Friday, 10 May 2013

How to engineer an Artificial Intelligence

Intelligence is a defining human characteristic, so it is somewhat doubtful that we would ever be able to pin down what it is precisely enough to make an artificial version of it ... we will always try to define and redefine the term "intelligence" in such a manner that humans remain separated and protected as a separate and distinct class of entities ... our collective ego demands no less.

However, if we put our collective ego to one side, we can surmise that intelligent behaviour consists of some general purpose learning and behaviour-directing mechanisms sitting on top of a whole heap of special-purpose sensorimotor mechanisms.

Engineering an artificial system to emulate some or all of that behaviour is a monumental engineering task. Irrespective of the fundamental breakthroughs in learning, generalisation and planning that may or may not be required, we are still left with an exceedingly large and complex software engineering challenge.

In my mind, this represents the primary obstacle to the development of a true Artificial Intelligence: Not better science, but better software engineering practices and (particularly) better software engineering tools to help manage, visualise, understand and communicate complicated software systems.

Now, this is an interesting problem, because software engineering at a large scale is much less concerned with hard technical challenges and much more concerned with "soft" human challenges of communication and politics. The same can be said for any engineering challenge where the complexity of the subject matter, combined with it's lack of visibility makes communication and documentation a key technical challenge.

Let us look at the communication challenge first: One thing that is becoming more apparent in our increasingly information-rich environment is that communication is constrained much more by the time-management and motivation-management of the reader than by the availability of the information.

In other words, it is not enough just to make information available, you have to manage the relationship between the reader and the information as well; so that information is not just dropped in front of the reader, but the relationship between the reader and the information is managed to support learning and effective decision making also.

How might one achieve this?