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Something Inspirational



We have approached Human/AI complementarity and Data-Driven decision-making purely from a Methodological, and Methodological lens vs a deep understanding of how the Human Brain makes decisions with data and trusts technology. 


The single greatest illusion played on us by our own brain is to have us believe we are "awake" and very aware of our surroundings when most of the time when we are in fact on "auto-pilot".


Humanity is at an Inflection Point. 

The Information Age has ended, and AI has ushered in the Age of Augmentation.  Never before in human history has such a complementary and near symbiotic technology been created. 


“Novel models of Human/Tech/AI Complementarity will touch every industry, power the advanced economies of tomorrow, and yield order-of-magnitude leaps in innovation and problem-solving. AI is intrinsically different yet uniquely complementary to the human brain.  It is this unique, near symbiotic relationship that will enable us to solve today’s unsolvable problems,”  Among the keys to unlocking this potential is the human factor.  We must translate our deep understanding of the human brain and how it makes decisions with data and trusts technology into operational efficacy; this means making Cognitive Neuroscience an accessible competency.” 

The key for organizations is to leverage models of Humans and AI working together to Innovate and Problem Solve.  The key is complementarity - not replacement. Replacement will only yield incremental gains, while complementarity will result in Innovation and value through Problems Solved.   

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Nothing incites more vitriol when discussing AI's integration into organizational models than the topic of Augmenting or Replacing humans.  This conversation is almost a non-starter for most firms if the decision-makers understand what we term AI for what it is.  AI is not Artificial Intelligence in any way, as conceived by Hollywood or mirroring the human brain. Simply put, it is not Intelligent; it does not possess knowledge or understanding, nor does it learn, perceive or solve problems like the human brain does.  Artificial Neural Nets (ANNs), despite the casually repeated statement that they are designed to mimic the human brain, is only true in the most abstract/low-resolution way.  This is not to say that Replacement is not a viable option in some circumstances but to emphatically state that the quantum gains in Innovation and Problem Solving will occur only when people are mated to AI in novel ways.  The gains from replacing humans with algorithmic constructs will largely be incremental. 


The competition and easily replicated nature of incremental gains in productivity or performance make the Replacement of humans a discussion largely for those seeking headlines and desiring to be offended on the part of others. 


Among the major issues plaguing Digital Transformation (DX) efforts, both in AI integration and Data-Driven Decision-Making, is the systemic flaw of approaching the challenge with little understanding of the Human Factor. 


If we accept that Humans and AI Complementarity/Augmentation are the keys to unlocking the future through value creation, then the human factor - specifically how the brain makes decisions with data and trusts technology must rise to par with the math and methods of Machine Learning and Data Science.  


The issue lies in the difficulty in understanding the brain, the logical but untrue tenets of how the brain makes decisions and trusts, and the Opaque nature of how this understanding can translate into design and operational goodness at the organizational level—those in management view Cognitive Neuroscience as an esoteric subject with little practical value. With the ushering in of the Age of Augmentation, this precept is now false.  Having organizational access to a deep understanding of the human factors as they relate to AI is critical to optimizing the interaction and engineering desirable outcomes. 



Organizations have seen a straight line between Modeling Scientists and revenue - create a model, prove a True or False, and insights can follow.  This has not been the case for Theoretical Scientists, who are seen as having little value in organizations that are linear in their thinking (which is the overwhelming majority) Some of the issues reside in the lack of understanding of the difference between the two. A modeling scientist (E.G., A Data Scientist) is they seek to prove something True or Not.  A theoretical scientist asks, "What is possible"- this is the innovation component, and the two beautifully complement each other ( think of Ying and Yang).  

Many organizations have sought to engrain "data-decision making" into the "DNA of the firm" with virtually no scientifically based knowledge of how the brain makes decisions with data.  In fact, one can argue that the brain does not make decisions with data; it makes decisions based on emotional responses elicited through data interrogation/analysis. This is because the decision region of the brain is the Limbic System, which controls emotions but not higher-order functions like data analysis - this is controlled by the Neo Cortex, which has no ability to make a decision.  This is a simplification of the interaction between systems but is nonetheless true.  We can thus design UX/UIs with this scientifically based understanding to perform various functions, from enabling learning, memory, data exploration, eliminating decision errors, correcting bias, and empowering our accessing of memory to solve problems. 

A fundamental component of AI Augmentation in business, government, and the military is developing models that are nearly symbiotic in their nature. This means structuring the AI from a Human Centric lens or complimenting the brain in ways that allow the AI to do what it does best in the job role and the human operator to do what the brain does best.  The relationship is uniquely complementary, but only if we have a deep understanding of brain functions - this is simply not the case in almost all firms.  This is where theoretical science will pay tremendous but officiated dividends to forward-leaning firms as they push the Art-of-the-Possible in asking "what is possible" in this domain, this job role, and these tasks when combining Humans and AI. 


This represents the challenge for today's firms navigating the road to tomorrow - an endless series of conversations on how precisely we can integrate people and technology from a human-centric lens to do what is today impossible. 


This topic is deep and encompasses multiple dissertations. For a deeper dive, check out the Blog section for downloadable Executive White Papers (10 min reads) and or contact me for a conversation. 


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