How Can we Design a New Relationship with AI?

Whether we admit it, like it, or believe it, we’re in a relationship with AI.

That’s the first of many powerful reflections made by Sara Vienna, Metalab’s Chief Design Officer, in her must-read manifesto about how design and product must evolve.

Unlike the design leaders who speculate about AI's impact, Sara and her world-class team are years ahead. They are designing disruptive AI product experiences and leveraging AI to elevate their workflows. Sara’s episode is one of the most important conversations we’ve had about the future of design and products.

Listen on Spotify | Listen on Apple Podcasts

She believes that AI will change how we work and what we build. Those who embrace the potential of AI will succeed in the oncoming disruption. But most importantly, the future of product+AI will be in making five mindset shifts:

They’re fundamentally principles for humanizing experiences.

The hope is that AI will finally bridge the divide so products can deliver the value we’ve always wished was possible in the most humanized way possible.

But there will be challenges in accomplishing this:

* Most product orgs are built around the concept of delivery, not design excellence

* Unlocking user data: Getting access to valuable data and knowing how to use it in a meaningful way are still more fantasy than reality

* In every direction we turn, trust is being diluted

* Design as we know it will need to be reborn to adapt to move from creating pixel-perfect interfaces to ones that adapt and spawn based on user interactions

Again, I highly recommend listening to the entire episode.

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Envisioning the future of design & product

If we extrapolate on Sara Vienna’s vision of how design should change, a couple of core reality checks come to mind:

* Today, we can’t even conceptualize what products will be able to do tomorrow. Just like new AI tools are being released faster than we can read about them, more teams than ever are competing to deliver the use case & interaction model that will redefine a category. It’s a race to an undefined & moving finish line.

* The underlying models may be the heartbeat of future products, but design will always be the brain. Products plug into whichever model suits them best at a particular moment, usually based on cost and accuracy. But just like each of our minds brings a different lived reality and way of using knowledge, the models are less important than the strategy that’s been designed into the product.

* Fewer designers and product managers will yield immense power. AI automation platforms —like Make and Loveable— can effectively replicate more than half of products today. This percentage will grow until such a point that any product will soon be able to be cloned, undermining its competitive advantage. The designers and product managers working on the future of design will have the funding that enables them to compete in a global race that they’re likely to lose because they don’t know what competition they’re actually facing. The rest of us will be working to keep the lights on.

Big question: How should we be using AI, today?

Photoshop celebrated its 35th birthday today and is a perfect reminder of how disruptive platforms eventually become part of the boring vocabulary of the everyday.

GenAI platforms, like ChatGPT, are in their infancy. Everything seems equal parts novel and confusing. We’re still unsure how to use this superintelligence, only that we should be using it. Photoshop’s rise was similar: a platform that opened up so many possibilities but whose ultimate impact wasn’t felt until it redefined the designer role many years later.

What’s happening today is that employees are smuggling AI into work and this makes sense given the recent McKinsey report that finds that leaders are slow to adopt because of risks and a lack of vision.

Our research finds the biggest barrier to scaling is not employees—who are ready—but leaders, who are not steering fast enough.

Anthropic, the maker of Claude, published their Economic Index report and found that AI use is most prevalent in computer & mathematical occupations.

Their AI model is mainly used for programming and administrative tasks.

What the data also show is that design and creative tasks aren’t core use cases, yet. And rightfully so, large language models best serve requests about processing content and code, not pixels and ideas. A report about how generative AI is used in journalism showcases this by highlighting that even the creative tasks are largely operational ones, like resizing images and animating.

This data highlights the divide in how leading organizations, like Metalab and Superside, leverage AI compared to the everyday user. While the average person uses Midjourney to generate stock art, leading designers automatically generate localized creative based on design systems and content guidelines.

The reality is that product teams have three core workstreams:

* Operations: Planning, organizing, editing, describing (e.g. Notion)

* Creativity: Ideating, revising, collecting, analyzing (e.g. Cove)

* Productivity: Deciding, planning, organizing, explaining (e.g. ChatGPT)

Every designer, product manager, writer, producer, and researcher completes tasks in these three workstreams. And every one of you should be taking the time to break down your typical workflows into discrete activities so that you can explore what AI solutions can either augment or automate non-critical tasks.

An example of this is how Kyle Soucy is using AI to streamline person and journey map creation. This type of knowledge work is considered sacred by traditionalists but as you can see in her article, she’s broken down her workflow to find effortful tasks to be augmented/automated.

We can question AI’s accuracy all we want. We can challenge if models were trained ethically. And we can debate what percentage of your job may benefit from using AI.

What will not change is the undeniable truth that the intelligence and capabilities of these models and tools will only improve. The sooner we embrace that truth, the better positioned we are to control our own fates.

For example, a recent study evaluated AI vs. human-generated therapy responses from 13 expert therapists (clinical psychologists, counseling psychologists, marriage and family therapists, and a psychiatrist). The report found (questionable) data to indicate that users couldn’t tell if a human or an AI made the responses. The AI also outperformed human therapists on empathy, professionalism, and cultural competence.

We’ll soon reach a point where generative AI can output designs that are indiscernibly human or automated. In this near-term reality, the role of designers must evolve or be replaced.

A recommended action plan for how you should be using AI today:

* Plan projects and workstreams using templates, resources, and added context

* Communicate ideas and insights better by using AI to iterate and expand

* Question the rationale, assumptions, and factors that impact the project goal

* Compile inspiration, ideas, and information that will broaden your thinking

* Analyze larger data sets and more sources than you could have before

* Challenge your concepts by making variants and exploring new directions

* Create more deliverables by automating localization, multiple formats, and generating content based on systems

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