Geoffrey Hinton, a pioneer in artificial intelligence and a longtime leader in Google’s AI research, has made the decision to resign from his position at the tech giant due to ethical considerations. Hinton, who is seen as the “Godfather of AI” for his major contributions to deep learning and neural networks, said his reason for leaving is to better express the potential risks and damages of AI, especially with the race to apply more powerful and sophisticated models.
Just last month, over 1,000 AI professionals signed an open letter calling for a moratorium on the training of AI systems more powerful than GPT-4, a model developed by OpenAI. The letter warned of the “profound risks to society and humanity” posed by AI systems with capabilities that rival humans.
Hinton’s resignation reflects the increasing rift between AI scholars and their employers, including the termination of two co-leaders from the Google’s Ethical AI team. Timnit Gebru and Margaret Mitchell were fired after condensing on the side effects of large-scale models produced by Google, as well as the lack of diversity and transparency within the AI industry.
Hinton lately had a call with the CEO of Google’s parent company, Alphabet, Sundar Pichai, but the details of the discussion were not released to the public. He did however comment that he believes Google has acted accordingly and responsibly. This action is closely related to Pichai’s announcement of the merger of Google Brain and DeepMind, forming a new organization called Google DeepMind.
Google is one of the leading technology companies in the world, headquartered in Mountain View, California. Founded in 1998, the multinational organization has focused on using their advancements in both hardware and software to create services and products such as maps, email and document handling, online advertising services and a search engine.
Geoffrey Hinton is a British-Canadian computer scientist and cognitive psychologist, currently a professor emeritus at the University of Toronto and a Google Fellow. He has made fundamental contributions to the development of AI, most notably on deep learning and neural networks, and is one of the leading pioneers in the field. He has published numerous papers as well as several books, and has been awarded various accolades.