The Myth of Artificial Intelligence: Why Computers Can’t Think the Way We Do
by Erik J. Larson
In "The Myth of Artificial Intelligence: Why Computers Can’t Think the Way We Do," Erik J. Larson critiques the prevailing narrative around AI, arguing that it is unfalsifiable and unscientific. He highlights that artificial intelligence systems, despite their limitations, are being applied across various sectors, raising ethical concerns about their impact on human values. Larson asserts that intelligence is not a standalone trait but is deeply situational and contextual, reliant on the interplay between individuals, their environments, and broader cultural contexts. He emphasizes that human intelligence is largely externalized within civilization, challenging the notion that it can be replicated by machines. The author critiques the technocentric views of futurists who equate intelligence with computation, suggesting that this oversimplification undermines our understanding of human capabilities. He warns against the dangers of AI becoming "intrusive and dangerous idiot savants," and argues that the future of machines should be considered a scientific question rather than a myth. Larson calls for a reevaluation of the role of scientists and thinkers, lamenting the shift from insight-driven inquiry to a reliance on big data and computational methods. Ultimately, he contends that while AI technology advances, it is crucial to recognize the unique insights and creativity that human beings bring to problem-solving, a lesson that has been overshadowed in contemporary discussions about intelligence and technology.
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Key Insights & Memorable Quotes
Below are the most popular and impactful highlights and quotes from The Myth of Artificial Intelligence: Why Computers Can’t Think the Way We Do:
Notice that the story [of technical progress accelerating indefinitely] is not testable; we just have to wait around and see. If the predicted year of true AI's coming is false, too, another one can be forecast, a few decades into the future. AI in this sense is unfalsifiable and thus--according to the accepted rules of the scientific method--unscientific.
This cuts the myth at an awkward angle: it is because the [artificial intelligence] systems are idiots, but still find their way into business, consumer, and government application, that human-value questions are now infecting what were once purely scientific values.
Understanding natural language is a paradigm case of undercoded abductive inference.
First, intelligence is situational—there is no such thing as general intelligence. Your brain is one piece in a broader system which includes your body, your environment, other humans, and culture as a whole. Second, it is contextual—far from existing in a vacuum, any individual intelligence will always be both defined and limited by its environment. (And currently, the environment, not the brain, is acting as the bottleneck to intelligence.) Third, human intelligence is largely externalized, contained not in your brain but in your civilization. Think of individuals as tools, whose brains are modules in a cognitive system much larger than themselves—a system that is self-improving and has been for a long time.
In the early part of the twentieth century, the philosopher of language Paul Grice offered four maxims for successful conversation:The maxim of quantity. Try to be as informative as you possibly can, and give as much information as is needed, but no more.The maxim of quality. Try to be truthful, and don’t give information that is false or that is not supported by evidence.The maxim of relation. Try to be relevant, and say things that are pertinent to the discussion.The maxim of manner. Try to be as clear, as brief, and as orderly as you can, and avoid obscurity and ambiguity.
Here, it’s best to be clear: equating a mind with a computer is not scientific, it’s philosophical.
General (non-narrow) intelligence of the sort we all display daily is not an algorithm running in our heads, but calls on the entire cultural, historical, and social context within which we think and act in the world.
World knowledge, as Bar-Hillel pointed out, couldn’t really be supplied to computers—at least not in any straightforward, engineering manner—because the “number of facts we human beings know is, in a certain very pregnant sense, infinite.
