When AI Meets Design Thinking

My professional work has never just been a "job." It's my launching pad for transforming the world around me.

During my 20s, while working as a journalist, I tried to break down, simplify, and explain complex and interconnected local, state, and national political issues.

As a United Methodist pastor in my early-to-mid-30s, I encouraged people to transform their lives—and, ultimately, change many of their embedded behaviors—through the prism of a specific set of spiritual teachings.

Across two years as a financial advisor with Morgan Stanley, during my mid-to-late 30s, I aimed to influence clients to “think beyond the immediate” and implement long-term investment planning for a more secure financial future.

And for just under 20 years, as a human resources professional, I leveraged coaching, consulting, speaking, and writing with the goal of transforming leaders and organizational cultures.

Mathematician and designer Horst Rittel coined the term “wicked problem” to describe a situation that lacks a “final” solution and necessitates less of a scientific approach than creative strategies in the context of embracing ambiguity. Rittel asserted that wicked problems bear incomplete or inconsistent knowledge; involve large numbers of people and viewpoints; present specific and significant economic burdens; and not only interconnect with other problems but are often symptoms of other problems.

“Complex and nuanced”

I’m encouraged that Rittel didn’t just throw up his hands and declare that wicked problems aren’t worth solving. In fact, they are the ones most worth addressing.

Furthermore, Rittel contended that the field of design thinking’s methodical, collaborative approach could unleash collective creativity and innovative ideas through bringing together people of different backgrounds, skills, and experiences.

I prefer to use the phrase “complex and nuanced” regarding the kinds of problems I’m exploring as a professional coach who uses design thinking in his practice. A couple of definitions:

Complex = consisting of many different and connected parts.

Nuanced = characterized by subtle shades of meaning or expression.

Rittel asserted that these sort of problems bear incomplete or inconsistent knowledge; involve large numbers of people and viewpoints; present specific and significant economic burdens; and not only interconnect with other problems but are often symptoms of other problems. Furthermore, Rittel believed that "design thinking" was one of the more effective ways to tackle such problems.

One such problem that's top of mind for me? American workers must develop the motivation and ability to constantly “reinvent themselves," in order to remain viable in an AI-driven economy.

First, some context

Exponential technology, with AI at its core, is rapidly evolving, endlessly converging, and ubiquitously disrupting industries, companies, and careers as it transforms nearly every aspect of how we work and live. As AI’s “capabilities” continue to proliferate, I’m wrestling with a question that is also vexing millions of other people across the United States: “Do my human skills and experiences still matter?”

I’ve always geeked when seemingly disparate topics or characteristics are revealed to be related parts of a greater whole. Correspondingly, I’ve seldom resonated with “either/or,” “good or bad,” “black or white,” etc., types of dualistic thinking.

I find that most ideas, mental models, “isms,” and certainly people are an (often paradoxical) confluence of many things. F. Scott Fitzgerald echoed this observation when he asserted that “the test of a first-rate intelligence is the ability to hold two opposed ideas in mind at the same time and still retain the ability to function.”

There’s a lot of unhelpful duality today regarding AI. The conversation often focuses on one extreme or another: how AI is the greatest thing ever and will definitely change the world for the better, versus how AI spells doom for jobs, society, and civilization as a whole.

Human-AI collaboration

In reality, the conversation should focus on how each of can leverage AI’s potential while helping to mitigate its risks. I think it’s crucial and urgent for each of us to become fluent in how AI is transforming our respective professions and find daily, ongoing ways to collaborate with AI.

The combination of human skills and AI skills can create a synergistic effect, leading to outcomes that are better than the sum of their individual parts. Here’s just three examples among many:

First, humans bring creativity, emotional intelligence, and complex problem-solving abilities, while AI excels in data processing, pattern recognition, and automation. By combining these strengths, organizations can address a broader range of tasks and challenges.

Second, AI can process vast amounts of data quickly and provide insights, while humans contribute contextual understanding, intuition, and ethical considerations. Together, they can make more informed and well-rounded decisions.

Finally, humans are responsible for setting ethical guidelines and values. Collaborating with AI requires human oversight to ensure that decisions align with ethical standards and societal norms.

The key is to view AI as a tool that complements human capabilities rather than replaces them. When integrated strategically and ethically, the collaboration between human skills and AI skills can lead to more efficient, innovative, and impactful outcomes.

Furthermore, effective AI collaboration rests upon professionals developing competencies such as business acumen; communication skills like influence, negotiation, networking, relationship building, public speaking, storytelling, and writing; learning agility; and a “suite of thinking skills” that encompasses creative, critical, design, exponential, innovative, integrative, lateral, strategic, systems, and visionary thinking.

American workers who demonstrate these abilities better than others will increasingly differentiate themselves from the rest of the pack. But that gives them only limited reason to celebrate, because if the majority of the American workforce is “left behind” society will unravel, and everyone will lose.

Some will just lose less than others.

What’s so “complex and nuanced” about this problem?

There’s incomplete and inconsistent knowledge, regarding AI-specific capabilities and potential impacts; which jobs to sunset and which new jobs to create; which specific skills American workers must prioritize in their development; and how to go about training and developing these workers.

This situation involves large numbers of people and viewpoints, with just under 168 million Americans currently in the workforce.

There’s a significant economic burden, with just one example being the costs that companies face in training current or new employees to thrive in these new roles.

This issue is interconnected with, and symptomatic of, other issues; too many for a comprehensive listing but some that are top of mind include the dynamics of diversity, equity, and inclusion; the efficacy of universities and job-training programs; organizational cash-flow and profitability; and shareholder expectations.

There are differentiated values at play, such as conflicting ways that people identify and prioritize which jobs to sunset, which ones to keep, and which ones to create; the most critical skills to develop; and the most pragmatic and ethical way to support employees who have significant skills gaps.Each person—in this case, each American worker—is unique, with their own diverse backgrounds, ambitions, strengths, weaknesses, advantages, disadvantages, and so much more.

Design thinking toward potential solutions

As I tackle this problem in my work with clients, I’m applying the phases of the aforementioned design thinking in the following manner:

Empathize: I can relate to the massive, ongoing change and uncertainty most American workers are experiencing and feeling in this age of AI.

Define: Implementation of AI is leading many employers to sunset existing jobs and create one ones with very different skill sets. American workers must continue to grow and develop in order to compete for these jobs, and organizations suffer when they’re not able to obtain the talent they need for these roles.

Ideate: Effective, ongoing professional coaching, as part of an organization’s people strategy (and business strategy!) can help top executives grow their own skills and equip their direct reports to do the same (and to replicate these efforts down the “food chain”).

Prototype: I’ve rolled out an MVP version of my coaching practice to experiment with and implement my ideation.

Test: Each day, as I fine-tune my business plan and focus on business development, I’m noticing the real-time results of attracting (or not attracting) new coaching clients. In addition, I’m seeking and implementing, in the context of constant iteration, balanced feedback from professional colleagues across various disciplines.

Let’s connect

I’m an ICF and Hogan certified coach, equipping professionals to develop their authentic human leadership capabilities in the age of AI. My customers are internal HR or L&D professionals seeking coaching for their business clients, as well as business leaders looking to connect directly with a coach for themselves or their team members. Use this link to schedule a call with me to discuss potential coaching services. You can also email me (john@johnmdemarco.com) or message me here on LinkedIn.