Proposes risk management for artificial intelligence in organizations

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The authors point out that the use of artificial intelligence algorithms by organizations requires an update of reference models for risk management to ensure reliable, fair and responsible systems.

The adoption of artificial intelligence by organizations can generate unpredictable impacts, such as discrimination, according to an article by researchers from the São Paulo School of Business Administration (FGV EAESP) Carlos Eduardo Brandão and João Luiz Becker, published in the magazine “GV Executivo”.

Therefore, ethical principles such as responsibility, with the implementation of audit mechanisms, transparency about the capabilities and limitations of systems vp quality email database and ethics, based on supervision and human intervention, are fundamental principles for dealing with this technology.

The research works with a systematic review of 173 scientific papers on the subject, accessed in databases such as Web of Science and Scopus. Based on the literature, the authors point out that the use of artificial intelligence algorithms by organizations requires an update of reference models for risk management to ensure reliable, fair and responsible systems.

Artificial intelligence consists of adapting technological resources and functions to interactions with humans to respond more and more accurately to user demands, the article explains. However, high levels of automation contribute to increased risks, such as the reproduction of biases and discriminatory practices caused by failures in facial recognition of criminal suspects, accidents caused by vehicles with autonomous driving systems, and interference in human learning processes.

The risk management process proposed by the authors is cyclical and aligned with the objectives of artificial intelligence in organizations. It includes measures such as identifying, categorizing, and evaluating mapped risks, considering the possibility of a risk event occurring in the organization. The impacts must then be recorded and communicated to stakeholders and regulatory bodies, with mitigation efforts and constant monitoring of results.