A Trickster’s Guide to Artificial Intelligence
PART TWO: Too Wired To Wonder?
“Trickster offers no fixed lesson, only the possibility of new ways of seeing.” —Lewis Hyde, Trickster Makes This World
Loki never planned to get caught. Tricksters never do. They push boundaries, rewrite rules, and stay ahead of the systems meant to contain them. But in one lesser-known myth, the Norse god of mischief falls into a trap of his own invention.
On the run from the other gods, Loki transforms into a fish, too slippery to catch by hand. But the pursuing gods find something unexpected in his abandoned home: a tangled web of knotted string Loki left behind. Always anticipating the next move, Loki had invented the world’s first fishing net—not as an oversight, but as a calculated act of trickery. He understood that to escape a trap, one must first understand how it works.
Yet Loki failed to anticipate that his ingenuity could be turned against him. The pursuing gods, recognizing the net’s purpose, replicate it, drag the river, and ensnare him. His creation—the tool meant to outmaneuver his pursuers—becomes the instrument of his capture.
Loki’s impulse was right: innovation demands that we think several moves ahead. But when creativity is not paired with foresight, even the cleverest strategies risk collapsing under the weight of unintended consequences. If miscalculated, the same tools we build for advantage can become the nets that entangle us.
That’s the challenge artificial intelligence presents today to developing America’s Creative Brain Capital. It started as a tool—designed to capture knowledge, automate processes, and eliminate friction. And like Loki’s net, it works. Maybe too well.
AI makes thinking easier, but we stop questioning if we lean on it too much. If we offload too much to machines, we risk diminishing the very skills that make AI valuable in the first place—curiosity, creativity, and independent thought. But the real danger isn’t that AI will replace human intelligence. It’s that we won’t learn how to use it wisely.
The choice isn’t between AI and humans. It’s whether we design a future in which AI expands human ingenuity or subtly erodes it. Balance is the key.
Here’s to the Crazy Ones
“Trickster is a boundary-crosser. Every group has its edge, its sense of in and out, and trickster is always there at the gates of the city, if not outside the walls.” —Lewis Hyde, Trickster Makes This World
Like the trickster, AI lives at the edges of knowledge. It supports the trickster’s efforts to test, deconstruct, and remake the boundaries of what is possible. Just as tricksters force societies to evolve by challenging rigid structures, AI pushes business, culture, and creativity into new, unpredictable territory.
Steve Jobs understood this kind of moment. When Apple launched its “Think Different” campaign in 1997 (video below), the message wasn’t just about marketing computers—it was about reclaiming the trickster’s role in shaping the future.
“Here’s to the crazy ones,” the ad proclaimed. “The misfits. The rebels. The troublemakers. The round pegs in the square holes.” The people who refuse to let existing systems define the limits of what was possible.
Tricksters don’t just break rules; they bend them to reveal new paths forward. That’s what’s at stake now with AI. Will we lead its evolution, question its assumptions, and use it as a tool for deeper, more original thinking? Or will we let it dictate the boundaries of creativity, reducing us to passive consumers and managers of machine-generated knowledge?
Loki’s mistake wasn’t building the net. It was forgetting to stay ahead of it. AI isn’t an enemy—it’s a tool. But if we fail to use it actively, creatively, and critically, we risk being caught in a system of our own making.
The Big Shift: AI and Human Thinking
“Trickster is the mythic embodiment of ambiguity and ambivalence, doubleness and duplicity, contradiction and paradox.” —Lewis Hyde, Trickster Makes This World
AI is paradoxical: depending on how we use it, it can amplify and limit human intelligence. It can make thinking easier, but if misused, it can dull the skills that make innovation possible. This duality demands that leaders and creators stay agile, skeptical, and adaptive.
Every major technological leap—writing, the printing press, calculators, the internet—has sparked the same concern: Does this make us sharper thinkers, or does it make thinking obsolete?
Socrates, who famously declared that wisdom begins in wonder, also feared writing would weaken memory, just as modern critics worry AI will erode critical reasoning. While there is no question that the magnitude of AI (and quantum computing) is unlike any technology before, the tension is nothing new; progress and doubt have always evolved together, a paradox at the heart of human innovation.
Despite the uncertainty, workers aren’t relying on leaders to create opportunities; many are taking their upskilling into their own hands.
The World Economic Forum’s (WEF) 2025 Future of Jobs Report notes that by 2030, nearly 40% of today’s workforce skills will be transformed or outdated. While AI/Big Data has risen to #11 on the list, the top ten must-have skills for thriving in the future of work are distinctly human-focused:
Analytical Thinking: The ability to logically evaluate information, identify patterns, and solve complex problems.
Resilience, Flexibility, and Agility: The capacity to adapt effectively to change, recover from challenges, and remain productive in dynamic environments.
Leadership and Social Influence: The skill to inspire, guide, and motivate individuals or teams to achieve shared goals.
Creative Thinking: Generating novel and valuable ideas to address problems or opportunities.
Motivation and Self-Awareness: Understanding and managing your emotions while sustaining the internal drive to achieve goals.
Technological Literacy: Understanding and using technology effectively in various contexts.
Empathy and Active Listening: The capacity to understand and share the feelings of others while attentively engaging in communication.
Curiosity and Lifelong Learning: A proactive desire to continuously explore, learn, and grow.
Talent Management: The ability to attract, develop, and retain skilled individuals to enhance team performance.
Service Orientation and Customer Service: The focus on meeting the needs and expectations of others to deliver value and satisfaction.
These ten skills are vital because they foster collaboration, adaptability, and creative performance within teams and organizations. Across the board, critical thinking is a key element. However, empirical evidence on how AI may influence critical thinking has been somewhat limited—until now!
A new 2025 study conducted by Microsoft, Carnegie Mellon, and Cambridge examined professionals using AI-powered tools like ChatGPT and CoPilot. It posed a crucial question: As AI handles more cognitive tasks, are we improving our critical thinking ability?
The answer? It depends on how we use it.
Key Findings From Study: AI’s Dual Impact on Critical Thinking
AI Reduces Cognitive Effort, but Also Critical Reflection
AI removes friction, making tasks like summarizing data or drafting ideas faster.
But easier doesn’t always mean better—if we stop engaging deeply, we risk losing complexity in our thinking.
Confidence in AI vs. Confidence in One’s Own Skills
People who trust AI blindly tend to engage less critically.
Those who trust their own expertise use AI as a sparring partner, questioning and refining outputs.
AI Reshapes How We Engage with Information
Recall & Comprehension: AI shifts our focus from learning to verifying.
Application: AI makes execution faster but can weaken independent problem-solving.
Analysis, Synthesis, & Evaluation: AI helps with oversight, but human creativity is still needed for breakthroughs.
AI Literacy Determines Its Impact
AI isn’t the problem—how we train people to use it is.
Many professionals don’t yet have the skills to interrogate AI-generated content, making them more likely to accept outputs uncritically.
If AI increases speed but decreases scrutiny, we are training a generation to accept rather than analyze. The problem isn’t AI itself—it’s how we integrate it into human learning and decision-making.
The Trickster’s Role: Keeping Culture and Creativity in Motion
“Without the play of the trickster, the world stagnates, repetition ossifies, and we forget that culture must be in motion to stay alive.” —Lewis Hyde, Trickster Makes This World
AI, when over-relied on, risks creating stagnation rather than transformation. Why? AI is trained on past data that will reinforce what already exists rather than inspire the unexpected.
Cognitive scientist Margaret Boden, a leading researcher in artificial intelligence and creativity, is widely recognized for her seminal work, The Creative Mind: Myths and Mechanisms (1990, 2nd ed. 2004). Her framework for understanding creativity—particularly the distinction between P-creativity (personal creativity, which is new to an individual but not necessarily to the world) and H-creativity (historical creativity, which introduces ideas never seen before)—has been foundational in cognitive science and AI research.
Boden was one of the earliest scholars to systematically explore how computational models can simulate aspects of human creativity, shaping discussions in artificial intelligence and psychology. Her research highlights a fundamental limitation of AI: while machines can generate, remix, and refine based on existing knowledge (P-creativity), they struggle with H-creativity—the kind of originality that breaks from precedent and redefines what’s possible.
Boden’s distinction between P-creativity and H-creativity shows that AI naturally favors recombination rather than originality. It works within established patterns rather than breaking them, and this is precisely where the trickster mindset becomes essential.
The trickster’s role is to keep culture in motion—not just by refining the past but disrupting it in ways that lead to paradigm-shifting breakthroughs—what Boden would call H-creativity.
The key question, then, is whether AI will simply reinforce P-creativity (remixing what already exists) or whether human intervention will ensure AI is a tool for fostering H-creativity (breaking loops, forging new paths, and expanding the limits of possibility).
Will AI be used to accelerate “knowable,” predictable iterations—or will leaders use it to amplify the kind of creative risk-taking that drives real innovation?
By framing AI’s limitations through the lens of historical creativity, this sets up the central challenge for culture, business, and media:
Culture (Arts) – Creativity’s Inflection Point
✅ AI helps artists draft faster, generate ideas, and remix styles.
⚠️ But AI also leans on past patterns, making true originality harder to find.
Great art has always emerged from friction, struggle, and unpredictability. If AI removes too much friction, are we also stripping away the weird, the radical, the unexpected?
Commerce (Business) – Efficiency vs. Innovation
✅ AI optimizes business decisions using data-driven insights.
⚠️ But when companies rely only on AI-driven analysis, they tend to play it safe, reducing breakthrough innovation.
The next great company won’t be built on AI insights alone—it will be built by leaders who know when to follow AI’s logic and when to defy it.
Media – The Age of Algorithmic Truths
✅ AI can fact-check, summarize, and automate content production.
⚠️ But it also reinforces engagement-driven narratives, amplifying bias and filtering what people see.
The danger isn’t just AI creating misinformation—it’s AI shaping reality in ways we don’t even notice.
A Model for Balance
“The best tricksters work with and against the order of things, opening gaps between what is and what could be.” —Lewis Hyde, Trickster Makes This World
AI should not be a replacement for human creativity, but a tool that expands possibilities. The companies and leaders who thrive in the AI era will be those who know when to work with AI—and when to push against its tendencies toward pattern reinforcement.
Tricksters aren’t just disruptors; they are explorers of possibility, always testing boundaries and forcing new ways of thinking. To keep AI in service of human-led exploration, we need to keep what I call Discovery Mode front and center.
Technology does not invent. It does not dream. It does not wonder. That’s our job.
Wonder: AI predicts, but humans ask What if?
Trust: AI processes, but humans foster collaboration.
Freedom: AI optimizes, but humans take creative risks.
Joy: AI helps feed engagement, but humans experience discovery.
The future does not belong to those who automate the past. It belongs to those who use AI to expand human creative potential—not replace it. The real choice ahead isn’t human vs. machine. It’s whether we build a future where AI helps us think better—or one where we let it think for us.
AI’s promise is enormous. But to realize it, we must remain engaged, skeptical, and willing to break the patterns AI tries to reinforce. The tricksters of the future won’t fear AI. They’ll bend it, break it, and reimagine it. The future of creativity isn’t about machines replacing us. It’s about making sure we never stop wondering.
Five Tips for Business Leaders to Lead With Wonder
“The road runs on because it is not fenced. If there is a gate, it is open; if there is a boundary, it is permeable. The road is an invitation to an unbounded experience.” —Lewis Hyde, Trickster Makes This World
Just as tricksters thrive on the open road, successful businesses must resist rigid, closed systems that rely too heavily on AI-driven optimization. The companies that lead with wonder will be the ones that keep the road open—for exploration, surprise, and the creative interplay between humans and technology.
The next big idea won’t come from a lone genius. It will come from companies with the creative know-how to LEAD WITH WONDER—where human imagination and AI-driven insights work together to unlock transformational innovation. Here’s how business leaders can align with Creativity America’s five action areas to future-proof their organizations.
1. Build Shared Mental Models for Creative Leadership
Streamline vision and communication to create a foundation for sustained collaboration.
✅ What to do:
Establish a common language for creativity across teams to reduce silos.
Use AI tools to synthesize insights, but ensure humans make meaning from them.
Develop decision-making frameworks encouraging curiosity, experimentation, and risk-taking at all levels.
⚠️ What to avoid:
Letting AI dictate company direction instead of using it to expand strategic vision.
Assuming that alignment happens automatically—creativity needs structure to scale.
2. Invest in Future-Proofed Talent With Creative Brain Skills
Ensure long-term relevance and success by developing AI-augmented problem solvers.
✅ What to do:
Train employees in adaptive thinking, complex problem-solving, and creative synthesis—the skills that make AI a tool, not a crutch.
Encourage interdisciplinary learning—AI may streamline work, but deep expertise across fields fuels breakthrough ideas.
Expand beyond efficiency-based metrics to include learning-based metrics—reward exploration, not just productivity.
⚠️ What to avoid:
Hiring only for technical skills while overlooking imagination, curiosity, and creative confidence.
Human creativity is innate—but it's the teachable creative brain skill sets that cultivate it, especially in an AI-driven world.
3. Design Co-Creative Ecosystems That Balance Logic and Emotion
Bridge human culture and technology to create environments where AI and people enhance one another.
✅ What to do:
Use AI as a sparring partner, not a dictator—ensure teams actively engage, refine, and challenge AI-generated ideas.
Prioritize trust-building in AI collaborations—people must feel safe questioning AI, not just relying on it.
Foster multi-perspective decision-making—combine data-driven logic with human intuition and emotional intelligence.
⚠️ What to avoid:
Over-relying on AI to replace human-driven ideation, strategy, and insight.
Ignoring the emotional and cultural aspects of innovation—they are what turn ideas into movements.
4. Develop Creative & Strategic Foresight
Anticipate culture trends and navigate uncertainty with creative strategy as a competitive advantage.
✅ What to do:
Train teams in scenario planning—AI can support trend analysis, but humans must interpret and act on the information.
Encourage pattern recognition—AI finds correlations, but people make connections that lead to transformative insights.
Embed future thinking into daily decision-making—great companies don’t react to change, they shape it.
⚠️ What to avoid:
Letting AI-generated insights become a shortcut instead of a starting point for deeper exploration.
Focusing only on short-term optimization—AI accelerates execution, but foresight requires long-term vision.
5. Systematize Creative Know-How for Adaptable Innovation
Integrate culture, commerce, and brain science to drive innovation performance.
✅ What to do:
Build processes for continuous ideation—use AI for efficiency but design structures for originality.
Combine scientific rigor with artistic intuition—AI enhances data-driven decisions, but creativity drives cultural relevance.
Measure innovation performance beyond productivity—track the depth, originality, and long-term impact of ideas.
⚠️ What to avoid:
Assuming creativity is unstructured and chaotic—empirical research has proven that innovation comes from disciplined creative systems.
Ignoring human motivation—AI can automate tasks, but only people can create meaning.
Agile Imagination: The Other AI
“The agile mind is pleased to find what it was not looking for.” —Lewis Hyde, Trickster Makes This World
AI can help businesses optimize—but only human minds can wonder, imagine, and embrace the unknown. The future will belong to those who stay open to serendipity and who see AI not as an endpoint but as a spark for new ways of thinking, working, and creating.
AI is a powerful amplifier, but how it is used will determine whether it fuels transformational breakthroughs or incremental optimizations. Wise business leaders will foster a culture of creativity, wonder, trust, freedom, and joy. An innovation culture that uses AI to enhance, not replace, human imagination.
The future belongs to those who don’t just follow trends but create them. The entrepreneurs, artists, companies, and cities that thrive in the AI era will be the ones that understand how to operate like the trickster… “the crazy ones, the misfits, the rebels… the ones who see things differently… because the ones who are crazy enough to think that they can change the world, are the ones who do.”
My Other Places, Other Frames
Culture Futurist Substack: Business, Innovation & Future of Work
Poetry Substack: Culture Kudzu: Poetry for Entrepreneurs -
Professional: Creativity America
Personal: Culture Futurist
Theo Edmonds, Culture Futurist® & Founder, Creativity America | Bridging Creative Industries and Brain Science with Future of Work & Wondervation®
©2021-2025 Theo Edmonds | All Rights Reserved. This article contains proprietary intellectual property. Reproduction, distribution, or adaptation, in whole or in part, requires accurate attribution. The views expressed are those of the author and do not necessarily reflect those of any affiliated organization or institution.
“Assuming creativity is unstructured and chaotic—empirical research has proven that innovation comes from disciplined creative systems.”
Theo, could you provide an example of what you mean by disciplined creative systems? Thanks!