From Mary Shelley’s 1818 novel Frankenstein to the humanoid robot character named Ash, who betrayed the team in the 1979 movie “Alien,” to Ava, the robot in 2015’s Ex Machina, the established culture has always been driven by scientific and technological advances and particularly in revealing social concerns about creating human–like intelligence.
Artificial Intelligence (AI) and robotics increasingly appear in our news feeds; It is an excellent time for the recently established Leverhulme Center for the Future of Intelligence. The Center is a joint venture run by the University of Cambridge with links from the University of Oxford, Oxford Martin School, Imperial College London, and the University of California at Berkeley and supported by the Cambridge Center for Arts, Social and Humanities Studies.
The aim of this Center, which brings together many thinkers from different fields, is to research and predict what the opportunities and challenges will be as the development of Artificial Intelligence (AI) accelerates and to provide a more measurable and valuable perspective on Artificial Intelligence (AI).
On the other hand, he also underlines the point that they are aware of, saying, “Focusing only on the risk of disaster has limited us in terms of the scope of this field, considering that there is much to be addressed in artificial intelligence.” Therefore, the Center is envisioned as a center that will host experts from similar disciplines dealing with Artificial Intelligence (AI) and examine its long–term and short and medium–term impacts, taking into account risks, opportunities, and challenges.
Although Artificial Intelligence (AI) has made headlines or been the subject of movies that alleviate practical perspectives, while scary stories about Artificial Intelligence (AI) give us chills, its current use is relatively limited.
This measured and multifaceted approach has enabled the Center to be open and enthusiastic about its opportunities while recognizing the serious problems brought up by new technology.
Artificial Intelligence (AI) Applications
From a scientist’s perspective, much of the challenge we face is to analyze and make sense of incredibly complex interconnected systems. It’s a tricky thing, even for multiple teams. But, on the other hand, the systems we’re currently developing are making sense of Big Data. For example, helping to analyze millions of genomes to find the origin of cancer, explore many aspects of climate change, or make solar energy, our power grid, or intelligent homes more efficient.
Dr. Ó hÉigeartaigh cites short–term concerns, citing the example of a taxi or long–distance drivers who have lost their jobs due to self–driving vehicles. But he says this can also give people time to do other things, and that’s why different areas should contribute to these discussions. While there are dangers to be addressed, such as Artificial Intelligence (AI) will soon develop versatile drones, Dr. Ó hÉigeartaigh states that there is no synthetic equivalent to human intelligence.
Many unsuccessful predictions have long been made towards more general Artificial Intelligence (AI) than the limited intelligence currently used in many technologies.
DIFFERENT TYPES OF INTELLIGENCE
Another issue that the popular discourse and discussions about Artificial Intelligence (AI) contain is that we have to consider that there are different types of intelligence in the world. Dr. Ó hÉigeartaigh argues that we have an approach that puts both humans and planet earth at the Center, from human intelligence to the intelligence of ravens from the crow family: “We should not limit ourselves to anthropocentric intelligence. “Types of Intelligence” is one of the first projects that we defined in the initial phase, and we have already started holding preliminary meetings about it.” Imperial College Neurology Professor Murray Shanahan is an expert in Mathematical Logic, and Machine Learning (ML). “All of these people are concentrating on coming up with relatively new ideas for different types of intelligence skills. So while it sits tough to say precisely what intelligence is, it might make our job easier to say what intelligence does and start from there.”
Another issue is how this type of Artificial Intelligence (AI) will evolve. Evolutionary biology has developed by trial and error, and Dr. Ó hÉigeartaigh explains that some with higher error rates have grown faster than others with low fault tolerance.
We are accelerating the development in this field at an explosive level by leading to more brainpower, more doctoral support, and greater allocation of resources to Artificial Intelligence (AI).
Still, it is not possible to predict how long it will take to make these breakthroughs or how much they will accelerate developments in the field.
But eventually, revolutionary breakthroughs will be made.