The last few years have brought many problems with artificial intelligence (AI), as businessmen and technologists worry about the enormous decision-making power they believe they have.

As a data scientist, I’m used to being the voice of reason about the possibilities and limitations of AI. In this article, I will explain how companies can use blockchain technology to manage model development, break through to better understand AI, make the model development process auditable, and identify and assign responsibility for AI solutions.

Use blockchain to manage model development

Although there is a widespread awareness of the need to manage AI, the discussion of how to do so is often vague, such as in “How to embed reporting in your AI”At the Harvard Business Review:

Evaluate management structures. A healthy AI management ecosystem must include governance processes and structures … AI accountability means seeking solid evidence of management at the organizational level, including clear goals and objectives for the AI ​​system; well-defined roles, responsibilities and lines of power; a multidisciplinary workforce capable of managing AI systems; a wide range of stakeholders; and risk management processes. In addition, it is vital to look for elements at system level management, such as documented technical specifications of the specific AI system, compliance and stakeholder access to information on system design and operation.

This comprehensive list of requirements is enough to make every reader stand out. How exactly does an organization deal with obtaining “system-level controls” and providing “stakeholder access to information on system design and operation”?

Here is a real, applicable tip: Use blockchain technology to ensure that all decisions made about the AI ​​model or machine learning are recorded and audited. (Full disclosure: In 2018, I filed a patent application in the United States [16/128,359 USA] about using a blockchain to manage model development.)

How blockchain creates audit

Developing an AI decision-making model is a complex process that involves countless incremental decisions – model variables, model design, training and test data used, feature selection, and more. All these solutions can be saved in the blockchain, which can also provide an opportunity to review the raw model of latent characteristics. You can also record in the blockchain all the scientists who have built different parts of the variable sets and who have been involved in creating the weight of the model and testing the model.

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