Despite the hype surrounding AI, creating an intelligence that rivals or exceeds human levels is far more complicated than we have been led to believe. Professors Gary Marcus and Ernest Davis have spent their careers at the forefront of AI research and have witnessed some of the greatest milestones in the field, but they argue that a computer beating a human in Jeopardy! does not signal that we are on the doorstep of fully autonomous cars or superintelligent machines. The achievements in the field thus far have occurred in closed systems with fixed sets of rules, and these approaches are too narrow to achieve genuine intelligence.
In contrast, the real world is extremely complex and open. How can we bridge this gap? Gary Marcus and Ernest Davis believe that the next development opportunity for AI is to “learn from” human thinking, because humans are still far superior to machines in understanding and flexible thinking.
Based on thinking about cognitive science (psychology, linguistics and philosophy), the two professors put forward 11 suggestions for the development of AI in the book “Rebooting AI”.
01 AI theory must not “immediately see”
From behaviorist psychology (behaviorism), Bayesian reasoning to deep learning, researchers often come up with simple theories to explain all human intellectual behaviors.
Firestone and Scholl put forward a point in 2016: “There is no single way to summarize the way the human brain thinks, because’thinking’ is not a specific thing. On the contrary, the brain’s thinking is composed of different parts, and each part operates The way is different: the way the human brain thinks when it observes a color is different from the way it thinks when planning a vacation, and the way it thinks when planning a vacation is different from understanding sentences, moving limbs, remembering facts, or feeling emotions.”
The human brain is extremely complex and diverse: there are more than 150 clearly distinguishable brain regions, about 86 billion neurons, hundreds (or thousands) of different…