Solving problems with AI
Created: January 25, 2020 / Updated: November 2, 2024 / Status: finished / 2 min read (~285 words)
Should I solve my problem with AI?
First start with a non-AI solution, then look into AI if what you have is unsatisfactory.
In this day and age, we want to make AI solve all kinds of problems, even those that don't require AI.
When you build a product, you generally have a problem you are trying to solve. With AI, companies are looking at existing problems and trying to find ways to turn them into AI problems. It is not a problem in itself to attempt the exercise, but it is a mistake to implement an AI solution where a non-AI solution would've been more than adequate. There is still a lot of work that needs to be done in the field of automation that does not require AI, but simpler statistical approaches.
A lot of research in the field of machine learning and deep learning like to point to Occam's razor in order to create simple models, but they sometimes seem to forget to apply the same principle to the whole solution, that is, do I need AI for this or would something simpler be as good?
A problem with the current wave of AI companies is their relation to AI itself. They corner themselves into doing AI only, while AI still highly relies on programming and IT, which are still highly technical but a lot less glamorous. It is definitely exciting to sell products that have AI in them, but starting with the tool and not the problem that needs to be solved is similar to trying to find all the problems a hammer can solve instead of knowing that you need a hammer when you want to nail something.