Geoffrey Hinton is a renowned computer scientist and artificial intelligence researcher. Hinton is known for his contributions to the field of deep learning. Geoffrey Hinton took his education from Kings College, and in 1970 he graduated with a Bachelor of Arts in experimental psychology. Hinton got a Ph.D. in “artificial intelligence’ from the University of Edinburgh in 2001 under the mentorship of Christopher Longuet-Higgins. Longuet-Higgins has a named prize in his honour in the year 2005, ‘Fundamental Contributions in Computer Vision that Have Withstood the Test of Time’. Geoffrey Hinton’s research paper that earned him a Ph.D. in artificial intelligence was overlooked by Longuet-Higgins. In the same year, 2001, Hinton was also awarded the Rummelhart Prize. This prize is the equivalent of the Nobel Prize in the field of cognitive science.
Early life and careerDespite earning a Ph.D. in ‘Artificial Intelligence’, he faced some difficulties in getting funding for his research in Britain. Hinton conducted his postdoctoral studies at the University of Sussex, following which he took a fellowship at the Canadian Institute for Advanced Research and shifted to the department of computer science at the University of Toronto. From 1998 to 2001, Hinton is credited with setting up the ‘Gatsby Computational Neuroscience Unit” at the University College London. Hinton has devoted his time to the programme ‘Neural Computation and Adaptive Perception’ from 2004 to 2013. He also acted as the director of the programme. The programme was funded by the Canadian Institute for advanced research. His biographical sketch from the University of Toronto cites that since 2013, Hinton has been involved with Google. Up until the year 2023, Hinton divided his time and expertise between Google and the University of Toronto before he declared his departure from Google, citing risks with the usage of AI. Hinton’s prolific journey witnesses his achievement of the Turing Award in the year 2018 for conceptual engineering and making deep neural networks a critical component of computing.
Departure from Google and AI’s ethical implications
Hinton’s departure from Google has opened conversations on the ethical implications of AI and throws light on the concerns regarding AI that many users had previously flagged as a risky enterprise. Today, we are witnessing AI’s revolutionary achievement of enabling its use in the creation of art, in enhancing education, and in replacing the traditional landscape of education. As revolutionary as generative AI has become in recent months as its popularity has risen, it has also automated previously manual tasks such as customer service, quality control, and fraud detection.
Hinton claimed that his departure from Google was not because he wanted to criticize the company. He claimed he left Google to raise awareness about the dangers of AI. On his withdrawal from Google, Hinton tweeted that he decided to resign because he did not want his statements about the ethical implications of artificial intelligence to affect Google.
Ethical challenges of AI
Hinton flagged that the immediate concern regarding AI is the spread of misinformation, which is only accelerated by the easy access to the internet for most people. Hinton cites that although there was concern about AI progressing to become smarter than humans, we were unable to control it. AI has the propensity to acquire completely unexpected new skills. Hinton, in an interview with a popular news media company in the US, claims that the tech companies race towards building generative AI to overtake their competitors is alarming. In a tweet, Hinton stated that Google has acted very responsibly towards AI.
In the NYT today, Cade Metz implies that I left Google so that I could criticize Google. Actually, I left so that I could talk about the dangers of AI without considering how this impacts Google. Google has acted very responsibly.
— Geoffrey Hinton (@geoffreyhinton) May 1, 2023
Some ethical challenges of AI include but are not limited to:
1. AI is not neutral- it reflects bias either inserted or embedded. Discriminatory outcomes and AI based decisions are very susceptible to inaccuracies.
2.There is no lucid understanding of AI tools.
3.There are still some concerns about how data is gathered and the privacy of users that are not addressed in depth.
Hinton’s success in artificial intelligence and computer science warrants some acknowledgement of his concerns regarding generative AI. Hinton was born in London on December 6th, 1947, Hinton’s ancestry boasts legendary personalities. Hinton is the great-great grandson of Mary Everest Boole, a mathematician whose pedagogy in ‘Philosophy and Fun of Algebra” was infamous. Boole was also married to a fellow mathematician, George Boole. Hinton’s great-great grandmother is also touted as a feminist icon for demonstrating how women made careers in competitive academic careers that primarily only accommodated men. Geoffrey Hinton’s father was a British entomologist who was a professor at the University of Bristol in the later part of his career. Geoffrey Hinton is also related to Colin Clark, an economist who pioneered the use of national income accounting, which was phenomenal in the development of macroeconomics.
The trend towards exceedingly using generative AI could make it impossible for laymen to discern whether the news they consume on social media, other forms of media is true or not. Making Hinton’s concerns regarding AI worth investigating and creating an instrument of guidelines for the safety and security of users.
