How close artificial intelligence (AI) is to human intelligence has been a question that has intrigued the world in both scientific debate and pop culture.
The Terminator series starring Arnold Schwarzenegger is the most famous cultural example of an AI with equal/superior intelligence to humans. The popular series has been hugely influential in how many people see the full potential of AI. While these depictions of AI had once only been considered science fiction, technology has evolved to a point where AI is rapidly being integrated into modern society. The market size of AI is projected to be $184 billion this year. One reason for this is how AI is being used in a wide range of applications, such as chatbots and generative text, that replicate how a human would think and respond. This has led many to question whether AI is much more similar to human intelligence than we may think.
How AI is Similar to Human Intelligence
Four key areas show how AI is very similar to human intelligence. eLearning industry lists these areas as processing, learning, decision-making, and ethical issues. Like the human brain, AI systems can recognize images to find patterns, retain past information, and combine this information with new insights to change behavior. AI can also mirror the brain in making decisions based on their training, the patterns they’ve learned, and through making decisions with biases. Like the human brain, AI can think strategically and work through complex problems using the available information.
The reason there is such a similarity is best demonstrated by examining how AI and the brain work. MongoDB’s post on artificial intelligence outlines how the brain and AI collect data and information similarly. The brain gets its input from reading, listening, and observing surroundings, allowing it to form patterns, save memories, and comprehend new situations based on past experiences. AI receives data from multiple sources, allowing it to find patterns, self-learn, and learn and comprehend new situations based on previous data and patterns.
To demonstrate how very similar AI is to human intelligence, researchers are creating advanced AI devices that mirror the brain. Researchers from Northwestern University, Boston College, and the Massachusetts Institute of Technology (MIT) recently created an innovative synaptic transistor (a device that can learn in ways similar to a neural synapse) to show the similarities. This advanced device processes and stores information, echoing the multifunctional nature of the human brain. Recent experiments have demonstrated how the transistor goes beyond simple machine-learning tasks and can categorize data for associative learning. Mark C. Hersam, who co-led the research, explained how “in the brain, memory and information processing are co-located and fully integrated, resulting in orders of magnitude higher energy efficiency. Our synaptic transistor similarly achieves concurrent memory and information processing functionality to more faithfully mimic the brain.”
Differences between Human Intelligence and AI
While AI is very similar to human intelligence, there are differences. In a BBC article on AI and human intelligence, Xaq Pitkow, an associate professor at Carnegie Mellon University, explained how, despite their sophistication, “AI algorithms that dominate the market are essentially prediction machines.” The brain, however, “is built for levels of reasoning, flexibility, creativity, and abstract thinking that AI still hasn’t replicated.” Creativity is arguably the biggest and, to many, the most important difference, as AI is unable to be spontaneous. An AI’s creativity depends on human inputs and prompts, and it cannot yet produce original work of its own accord. Human intelligence is also closely linked with emotional intelligence, which allows them to form connections with other people by responding to emotions through empathy. An AI’s consciousness cannot replicate this social awareness and can easily misinterpret emotional cues. It should be noted that experts often use the cavitate of “yet” when speaking of these differences. Every year, these differences become less and less obvious.
For more insights on AI, do read Erik Lawrence’s Understanding AI: A Guide to Artificial Intelligence where he breaks down the complex world of AI into accessible, digestible chunks, making it an invaluable resource for a broad audience. It is a must-read for aspiring AI aficionados and is a good indicator of how AI will continue to change society.