Designing Intelligence

This topic is not to be confused with the creationist anti-theory of intelligent design. 

It might be because I'm more aware than most people on this subject, but I continue to hear more about the introduction of intelligent systems into business infrastructures and applications.  Simple straightforward data applications are no longer enough to feed the demands for metadata and analytics. 

I just got my copy of the latest The MIT Press Computer Science & Intelligent Systems catalog.  To me this is like the Sears catalogs I remember when I was a child.  The MIT press inventory is full of new tomes on programming, the internet, and the usual computer science periodicals.  But the content for intelligent robotics and complex adaptive intelligent systems is very impressive.  Here are some of the books on the way to my house.

 

Elements of Argumentation

"In Elements of Argumentation, Philippe Besnard and Anthony Hunter introduce techniques for formalizing deductive argumentation in artificial intelligence, emphasizing emerging formalizations for practical argumentation. Besnard and Hunter discuss how arguments can be constructed, how key intrinsic and extrinsic factors can be identified, and how these analyses can be harnessed for formalizing argumentation for use in real-world problem analysis and decision making."

Evolutionary Computing

"In this clear and comprehensive introduction to the field, Kenneth De Jong presents an integrated view of the state of the art in evolutionary computation. Although other books have described such particular areas of the field as genetic algorithms, genetic programming, evolution strategies, and evolutionary programming, Evolutionary Computation is noteworthy for considering these systems as specific instances of a more general class of evolutionary algorithms."


Introduction to Machine Learning

"Introduction to Machine Learning is a comprehensive textbook on the subject, covering a broad array of topics not usually included in introductory machine learning texts. It discusses many methods based in different fields, including statistics, pattern recognition, neural networks, artificial intelligence, signal processing, control, and data mining, in order to present a unified treatment of machine learning problems and solutions."

While not all of these books are new, I believe their relevance is increasing.  I remember in the early 1990's when the computer sections of book stores started to grow exponentially.  I feel this is a similar sign but on a smaller scale. 

Intelligent system design skills will be the next great sought after resource in computer science employment. Business and data application programming has been commoditized.   The creativity has mostly been exhausted.  The next great leap in system processing will be system intelligence.  And the best part about entering this field at this time is that it is wide open for new designs, and new ways of thinking.

Its already starting in many of the areas I've talked about on this site.  Stock trading programs now influence entire markets.  Intelligent traffic systems are catching on with congestion tolling and EZ Pass drive through tolling technologies.  Large scale intelligent traffic systems are right around the corner.  Breakthroughs in the medical field are occurring in many areas of research through digital pattern recognition, DNA modeling, and pharmaceutical research.  Then we have the military and police aspects of data mining and predictive analysis, all in the infant stages.

So what does this mean?  It means that if you want to get the next high paying technology job, and still be a US citizen, you need to be able to distinguish yourself in your skills.  Simple programming skills no longer suffice.  The top jobs are going to require a basic understanding of neural and evolutionary systems.  We may eventually see a merging of biological, chemistry, and computer sciences into whole new research areas around intelligent systems.  No single branch of science is enough to move this technology forward.  You cant design intelligence without knowing what intelligence is. 

This will have philosophical implications as well.  This isnt about thinking outside the box, this is more like saying "what box?".  In preparation for this shift, we'll need to expand our understanding of how our memory works and how we develop and manage our models of the world.  We have a long way to go before we can get a word processor to actually understand what you're trying to type, and there are going to be plenty of seats on the bus headed to the labs to develop this technology.  I hope to be one of the bus drivers.