To ensure AI is a help rather than a hinderance to problem-solving, business goals and problems must be defined first, warns Frank Langva, senior advisor at Sopra Steria Norway.
Next time you use artificial intelligence, try thinking a bit more like the sergeant in the military training-inspired TV series Kompani Lauritzen. The programme is similar to the UK’s SAS: Who Dares Wins series and shares the same principles. This might help you stay afloat and deliver what you need to deliver.
Artificial intelligence helps us to create summaries and presentations, find patterns in large datasets, and provide developers with shortcuts by generating ready-made algorithms. Technologists advocate for new frameworks that can connect data and no-code solutions that give you dashboards and reports on how the solutions perform.
But who defines the right goals and identifies the problems that need solving? Have we forgotten this amidst all the technology? "Watch what you spend your time on" would be a typical quote from the sergeant in Kompani Lauritzen. An attempt at a shortcut to the goal can quickly become a detour.
Quick fixes from artificial intelligence can be tempting to rely on as shortcuts to the goal. If the shortcut is ChatGPT, you often get a product based on training data from what others have done before. This is not specifically tailored to your needs. Achieving 80% of a goal that resembles problem-solving is still far from satisfactory.
What effect do you desire?
It's easy to lose sight of the right goal, especially if you are a technology optimist who gets excited about what is possible to achieve. It's easy to be enticed by what comes out of the box.
That’s not to say it isn't useful, but it isn't necessarily the primary need of the users. Nor is it certain that it contributes to creating the effect you primarily desire. In other words it doesn't help to have the best tool to measure the effect if we haven't done anything to achieve the effect in the first place. We must first solve the task that generates the effects we want to measure.
Those of us who are advisors and drivers in digital transformation must be aware of our responsibility and constantly keep our eyes on the ball. What is most important for the business to achieve, which problem must we address to achieve this, and which solution do we use to solve the problem?
Only when we know the answers to these questions should we let the developers start writing the actual code. And then it isn't so important if the process owner "doesn't know all the data stuff," because it is we, as good technologists and advisors, who must translate from business to technology. And back again.
Tools with an AI label
Back to the sergeant in Kompani Lauritzen. When he says that it isn't the activity of "cleaning" he's after, but the goal of achieving the result "clean," it's up to the contestants to figure out how to best solve the task.
The team makes good use of available cleaning technology, such as long-handled brushes and mops, but the activity of cleaning is not the goal itself. This also applies if it is labelled artificial intelligence on the box we get the tool from. It isn't the technology itself that is the goal; it is a tool we use to achieve the goal. Remember that next time, and you have a better chance of contributing to digital transformation instead of drowning in technology.
The article was first published in Digi.no on 22 May 2024.