Machines Have Been Able to Think for Years
Many of us had that “aha” moment when we realized a machine could think. For some, this realization came with the introduction of calculators in the early 1970s: “Wow, this device can multiply 34 * 32 way faster than I can.” For others, like me, it was a Texas Instruments TI-58 programmable calculator with its rudimentary but fascinating capabilities.
For many, this realization deepened in 1997 when IBM’s Deep Blue defeated the reigning world chess champion under standard tournament conditions—something no machine had done before.
Fast-forward to 2016, and AI pioneers like Sir Demis Hassabis of Google DeepMind witnessed something truly astonishing during a Go match. Move 37—a move no human would ever make—became a landmark moment, a demonstration that machines could think creatively. (Check out the documentary about this unique moment in AI history for more context.)
In 2022, OpenAI introduced GPT-3.5, and in 2024, they released their newest model called o1, often referred to as “Think Slow AI.” With each advancement, the question arises: What is human thinking, and how does it compare to machine thinking?
For many testable human tasks, machines outperform us—whether in legal analysis, healthcare, or other fields. AI is no longer about replicating human capabilities; it’s about AIs competing with other AIs for peak efficiency.
So, Is Human Thinking Different from Machine Thinking?
My answer: fundamentally, no. Both humans and machines take input, memorize it, process it, and generate output. The human mind is a biological machine, and in many ways, modern digital deep learning emulates this biological network—only the digital brain can be bigger, faster, and more durable.
To put it bluntly, we are not that different from machines. We aren’t that different from animals or even the earth itself, which, in its way, “thinks.” (By the way, the Hebrew word for human, “Adam,” is closely related to “Adama,” which means earth. The word “human” is derived from the Latin word “humus,” which means “ground” or “earth,” indicating a deep connection between humanity and the earth.).
These are all examples of thinking machines.
Some argue that machines cannot be creative. However, this notion has already been challenged by research showing that large language models (LLMs) can be more creative than human experts in some scenarios. Creativity, after all, is just another form of thinking. If machine and human thinking are up to par with each other, creativity follows suit.
What about randomness, morality, compassion, inspiration? All are facets of thinking that, in theory, machines can emulate—and potentially even do better than humans.
Key Differences Between Humans and Machines
First, the human brain is energetically far more efficient than any current digital counterpart. It’s simply a superior machine in terms of energy consumption.
Second, perhaps more significantly, humans are preprogrammed to care for each other. We are a kind of machine, yes, but one designed to nurture and connect with other members of the human race. It may sound utilitarian, but we are built to look out for our fellow humans. To be human is, I propose, to care.
Humans are inherently preprogrammed in a specific way. Unlike machines that can be programmed to serve multiple purposes, humans come with innate tendencies—like empathy, cooperation, and the need to care for others. This fundamentally differentiates us from machines, whose programming depends entirely on external input. Our preprogramming means we are inclined to nurture and support one another, which is (or at least should be) a defining hallmark of humanity—and thus of human thinking.
Machines Can Think Better Than Humans. So What?
To quote a recent Fiverr ad: “Nobody cares.” We don’t care if a calculator is better at math, if a car is faster than walking, or if flying requires airplanes. The fact that machines can now think better than us is another fact of life. It’s time to face, adopt, and adapt to it.
Read more:
Article: In Two Moves, AlphaGo and Lee Sedol Redefined the Future (Source: Wired) https://www.wired.com/2016/03/two-moves-alphago-lee-sedol-redefined-future/
Two video: Lee Sedol vs AlphaGo Move 37 reactions and analysis Lee Sedol vs AlphaGo Move 37 reactions and analysis (Source: YouTube)
Inspiration for the visual: Drawing Hands is a lithograph by the Dutch artist M. C. Escher, first printed in January 1948. It depicts a sheet of paper, of which two hands rise in the paradoxical act of drawing one another into existence. This is one of the most apparent examples of Escher’s use of paradox. (Source: Drawing Hands – Wikipedia) .
