Part 2 of a 2-part series exploring the following questions. Read Part 1.
Will artificial intelligence (AI) create an environment where design thinking skills are more valuable than data science skills? Will AI alter how we define human intelligence?
What is innovation or creativity?
Creativity is the application of imagination plus exploration with a strong tolerance to learn through failure.
Innovation and creativity are the human ability and willingness to ask provocative questions (like Tom Hanks in the movie Big); embrace diverse ideas and perspectives; blend these different ideas into a new perspective (frame); and explore, test, fail, and learn to apply the new blended perspective to real-world challenges.
No, that definition doesn’t exactly fit into our ACT, SAT, GMAT tests of intelligence, and that is exactly the point! As AI models take over more of the tasks and jobs traditionally associated with intelligence, humans need to focus on those human skills that make humans unique. Humans need to become more human – which is why I think design thinking is such a critical ability in a world where AI will eliminate rote-skill jobs (e.g., flipping burgers, operating a machine press, detecting cancer, replacing broken parts, driving cars).
Design thinking is a human-centric approach that creates a deep understanding of and empathy for users. This allows you to generate ideas, build prototypes, share what you’ve made, embrace learning through failure, and put your innovative solution out into the world (see Figure 1).
Figure 1: “Design Thinking Humanizes Data Science”
The “empathize” stage of design thinking is particularly critical, as it sets the frame around which we can apply creative and innovative thinking and exploration to come up with different, relevant, and meaningful real-world solutions.
The “empathize” stage captures what your users are trying to accomplish (tasks, roles, responsibilities, expectations, gains, and pains). Walk in your users’ shoes by shadowing them and, where possible, actually become a user yourself. That involves understanding: What are their usage patterns and engagement characteristics? What are they trying to accomplish and why? What matters to this person? What are their gains or sources of value in their endeavor? What are their impediments to success (pains)? What frustrates them most?
Answering the questions
So, let’s get back to those original questions, posed in Part 1 of this series, with my answers. (You can grade me and send me my score so that I can see what colleges I am qualified to attend.)
Will AI create an environment where design-thinking skills are more valuable than data science skills?
Yes. As AI and its associated deep learning, machine learning, and reinforcement learning capabilities continue to expand almost exponentially, the challenge with AI won’t be building AI models that work. The challenge will be in defining and codifying the difference between “right and wrong” in order for the AI rational agent to make “intelligent” decisions. I expect that one day soon, auto-ML/auto-AI capabilities will expand to the point where AI models can build themselves and will rely upon humans only to define the criteria (AI utility function) against which to optimize performance. And design thinking will play an indispensable role in ensuring that we are building holistic, coherent, and intelligent AI utility functions.
Will AI alter how we define human intelligence?
Yes. Since AI models can be shared and reused and learn without human intervention (see “Crossing the AI Chasm with Infographics” blog), this will allow humans the time and perspectives to build out the skills and capabilities that make humans human. Design thinking will play a critical role in helping humans blend, bend, reframe, ideate, and innovate in ways that AI models cannot.
Will AI force humans to become more human?
Yes. The people who will thrive in the future are those who excel with their ability to empathize, define/refine, ideate, prototype, test, and learn about the human condition – the key capabilities that design thinkers with their black bag of incantations have mastered. And the understanding, articulation, and formulation of the human “ethics equation” will become even more important as AI forces humans to actually become more human.
It’s interesting that the technology that potentially threatens so many human jobs might actually be the technology that forces humans to become more human.
As technology embeds deeper into our lives, companies need to elevate the role of people and culture.
This article originally appeared on LinkedIn and is republished by permission.