A Requirement for AI Systems
Posted by bsstahl on 2017-05-24 and Filed Under: development
I've written and spoken before about the importance of using the Strategy Pattern to create maintainable and testable systems. Strategies are even more important, almost to the level of necessity, when building AI systems.
The Strategy Pattern is to algorithms what the Repository Pattern is to data stores, a useful and well-known abstraction for loose-coupling.
— Barry Stahl (@bsstahl) January 6, 2017
The Strategy Pattern is an abstraction tool used to maintain loose-coupling between an application and the algorithm(s) that it uses to do its job. Since the algorithms used in AI systems have many different ways they could be implemented, it is important to abstract the implementation from the system that uses it. I tend to work with systems that use combinatorial optimization methods to solve their problems, but there are many ways for AIs to make decisions. Machine Learning is one of the hottest methods right now but AI systems can also depend on tried-and-true object-oriented logic. The ability to swap algorithms without changing the underlying system allows us the flexibility to try multiple methods before settling on a specific implementation, or even to switch-out implementations as scenarios or situations change.
When I give conference talks on building AI Systems using optimization methods, I always encourage the attendees to create a "naïve" solution first, before spending a lot of effort to build complicated logic. This allows the developer to understand the problem better than he or she did before doing any implementation. Creating this initial solution has another advantage though, it allows us to define the Strategy interface, giving us a better picture of what our application truly needs. Then, when we set-out to build a production-worthy engine, we do so with the knowledge of exactly what we need to produce.
There is also another component of many AIs that can benefit from the use of the Strategy pattern, and that is the determination of user intent. Many implementations of AI will include a user interaction, perhaps through a text-based interface as in a chatbot or a voice interface such as a personal assistant. Each cloud provider has their own set of services designed to determine the intent of the user based on the text or voice input. Each of these implementations has its own strengths and weaknesses. It is beneficial to be able to swap those mechanisms out at will, along with the ability to implement a "naïve" user intent solution during development, and the ability to mock user intent for testing. The strategy pattern is the right tool for this job as well.
As more and more of our applications depend heavily on algorithms, we will need to make a concerted effort to abstract those algorithms away from our applications to maintain loose-coupling and all of the benefits that loose-coupling provides. This is why I consider the Strategy Pattern to be a necessity when developing Artificial Intelligence solutions.
Barry S. Stahl (he/him/his) - Barry is a .NET Software Engineer who has been creating business solutions for enterprise customers for more than 35 years. Barry is also an Election Integrity Activist, baseball and hockey fan, husband of one genius and father of another, and a 40 year resident of Phoenix Arizona USA. When Barry is not traveling around the world to speak at Conferences, Code Camps and User Groups or to participate in GiveCamp events, he spends his days as a Solution Architect for Carvana in Tempe AZ and his nights thinking about the next AZGiveCamp event where software creators come together to build websites and apps for some great non-profit organizations.