Artificial Intelligence (AI), sometimes more appropriately referred to as Machine Learning (ML), swoops in as yet another fashionable attribute used by burgeoning startups to raise money in Silicon Valley. A long list of hasty and hollow monikers alone should give a critical bystander, and many a venture capitalist, enough pause to question its foundational premonition.
But let’s say you haven’t experienced the damaging socio-economic impact from the snake-oil promises by technology just yet, and still believe social media – err, socialism – is actually good for humanity, and with unfettered positivity, you are intent on believing and accepting computers best someday rule us. For you, this missive is a stern warning of evolutionary discourse.
First off, there is no doubt specific laborious and dangerous activities performed by humans may be helped by machines, first with the assistance of rudimentary tools, then automated machines, then machines with more sensors to decide on a better and dynamic course of action. Such devices already exist in many factories all over the world today, and way before we decided to slap artificial intelligence as the moniker on them.
In fact, many of these kinds of machines, we with a glance to the future refer to as robots, are not intelligent at all, for what they contain is a sophisticated algorithm to weigh the priorities of the many signals received from its sensors to decide on a most precise or appropriate course of action. A course of action that mimics the decision a human with experience would ideally make or would like to see made.
Which brings us to the very meaning of intelligence, as the loaded noun in the moniker of artificial intelligence. We commonly assign the merit of intelligence to a person with a lot of knowledge, a mistake we also make when referring to artificial intelligence, which by its dependence on data, should instead be referred to as artificial knowledge.
Einstein (1879-1955) referred to intelligence as
“Intelligence is not the ability to store information, but to know where to find it.” — Albert Einstein
Cause and Consequence
Those who promote artificial intelligence in its current form intrinsically believe that a deep understanding of hindsight, from which knowledge is derived, extrapolates to meaningful foresight that breaks the norm.
Knowledge in and of itself nothing more than memorization of consequence, not to be confounded with a comprehension of a cause. A confounding of consequence and cause that leads, and in practice in specific domains has already led, in the words of Nietzsche (1844-1900) to grave depravity of reason.
In that context, technologies that use data as the primary basis for decision-making do not yield any intelligence to deviate meaningfully from the norm, as correlation does not yield causation. And worse, a dependence on correlation leads to fundamentally flawed decision making.
Not just as in two games of soccer with the same final score falsely suggesting gameplay must have been identical. Hence, dependence on a correlation of consequence in artificial intelligence will deter and blur the identification of cause and instead lead to stale and faulty intelligence. Artificial as the adjective more insightful than initially intended.
Nature’s laws of evolution dictate intelligence cannot come from consequential data hopelessly attempting to revert to cause. We can all witness how a technology tool like Apple’s Siri spawns a disturbing number of false-positives and false-negatives that make the tool unusable for all but the most robotic of tasks. Tasks we could hardly proclaim to yield intelligence.
So, will machines ever surpass human intelligence?
No. For intelligence that breaks the norm cannot be modeled, for such imagination has no precedent. And the endless and rapid regurgitation of downstream optimization from consequence pursued by artificial intelligence will not yield a better comprehension of cause, let alone lead to a new and better normalization of truth as the much-needed reinvigoration of the norm.
But the blind belief, human stupidity (as Einstein calls it) from a systemic confounding of consequence and cause, already omnipresent in many systems of humanity deployed worldwide, promulgated by far-fetch promises of artificial intelligence today, have, can and will lead to a further dumbing down of humanity, if we let it.
“I fear the day that technology will surpass our human interaction. The world will have a generation of idiots.” — Albert Einstein
We shall instead develop systems to embrace a wider standard-deviation of human ingenuity with innate respect and appreciation for our meaningful differences. So, we can discover the outliers responsible for our improving adaptability to nature.
The learning capabilities of machines will improve, with increasingly complex knowledge masquerading as intelligence. No different to how we sell knowledge as intelligence to ourselves.