The internet, personal computing, cloud computing, databases, and machine learning all emerged from the same underlying vision, the world as information, computation, networks and probabilistic systems. AI extends this logic, but doesn’t replace it.
The philosophical worldview underlying AI is continuous with the one established by the Information Revolution. This includes Leibniz’s dream of a universal calculus, Humean associationism and statistical regularity, cybernetics and systems theory, information theory and connectionist models of mind.
In that sense, ChatGPT may be to the Information Revolution what the steam locomotive was to the Industrial Revolution, transformative but not a new cultural logic.
The Industrial Revolution expressed a Baconian-Cartesian worldview that thought of nature as object, knowledge as control, mechchanization, predictability. and human mastery.
The information Revolution embodied a different ontology. It was about information over substance, networks over hierarchies, systems over mechanisms, probability over certainty and emrgence over linear causality.
My claim is that current AI doesn’t introduce a third worldview but merely intensifies the second. AI does not yet offer a fundamentally new metaphysics. It still treats intelligence as information processing, learning as pattern extraction, and knowledge as computation. These are the assumptions that have governed the digital age for decades.
So a.i. doesn’t represent a technological leap in terms of its philosophical underpinnings, but that doesn’t mean that it wont be profoundly disruptive in its effects on more traditional segments of culture and their ways of life.
In the 1970’s and ‘80’s, writers like Timothy Leary, Alvin Toffler and Stewart Brand recognized that the digital tech revolution expressed ways of thinking which broke from the older established cultural modes, not just in technology and business but across many other areas of society.
If you look at those today who are making similar claims for the implications of a.i. (Ray Kurzweil,etc), they tend to be those who are buying into the same assumptions, the same worldview which drove the tech revolution of 50 years ago (Leibnitz-Hume-Kant). They, along with today’s tech moguls, rightly see a.i. architectures as expressions of paradigms of organization which easily translate into politico-economic concepts of free market capitalism, neo-liberalism and technocracy.
If you listen instead to those thinkers whose ideas have been influenced by figures like Hegel, the Pragmatists, hermeneutics-phenomenology and Wittgenstein, you’ll find people who see through the hype. For instance, Evan Thompson writes:
The map does not know the way home, and the abacus is not clever at arithmetic. It takes knowledge to devise and use such models, but the models themselves have no knowledge. Not because they are ignorant, but because they are models: that is to say, tools.’They do not navi-gate or calculate, and neither do they have destinations to reach or debts to pay. Humans use them for these epistemic pur-poses. LLMs have more in common with the map or abacus than with the people who design and use them as instruments. It is the tool creator and user, not the tool, who has knowledge…
We said above that LLMs do not perform any tasks of their own, they perform our tasks. It would be better to say that they do not really do anything at all. Hence the third leap: treating LLMs as agents. However, since LLMs are not agents, let alone epistemic ones, they are in no position to do or know anything.
True technological revolutions express paradigm shifts in philosophical worldviews. Today’s tech engineers, ceo’s and media cheerleaders are drawing from the same moldy-oldy worldview which was fresh 50 years ago and reaching its final stage or its ultimate realization today.Whats new aren’t the ideas embedded in today’s but the hegemonic reach it makes possible for the old ideas. Heidegger warned that technological thinking was producing a transformation of the human being and culture as a whole into ‘standing reserve’ to be utilized for programmed ends.
His point concerned not what the technology itself was doing but how we were understanding it, and ourselves through it.