The synergies between Design Thinking and Artificial Intelligence

07/10/2020 13

In recent years, Design Thinking (DT) has become one of the most popular methods within the innovation process. DT uses designers’ methods to meet people’s needs considering technological feasibility and commercial viability. This concept has its origin in the design methods of the 60’s.

Later, different authors such as Herbert A. Simon, Robert McKim, Bryan Lawson and Peter Rowe published works evolving the concept. Rolf Faste integrated DT into the Stanford University curriculum and it was adapted to the world of design consulting by David M. Kelley at IDEO. Design thinking consists of 5 steps: (1) empathize, (2) define, (3) devise, (4) prototype, and (5) evaluate.

DT is a good example of a methodology that makes the most of the “Small Data” that usually deals more with the qualitative data. The use of “Small Data” usually provides small clues, “Insights” that companies use to discover opportunities and turn them into innovative products or services. Remember that Big Data is different since it usually analyzes behaviors and predictive patterns on a large scale.

In a 2018 article for HBR, the author Jeanne Liedtka explained, “Why design thinking works”. After a seven-year study where she analyzed in depth fifty projects from different sectors, she found that DT has the potential to innovate by bringing out the creative energies of people, winning their commitment and radically improving processes.

DT uses designers’ methods to meet people’s needs considering technological feasibility and commercial viability.

Jeanne believes that DT’s structure creates a natural flow from exploration to exploitation. Immersion in the customer experience generates invaluable data that is transformed into ideas. These will guide the teams to channel the design criteria that they will use to generate solutions.

Assumptions about what is critical to the success of these solutions are examined and then tested with “proof of concepts” and “minimal viable prototypes” that will iteratively provide new data. This new information will help teams further develop innovations that will increasingly fit the real world.

The DT process works in such a way that it counteracts human biases that frustrate creativity. Moreover, while solving the target challenges, it does so with superior solutions and with reduced costs / risks.

Design thinking is a process that recognizes organizations as collections of human beings motivated by different perspectives and emotions. In this way, it emphasizes commitment, dialogue and learning. By involving customers and users in problem definition and solution development, design thinking generates broad commitment and consensus.

DT has the potential to innovate by bringing out the creative energies of people, winning their commitment and radically improving processes.

Finally, by providing a clear structure to the innovation process, this method helps innovators collaborate and agree on what is essential. Jeanne’s study confirms that DT’s method works today to develop innovative products and services. But, the question that is emerging is how to combine a method that draws from areas of knowledge such as psychology or ethnography with exponential technologies such as AI.

From the last two years, we are beginning to see how some authors are beginning to connect both worlds. In a 2017 Deloitte article for The Wall Street Journal titled, “Why AI needs a dose of design thinking »the combination of design thinking with Artificial Intelligence is explored.

Human-centered design thinking can help organizations make the most of cognitive technologies. Artificial intelligence technologies do not automatically produce the best business or social results.

While algorithms can automate many routine tasks, the limited nature of data-driven artificial intelligence means that many other tasks will require human participation. In such cases, algorithms must be viewed as cognitive tools capable of augmenting human capabilities and being integrated into systems designed to follow the flow of human and organizational psychology.

Human-centered design thinking can help organizations make the most of cognitive technologies.

Deloitte calls this emerging discipline “cognitive design thinking.” Author Alan Jacobson published an article last year for TechTalks explaining that DT keeps humans at the center of the problem-solving process in the age of Artificial Intelligence. We will see more and more synergies between DT and AI.