Guido Palazzo is the author of The Dark Pattern and a Professor at the University of Lausanne in Switzerland . You can follow him here on LinkedIn.

In this conversation, Guido Palazzo discusses his book ‘The Dark Pattern’ and critiques the prevailing neoliberal ideology in business education. He emphasizes the systemic nature of corporate scandals, arguing that unethical behavior often stems from contextual pressures rather than individual character flaws.

Guido shares his personal journey, influences, and evolving perspectives on the future, advocating for a more collaborative and ethical approach to leadership and organizational behavior. He introduces the concept of the ‘bright pattern’ as a counter to the dark patterns observed in corporate scandals, highlighting the importance of treating individuals with dignity and fostering a culture of ethical dialogue.

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Next on Part-Maven Part-Maverick, we will speak with Brett Gardner about Buffett’s Early Investments.

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Musa al-Gharbi is the author of We Have Never Been Woke: The Cultural Contradictions of a New Elite and an Assistant Professor at Stony Brook University. You can follow her here on Substack and LinkedIn.

Join us for an insightful conversation with Musa al-Gharbi as we dive into his critically acclaimed book and its exploration of social justice, elite influence, and the dynamics within academia.

Musa shares his unique journey from studying to be a Catholic priest to selling shoes, and how these experiences shape his approach to research and writing.

We discuss the divide between the symbolic capitalists and the general populace and how elite interests often clash with genuine social justice work.

Musa also unpacks the role of language in societal divisions and the importance of focusing on practical solutions over symbolic gestures.

Don’t miss this compelling episode that challenges the status quo and offers fresh perspectives on how we can drive meaningful change.

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Next on Part-Maven Part-Maverick, we will speak with Guido Palazzo about The Dark Pattern.

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Marc Hijink is the author of FOCUS The ASML Way and a technology reporter and columnist at NRC Handelsblad. You can follow him here on LinkedIn.

In this episode of Part Maven, Part Maverick, we welcome Marc, the author of ‘Focus the ASML Way,’ to discuss the rise of ASML and its pivotal role in the semiconductor industry.

Marc shares his insights into the personal stories and cultural background that built ASML’s success.

We dive deep into the company’s history, its long-term relationships, and how it has navigated geopolitical and market challenges.

Marc helps us understand ASML’s unique company culture, built on collaboration and innovation, and its focus on continuous improvement and customer alignment.

Tune in to explore how ASML’s strategic decisions, including its partnerships, R&D investments, and operational strategies, have positioned it at the forefront of global high tech.

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Next on Part-Maven Part-Maverick, we will speak with Musa Al-Gharbi about We Have Never Been Woke.

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Doug Guthrie “The China Whisperer” is the author of China and Globalisation, and Dragon in a Three-Piece Suit and a Professor at Thunderbird School of Global Management at Arizona State University. You can follow her here on LinkedIn.

In this insightful episode of 'Part Maven, Part Maverick,' we sit down with Doug Guthrie, famously known as Apple’s 'China Whisperer,' in Patrick McGee’s book Apple in China, to explore the intricate relationship between China and global businesses. Guthrie, who has authored several books on China and has held prominent academic and corporate positions, shares his journey—from studying Chinese language and literature to advising Apple in China. The discussion delves into the critical role of strategic learning, China’s sophisticated manufacturing supply chains, and its effective industrial policy. Guthrie also provides an in-depth look at the role of Apple University, China’s global ambitions under Xi Jinping, and the geopolitical implications of current U.S.-China relations. This episode sheds light on the evolving landscape of global trade, the importance of humility in learning, and the potential future of democracy in China. Join us as we unpack these complex dynamics with an insider's perspective.

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Next on Part-Maven Part-Maverick, we will speak with Musa al-Gharbi about his book We Have Never Been Woke.

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Allison Taylor is the author of Higher Ground and a Clinical Professor at NYU Stern School of Business. You can follow her here on LinkedIn.

Prateek Raj is the author of Atypical and an Associate Professor of Business and Health at UCL. You can follow him here on LinkedIn.

In this insightful conversation, Alison Taylor and Prateek Raj discuss their respective books, focusing on their fundamental disagreements with the status quo in corporate responsibility and ethics. They explore the issues of jargon, misleading consultancy advice, and the disconnection between ethics, sustainability, and PR conversations. Both stress the importance of empathy-driven, pragmatic multi-stakeholder approaches to business decisions. They criticize the oversimplification in current literature, argue for more holistic frameworks, and emphasize the need for integrating stakeholder perspectives, especially those from marginalized or atypical groups. The episode touches on the misalignment in ESG constructs, advocating for a more nuanced understanding of corporate impact as an open social system rather than a singular entity.

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Next on Part-Maven Part-Maverick, we will speak with Doug Guthrie about what the world can learn from China.

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Patrick McGee is a longtime Financial Times journalist who has reported from Hong Kong, Germany, and California, covering Apple, digital advertising, EVs, and more. His award-winning work has appeared in leading outlets worldwide, and his debut book, Apple in China, draws on 200+ interviews to reveal how Apple’s deep entanglement with China reshaped its future and U.S.–China relations.

Follow Patrick McGee here and order his book - Apple in China here

In this episode, I sit down with Patrick, the author of the thought-provoking book Apple in China exploring the intricate relationship between Apple and China.

Patrick discusses the smart marketing behind his book title, how technology transfer has benefited China more than Apple over time, and the resulting geopolitical implications.

We dive into the manufacturing strategies, the role of Chinese suppliers, and the surprising consequences for global supply chains and national interests.

Additionally, Patrick shares his personal journey, his passion for journalism, and his rigorous research process.

Whether you're interested in business strategies, geopolitics, or simply love a good story, this conversation offers valuable insights into one of the most significant corporate stories of our time.

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Next on Part-Maven Part-Maverick, we will speak with Alison Taylor and Prateek Raj about ethical decision-making in business.

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In probability theory, the word ergodicity has a very precise meaning: it describes systems where, given enough time, the trajectory of a single element is statistically indistinguishable from the behavior of the whole system. In other words, if you wait long enough, one path through time will look like the average across all possible paths.

That sounds abstract, but here’s the kicker: most of the systems we live and work in are not ergodic. And the difference between ergodic and non-ergodic systems explains why so many ambitious people, organizations, and even nations fail to achieve their long-term goals.

Time vs. Ensemble

The best way to think about ergodicity is to distinguish between two types of averages:

* Ensemble average: What happens when you take a large number of possible outcomes at one point in time and average them?

* Time average: What happens when you follow one trajectory through time and average the results across its lifespan?

In an ergodic system, these two averages match. Flip a fair coin enough times, and the average of your flips (heads vs. tails) converges to the same 50/50 distribution you’d get if you flipped millions of coins once.

But in non-ergodic systems, the two diverge. What happens to the “average person” is not what happens to you over time. And here lies the trap: we often mistake ensemble averages for time averages.

Think of a friend who hears that “on average, startups raise millions.” That’s the ensemble average. But over time, one founder’s actual journey might include irreversible bankruptcy if they overextend too soon. The trajectory doesn’t match the average.

Why Survival is Everything

In non-ergodic systems, the key factor is irreversibility. Certain outcomes cannot be undone, and once they occur, they alter the trajectory forever. This makes the time average much harsher than the ensemble average suggests.

For example, consider personal health. You might think that “on average” you can push your body hard, skimp on sleep, and still bounce back. But if you suffer a serious injury or burnout, the trajectory changes permanently. You don’t get infinite retries; the damage carries forward.

This is why survival is not just a condition for performance; it is the overriding constraint of any long-term endeavor. The difference between systems that allow you to “bounce back” and systems where certain failures end the game is the difference between ergodic and non-ergodic thinking.

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Leadership For Non-Ergodicity

Leadership, too, must be grounded in ergodic awareness. When you are responsible for an organization, you’re not managing a static distribution of possibilities—you’re guiding a trajectory over time. Decisions that look costly in the moment may be essential because they prevent irreversible outcomes or because they compound cultural capital for the future.

Imagine a manager who refuses to compromise on ethical standards in order to land a big client. In the short term, revenue is lost. But in the long term, the organization builds a reputation for integrity that attracts better opportunities. That one “loss” prevents the irreversible outcome of reputational collapse and allows the trajectory of the company to keep improving.

What separates sustainable organizations from fragile ones is not quarterly performance but the ability to absorb shocks without collapsing. Leaders who understand non-ergodicity act accordingly: they trade off some immediate efficiency for resilience, signaling through their actions that the preservation of the game itself takes priority over maximizing this particular round.

The full conversation with Luca Dellanna:

Follow Luca Dellanna here:

https://luca-dellanna.com/

https://www.linkedin.com/in/dellannaluca/

https://substack.com/@lucadellanna

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How I Apply This to my Life Right Now

Below is a summary of the key ideas that I am applying to my life.

Long-Term Games Demand Non-Ergodic Awareness

What does this mean in practice? It means that strategies optimized for short-term gains often collapse in the long run, because they ignore the absorbing nature of certain risks. Maximizing each individual step as if it were independent is an error; the outcomes accumulate, and some outcomes foreclose future opportunities.

To play a long-term game well, the goal is not to maximize every move but to construct a trajectory that remains viable over time. That requires:

* Risk reduction: not eliminating all uncertainty, but specifically reducing the kinds of risks that are irreversible. For instance, a career setback like missing a promotion can be temporary, but destroying your reputation through dishonesty can permanently close doors.

* Compounding assets: focusing on things that grow with time—skills, relationships, reputation, trust—because these allow your trajectory to keep improving without relying on a perfect sequence of short-term wins. Just as steady deposits into a retirement account build compounding wealth, daily learning or nurturing a professional network compounds into opportunities that short-term optimizers overlook.

* Temporal patience: giving problems and opportunities a horizon of months or years, not days, because longer timeframes allow for strategies that minimize irreversibility while still moving you forward. Training for a marathon, for example, works best when approached patiently over months; rushing risks injury that can set you back for years.

In short: long-term players think about the time average. Short-term players get seduced by ensemble averages.

Living in a Non-Ergodic World

Understanding ergodicity doesn’t mean we stop aiming high. It means we approach ambition differently. The central insight is that the fastest way to achieve your goals is not by trying to achieve them as fast as possible, but by ensuring you remain in the game long enough to reach them.

Non-ergodic awareness encourages us to:

* Treat health, safety, and trust as non-negotiables. Think of how prioritizing sleep and exercise isn’t about “losing” hours today, but about ensuring your body and mind can sustain decades of productivity.

* Invest steadily in capacities that accumulate over time. The person who reads a little each day or consistently practices a craft isn’t just learning—they’re compounding.

* Avoid irreversible risks, even when the odds look “favorable.” In personal finance, this means not betting your entire savings on a “sure thing.” In relationships, it means not sacrificing trust for a single win in an argument.

* Reframe success as endurance: not just achieving goals, but sustaining the ability to keep playing.

The mathematician might say: “In an ergodic world, time and ensemble are the same.” The strategist must say: “In the real, non-ergodic world, survival shapes destiny.”

That’s the paradox of long-term games: the true path to speed is patience, the true path to performance is resilience, and the true path to winning is making sure you don’t lose the ability to keep playing.

Thanks for reading Part-Maven Part-Maverick! This post is public so feel free to share it.

Next on Part-Maven Part-Maverick, we will speak about China in Apple with Patrick McGee, author of Apple in China.

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https://www.slasog.com/scorecard

https://www.amazon.com/Data-Impact-businesses-LEVERAGE-SIMPLIFY/dp/178133921X

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Germany, the world’s most functional dysfunction, is having an identity crisis. And not the cute kind that ends in a sabbatical in Bali. This is more like a national-level panic attack caused by groupthink and conformism, driven by mercantilism, tied up with red tape, and all of this while being 4 hours late because of Deutsche Bahn.

In their book Broken Republik—and in the excellent podcast episode on Part-Maven Part-Maverick—Bloomberg senior journalists and authors Chris Reiter and Will Wilkes peel back the layers of Germany’s malaise. What they uncover is less about policy and more about the soul of a nation that never quite figured out who it is.

Yes, Germany is an export powerhouse. Yes, it officially balances budgets like a kitty party of Swabian housewives (oh, let’s pretend those special funds and ballooning pension and healthcare social security problems don’t exist). But underneath the mechanical precision is a society that’s emotionally adrift. It knows what it does. It has no clue what it wants. And worse, it’s unwilling to have a serious open-minded discussion to define it’s own vision for the future based on national interests.

Let’s start with the obvious: infrastructure is falling apart, housing is unaffordable, and the dual track eduction system that is increasingly unfit for the data-driven digital paradigm. But these aren’t just technical failures. They’re symptoms of a deeper problem—Germany’s postwar identity vacuum.

The country has struggled with two traumas: the guilt of its Nazi past and the paralysis of Cold War division. The result? A culture that prizes order, avoids risk like the plague, and treats vision as something too vague to bother about.

You see it everywhere: a nation obsessed with cost-cutting but terrified of financial leverage. A welfare state designed to enslave, not empower. A citizenry that rents forever and owns little—modern-day serfs in subsidised housing.

And then there's the question of identity. Or rather, the avoidance of it.

Germany’s real crisis isn’t economic. It’s the inability to ask, “Who are we now?” without immediately spiraling into historical trauma or political binaries. You either follow the mainstream groupthink, or you get labeled: nazi, left lunatic, etc. The most important requirement to blend in is not to ask hard questions about what it means to belong.

Because belonging isn’t just a warm fuzzy feeling. It’s the bedrock of trust, risk-taking, and building things that last. As the podcast notes: you can't design policy, build housing, or even hope for a better future, on a shaky foundation of unresolved identity.

As Chris and Will argue, it’s time Germany embraced its inner Black Forest cake: messy, layered, contradictory, but still a magnificent whole.

A culture of civic imagination—rituals, stories, shared ambitions—might do more for Germany than another 200-page policy white paper. Because regulations don't make people feel seen. Community does.

Germany doesn’t need another commission or ministry. It needs courage. It needs chaos. Maybe even some good old-fashioned Keynesian animal spirits.

Or, to put it less academically: Germany needs to become a little more maverick again. Take risks. Dream big. Stop managing decline and start envisioning the future.

Because in the end, if you don’t know who you are, how do you know where you’re going?

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Watch the full video episode:

Get Broken Republik: https://www.amazon.com/Broken-Republik-Inside-Germanys-Descent-ebook/dp/B0DPML39R3

Follow Chris Reiter: https://www.linkedin.com/in/chris-reiter-56780410/

Follow Will Wilkes: https://www.linkedin.com/in/will-wilkes-42294625/

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What does Agency mean in a German context?

While pondering about the necessity and implications of German identity, I came across this thoughtful post by product leader Jennifer Michelmann: Building Agency Within Cultural Constraints.

After a couple of comments — including by Christian Hansel — and some DMs with Jennifer, I committed to thinking more deeply about this question, and writing a my thoughts down. This is the outcome of that. Thank you Jennifer (and Christian) for showing agency by triggering this conversation and for making me embark on this intense but rewarding journey!

Jennifer’s post hit a deep nerve: the question of agency, the ability to act with intention, courage, and imagination within one’s cultural frame. And if there’s one thing Germany needs right now, it's a rediscovery of its own agency, not as management, not as process, but as a living, breathing national élan.

True agency in the German context isn’t about control or compliance. It’s about wild ambition. And Germany, for all its systems and structures, has lost touch with that sense of wild ambition. But this wasn't always the case.

Otto von Bismarck wielded agency with ruthless clarity, not because he sought power for himself, but because he envisioned a unified German state that could win on its own terms. His genius lay in realism married to vision: a willingness to make messy, imperfect decisions in service of something larger. It was not rigid groupthink ideology that drove him, it was bold and adaptive strategy.

Bertha Benz showed a different kind of agency. Hers was the quiet defiance of a woman who believed in the future of German technology and proved it with a 106-kilometer drive through unpaved roads and public skepticism. She didn’t wait for permission. She acted, knowing that action itself would generate belief. That’s what agency does: it pulls the future forward.

Einstein, too, embodied German agency, not through conformity, but through bold intelligent rebellion. His breakthroughs came from questioning the unquestionable, from imagining what others dismissed as impossible. He didn’t just solve equations. He redefined our view of the universe. That’s the apex of intellectual agency: challenging the rules because you understand them.

Germany today often confuses order with progress, compliance with trust. But agency lives in tension with uncertainty. It demands risk, and it thrives on discomfort. It means saying yes before you’re entirely ready. It means trusting in your ability to figure things out as you go.

So what does agency mean in a German context? It means reclaiming the spirit of Bismarck’s vision, Bertha’s daring, and Einstein’s imagination. It means replacing fear with courage, analysis with action, management with movement.

Germany doesn’t need more optimization. It needs orientation. It needs people who say, “This is what we believe and here’s what we’re building because of it.”

Because agency, in the end, is the opposite of drift. It's direction. It's momentum. And it’s high time Germany remembered that.

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Next on Part-Maven Part-Maverick, we will unpack with Luca Dellanna how life is primarily non-ergodic and what it takes to win long term games.

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Subscribe to be first to know when the episode drops: https://www.youtube.com/@SLASOG

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Get my book Data Impact for a pragmatic take on data-driven value creation for business: https://www.amazon.com/Data-Impact-businesses-LEVERAGE-SIMPLIFY/dp/178133921X/

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Who Wins When AI Reshuffles, Reshapes, and Restacks the Economy?

War is the most ruthless form of competition and the best metaphor for what’s happening in today’s AI-fueled economy. As Sangeet Paul Choudary explains in his new book Reshuffle, the French generals after World War I weren’t foolish. They were simply brilliant in the wrong paradigm. They built the Maginot Line: 450 miles of bunkers, turrets, and underground fortresses. But when German forces launched the blitzkrieg, they bypassed it entirely.

The Maginot Line didn’t fail because it was weak. It failed because it answered the wrong question.

That’s exactly what most companies are doing with AI today: treating it as a high-tech fortification. Bolting it onto legacy workflows and rebrand yourself as “AI-powered”. The real edge doesn’t come from slapping LLMs onto old pipes. It comes from ripping the system open, mapping its friction points, nodes, feedback loops, and asking: What happens when AI changes how this system works altogether?

SaaS companies are especially guilty here. Add a chatbot to your product, build some automation into your backend, and suddenly you're “AI-first”? It’s the most ridiculous form of window-dressing, a short-term rebrand. And worse, it’s shortchanging customers. These superficial upgrades don’t solve deeper problems of coordination or deliver system-level value. They just inflate price tags with zero structural change.

Most business leaders unfortunately still start with the tech, not the terrain. They chase the hottest models, slap them onto dusty workflows, and hope for ROI. That’s like adding turbochargers to a horse cart and expecting lift-off. Sure, you’ll get more speed, but you’re definitely not leaving the ground.

Forget ownership. That’s yesterday’s source of power. In the agrarian age, it was land. In the industrial era, it was factories. In the 20th century, it was IP. Today, power flows to those who coordinate what they don’t own—supply chains, developer ecosystems, user networks, fragmented data.

AI isn’t just a better tool. It’s a system reshaper. It’s a chance to rewrite the rules of engagement. And the real advantage lies not in automating tasks, but in orchestrating systems. But you’ll never see that if you treat it merely as a plug & play tool.

The magic happens when you use AI to solve coordination problems:

• What are the decision bottlenecks?• Which handoffs introduce delays?• Where does misaligned data cause friction?

Solve those, and you don’t just cut costs. You unlock new possibilities.

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Think Blitzkrieg, not Maginot. Germany didn’t win by building bigger tanks, they won by syncing infantry, armor, air cover, and supply chains into one blistering advance. It wasn't just a change in technology, but a change in military doctrine. AI works the same way in modern business: sure, it can automate invoice approval or customer chat. But its strategic superpower is dismantling coordination barriers.

In Reshuffle, Sangeet Paul Choudary argues that AI’s true story is one of system evolution, not tool installation or upgrade. Sustainable advantage grows from system‑first thinking, relentless focus on coordination, and unleashing compounding and cascading effects to change your scope.

This cascading dynamic is the untold tale of global trade’s second wave, and the real story of AI today. The first wave of breakthroughs—faster GPUs, bigger models—grab headlines. The second wave, of unlocking coordination will reshapes economies.

Want proof? Look at logistics giants that use AI to coordinate fleets in real time, rerouting trucks, drivers, and dock slots with relentless precision. They didn’t just save money, they invented on‑demand supply chains that redefined customer expectations.

AI isn’t the answer to an isolated task. It is the lever that shifts entire systems from static panels to adaptive networks.

Ignore this, and you’ll build digital Maginot Lines: sleek dashboards, fancy bots, and shiny analytics that fail to move the needle when the real world flips the script. Understand this, and you’ll orchestrate an AI-powered Blitzkrieg, where synchronization becomes your moat.

The takeaway from Reshuffle?Sustainable advantage starts with systems, not tech stacks.It flows from orchestration, not automation.It’s earned by redefining the game, not by playing it slightly better.

Rethink the system you’re operating in, from first principles. Then play to win.

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Watch the full video episode:

Follow Sangeet Paul Choudary on LinkedIn: https://www.linkedin.com/in/sangeetpaul

Buy Reshuffle by Sangeet Paul Choudary: https://www.amazon.com/Reshuffle-wins-restacks-knowledge-economy-ebook/dp/B0DTKW6NQV/

Follow Sangeet on Substack:

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How I Apply This to “AI“ Right Now

Here’s a summary of the key points I learned and will apply to my work:

We tend to overvalue AI’s automation capabilities because we undervalue coordination’s role in economic evolution. While efficiency is AI’s visible benefit, the hidden reward lies in gaining control over how others align with your system.

Coordination—which hinges on five structural levers: representation, decision-making, execution, composition, and governance—drives productivity by allowing components to specialize and scale in unison.

If AI is added without changing coordination mechanisms, you end up building leverage for the AI vendor rather than for yourself. So, instead of asking, “What can’t AI do?” ask, “What does AI break?” The next major opportunity arises from the constraints AI introduces, not from the tasks it hasn’t yet mastered.

Reskilling alone falls short when AI restructures the systems that once valued those skills. AI introduces new choke points where contextual value concentrates—often beyond traditional roles. In a world of abundant answers, value shifts toward asking the right questions and identifying the right signals, making curiosity and curation increasingly vital human traits.

Economic value hinges more on scarcity and relevance than on mere skill or effort. Jobs, therefore, exist to manage constraints rather than execute tasks, and roles are valuable when they resolve the system’s most limiting factors.

To operate ‘above the algorithm’ is to shape the system; to operate ‘below’ it is to be shaped by it. AI intensifies the divide between tool users and those who build integrated solutions around them. Strategic advantage now resides with solution architects, not just skilled operators.

Historically, autonomy and coordination have been at odds in organizations: more autonomy reduced alignment, while more coordination slowed execution. AI shifts this dynamic—greater autonomy enhances coordination and vice versa—generating a flywheel of value creation.

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Next on Part-Maven Part-Maverick, we will discuss with Chris Reiter the challenges that the world’s 3rd largest economy Germany faces and the implications for the future.

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Get my book Data Impact for a pragmatic take on data-driven value creation for business: https://www.amazon.com/Data-Impact-businesses-LEVERAGE-SIMPLIFY/dp/178133921X/

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What is a lie?

I always thought that a lie is a bold and shameless falsehood. It turns out that a lie is just a complement of truth. And given the high bar of truth, anything may contain lies. That’s in fact the title of Alex Edmans’ book: May Contain Lies.

Lies are everywhere; they come wrapped in facts, backed by data, supported by studies, or amplified by authoritative voices. And they feel true, because they flatter what we already believe.

I spent my teenage years devouring behavioural economics books. Daniel Kahnemann, Dan Ariely, Richard Thaler, V Raghunathan. This resulted in a vast zoo of behavioural biases that I always tried to keep in mind when thinking things through. That was rather unwieldy, because it is hard to go through an extensive checklist of biases for every thought or decision.

In May Contain Lies, Alex Edmans argues that when one already has a point of view on something, then Confirmation Bias is a huge danger, and otherwise, when one doesn’t have a point of view, then Black and White Thinking is lurking around.

Confirmation Bias is a cognitive bias where people tend to search for, interpret, favor, and recall information in a way that confirms their pre-existing beliefs or assumptions, while giving less attention to or dismissing contradictory evidence.

Black-and-White Thinking, also called all-or-nothing thinking or dichotomous thinking, is a cognitive bias where people view situations, people, or events in extreme, either/or terms, ignoring any middle ground or nuance.

Alex Edmans argues that by being aware of just these 2 biases, one can improve critical thinking across the board. That sort of parsimony is rare and enlightening — and boy, do I love the Pareto principle!

Reality is not a flat surface where our thoughts wander. The geometry of thought has some steep slopes shaped by Confirmation Bias and Black and White Thinking. Being aware of this nature of our minds makes the self-correcting nature of critical thinking essential for not slipping into a vortex of lies.

A useful framework Alex Edmans introduces is The Ladder of Misinference:

* A statement is not fact: it may not be accurate.

* A fact is not data: it may not be representative

* Data is not evidence: it may not be conclusive

* Evidence is not proof: it may not be universal

What May Contain Lies by Alex Edmans taught me more than anything else is that truth-seeking is a mindset, a process, and a way of life.

And given how easy it has become to generate text/multimedia, the price of creating misinformation is tending towards zero. And with that, the need and ability to think critically is becoming increasingly priceless.

Watch the full video episode:

Follow Alex Edmans on LinkedIn: https://www.linkedin.com/in/aedmans/

Find out more about May Contain Lies: https://maycontainlies.com

Buy May Contain Lies by Alex Edmans: https://www.amazon.com/May-Contain-Lies-Statistics-Biases_And/dp/0520405854

How I Apply This to “AI“ Right Now

To bring greater clarity to the current “AI“ landscape, here’s a summary of how I applied what I learnt.

1. Uncover vested interests

Anyone selling “AI” or to “AI” is probably bullish due to their incentive to sell.

Any investor in “AI” companies that has deployed lots of capital and needs growth.

2. Ignore extreme sensational positions that ignore nuance

Hypists: The world has changed dramatically because “AGI“ has been achieved.

Doomers: the world will end because of “AI“ or “AGI“.

3. Be honest about confirmation bias and its origins

I am trained as a mathematician with a research specialisation in machine learning. Over a decade, I have operated by training and deploying learning algorithms and am thus sceptical that just scaling compute and data will result in “AGI“

4. List all nuanced points of view and explore them with curiosity and deliberate open-mindedness

I make an effort to gather a wide range of perspectives, especially those that challenge my views. I approach them with curiosity, not defensiveness, and remind myself that no one has a monopoly on truth.

5. Articulate the smallest set of perspectives that are exhaustive and as orthogonal as possible

I try to reduce the noise by mapping out a minimal set of distinct and independent perspectives, those that together cover the landscape without too much overlap. This avoids drowning in details and helps sharpen thinking. Something similar to a Principal Component Analysis in mathematics.

6. Reflect and do thought experiments to simulate in my mind the nuanced implications of each point of view

I deliberately imagine how the world might look in each scenario. I ask myself: What changes about how value is created? What changes about how value is captured?

This mental simulation forces me to think through second-order effects, not just headlines.

7. Try to identify gaps in knowledge or insight

After going through this process, I focus on spotting my blind spots.

Where am I the most certain or uncertain?

What areas feel underexplored?

Where do experts seem to disagree sharply, or where am I relying on assumptions that I haven't fully tested?

Next on Part-Maven Part-Maverick, we will discuss with Sangeet Paul Choudary how value is created in the age of AI, who captures it, and what the implications are for businesses and us as humans.

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