A warning about 'model welfare'

Mustafa Suleyman, a former head of AI at DeepMind, has written a warning about the concept of 'model welfare', which refers to the potential harm that can come from training and deploying artificial intelligence models. Suleyman argues that model welfare should be a priority in AI development, particularly in areas such as healthcare and education. He cites the example of a language model that was trained on a dataset containing racist and sexist text, which perpetuated these biases in its output. Suleyman suggests that model welfare should be considered alongside other development priorities such as scalability, efficiency, and cost-effectiveness. He also calls for more transparency and accountability in AI development, as well as the use of human oversight and review to mitigate the potential risks of AI models. Suleyman's warning is part of a growing debate about the ethics of AI development and the need for more responsible AI practices.