Intent-focused, not tech-led: Take AI past the experimentation phase
Learn what it looks like to bring everyone into the mix
Artificial intelligence is becoming increasingly relevant to how everyone moves through the world. However, many people don’t feel empowered enough to shape that relationship.
There’s a real need right now to resolve this tension, which means a select few can’t act as all-knowing gatekeepers. As long as we have a destination or a goal in mind, we can all play a role in how our teams get there.
That’s why we launched a new online course, Team Essentials for AI. It breaks down how to map design thinking methods to the technical realities of AI.
The course uses a fictional case study to walk through how to build an intentional, responsible AI action plan and gives people the resources to try it for themselves in a workshop. It takes a few hours to complete, and the workshop the course prepares you to run should last about a day.
The course is derived from IBM Design’s AI Essentials Framework, which walks teams through a series of activities that help them come together on a shared vision for AI.
How we got here
This framework started as good old-fashioned design thinking.
“We’d been running design thinking workshops with various product teams,” Adam Cutler, Distinguished Designer of AI Design and Cognitive Enterprises recounted.
“And we realized teams weren’t aligned on understanding what AI was, how to design for it, or what to build for it.”
Software Designer Andi Lozano remembers when her team showed up to a workshop with Adam’s team to improve an AI feature, they came prepared in the traditional design thinking sense. They identified user pain points, fleshed out personas, and mapped their users’ current experience.
But when Adam asked about their intention behind their use of AI, the room fell silent.
“We thought we had more alignment going into it than we did,” Andi recalls.
The workshop reframed how the team discussed the relationship between AI and their users: security analysts. The importance of ethics and explainability continues to stick with Andi.
“It’s a security analyst’s job to be really skeptical, and if we provide no evidence for the insights we give them, why would they even trust it?” she said. Now, when she and her teammates vet each other’s ideas, they always frame the conversation around an analyst’s trust.
After a while, Adam realized his team couldn’t reach everyone directly, but they could pass along the valuable lessons learned through these workshops in an online course. It found its natural home on our platform.
Why this course, and why now?
The more AI begins to venture out from innovation initiatives to underpin the nature of modern business, the more all employees and customers should shape how their companies use it.
The days of a chatbot for the sake of it are at their sunset. In order to push into the next phase of innovation, AI can no longer just be a shiny touchpoint; it must be useful, intuitive, and responsible. As design thinking and its success has taught us, all worthwhile solutions start with a human problem. The same rings true when it comes to AI.
That still requires developers and data scientists, of course, but it also requires everyone else to jump into the ring.
A digital marketer may be up to speed on personalization trends. A researcher may know how users feel about the various ways in which their data gets collected. A compliance professional knows data and privacy regulations like GDPR backwards and forwards. That information’s all valuable from day 1 and has to ability to shape foundational direction for the better.
Teams often struggle to align early in the AI development process. This leads to wasted time and opens the door to unintended side effects of AI models. Through this course, you can pick up the tools to answer important questions and set a direction together before any model gets built.
Even as a former workshop participant, Andi was eager to take the online course. She found the newer activities — ones she never went through before — actionable and accessible. They set guardrails for productive conversation.
She also enjoyed the balance between observing a team as they figure out how to insert AI into their experience and the space to reflect on what she would do in their situation.
How to get started
At the end of the day, this is a design thinking course at its core. That means you need to have a basic understanding of design thinking to get the most out of it.
Before you take the Team Essentials for AI Course, you need to earn your Enterprise Design Thinking Practitioner Badge. You can take our free Practitioner Course to make that happen. (We promise there’s lots of good stuff in that course, too!)
Only the first step
If you find yourself thinking, “This was cool, but I want more,” after you take this course, then you’re our ideal person. You’re also in luck. You can find information about data, ethics, and conversation design on the IBM Design for AI site.
Bringing in AI often means you augment tasks traditionally done by humans. To do it right requires people to infuse deeply human conversations into every decision—to anticipate more things than a couple of individuals’ experiences could think up.
You’ll need your team members to get an AI initiative off the ground. They’ll need you, too.
