The technological ethics of AI

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Impartiality, bias, and ethics in machine learning are topics of interest among researchers and practitioners alike. As the technical barrier to entry for building and implementing systems in the artificial intelligence generation has dropped significantly, the ethical issues surrounding AI have become more apparent to the general public. Startups and large companies are rushing to implement and release generative models. The technology is no longer controlled by a small group of actors.

The AI ​​Index report highlights the tension between raw model performance and ethical issues, as well as new metrics that quantify bias in multimodel models.

Industry is ahead of education
Until 2014, the most notable machine learning models were published by academia. Since then, belarus rcs data industry has taken over. In 2022, there were 32 notable machine learning models from the industry sector, compared to just three from academia. Building cutting-edge artificial intelligence systems requires increasingly large amounts of data, processing, and money. All resources that industry players naturally have in greater quantities than non-profit organizations and academic institutions.

The number of incidents involving the misuse of AI is increasing.
According to the AIAAIC database , which tracks incidents related to the ethical misuse of AI, the number of AI incidents and controversies has increased 26-fold since 2012. Some notable incidents in 2022 include a deepfake video of Ukrainian President Volodymyr Zelensky surrendering. This growth is evidence of both the increased use of artificial intelligence technology and awareness of the possibility of improper use.