From Human-Centric Design to Human-Centric AI

May 16, 2024
Dana Vetan

Imagine having an Einstein in your basement. This genius can master any field and solve your problems in a heartbeat. But just like the quality of his solutions depends on the input you provide and your prompting skills, the value you get from Einstein hinges on your focus.

It's not enough to have this brilliant mind at your disposal; you need a clear direction for him. What problems do you need him to crack? Where can his unique perspective give you the biggest edge? Many leaders feel overwhelmed by this potential, unsure how to best utilize Einstein's genius. Here's where FOCUS becomes paramount.

Traditionally, we've relied on human-centric design, meticulously crafting products and services based on what we perceive customers need.

But what if the future lies elsewhere?


According to ChatGPT:

Human-centered AI (HCAI) is an approach to artificial intelligence that prioritizes human needs, values, and ethical considerations in the design, development, and deployment of AI systems.

Human-centric AI goes beyond simply having a powerful problem-solving tool at your beck and call. Imagine your "Einstein" continuously learning and evolving. Fuelled by real-time customer data and feedback, this AI would constantly refine its solutions to perfectly match ever-changing customer needs. This collaborative approach, where human focus guides AI development, has the potential to unlock a new level of innovation.

Here's where the traditional approach falls short. Human-centric design, while valuable, relies on our interpretations of customer needs, which can be inherently flawed. Human-centric AI, on the other hand, leverages the raw power of data to gain a deeper understanding of customer needs and desires. Not only that, but AI can process and analyze vast amounts of data at scale, providing insights that human-centric design cannot achieve alone due to human limitations.

Beyond Human-Centric Design: 3 Advantages of Human-Centric AI

Human-Centric AI → Adaptability

Human-centric design is typically static, based on initial assumptions about customer needs gathered through research, feedback forms, surveys, etc. These needs, however, can evolve rapidly. Human-centric AI, on the other hand, is constantly learning and adapting from ongoing interactions with customers and new data streams. This allows it to identify and address shifting needs much faster and more effectively.

Imagine a music streaming service designed through human-centric design.  While it might cater to popular genres based on initial research, it wouldn't be able to adapt to a user's sudden interest in a niche genre based on a new playlist they discover.  Human-centric AI, however, could analyze this shift in listening habits and recommend similar artists or playlists, personalizing the experience in real-time.

Human-Centric AI → Predictive Capabilities

Human-centric design often relies on historical data and intuition to anticipate customer needs. Not once you’ve heard key stakeholders say: “I’ve been here before. I know what to expect.” Human-centric AI, however, can analyze vast amounts of data to identify patterns and predict future trends and behaviors. This allows businesses to proactively address customer needs before they even arise.

For instance, an e-commerce platform might use human-centric design to personalize product recommendations based on past purchases.  Human-centric AI, however, could leverage purchase history, browsing behavior, and even social media trends to predict a customer's interest in a new product about to launch, recommending it before they even know they need it.

Human-Centric AI → Personalization

Human-centric design often aims at a generalized user base, creating products or services that cater to the target customer segment. This approach can miss the mark for individual needs and preferences. Human-centric AI, however, can deliver highly personalized experiences by analyzing individual user data.

Think of a fitness app designed through human-centric design. It might offer a variety of workout routines, but wouldn't be able to tailor them to a user's specific fitness level or goals.  Human-centric AI, however, could analyze a user's activity data, health information, and preferences to create a personalized workout plan that adapts and evolves as the user progresses.

So, how do we unlock the true potential of this "in-house Einstein"?

The answer, as always, lies in focusing on the core: the customers. What are their unmet needs, their frustrations, their aspirations? By going back to basics, human-centric AI can address these needs in ways traditional solutions simply can't.

But, what does it mean for Design Thinkers, Service Designers, Corporate Innovators? Will HCAI replace their expertise?

I don't think it's a case of replacement. Instead, it's an opportunity to amplify their impact. By embracing this approach, design thinkers can become even more valuable.
This shift towards Human-Centered AI will require expanding their area of expertise and understanding.

Gain new skills: HCAI demands an understanding of AI capabilities and limitations. Design thinkers may need to learn about data analysis, machine learning, and how to collaborate effectively with data scientists and AI engineers.

Work with AI outputs:  The focus might move slightly from solely user research and empathy to incorporating data analysis and working with AI outputs. This doesn't negate empathy, but adds another layer to consider.

Overall, HCAI elevates their role. By embracing this new approach, design thinkers, service designers and innovators in general can become even more valuable in creating human-centered experiences that leverage the power of AI. They can act as a bridge between human needs and the capabilities of AI, ensuring technology serves humans in a meaningful way.