The A.I. Advantage: How and Why A.I. helps you with Decisions, Learning, Communication, and Success.

Relax; we're not talking about getting brain implants or strapping you into a big computer.  We're talking about how you can become a better communicator, thinker, decider, learner, and speaker -- today -- with some advantages offered from an amazing field of study. 

Let's clear up some A.I. Misconceptions.

I'm Jonathan (the author behind this blog entry & website; the other guy in the picture is a photographer's model).  

Most of you already know me (thanks for visiting again to read this blog entry!).  For those who don't, I've been training applications of NLP since 1997 (~17 years, now).  My first career was in Artificial Intelligence, specifically, expert systems (building intelligent decision-making software).

Most of us know A.I. has been madly misrepresented in the media and film industry. Many have been exposed to a version of AI like that in films, like "Transcendence", or the "Terminator" movies, "I, Robot", Spielberg's ridiculous "A.I.", or even "Wargames."  

I'm more interested (& trained) in the AI that makes Google a bit smarter when it searches for what you want, instead of what you asked for.  Or the AI that helps drive Google driverless cars, and fly airplanes, and schedule transportation amidst a constantly fluctuating chaotic world with moving parts.  Like the AI that's behind Siri on your iPhone.  Like the AI behind massive CGI battle scenes where computer-generated armies are filmed without requiring animators to make individual character movements.  Like the AI in video games.  Like the AI that figures out when its time to offer you a specific additional service on top of existing services.  Like the AI that approves your mortgage or ascertains your insurance application (no, not science fiction, I helped build some of these systems over 15 years ago).  Possibly also a little like the AI-based ad-retargeting systems that see you click on an organic food website and know that an ad for "non-GMO products" will be more likely to work with you than with someone else.

The field of A.I. can make you a more effective NLP student and communicator; indeed, a more successful professional.

In 1997, I began learning and then later training NLP.  I noticed early on that many other trainers were gifted at multi-channel congruent communication (words that are aligned with behavior, multiple messages that coordinated well, and very compelling communication that made me listen more closely).  I also noticed that many were not that compelling or congruent, or capable of demonstrating nonverbally what they were talking about verbally at the same time.  

At the time, I borrowed another computer metaphor for this, and labelled this for myself as the difference between serial communication (one skill described or demonstrated at a time) and parallel (many demonstrated at a time, well integrated and congruent).

Serial training rapidly became a turn-off.  Parallel training attracted me.

For me, 'Serial' trainers provide minimal more value in person than we get from a book or dvd.

Parallel trainers are amazing to observe and listen to, and are always worth the live training experience (& CDs/books pale by comparison).

Simply put, serial trainers bored me.  I wanted to learn to use these skills in an integrated, natural, massively parallel fashion, without having to consciously manage it all.  In keeping with the concept of NLP Modeling, if you want to get good at something, its best to model the skills and behaviors of, and learn from, people who are demonstrably good at what you want to achieve. So if you want to get good at using a wide range of NLP skills together, real-time, as I did, then you're going to want to choose to learn from trainers who are known for multi-channel communication.  

I learned early on that serial trainers weren't going to get me there, and don't seem to me to be good exemplars for getting really good at multi-channel communication - especially in the faster paced world of business.  So I sought out trainers who were clearly skilled at multi-level communication, and augmented it with supportive written, audio and video material from other wonderful trainers (even a few serial trainers who do great work, but just wouldn't be able to maintain my attention in a classroom).

As I was learning and attending courses with these amazing communicators (like Richard Bandler, and Rex Sikes), I found that my background was enabling me to absorb NLP skills and knowledge much faster than those I was learning alongside.  Further, I found that arguably the most important skill for an NLP trainer -- NLP Modeling -- was getting a lot of lip service, but not a lot of action, and not a lot of clarity.  Many people were talking about it, but not doing it, and couldn't seem to explain it to me.  Yet I was already doing a form of modeling from my years in A.I. -- I was paid to interview experts, and replicate their thinking and decision making in computers.

So when it became clear that A.I. offered benefits to NLP'ers, I started offering courses called "Knowledge Engineering" for modeling and belief system mapping.  And then later "Belief Craft" with Doug O'Brien, combining KE with Sleight of Mouth."  And over the years, I've designed learning exercises that help people develop the creative use of deeply integrated skills, for natural, parallel multi-channel communication.  In more recent months, it's become obvious to me that some of the exercise-drill designs that have gotten enormous attention and student praise, all come at least partly from my years in A.I.  This distinction that is impossible to find from other NLP trainers (whether serial OR parallel).

Shortsightedness in NLP is rampant.

Once in a while someone says "But AI was meant to emulate the mind, not the other way around."

This can be translated to "why should people interested in NLP study how computers have been taught to think like people?"  Or "shouldn't AI folks be studying us, instead of us exploring or studying AI?"

Avoid that very costly short-sighted perspective, and become a far more effective student of NLP.

Another field of study apart from NLP spent decades prior to and concurrently with NLP, learning to 'unpack' and optimally emulate how people think... and coming up with reflections of how people learn and make decisions, that were then tested and refined in measurable ways.

NLP students should want to glean everything they can from discoveries and representations created by such a field.

My perspective is that an A.I. background (even exposure to one), leads people to greater depth of skills, as well as more natural use of more than one skill at a time, faster than many other methods or backgrounds can.

Let's look at Neural Networks.

Once you get a sense of how neural networks learn, you'll likely find yourself more easily willing and able to immerse yourself in unusual non-rational learning experiences (as opposed to always needing rational explanations before determining if you've actually learned anything). Many people give the idea of "unconscious learning" lip service, and then still demand only conscious understanding and explanations -- and if they don't get it, they ignore any potential value experienced/learned. A willingness to learn in a 'variety of ways' (to quote Milton Erickson) is a critical factor to truly gettting the most from NLP. 

If you'd like to become better at (1) learning anything, (2) learning unconsciously, (3) unconscious uptake (what we like to call learning by osmosis!), (4) allowing yourself to reap the benefits of more than just conscious acquisition of understanding, then study Neural Networks.

In studying Neural Networks, focus on the evidence that explains how we draw conclusions and make decisions without any rational basis, entirely mathematically as a result of strengthening some neural traces and weakening some others.  From an NLP perspective, this could help free you from analysis paralysis and may even lead you to greater emotional intelligence. For those who are deeply stuck in ruts, this could just free you... from yourself.

Let's look at Expert Systems
(my prior domain of expertise).

The subfield of A.I. that deals with expert decision-making is called "Knowledge Engineering."  Knowledge Engineers interview experts, find out what they know, and then build pseudo-intelligent (not sentient) Expert Systems.  These have been in use for 30+ years.  I've built many financial expert systems currently being used by companies like Equifax, Chase Manhattan Bank, Ernst & Young, GTE (now Verizon), and contributed in some way to many more.  

When I arrived at the field of NLP, it became obvious fast that Knowledge Engineering would be valuable for NLP students.  So I created a course to train these skills.  Knowledge Engineering actually provides a conscious way of mapping entire areas of cognitive expertise, of decision systems, of belief systems, including kinesthetic information and values, etc. It offered a thorough and flexible decision and belief mapping system -- before NLP ever came along.

This is useful for doing actual (explicit/analytical) modeling, knowledge mining & transfer, business process re-engineering, consulting, coaching, and so much more.

From an NLP perspective, my KE (& Belief Craft) students often tell me that after they learn KE, they can literally see how people's decision systems and belief systems get them into trouble (or success), predictably. And when they turn that same skillset on themselves, it's transformational. People start cleaning up whole areas of their lives -- and not just magically/unconsciously thanks to some silly external provocation, but in a way they can easily understand and explain afterwards.  My expertise from this career covers cognitive modeling, mapping beliefs, unpacking belief systems, and reprogramming/rewiring belief systems.  For businesses looking to gain from that, I help people make smarter (sometimes seemingly impossible) choices, acquire and optimize and then share/retrain expertise to others.

KE explains how, when, why, where, and what you do, in a visual mapping system.  When KE is used to map a small piece of someone's mind, it becomes crystal clear why they're successful and why they're stuck.  More importantly, it provides perfect clues as to how to get them unstuck, or optimize what they're doing.  And it helps us to clarify someone's thinking, and get them from confused to clear, or from conflicted to congruent, or from hesitant to go for it.

And this is important:  most people trained in NLP, when presented with a real-world difficult situation, will not do the same things the same way.  NLP is not a consistent system.  But KE... is.  When properly trained in KE, people would go about unpacking beliefs and choices in very similar ways, and would result in very similar if not identical maps of what they're modeling.

Let's look at Hybrid Systems:

The intentional combination of multiple learning and deciding methodologies. This is where things get even more interesting. Allowing the parts of a larger system to do their jobs where they're most optimal. You shouldn't trust key decisions to unconscious feelings. But you also shouldn't trust learning to the conscious mind alone.

If you'd like to become better at complex marriages of very different skillsets, Study Hybrid Systems. From an NLP perspective, You can think of your own brain as a hybrid system, and check to see if you're using the right or wrong skill for each job, or perhaps the right or wrong MOOD (yes, emotional states matter). You can think of an entire team of people as a hybrid system. Where do they need to communicate? Where is communication bogging things down?

Let's look at Genetic Algorithms:

This is a search or exploration heuristic that mimics the process of natural selection in decision making and other areas of thinking. Often used in population studies in science, or in predictions of species intermingling, WE might want to learn more from this area of thinking to learn more about where teams become inefficient, and how to optimize them. Or what kinds of communication patterns take us from resourceful to unresourceful, or vice-versa.

If you'd like to become better at identifying inefficient or less optimal choices and replacing those with more resourceful choices, study genetic algorithms. From an NLP perspective, this is extraordinary useful for pattern-matching skills, developing a lower tolerance for inefficiency, and an awareness of when habits get stale.

Let's look at Organic Systems:

Organic Systems are an effort to represent and reproduce human cognition and organic thinking/computing. The truth continues to emerge that while we still don't have a crystal clear idea of how it all works together in our minds -- we do continue to progress towards an increasingly accurate understanding of the complex massively parallel operation of our minds. If you want to be on the forefront of learning about improving human cognition and optimizing human communication skills, there is a high cost to ignoring this area of study.

From an NLP perspective, when I consider group dynamics, I'm typically thinking in terms of organic systems. In small groups, Virginia Satir's family constellation work can be extremely helpful. But in larger groups, taking her approach makes things infinitely difficult to unravel. Organic systems help provide greater awareness of forces at play in larger groups, and help us choose good ways to navigate these choppy waters.

It usually only takes one profound unexpected learning experience, one powerful Eureka moment, to free hyper-analytical minds from their own limitations.  Put differently, one cannot 'understand' the pieces of organic systems easily.  However, one can experience organic systems, holistically, and then drill down to the dynamics at play.

Why would Exposure to A.I. Experience be a Valuable Criteria for NLP Training?

It's important for NLP professionals to do more than just think and wax poetic about "how" people think, and also do more to study these things, than just read articles about language, neurology, and behavior, on the web.  

It's important for all of us to test assumptions thoroughly, in the contexts where the results of those tests would be most valuable.  

A.I. taught me to make and constantly test refinements in long-standing models of learning, cognition, and decision-making.  In turn, this means my courses and home-study materials are designed for maximum acquisition and retention.  They're designed to reach the widest range of types of potential learners.

I've also always been deeply fascinated by unconscious learning and accelerated learning, and have been exploring (for two decades) what is required of me, to help people take that critical leap of faith into "learning to learn differently."  As well as to both demonstrate and explain, concurrently.

There is quite a bit more I learned and accomplished through A.I., and hopefully the above examples share with you how my experience in A.I. translates to some of the benefits you'll have enjoyed from my material and courses.

How Else can you Benefit?

My perspective is that NLP'ers can gain immense value from established and constantly-refining models of how people think.  Seems useful, doesn't it?

If you want to learn about specific areas of study above, search the web for resources on the above named areas, like Neural Networks, or Hybrid Systems, etc.

If you'd like exposure to AI -influenced NLP material, you can invest in some home-study materials.  My "Knowledge Engineering" course is the closest detailed home-study course.  Also, "Belief Craft" is a blending of "Knowledge Engineering" and "Sleight of Mouth."  Indirectly, all of my other NLP home-study recordings represent my approach to training and learning NLP, so, of course, I'm biased to think you'll benefit, no matter which titles you pick.

And if you'd like to learn either Knowledge Engineering or Belief Craft, these courses will be scheduled again soon.

Additionally, I'm working on a course currently called "The Refined Mind: AI Inspired Breakthroughs..." which aims to combine some of my most popular multi-channel learning experiences designed to help you become a more gifted thinker and communicator.  Coming soon!

To open a discussion here -- feel free to include comments below -- what area of your thinking and communicating skills, do you think you want or need the most help with?

author: Jonathan Altfeld