Designing great AI products — Effective collaboration for designers

The following post is an excerpt from my book ‘Designing Human-Centric AI Experiences’ on applied UX design for Artificial intelligence.

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Building AI products is technical but also requires creativity. Popular culture depicts people who work in technology as science and math nerds with low EQ. Characters like Steve Urkel on Family Matters, Sheldon Cooper on The Big Bang Theory, and Dennis Nedry from Jurassic Park all create a picture of social misfits, man-children, more comfortable with a slide rule than a conversation¹. The media loves to perpetuate these stereotypes, which can be incredibly misleading. While most people in tech are interested in science and technology, the best people I know that build AI products have eventful lives with interesting hobbies. Building AI products is more similar to making music or producing a film than doing math or science.

Building AI products is more similar to making music or producing a film than doing math or science.

An orchestra needs different musicians to communicate, collaborate and work together to create a great performance. Similarly, different members of your AI product team need to work together to build a great user experience. If you wonder why ‘simple’ changes to your product take so long to make, then start by understanding the interaction between you and your engineering team.

Think of engineers less as people who churn out code and more like creative problem solvers. Building a great user experience is everyone’s responsibility. Extend your UX family. As a product designer or product manager, getting too prescriptive too quickly may result in unintentional anchoring and diminish the creativity of your engineering counterparts. There are many ways to approach any AI problem, and your engineers love overcoming technical challenges. Trust them to use their intuition and encourage them to experiment².

Your job as a designer is to help your product team make great user-centered choices.

Effective collaboration

At its heart, building AI products is a creative endeavor. You are trying to solve a user problem by building not just the software but also imbuing it with intelligence. Training an AI model is a slow and iterative process. Engineers often need to use their judgment and imagination when tuning the algorithm. Your job as a designer is to help your product team make great user-centered choices along the way³.

Collaboration is a two-way activity. Inspire your team members with stories, prototypes, customer feedback, findings from user research, and introduce them to UX methods and design principles. Sharing the design process can help your team be comfortable with iteration and work wonders for your ability to influence the product. Mostly, you just have to treat your team members as people, full of ambitions to learn and grow, motivations to do their best work, and a range of skills they want to exercise.

Our attempts to create artificial intelligence have, at the very least, helped highlight the complexity and subtlety of our own minds.

Easy things are hard

Many of the things that children can easily do, like picking up objects of different shapes, recognizing the tone of voice, navigating playgrounds, etc., have turned out to be surprisingly difficult for AI systems to achieve than seemingly complex tasks like diagnosing diseases, beating human champions at Chess and Starcraft, or solving complex algebraic problems. Easy things are hard. There’s a famous rule of thumb in any complex engineering project: the first 90 percent of the project takes 10 percent of the time, and the last 10 percent takes 90 percent of the time⁴. And while child’s play is hard, our most critical jobs such as running organizations, governments, caregiving, or teaching chemistry that have mostly complex and unobservable environments are even harder for AI. Our attempts to create artificial intelligence have, at the very least, helped highlight the complexity and subtlety of our own minds.

Collaborate, don’t dictate

Most designers I know cringe at the idea of someone sitting next to them and asking them to change fonts, colors, and other elements on a design artifact. To me, nothing is more annoying than someone breathing down your throat and micromanaging your work by telling you exactly what to do. It might be ok to do it in some cases, but most times, I’d like to be left alone to do focused work. Apart from demotivating people, micromanagement signals that you don’t trust them to make decisions.

Many of us do the same when it comes to working with tech teams. After building a proposal, getting buy-in from leadership, we go to our engineers and say something like ‘Hey, do this quick, by this deadline’ and then run away. Engineering teams then come back with a timeline that you did not account for. Seemingly ‘simple’ changes take much longer than anticipated. Your tech team does not seem as excited, engaged, or motivated. The relationship between developers and businesspeople is not well understood, but is critical to solving business problems with technology⁵.

Apart from demotivating people, micromanagement signals that you don’t trust them to make decisions.

Saying things like ‘This should just be a quick thing,’ or ‘You can do this in a day’ is not only annoying but also meaningless. Unless you understand how things are put together, unless you know how the infrastructure is built, you have no idea how long it will take⁶. How can product teams commit to a deadline if they don’t understand how long something will take to build? And not having enough time to build will lead to one or more of these undesirable outcomes:

• Features will get cut to meet the deadline.
• Product quality will suffer.
• Your team will be burnt out.

Share problems, not solutions

The key to getting product teams and developers to work well together is for the product teams to share problems, not solutions. Instead of presenting engineers with a solution that’s already defined, product designers and managers can share the problem and ask engineers to help figure out the fastest way to solve it based on how the existing systems are constructed. Including your tech teams early in the discussion is not just about being nice or not hurting their feelings; it also has serious advantages. Many developers have some deeper insight into the integration or feasibility of some products or some features. Finding the shortest technical path in context is what engineers do for a living. It’s what they’re trained to do in computer science classes⁷. But instead of harnessing their knowledge and insight, most companies just tell engineers precisely what to do. They ask them to take off their creative and problem-solving hats. Don’t tell, ask. Share problems, not solutions.

Don’t tell, ask. Share problems, not solutions.

The key to building great AI products is to engage your product and tech teams in leveraging their whole brain towards the problem. Design is creative, and so is code. “I’ve always thought that engineering is one of the most creative jobs in the world,” Amazon’s CTO, Werner Vogels, says⁸. Yet many teams don’t realize that writing code is creative; they don’t create an environment where developers can exercise this creative muscle, and everybody loses. Trust that your tech teams are adept at applying the craft of software to serving customers and solving problems, and building great products.

Imagine you are trying to decide between two equally important features to present to the leadership team for buy-in. Before you do that, you share these two features with your tech teams to get some early estimates. After discussing with your developers, you realize that one of the features will take one day to build vs. another that would take three months. Wouldn’t your pitch to leadership change based on this newly acquired information? Engineers can often make these quick estimations, and you should leverage their instincts in picking ideas that give the most return on investment.

You could define the biggest, scariest problems your organization faces and do a ‘call for solutions.’ While not every solution might be worth pursuing. But by framing the largest problems, you give your team members the opportunity to think about and empathize about the same thing. This can also save you from the trap of falling in love with your own idea. Great ideas can come from anywhere. As designers and managers, our goal is to let the best idea win, not the idea of the person with the best compensation.

Don’t dictate what tech teams should build. Don’t tell them what code to write or how to write it. Start with simple questions like, ‘Hey, wouldn’t it be cool if we could do X?’, ‘Hey, is there some way to build this?’ or ‘what’s the fastest/best way to make X possible?’ Collaborate with them and trust them to make great engineering decisions. Don’t turn to your engineers just for code, but also for creative problem-solving. When you tell someone exactly how they should do something, it’s a one-way street, and you don’t engage them. But when you ask someone to solve a problem, the conversation becomes more collaborative, and they are likely to become more engaged.

Motivation

Motivated and engaged teams are key to effective collaboration. When you’re a designer working in an AI product team, motivating and engaging your team members is less about standing in front of a podium and giving a sermon and more about small, regular, and consistent interactions about the user experience. While you might sometimes get a chance to present in front of a large audience, you would often communicate with a small set of people in person, over video calls, through documents, and over email or messaging. Don’t wait for the perfect solution. Share progress with your team members and involve them early. Inspire them with examples, slideshows, personal stories, vision videos, prototypes, or even analysis from user research. Help them build a deeper understanding of your product principles and experience goals. Aim to create a feeling of urgency, energy, and that what they are building is important.

When you’re a designer working in an AI product team, motivating and engaging your team members is less about standing in front of a podium and giving a sermon and more about small, regular, and consistent interactions about the user experience.

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References

• 1, 5, 6, 7, 8: Lawson, Jeff, and Eric Ries. Ask Your Developer. Harper Business, 2021.
• 2, 3: Holbrook, Jess. “Human-Centered Machine Learning”. Medium, 2017, https://medium.com/google-design/human-centered-machine-learning-a770d10562cd.
• 4: Mitchell, Melanie. Artificial Intelligence. 1st ed., Farrar, Straus And Giroux, 2019.

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The above post is an excerpt from my book ‘Designing Human-Centric AI Experiences’ on applied UX design for Artificial intelligence.