Welcome to my new Blog! I hope you’ll join me in the coming weeks and months so that, together, we can explore some of the fascinating developments that are taking place, both academically and commercially, on the borderlines between Artificial Intelligence (AI) and Infrastructure and Application Management (IAM). There has always been a high volume of traffic between these two fields. In fact, a good case can be made that the market for independent IAM software first emerged as a result of the Cold War wind-down induced collapse of AI market in the late 1980s, when refugees from companies like Symbolics, Aion, and Thinking Machines (and their non-military investors) sought to recommercialize their IP in the form of service desks and event correlation and analysis systems.
In recent years, there has been a three to four order of magnitude increase in the amount of performance and event data which IT operations and application support teams need to process in order to anticipate, track and resolve performance problems. As a result, IAM vendors and practitioners are once again reaching out to AI technology and concepts in the hopes of discovering powerful and efficient techniques for discovering, analyzing, and reacting to patterns in large performance and event data volumes and the weak signals that indicate the presence of such patterns.
Responding to the prevalence of distributed computing and the Internet, the study of AI, itself, has undergone a rapid development as it has incorporated and modified the results of three fields: the graphical modelling of probability distributions, game- theoretic economics, and modal logic (the logic that studies the relationship between what is valid locally and what is valid globally.) The net result of this development is increasing sophistication in the representation and simulation of how groups of individuals (or automated agents) discover, analyze, and react to the presence of significant patterns. In other words, we have seen the emergence of a Social AI that is, increasingly, superseding (without negating) the more individual mind or agent oriented AI of the past. Some of these technologies and concepts have indeed already made their way into commercialized product but it is my belief that the impact of Social AI on IAM is only just beginning.
Beyond sharing and discussing some very interesting ideas, I am actually hoping that together we may be able to do a bit more. The Prisoners’ Dilemma is commonly used to introduce some of the basic issues in Game Theory. Two captured criminals are separately presented with the choice of either confessing to a crime or not confessing. They are told that if they both confess they will each receive a 1 year prison sentence. If one of them confesses, while the other does not, the one who does confess will get 5 years, while the one who does not confess will get off scot-free. Finally, if neither confesses, they will both get 4 years.
Each criminal reasons as follows: Suppose I confess. My partner in crime can do one of two things: confess or not confess. If he confesses, then I will get one year. If he does not confess, I will get five years. On the other hand, suppose I don’t confess. If my partner in crime confesses, then I am a free man. If he doesn’t confess, I will get 4 years. Whatever he does, it makes sense for me not to confess, so I won’t.
Since both criminals reason in an identical manner, they both wind up not confessing and both end up spending 4 years in prison. Clearly, it would have made a lot more sense for both of them to confess but that would require cooperation, guarantees, and shared knowledge which the situation did not provide.
I think that the IT market unfortunately often functions much like a Prisoner’s Dilemma. The knowledge gap between vendor and buyer can be an abyss. Buyers lack knowledge of the functional capabilities of the technologies being sold and vendors lack knowledge of the actual and potential business uses for the technologies in their portfolios. As a result, features and prices settle into stable but not optimal equilibria. Value that could be obtained by both sides is simply left on the table in the same way that the two criminals end up spending many more years in prison than they actually had to if they had been aware of all the possibilities.
By sharing knowledge and discussing novel opportunities for the application of AI to IAM problems, this blog, once again with your help, may move the IT market from the suboptimal equilibria to equilibria where at least some of that value that would otherwise just dissipate allows both vendors and buyer to better accomplish their respective goals. I am looking forward to the conversation!
Read Complimentary Relevant Research
Predicts 2017: Artificial Intelligence
Artificial intelligence is changing the way in which organizations innovate and communicate their processes, products and services. Practical...
View Relevant Webinars
The Education CIO Challenge: IT Is a Team Sport
This video will outline key Education CIO challenges and recommendations based on business and technology trends in education as well...
Comments or opinions expressed on this blog are those of the individual contributors only, and do not necessarily represent the views of Gartner, Inc. or its management. Readers may copy and redistribute blog postings on other blogs, or otherwise for private, non-commercial or journalistic purposes, with attribution to Gartner. This content may not be used for any other purposes in any other formats or media. The content on this blog is provided on an "as-is" basis. Gartner shall not be liable for any damages whatsoever arising out of the content or use of this blog.