digital ledger that can help to prevent any corruption in AI chatbots. Blockchain ledger can also unlock collaborative AI innovation that can eliminate any failures like the Tesla fire truck blind spot incident.
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Most AI solution leverage variants on deep learning algorithms that learn how to recognize, categorize, and respond to inputs by ingesting training data. For instance, the AI-enabled facial recognition program learns to recognize faces by analyzing millions of images that contain face and some without a face. The solution then develops its own set of basis to distinguish between pictures with face and photographs without a face. The training data helps the AI programs to grade its results and repeat the process until it gains reliable competence.
The chatbot Tay failed because it used conversations with real, online users as the training data, and some users intentionally corrupted its data. Blockchain technology can prevent the corruption of training data as it can keep the record of the core algorithms that are developed to train a set of data. Blockchain eliminates the use of middleman and provides a high degree of transparency that can encourage AI developers to share their data without the fear of data corruption or data stealing.
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