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Design Thinking In AI – The Exigency & Obligation

“Human-centered design is a philosophy, not a precise set of methods, but one that assumes that innovation should start by getting close to users and observing their activities.”

Donald A. Norman, co-founder, Nielsen Norman Group

Artificial intelligence has permeated all facets of our lives — lifestyle, healthcare, automobile, and personalised recommendation systems, to name a few. And many companies tend to go for AI overkill to seem fashionable.

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But before throwing AI at everything, organisations should consider the 3Ws & 1H (what, why, where, and how). Figuring out answers to these questions help them to deploy AI efficiently in their processes. And that’s where design thinking comes into play.

Why Is Design Thinking Important?

Design thinking refers to developing design concepts that seek to understand the product from a user’s perspective. It is an iterative process and involves stages such as empathising, defining, ideating, prototyping, and testing.

Design thinking encourages developers to question, observe, network, and experiment. Instead of looking at a problem and immediately charting a course to arrive at a solution, design thinking takes the longer route of first understanding the end-user’s expectation and capabilities. This mindset is also an essential factor in developing a successful AI design.

“AI has an exponentially growing role to play in coming times as a part of our day to day tech applications. But at the end of the day, it is just like any other tool whose impact depends heavily on how it is used. That’s where Design Thinking comes into play. To make the most of the potential of an AI application to any use case, there needs to be a deep understanding of the end user’s point of view. Using a ground-up approach by involving the end-users in the creative problem solving and close feedback loop will make AI work effectively,” said Rasik Pansare, Co-founder & CMO of Get My Parking.

Current AI technologies are data-driven solutions. In other words, the algorithms are only reliable as the data used to train them. If the data is slightly out of place, it can lead to absurd and undesirable results and, in some cases, societal biases.

While machines might be getting smarter with each passing day, most of them still require human supervision. For the best results, humans and machines need to work in tandem to counteract either party’s weaknesses. Getting to this stage requires design thinking.

Phases of Design Thinking 

In general, there are five main steps in design thinking:

Empathise: This includes understanding and analysing the problem at a deeper level. At this stage, an element of innovation needs to be introduced, especially in the context of how well AI can be integrated into a system. 

Define: The first logical step to understanding a problem is defining it. A clear definition helps in building scalable solutions rapidly. 

Ideate: At this stage, companies formulate workable solutions for the problems at hand: Teams think about how deep learning and machine learning can be incorporated into the solutions. The developers think through the problem to conceptualise a model, leveraging available information.

Prototype: Things move from theory to practice at this stage. A prototype is an early sample to test your concept. Realising the solution in physical form offers a more realistic perspective. A prototype serves as a crystal ball to foresee design loopholes further down the road. Going ahead, companies can design more multidimensional products and localise to provide solutions within a domain. 

Deployment and Testing: The actual product is an iterative improvement of the prototype. Once the product ships, developers have to deal with real-world use cases like fixing bugs, adding features, or smoke testing. Every product is a work in progress, and empathetic thinking and an active feedback loop go a long way in a product’s posterity.

Wrapping Up

From an organisational viewpoint, design thinking is a good mental model for lasting success. Putting the customer at the centre, building products and experiences based on the user’s needs are critical in driving innovation and securing a competitive advantage. 

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Shraddha Goled
I am a technology journalist with AIM. I write stories focused on the AI landscape in India and around the world with a special interest in analysing its long term impact on individuals and societies. Reach out to me at shraddha.goled@analyticsindiamag.com.

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