In May 2023, the 2024 Physics Nobel laureate Prof. Geoffrey Hinton wrote a tweet on X platform saying: “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.” This tweet caused a tremendous shock because Prof. Geoffrey Hinton is a Turing Award winner and is considered one of the godfathers of deep learning; a modern branch of artificial intelligence (AI).
AI is a branch of computer science that studies the ability of machines to simulate human intelligence and build intelligent systems capable of mimicking human advanced and complex functions, including learning, reasoning, problem-solving, and language understanding. Although the term AI has been popular in recent years, assuming that it has developed recently, in fact, the science of AI started with the introduction of the algorithm by Al-Khwarizmi. The algorithm is a crucial concept in computer science and artificial intelligence.
In 1950, Alan Turing, widely considered the father of theoretical computer science, introduced the “Turing Test”; a test that measures computer intelligence. The turning point came in 1956 when Marvin Minsky and John McCarthy organized the “Dartmouth Workshop”, wherein AI was established as an academic discipline, followed by McCarthy’s development of Lisp programming language, a standard programming language for AI.
Another important step was the development of “Machine Learning”, a concept based on enabling machines to learn from the data. “Artificial Neural Networks”, a revolutionary AI type, was inspired by the brain neural connection and Geoffrey Hinton is one of the pioneers in this field.
Our brain is composed of neurons, neural cells, that communicate with each other through synapses. “Artificial Neural Networks” technology mimics this function where nodes replace neurons. Geoffrey Hinton developed the Boltzmann machine, an advanced type of artificial neural network able to discover properties in data that can be used in image analysis, for which he won the Nobel Prize. His revolutionary invention can be applied in many fields, such as medical imaging, leading to promising advancements.
All the mentioned contributions of esteemed scientists paved the way for the current transformative revolution of AI, which can be of great benefit when applied in diverse domains, including health, education, manufacturing, retail, etc. AI advantages involve decreasing consumed time, repetitive tasks automation, faster insight extraction from data, reducing human error and physical risk, and enhancing decision-making.
For example, in health, it can help to better medical imaging analysis; it can be applied in models used in personalized medicine for more efficient tailored treatment protocols. Moreover, it can monitor a patient’s health condition virtually or by using devices powered by AI, or be a smart surgical assistant helping surgeons for better surgical outcome. In education, it can help make a more personalized adaptive learning environment and used as a smart educational chatbot.
Although AI can potentially transform diverse domains, it holds threats like privacy and ethical concerns regarding data usage, biased model training, and decision-making. It can also replace many jobs or transform them, which puts a burden on their current employees to find other jobs or acquire new skills. AI market monopoly by only AI technology giant companies may raise the bias risk. AI models need enormous power to develop and operate, which raises environmental and power-using risks.
During his long research journey with artificial neural networks, Prof. Geoffrey Hinton believed the systems were inferior to the human brain in some ways, but later, he said “Maybe what is going on in these systems is actually a lot better than what is going on in the brain”; he added “But most people thought it was way off. I thought it was way off; I thought it was 30 to 50 years or even longer away. Obviously, I no longer think that”, raising existential threats. Despite all the benefits of AI, the risks are there, and they may be catastrophic. A lot of work needs to be done to regulate its usage so that we can benefit from its advantages and prevent or reduce its risks.
References
nobelprize.org
youtube.com