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A Call for Proactive Policies for Informatics and Artificial Intelligence Technologies

2021; RELX Group (Netherlands); Linguagem: Inglês

10.2139/ssrn.4000077

1556-5068

Jim Samuel,

Big Data and Business Intelligence

Artificial Intelligence (AI) presents a powerful paradigm shift opportunity to human society as no other technology-dimension has done in the history of the human race. The reason for this is evident: past scientific and technological revolutions replaced human muscle power and this increased the value of human intelligence. Thus, in spite of labor displacement, mass human capital remained relevant and vital. In the information age, computers helped create, store, process and share vast quantities of digitized information, and human intelligence began to be valued even more highly for its capabilities to manage computing meaningfully and profitably. However, the dawn of the AI technology dimension challenges the human identity as never before as AI has begun competing for the crown of superior "intelligence" with human entities. AI is on a winning trajectory in many of the battles with human intelligence, as has been seen in gaming through the sustained victories of AI agents over the best of human Chess and Go grandmasters. These AI technologies' powerful evolution, pervasive growth and ubiquitous opportunities present humanity with many risks and challenges, some of which we understand and others we have just begun to identify. In a simplified view, Artificial Intelligence is a set of technologies that mimic the functions and expressions of human intelligence, specifically cognition and logic and informatics is advanced technology driven big data analytics. (Samuel et al., 2021). The general sense is that we are yet to perceive the best and the worst impacts of the AI technology-dimension. The 2021 Stanford globalAI-100 report (Littman et al., 2021) states that few nations "have moved definitively to regulate AI specifically". The critical question then becomes, can governments and organizations continue to use the same post-hoc catch-up strategy that has been used for pre-AI technologies for effective governance of AI technologies and their applications?