March 2021
Intermediate to advanced
73 pages
1h 37m
English
Content preview from Operationalizing AI
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Chapter 3. Design Thinking
Systems to support artificial intelligence are too complicated to architect without a guiding framework for problem solving. Design thinking allows teams to create a shared language around a shared problem within the organization, as well as processes and designs for how best to solve enterprise problems and, indeed, artificial intelligence problems. Adding in a problem-solving framework and workflow like design thinking shortens the time to get from problem to insight, and ultimately to delivered AI solutions. We discussed personas to include in these AI planning steps in the previous chapter, one of which could be a design thinking facilitator. If that isn’t a dedicated function of an organization, other personas can facilitate the processes as well, as long as they understand what the team is trying to accomplish with design thinking.
Design thinking is a process that helps teams solve problems at speed and scale. It’s a three-step, iterative cycle in which team members repeatedly loop over steps to observe, reflect, and make. Those are terms for the general practice of design thinking. In this report, we’ll refer to the steps instead as iterations in which we must reflect, explore, and model the problems at hand.
At IBM, we use this methodology as a way to build our own products, and IBM also takes the design thinking approach to clients to help them solve their problems. Please note that IBM is not the only organization with expertise in design ...
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.