-- The Cognitive Engine - 10RULE WHITE PAPER

WRITTEN BY

Gary Morais, Bottom Line Results, LLC

Dennis Cagan, Caganco Incorporated

Chris Spivey, Spivey & Co. LLC

The Cognitive Engine: a white paper

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TECHNOLOGY MEETS BRAIN SCIENCE What is a cognitive engine and what is the right approach to developing one? The chemistry or electronics of the mind are the source of thinking and the originating cause that generates human behavior and actions. Manifestations of the brain’s thought patterns, actions and behaviors comprise a human being’s performance in any endeavor. We call this “performance thinking” In a workplace environment, this equates to competency, contributions, performance, skills, and outcomes – which may be either good or bad. To use a digital circuitry analogy, this performance thinking – think of it as wiring or algorithms, are the original creation of the impulses that generate the other performance behaviors and results. To continue, this performance thinking, and its resulting behaviors, can be impacted and modified by various factors over time. Often, we see that demographics are used as a substitute for performance thinking. What are demographics? Demographics are simply statistical data relating to the population and particular groups within it. Demographics do not represent actions, or behaviors, or performance, or thought processes. The statistical information includes things like age, gender, geography, education levels, ethnicity, and perhaps even the statistical proportion of people that have performed certain actions or exhibited specific observable behaviors. But, demographics are not the actions or behaviors, or their cause or root. Performance thinking is.

LOOKING WHERE THE LIGHT IS SHINING One of today’s biggest buzzwords is Big Data – pun intended. Big Data and Data Analytics go hand-in-hand. Collect it, and analyze it. We should not for a moment confuse cognitive technology with the observation of actions and behavior, and demographic statistics, massively compiled is a big database, and then analyzed and dissected for measurable correlations and causality. We propose that what most computer scientists and software vendors term a cognitive engine is the massive aggregation, compiling, cross referencing, and

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correlation of observable actions and demographic data sets. In this approach, we find “streetlight” bias.

According to Quote Investigator (www.quoteinvestigator.com) there is a brilliant comical allegory that depicts the biases inherent in many types of scientific research. The allegory is illustrated by a tale whose publication in slightly different forms traces back to at least 1924, if not earlier.

A police officer sees a drunken man intently searching the ground near a lamppost and asks him the goal of his quest. The inebriate replies that he is looking for his car keys, and the officer helps for a few minutes without success then he asks whether the man is certain that he dropped the keys near the lamppost.

“No,” is the reply, “I lost the keys somewhere across the street.” “Why look here?” asks the surprised and irritated officer. “The light is much better here,” the intoxicated man responds with aplomb.

Some sound scientific research is shaped by the need to perform and verify replicable measurements. But these measurements do not always accurately reflect the phenomenon that is being investigated. The term “streetlight effect” is sometimes used to name this form of observational bias. Because the data is available, and statistical correlations can be drawn, the industry is arguably looking for the keys under the “Big Data streetlight”.

TRADITIONAL APPROACH IN REVERSE

In our extensive research, traditional investigative approaches are not truly cognitive; rather it is specifically investigative research compiling multi-source data sets, analytics, actions, outcomes and demographical data, in the hope of finding ways to automate tasks that would mimic the perceptual and cognitive skills of humans.

Many have approached talent engagement by assessing or researching styles, personality, preferences, talent themes, or by using competencies and values-based approaches, which fall short because these all rely on static identifiable data, and not alterable coefficient of human behavior. They make it difficult to measure a sustainable ROI. Their failure is based on a lack of baseline scientific performance algorithms, and proven dynamic clinical tools, which can allow for the modification of existing algorithmic brain functions, reforming a brain’s formulas to accelerate measurable positive changes in productivity.

True cognitive science is much deeper than collecting external observable behavioral data sets and correlation research.

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The secret is ‘between the ears’, the human brain science, real cognitive thinking. It is the discovery of the ‘root source algorithms’ that provide what we will term performance thinking. These are the driving force that impacts all aspects of human behavior and workforce productivity, from leadership, sales, customer service, meeting goals, following processes, procedures, working effectively in teams, and building a high performance culture. An algorithm is defined as a problem-solving procedure, or in the case of a computer or brain, a program. The brain’s programs/algorithms that comprise thinking - performance thinking, are the root source of all behavior and decisions in a human’s workplace functions – therefore, the lifeblood of any business. By identifying and emulating these, you have the true cognitive brain ‘files’, which we call performance drivers. With these in hand, and coded into the proper software platform, you can then predict outcomes, execution performance, and the results of people’s engagement.

ARTIFICIAL INTELLIGENCE VS. COGNITIVE BRAIN PERFORMANCE DRIVERS Without debating the similarities or differences between artificial intelligence and a cognitive engine, hopefully we can agree that the integration of the cognitive formulas behind what drives behavior - performance drivers, has the potential to contribute vital value added data and predictive analytics into current and new technologies and applications. After over twenty years of research in this field – not where the light is shining, but where impulses originate – we believe that as they are identified and emulated, these cognitive brain algorithms will be the breakthrough force for today's new disruptive technology companies. This leap forward in integrating true cognitive performance thinking could be the ‘holy grail’ for future applications and solutions.

THE REAL OPPORTUNITIES FOR BUSINESS

In a recent article in the Deloitte Review, Issue 16, titled Cognitive technologies: The real opportunities for business, David Schatsky, Craig Muraskin, & Ragu Gurumurthy noted: "We found that applications of cognitive technologies fall into three main categories: product, process, or insight." They go on to summarize “…Product applications can provide end-customer benefits, while Process applications can automate or improve operations, while Insight applications uncover insights that can inform operational and strategic decisions across an organization." Given that performance thinking is the root source of all human productivity, the brain’s performance drivers (performance thinking algorithms) are certainly the source for new Product applications, or services, which deliver greater efficiencies and added value productivity. Imagine being able to predict the productivity of an

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entire organization or being able to sustainably replicate the top performers in organizations such as project or sales teams. With regard to Process applications, applying these performance drivers to automate or improve organizational development, will also allow transformational business operations by getting to the ‘root source’ for solving diverse business engagement challenges, and it will build sustainable high performance cultures faster and with greater efficiencies. With regard to Insight applications, applying performance drivers to a company’s talent audit management technology solution can capture the critical talent engagement data to uncover insights that can inform and shape operational and strategic decisions, structures, and initiatives across an entire organization.

THE NEW FUTURE OF COGNITIVE TECHNOLOGIES Cognitive technologies with embedded performance thinking algorithms will be the new products in the field of artificial intelligence. One can imagine being able to positively change human behavior and engagement that traditionally only humans used to be able to do. Or being able to identify top performing talent before you open a resume, or mining an entire organizations’ or nations performance capabilities. Wise and appropriate investments in embedding true cognitive brain algorithms (as opposed to data analytics) can dramatically improve current enterprise applications and future innovative technologies. Imagine actually automating the mind’s own thinking patterns to build future innovative and disruptive technologies.

AUTHORS

Gary Morais is a psychotherapist and the inventor of Performance Drivers™ (Performance Thinking Algorithms) and the 10Rule® business performance transformation suite of cloud-based software product (www.10Rule.com). Morais is the managing partner of Bottom Line Results, LLC. and a business strategist applying the 10Rule’s Hybrid Cognitive Technology strategy and solutions for company CEO’s and President’s for over 25 years.

Dennis Cagan is a noted high-technology industry figure. He has founded or co-founded over a dozen different companies, and has served as CEO of both public and private companies, a consultant, venture investor, mentor and professional board member – 53 fiduciary corporate boards. In 2011 he was elected to the IT Hall of Fame. He has authored numerous articles in magazines including NACD Directorship, Directors & Boards, Private Company Director, and Family Business.

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Chris Spivey has a background of driving people and technology together for business results. He has well over two decades of implementing HR systems and analytics and speaks for organizations such as the AICPA and the Institute for Internal Auditors and has been quoted in publications such as CIO magazine, CFO magazine and Automation World.

© 2016 by Bottom Line Results LLC. All rights reserved. No portion of this document may be reproduced in any form whatsoever without prior written permission from the publisher.