Assessing and Balancing the Value of Artificial Intelligence Products in the Digital Age

Анотація

The digital age provides, on the one hand, extraordinary opportunities for modern information technologies, including artificial intelligence (AI) products; on the other hand, it creates new problems for humanity, for example, of a legal and ethical nature. In addition, AI products can be highly effective and attractive from a commercial point of view; and from the point of view of humanity as a whole, they can signify a huge problem. Thus, there is a need to balance the value of these products, taking into account their multiaspectual nature. The purpose of this study is to develop a conceptual approach to assessing and balancing the value of AI products. Balancing involves assessing the value of AI products, comparing it to some standards, and adjusting it based on the identified inconsistencies. It is found that balancing the value of AI products should take into account three areas of view and evaluation – individual, business, society (humanity). Such an integral view will provide coverage of the main levels that are affected by AI products. A method for assessing the value of AI products has been proposed, which takes into account the multiaspectual nature of product consideration for each area (individual, business, society) and the priority of each aspect. It is also proposed that in the future, it is artificial intelligence that should provide this assessment of the value of AI products, taking into account a significant amount of necessary information. A conceptual scheme has been formed that links the increase in the level of development of AI products with the level of their responsibility, especially for those products that are designed to evaluate and determine the necessary areas of harmonization and balancing of value. This will ensure the development and commercial use of AI products with risk minimization from various perspectives. It is evident that these results are only a conceptual approach, on the basis of which it is possible to develop specific algorithms for evaluating and balancing the value of AI products.

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