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Nov 2, 2023

Please visit my web page "Urban Tenets" at https://urbantenets.nl/

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The secret of the human edge over AI lies in undocumented knowledge.

The quality of online search results has improved manifold over say past 15-20 years and the quality and speed with which results are generated shall continue to improve with the advent of LLM, but the quality of such search results essentially still remains a function of underlying bulk content. The more data that will get added for processing the more refined results we’ll get, and more the data that will be used, segmented, labeled, and annotated to train machines, the more efficient AI use cases will be.

Thinking of machines and humans and what differentiates them, and taking a case of the decision-making process. The potential application of Artificial Intelligence (AI)  in boosting the degree of confidence in judgment is well understood. The application of AI in critical and scientific decision-making processes is also understood. It is also acknowledged that AI holds immense potential to supplement or eliminate part or bulk of human manual efforts and provide a fast baseline content for judgment and decision-making. That being said, still, the chances are that the key decisions across industry, businesses, and governance will continue to be made based on human judgment. The human judgment that stems from the life experiences of individuals and fraternity, not surprisingly most of which never gets documented. What differentiates the decision-making process of AI and human beings outside of the scientific application, is that the key decision made by humans goes beyond empirical evidence, rationality, and explanation and are also based on their instinct and their belief system. We are not even discussing the occult, spiritual, and depth of human subconsciousness. It is also noteworthy that AI is only as smart as the data it has access to, even if it may claim to extrapolate the data gap.  

AI including Large Language Model (LLM) is fueled by data, but no amount of data seem to be enough to supersede the collective consciousness of human. The data that is undocumented is the missing piece of the puzzle and the documented data that AI has access to and on which it is being trained is possibly only the tip of the knowledge iceberg, and that's what will continue to differentiate humans from machines. This undocumented knowledge or data is almost like a treasure that is seated within the individual’s psyche, cultural experiences, contextual understanding, belief system, and their evolutionary instinct; such knowledge or data is hidden in plain sight and never gets documented, as there is no need.

How humans behave or act is many a time counterintuitive, intriguing and captivating. Each of these acts translates into experiences, the kind of experience that enriches individuals and fraternity but never gets documented, hence never becomes a data point. For instance, those seasoned drivers and commuters who take the shortcut route other than what is shown by the navigation app, by instinct as they have known the rhythm and streets of the city by heart over decades. Those investors who will buy stocks, or strike a deal based on numerology and their lucky number or based on perceived auspicious time or period, a deal that is different from predicted trends or obvious choice, as it goes with their belief system and has worked in their favor in the past. Those project leaders who navigate smoothly through challenging situations based on their life learning, that is nowhere to be found in textbooks and hardly get documented. Those businessmen who take day-to-day and big decisions based on the wisdom earned since childhood while helping their parents in their business, a kind of emotional intelligence not to be gained from business school. Also, those local guides who take you to hidden jewels of the city not to be found in best of the travel guide books, somehow remain a trade secret. Likewise the ordinary and extraordinary trade secrets or individuals, collective, fraternity, and sectors. The million interpretations of a single art piece and craftwork in the gallery and museum by varied spectators, many of which are no less vivid than the interpretation of an art critic. Even the quantum and richness of knowledge that gets instantly and momentarily generated in classroom discussions, ideation and Q&A sessions, but never find their way to the published literature of any kind or public domain. Examples of undocumented knowledge are innumerable, prolific and unfathomable.

The quest of mankind is to structure the knowledge, and the underlying assumption is that every case that is to be analyzed for empirical research has been categorized already, but no amount of sample size is large enough to tap into the experiences of individuals and the consciousness of the collective. Each individual’s experience is the rich embodiment of exceptions, like their life journey, meanwhile, the exceptions always get discarded in quest of a pattern, hence missing out on vital knowledge or data that stems from the individuals, subsets, and fraternity. This is an example of unstructured, undocumented data. AI and LLM while processing seemingly vast, heterogeneous data will most likely still continue to face the challenges of not having access to knowledge that is there but not documented, especially that is seated within individual, community, and culture, and remains obscure and unintentionally out of reach. Yes, one can pay to get the experiences documented and labeled for machine learning but that will still be like scratching the surface.

Acknowledging that humans bring a different value to the table, might be a solace in the turbulent changes in the technological landscape that is happening right now with no sign of slowing down.

Author: Anoop Jha

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