In-person Experiences: The IBM Watson Primer
The big question: How do you showcase the power of Watson in a way that’s engaging and informative for everyone, from averages Joes to CTOs?
One sentence summary: I led case study curation, content design and copywriting for the Watson Primer, an immersive experience that introduced people to IBM’s AI technology at major events and conferences.
10-second backstory:
In 2017, most people knew Watson as one of two things: the witty talking box that bantered with athletes, authors, and celebrities in IBM’s TV commercials, or the AI that dominated Ken Jennings in Jeopardy back in 2011.
Those campaigns helped put Watson on the map, but many people still knew next nothing about how the technology worked, what it was capable of, and what value it was adding to the world. So, we set out to build an immersive, interactive exhibit to introduce people to real-world examples of Watson at work while also explaining some fundamental AI concepts along the way. In other words, a Watson “primer”.
PHASE I: My self-taught AI crash course.
When this project kicked off, my understanding of AI was superficial at best. That said, there was no time for me to go off and take an AI course before I started working on the Primer content; I had to build up my domain knowledge in parallel with my efforts to identify and vet compelling Watson use cases to feature in the exhibit. (SIDENOTE: When I say “use cases,” I basically just mean examples of people using Watson to do cool and compelling things. I’ll use that term a lot in the next coupe paragraphs.
My journalism background — specifically the interview-based research aspect of it — really came in handy here. I started my research by gorging myself on blogposts, articles, and videos about Watson, trying to build a basic understanding of the space while pulling out the names of potential experts whenever I came across them. I added to that list by asking colleagues who they thought IBM’s smartest AI experts were, and started reaching out to those people within the first few days of the project.
Talking to the experts
I asked each expert on my list if they’d be willing to take 30 minutes to help me understand Watson a little bit better. Almost everyone said yes. (FRIENDNOTE: Shoutout to my main man Adam Tate, who was one of those experts and my partner-in-crime on this project.)
When I spoke with these folks, I used them primarily to test my existing knowledge. I spent much of my time describing AI concepts or use cases as I understood them, and then asking them what I got right and what I got wrong. And, of course, I made sure to ask every one of them about their favorite Watson use cases. In this way, I quickly built up a wealth of technical knowledge and a stable of potential applications that we could feature in the exhibit. All in all, I gathered a list of more than 70 different use cases.
PHASE II: Making sense of it all.
My brain works in systems. As I discovered more and more use cases, I automatically started trying to group them in different ways. Two categories in particular really interested me.
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Industry. This was an obvious grouping, but it was also the key to engaging the audience. We assumed (with a fair amount of confidence) that people browsing stories in the Primer would naturally ask what Watson was doing in their fields of work. We also wanted to show that Watson was already driving business value across all sorts of different industries.
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Type of use case. I knew that one of the most commonly asked questions would be, “What sorts of things can Watson do?” and I wanted the Primer content to answer that question directly.
With this in mind, I started grouping use cases based on what Watson was actually being used to do — accelerating research, anticipating disruptions, scaling expertise — many interesting themes emerged as my list grew.
The Watson Advantages
This second exercise became the foundation of a system capabilities we would later dub the “Watson Advantages.” Essentially, I curated the list of use case types down to six recurring patterns. Then, I associated each pattern with the handful of Watson tools that made the capability possible.
For example, I paired the pattern of “accelerating research” with tools like Watson Discovery, which is essentially an AI-enhanced search tool, and Watson Knowledge Studio, which allows you to train AI models to recognize and understand the specific language of your occupation or industry.
The Watson Advantages allowed us to talk about what Watson could do in a way that was concise, easy to remember, and approachable to people who didn’t fully understand the technical details of AI. More importantly, it shifted the way we positioned Watson, from talking about individual tools and capabilities to painting pictures of what those tools could actually do when applied to real-world problems.
This new ontology was so powerful that the Watson Brand team decided to use it on the Watson homepage, where it continues to live on today. Go check it out!
PHASE III: Creating an interconnected content system.
The team had two primary goals for the Primer: 1) illustrate how Watson was already delivering business value across many different industries; and 2) help build people’s understanding of how AI works.
We accomplished this by creating two interactive experiences:
- The Story Wall, a 10 -foot touchscreen where attendees could browse through stories of Watson transforming how companies were doing business, and
- The Tech Table, a 3-panel podium where attendees could...
- learn about the Watson Advantages and the sets of different tools that came together to deliver them;
- explore the wide variety of data sources that could be tapped for use with Watson and learn about how data must be cleansed to get the best results out of your AI; and
- learn about how AI models are trained through gamified training simulations
Check out more pictures of the Primer below!
