In a recent episode of Hello Monday, Jessi Hempel interviews Dr. Natalie Nixon on creativity and her new book, The Creativity Leap. Natalie’s PhD in Design Management—plus her work in fashion, design, and business—led her to a catchy and compelling description of creative work. We accomplish creative work, she says, “by toggling between wonder and rigour.”
In the podcast conversation, Jessi and Natalie talk about intuition—and I was struck by something. “We don’t talk about intuition,” Natalie notes at about 6 minutes in. “We don’t talk about intuition in business school, in law school, or in medical school.” And yet, she says, “I observed that really successful leaders—especially really successful startup leaders—in their origin stories, there’s always this moment where ‘Something told me not to do the deal. Something told me to work with her over him.’ […] Every successful leader really reckons with incorporating acting on their intuition to make decisions.” Jessi agrees, noting that intuition comes up often in her interviews with leaders on Hello Monday as leaders cite it as the reason for their success.
The thing is, just because we don’t name intuition doesn’t mean we aren’t talking about it. That’s because intuition is really just confident, logical thinking.
Charles Sanders Peirce was a philosopher. He investigated how we inquire into and discover new knowledge.1 Before Peirce, we generally recognized the logical processes of deduction and induction. Deductive thinking helps us identify what must be true about a situation in order to explain it. When we deduce something, we look at the general rules and principles we know of and draw specific conclusions from that evidence. Inductive thinking involves drawing general conclusions from specific, limited evidence.
Peirce argued that effective reasoning follows a pattern: we determine the specific consequences of an idea (deduction), and then we judge whether the available evidence fits that idea and its consequences (induction). But how do we develop ideas?2
Abduction is the name of the logical process Peirce described for developing ideas. To think abductively means to generate and choose ideas that fit the situation at hand. A good idea should be verifiable—we should be able to use evidence to judge its fit—and should help us resolve the situation at hand. Peirce also had criteria to help choose the best ideas to test. He suggested that we should strive to conserve resources (e.g., those that most are most efficiently verifiable and usable in the situation), identify the most valuable ideas (specifically the “uberty” of an idea, or how likely it is that a possible idea might bring about an innovation), and the most relevant ideas (e.g., those that may apply beyond our current focus, too).3
Abduction is clearly an important step in any innovative process—but it is no more important than testing and using the ideas you generate. What, then, if you don’t have enough evidence to truly test and prove your ideas?
The process Peirce described—abduction, deduction, induction—is the ideal. However, we do not always have time and energy to follow the process diligently. Instead, we quickly make creative judgements based on a few observed qualities. This requires two related processes.4 The first Peirce called “abductory induction,” and it combines the first and last step of the inquiry process. We observe the qualities of the situation, and we generate possible ideas to resolve it based on those observations. The second process is known as “inference to the best explanation” (IBE).5 IBE is exactly what it sounds like. Given a number of possible ways of resolving a problem, choose the best one. (Peirce’s criteria, noted above, apply here.)
So what does all this have to do with intuition?
Intuition is the confident application of these shorthand logical approaches to creative problem solving. As Jessi and Natalie noted, we aren’t often explicitly taught about strengthening our intuition. Yet, everything we learn supports its development. The more we have to draw on in order to pull into the processes described above, the better our intuitive decisions will be.
I say that intuition is the confident application of these processes because they only work when we follow through. In reality, we use abductory induction and IBE all the time. When we engage in creative problem solving, we’re not only using information from the evidence in front of us. We’re drawing on our lived experience and our knowledge base. Even if we don’t directly recall or reference that background information, it is drawn into the creativity of abduction and it defines the general rules and principles we use in deduction. It provides us with the heuristics we use when engaging in IBE. But if we don’t have a bias towards action and instead operate with e.g., perfectionism, we fail to actually execute on these ideas. Thus, we need to have confidence in our abductory induction and IBE processes.
All this is simply a gentle challenge of the idea that we don’t talk about intuition. I think that all knowledge management practices and forms of education are actually fundamentally about strengthening our intuition.
That said, Natalie’s work is fascinating. I recommend the episode of Hello Monday and plan on picking up her book!
Peirce was actually specifically concerned with science and hypotheses generation, selection, and testing. Here I refer to generating, selecting, testing, and using ideas to apply these concepts to problem-solving more broadly.↩︎
He also cautioned not to produce ideas that stop the inquiry process—e.g., magical thinking, or by suggesting that whatever happened must be a complete mystery.↩︎
Actually, the difference between these two processes is the subject of substantive, controversial debate. This is in part because the scholars who study inference to the best explanation have also used Peirce’s term “abduction” to describe it. This understandably caused extensive confusion, but also probably a lot of philosophical debates and scholarship, so maybe it was for the best.↩︎
One of the core issues of the talk is innovation doubt—the “if it ain’t broke, don’t fix it” mentality. To paraphrase Piret:
[…] why are we doing innovation at all? Maybe sometimes things are working fine, why do we think about innovation at all? We start off with four questions:
- Do you want to do things better?
- Do you have goals and purposes to fulfill?
- Do you want to address the needs of your stakeholders?
- Do you want to prepare for the risks and uncertainties that the future holds? If you answered “yes” to at least one of those questions, then your job is to do innovation—your job is to be a changemaker.
Also, the talk includes a neat model for different varieties of innovation, image courtesy of this post by Adrian M. Senn over on Medium:
In the next three years, as many as 120 million workers in the world’s 12 largest economies may need to be retrained or reskilled as a result of Artificial Intelligence (AI) and intelligent automation.
cf. Lee Se-Dol.
This is according to the latest IBM Institute for Business Value (IBV) study, titled The Enterprise Guide to Closing the Skills Gap.
Seems like an interesting guide. This metric surprised me:
In 2014, it took three days on average to close a capability gap through training in the enterprise. In 2018, it took 36 days.
I didn’t know this measure existed, but I can see the utility. As knowledge work grows ever more specialized, this time-to-capability can only grow.
In two senses, the work of innovation for public value and social impact is changing in Australia and around the world. What we expect public innovation to do and what we need it to achieve, and how that work should be done, are both changing. And they are changing together while they are changing each other.
It’s true. It’s hard to keep up with the discipline of changemaking, but it’s even harder to keep up with the change that needs to be made. Therefore Martin Stewart-Weeks calls for optimism:
Despite some of the uncomfortable and unsettled conditions, there is real energy in the search for more effective ways to solve the big problems we face in common — managing our complex cities, rewiring large and complex health and social care systems, tackling climate change, searching for better ways to integrate the human and technology capabilities of the digital age and making our communities healthy and resilient.
The speed, intensity and sheer connectedness of these and many other complex, public challenges are giving rise to new methods and tools that can help to tackle them with purpose and skill.
The ever-refreshing Paul Jarvis shares some uncommon thoughts on productivity in Jocelyn K. Glei’s Hurry Slowly podcast.
In particular, Paul and Jocelyn discuss the importance of resilience. Citing research and his own experience, Paul points out that resilience is a more important factor in success than many others.
Obviously, though, enabling resilience is not as easy as simply pointing out how important it is. As they discuss, resilience isn’t something innate—which means that it can only be developed through experience. And this is where things get tricky: who gets to have resilience-building experiences?
In my research on innovation skills, I discovered that resilience was one of three key domains that wasn’t an important outcome for our public education systems. This means that resilience training isn’t necessarily a public good. Only if you’re lucky (or privileged) will you have the chance to build up your resilience muscle.
innovation doesn’t happen in isolation.
Great ideas come alive when groups of passionate people come together to inspire, support and collaborate. From Stockholm and Tel Aviv to Seoul and Berlin, and of course, Silicon Valley — we have seen, time and time again, the benefits that such rich ecosystems bring entrepreneurs.— Innovation must involve all Canadians to succeed
Warren Buffett manages to entertain and inform in his 2015 letter to shareholders.
(This quote comes from Mr. Buffett’s discussion on the unpredictable but beneficial technologies that come from market-driven innovation.)
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