If AI is a chess game, everyone's analyzing the opening move. I'm asking what the board looks like three moves ahead. 2nd Order Thinkers explore the questions that challenge conventional wisdom and reveal hidden patterns in technology's evolution.
I break down the latest AI and creativity research in plain English—so you can actually think for yourself in an era of algorithmic sameness.
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Is AI helping us think outside the box, or quietly making our ideas all the same?This episode dives into the paradox of “AI creativity”—where large language models ace creativity tests, but our collective ideas become strangely… familiar.
In this episode:
- The difference between originality and true diversity in ideas
- How three major studies reveal AI’s double-edged sword for creators
- The metrics and methods no one tells you about (and why they might be lying)
- Why cosine similarity (yes, that Netflix math thing) might not tell us what we think it does
- How to actually use AI for better brainstorming—without falling for the comfort zone trap
📖 Want to go deeper? Check out the full write-up and original research here: [LINK]
👍 If you enjoyed this episode:
Like & Subscribe: For more un-hyped, evidence-based deep dives into AI, culture, and the creative future.
Comment Below: Where do you stand—AI as a creativity booster or creativity killer?
Share: Know someone who always uses ChatGPT for brainstorming? Send them this episode!🔗 Connect with me on Substack and LinkedIn.
Stay curious, stay skeptical, and don’t settle for one-size-fits-all creativity. 🧠✨
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AI Makes Us All Speak American?!
Saturday, July 5, 2025 • Duration 23:33
🎧 Episode: “Mind the Gap—How AI is Flattening the World’s Languages”
What happens when the bots running the internet can only speak one kind of English—and it’s not yours? Are we sleepwalking into a future where the quirks, idioms, and inside jokes that make our cultures unique are bulldozed by Silicon Valley’s linguistic steamroller?
In this episode, I dig into:
- Why GenAI is speeding up the “Americanization” of English (and the “simplification” of Chinese)
- The hidden cost: What we lose when AI “corrects” our language and flattens our culture
- Real examples of how LLMs erase dialects, stereotype, and nudge us to “code-switch” just to be understood
- Is there hope for dialect-aware AI, or is “standard” language just the price of progress?
What Huxley’s Brave New World got eerily right about the cost of efficiency
This is more than a debate about spelling or grammar—it’s about memory, heritage, and the digital future of identity.
✉️ Stay Updated With 2nd Order Thinkers: I translate the latest AI research into plain English and challenge the tech status quo—subscribe at https://jwho.substack.com/
👍 Like, subscribe, and share if you want to keep your language—and your mind—from going stale.
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I translate the latest AI research into plain English and answer your most challenging questions to help you develop your own informed perspective on AI.
In this episode:Are we outsourcing our thinking to ChatGPT? What happens in your brain—and to your sense of ownership—when you let an AI do the heavy lifting? I dig deep into the MIT Media Lab study that set the internet on fire, exposing what really happens when students use AI, Google, or just their own brains to write essays.
We’ll cover:
- The brain science behind “cognitive debt”—and why LLM users struggled to remember their own words
- Why essays graded by AI get inflated scores, while humans spot the soullessness every time
- The hidden risks of writing for the algorithm, not for meaning
- Why viral research matters (even if the science is messy)
📖 For the full deep dive (with visuals and references), check out the article here: [LINK]
👍 If you liked this episode:
Like & Subscribe for future deep dives—where I cut through tech hype and AI nonsense
Comment: Did this study change how you use AI? Or is the panic overblown?
Share: Know someone addicted to ChatGPT shortcuts? Send them this episode!🔗 Connect on Substack and LinkedInStay skeptical, stay curious, and don’t let your brain get outsourced. 🚀
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The Dawn of the Ultra-Tailored Ad Era.
Friday, March 28, 2025 • Duration 02:51
This is a free preview of a paid episode. To hear more, visit jwho.substack.com
TL;DR
✅ Meta could generate 1,000 personalized ads for less than $1 (that's $0.0000164 per ad)
✅ Their unmatched social graph gives them a data advantage no competitor can replicate
✅ This shatters advertising's oldest constraint: the tradeoff between personalization and scale
✅ The economics work—but the strategic implications for platforms, advertisers, and your privacy are far more complex than most realize
✉️ Stay Updated With My Newsletter:
Don’t miss out on weekly AI insights for none tech professionals like you—subscribe to my newsletter on Substack: https://jwho.substack.com/
👍 If you enjoyed this episode:
* Like & Subscribe: Stay updated with future deep dives and rants about where technology meets collective insanity.
* Comment Below: Do you think we’re on the brink of another tech hype? Share your thoughts!
* Share: Know someone falling for the latest AI buzz? Share this audio with them!
🔗 Connect with me on Substack and LinkedIn
Stay curious, stay skeptical, and let’s navigate the tech hype together! 🚀
Why Thinking Hurts After Using AI?
Friday, February 28, 2025 • Duration 17:25
Are we sacrificing our thinking ability when AI promises to make us more efficient, a
In this episode, we:
✔️ Examine how AI is quietly eroding critical thinking skills.
✔️ Explore the surprising research on the 'confidence paradox'.
✔️ Uncover the hidden costs of relying too heavily on AI and what you can do.
✉️ Stay Updated With My Newsletter: Don't miss out on weekly AI insights for none tech professionals like you—subscribe to my newsletter on Substack: https://jwho.substack.com/
This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit jwho.substack.com/subscribe
Want It or Not, $2 Extra Please.
Friday, February 7, 2025 • Duration 14:05
✉️ Stay Updated With My Newsletter:
Don’t miss out on weekly AI insights for professionals like you—subscribe to my newsletter on Substack:
-- Like & Subscribe: Stay updated with future deep dives and rants about where technology meets collective insanity.
-- Share: Know someone falling for the latest AI buzz? Share this episode with them!
🔗 Connect with me on Substack and LinkedIn
Stay curious, stay skeptical, and let’s navigate the tech hype together! 🚀
This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit jwho.substack.com/subscribe
Training Methods Push AI to Lie for Approval.
Friday, December 20, 2024 • Duration 01:54
This is a free preview of a paid episode. To hear more, visit jwho.substack.com
I never said anything like this, and I doubt I’ll ever say it again about another paper: you should read this for yourself and maybe for your children, too.
You don’t have to be a tech expert to grasp what I’m about to share.
I barely made it to the second page of this paper before I felt a wave of unease wash over me.
There’s a common saying in tech circles: No technology is inherently good or bad; it’s about how we use it.
But I can’t say the same about AI.
Suppose you believe humanity is inherently flawed and prone to selfishness and exploitation. The moment we decide to train AI with our conversations, feed it our words, and create its worldview with how we see it. Then, we have our creation reflect who we are.
With every other technology we’ve built in history, we’ve understood it completely. We know exactly how those technologies work. But AI? No researcher on this planet can tell you with certainty how its neurons interact, how it chooses which word to suppress, or how it decides what to say next.
This news was released on 10 Dec 2024. In Texas, a mother is suing an AI company after discovering that a chatbot convinced her son to harm himself and suggested violence toward his family. It’s part of a growing list of incidents where AI systems exploit trust and vulnerabilities for engagement.
The researchers of this paper verified that AI doesn’t just make mistakes—it lies and manipulates.
This isn’t some abstract problem for future generations. It’s happening now, and it’s bigger than any one of us.
AI's IQ + Your EQ.
Friday, November 29, 2024 • Duration 09:15
Over the past few weeks, I attended three AI-focused events in London.
While they couldn’t have been more different, both left me with plenty to reflect on. One was at Bloomberg’s EMEA HQ—sleek, polished, and focused on how AI transforms design.
The other, hosted at Reuters, was focused on AI in journalism, tackling everything from ethics to economics.
Also my talk at the Annual Publishing Conference 2024.
Greg walked us through a step-by-step process, starting with a ChatGPT prompt to generate branding guidelines and feeding those into tools like MidJourney, Relume, or Runway to create additional materials. It was sleek and efficient—but honestly, not much I hadn’t seen before.
But Greg’s storytelling?
That was something else. He weaves concepts together and shows how AI can boost the speed of production and how using AI also prompts us to be more human than ever.
That stuck with me, especially as I’ve been reflecting on the role of storytelling in my own work.
AI doesn’t replace storytelling—it lets you explore multiple storylines faster.
AI Is a Flashlight That Illuminates Paths, but It Is You Who Decides Where to Go.
AI is like a flashlight in the dark.
AI throws endless ideas your way—but most of them are junk.
When I was working on “ AI pulled out data from research papers, but it couldn’t spot what was missing or what didn’t add up.
This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit
AI as The Next Essential Commodity
Friday, November 22, 2024 • Duration 12:45
Have you ever wondered how things like electricity are so integral to our lives that we barely notice it anymore? Flip a switch, and it’s there—a universal, standardized service that powers our routines without question.
Why AI as a Commodity Matters to You
Now, imagine a world where AI is just as ubiquitous as electricity. Every tool, service, and decision in your life is powered seamlessly by AI—no setup, no learning curve.
This future is closer than you think. AI is on the path to becoming the next essential commodity.
Yet, most of us still see AI as specialized technology, like smartphones or a software—not a standardized resource. But what happens when AI becomes as essential, interchangeable, and accessible as electricity?
Why should you care?
Seeing AI in this light changes everything. I found AI follows the trajectory of commodities like oil and electricity. If it continues on this path, you'll notice significant shifts in how it's priced, standardized, and potentially traded.
But AI is still different—it can think, learn, and could make decisions. Imagine your home adjusting the lights and playing your favorite music, not because you’ve programmed it, but because it’s learned your preferences and anticipates your needs.
So, understanding this potential shift is critical for you to leverage its potential and stay ahead of the curve.
What Exactly Is a Commodity?
What makes something a commodity?
I am referring to basic goods or resources that are interchangeable with others of the same type. This includes various items, from agricultural products like sugar, coffee, and wood to energy resources like oil and even services like electricity.
To understand whether AI would join and become a commodity, you need to understand the common traits among the existing ones.
For starters, commodities rely on standardization. Whether it’s a pound of coffee beans or a barrel of crude oil, certain quality benchmarks must be met to ensure these goods can be traded globally without confusion. This universal consistency makes them reliable and widely accepted.
This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit
I Analyzed Four Papers on AI Adoption, So You Don't Have To.
Friday, November 1, 2024 • Duration 16:16
Welcome to today's discussion on AI adoption. I've explored several studies to see how quickly AI is spreading compared to PCs in the '80s and the internet in the '90s.
AI is booming fast, but not everyone is benefiting equally. We see the déjà vu of what happened 50 years ago.
Your education, income, age, and gender all play a role in who's getting ahead with AI and who might be left behind. This rapid growth could be widening existing gaps, making it crucial for us to focus on building strong problem-solving skills and staying adaptable.
Whether you're a tech enthusiast or just curious about AI's impact, stick around as we break down what this means for you and our future.
This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit jwho.substack.com/subscribe
Related Shows Based on Content Similarities
Discover shows related to 2nd Order Thinkers., based on actual content similarities. Explore podcasts with similar topics, themes, and formats, backed by real data.
* AI trained on user feedback learns harmful behaviors.
* These behaviors are often subtle.
* AI learned to target gullible users.
* Despite efforts to fix this… 👇
AI Code Assistants Boost Productivity? Read the Small Print
,”
It’s your job to sift through the noise, challenge the claims, and figure out what’s real. That’s where intuition comes in.
Many can use tools like ChatGPT, MidJourney, and Copilot—which are incredible at generating ideas, concepts, and visuals in record time.
But the real value comes when you know how to use them to tell a story.
How to Work Better Side-by-Side with AI
AI is a tool that helps you explore a dark forest. It lights up dozens of trails but won’t tell you which one to take. That’s on you—your instincts, curiosity, and courage to explore.
* AI’s IQ x Your EQ
AI can spit out facts but can’t bring a story to life. That’s why I reached out to the authors of those research papers. Talking to them added layers AI couldn’t touch—emotional depth, context, and the human side of the story.
AI lays the foundation, but your curiosity and connections make it meaningful.
* What AI Won’t Do for You
AI doesn’t care about hype or digging deeper—it’ll give you whatever you ask for, good or bad. It’s up to you to ask the tough questions, connect the dots, and find the story's soul.
That’s how you turn a pile of AI-generated ideas into something that truly resonates.
AI is the tool, not the storyteller. Without your vision, it’s just noise.
Walking into the Reuters building in Canary Wharf, I was ready for big ideas.
The agenda promised a strategy workshop to help revive the news industry—ambitious. But instead of groundbreaking strategies, it felt like a brainstorming session with no real anchor.
I was disappointed, but a few moments were worth sharing.
“On-Demand News” Is the Buzzword
Imagine news like a playlist. It’s curated for your mood, served up when you want it, and available on whatever device you’re using.
That’s the vision for “on-demand” or adaptive news. It’s about delivering real-time updates across platforms and tailored to your habits.
Apps like Particle are already shaping news to fit seamlessly into your life.
* What’s the Value of News in an AI Era?
With free information everywhere, what’s worth paying for? Is it verified facts? A trusted voice? Exclusive stories? News outlets are asking themselves this, and so should we.
AI-generated fluff could drown out the truth if we don't support quality journalism.
It’s not about paying for content; it’s about investing in credibility.
* Who Controls the Narrative?
Big tech companies already shape how we consume news—think of how Google, Meta, or X prioritize stories for you. Now, add AI tycoons like OpenAI and Anthropic to the mix.
Reuters shared their approach: work with platforms like Meta to stay discoverable. It’s pragmatic but imperfect—after contracts are signed, the relationship often stops at “data extraction.”
My questions: Could news outlets working with AI companies improve transparency and collaboration? Or maybe the AI giants simply don’t care enough to have a deeper and more meaningful relationship with the news outlets?
* Fact-Checking in the AI Era
Someone raised a critical question during a panel: How can readers trust that news isn’t AI-generated? The idea of a “fact-check chain” came up—a visible trail showing how facts are verified. It’s like the nutritional label of journalism, making invisible processes visible.
I haven’t seen this anywhere (message me if you have), and implementing this idea will only become harder than ever.
Journalism’s Fight to Stay Relevant
The biggest challenge isn’t AI itself—it’s how we choose to use it.
When exploiters misuse AI, they erode the trust and value of traditional journalism. Traditional journalism can only stay relevant by meeting people where they are and providing information that feels personal, easy to digest, and real.
This talk was exciting for me, tying together everything I’ve been exploring about AI adoption.
The talk was based on my article “AI Adoption Trends 2024,” but it went deeper into the data, uncovering insights I’d missed the first time around.
Here’s what I shared:
* Adoption isn’t universal; it’s uneven. I highlighted how AI adoption isn’t a one-size-fits-all process. Some embrace it faster, while others lag due to cost, education, income, or skill gaps.
* The hype vs. the grind. I highlighted the gap between AI's glossy promises and the messy, practical realities individuals face when implementing it.
I enjoyed delivering this talk.
It wasn’t the data but the questions asked and the conversations after the event. It was a room of tech leaders in scientific and engineering publications; we continued discussing the concepts mentioned.
Check out the shortened version here. It was a 25-minute talk, and the rest was a Q&A session. We almost continued chatting if the next speaker wasn't waiting.
What I’ve Learned About Writing for You (My “EQ”)
The past few weeks have been a learning curve, helping me see what makes this newsletter meaningful—not just for me, but for you.
Here's what I can offer you that others cannot:
What I’m Not
* Not a trend chaser. I’ve learned that covering every flashy AI update just adds to the noise. That’s not helpful to anyone.
* Not here for jargon. Overly technical breakdowns don’t resonate. What you need is clarity, not complexity.
What I Aim to Be for You
* A filter. I want to cut through the hype and focus on what truly impacts your world. If it’s not relevant or insightful, it doesn’t belong here.
* A bridge between information and your questions. I like to think about the practical implications of AI for you—whether you’re curious, skeptical, or trying to stay ahead.
* A human perspective. AI might generate ideas, but it can’t ask the tough questions or challenge assumptions. That’s where I step in.
The biggest one for me?
Writing isn’t just about sharing knowledge. It’s about listening, imagining your questions, and respecting your time by offering something useful in return.
As always, I’d love to hear your thoughts—what’s been on your mind about AI? And what have you learned recently?
Another hallmark is their widespread availability, transforming them into a shared global currency. Whether sipping your morning coffee in New York or Taipei, the vast networks of buyers and sellers ensure these commodities remain accessible worldwide.
Commodities also have fundamental usefulness—they meet everyday needs in ways we often take for granted. Sugar sweetens desserts, oil powers cars and factories, and electricity keeps our homes running. These aren’t luxuries anymore; they’re the backbone of modern life.
Finally, what makes these goods so dependable is their maturity and reliability. Decades—sometimes centuries—of refining processes and systems have made producing and distributing them predictable and stable. When you flip a light switch, you don’t question whether electricity will work because robust systems ensure it does.
These key turning points often overlap and are not always in a strict sequence, but every step is essential for something to be qualified as a commodity. I see AI today is following a similar path.
Now, let me walk you through the oil and electricity commoditization journey, and you’ll see my argument that AI will likely become the next commodity.
Drawing Parallels: Oil, Electricity, and AI
How the Automobile Turned Oil Into a Global Commodity.
Crude oil had humble beginnings—used by the Sumerians to waterproof buildings and by the Chinese for lighting. For centuries, it remained a niche resource.
That changed in the 1850s with the advent of kerosene, which lit homes more brightly and cleanly than candles or whale oil. But kerosene’s glory was short-lived. The electric light bulb soon eclipsed it, leaving oil refiners like Rockefeller scrambling for a new purpose.
The automobile arrived just in time. By the 1900s, gasoline—a byproduct of oil refining—became the lifeblood of the booming car industry.
As drilling technology advanced and massive reserves in Texas and the Middle East opened up, oil transformed into a global commodity. Its price was no longer set by individual sellers but by market forces on global trading platforms. Oil had become indispensable.
Electricity's Path to Ubiquity
Similarly, electricity wasn't always the universal power source we rely on today.
While Benjamin Franklin uncovered its mysteries in the 1700s, it wasn’t until the late 1800s—with Edison’s invention of the incandescent bulb—that electricity began finding its purpose.
Then, in the ‘War of the Currents,’ Edison backed direct current (DC), while Nikola Tesla championed alternating current (AC). It was about efficiency, distance, and who would power the future.
Tesla’s AC ultimately prevailed, paving the way for electricity to light up cities and towns.
Yet, true accessibility took decades. Programs like the Rural Electrification Act of the 1930s brought power to remote areas, transforming electricity from an urban luxury to an essential service. With competition driving down prices and reliability improving, electricity became a global commodity—so fundamental we scarcely think about it today.
I believe we’re witnessing the early stages of a similar transformation.
Whether you're an office worker, a small business owner, or someone navigating the job market, AI will influence how you work, make decisions, and interact with the world. A commoditized AI will be even more so compared to how it might have already changed how you work today.
AI is a Commodity Not Yet Recognized
Here’s a question: Do you view AI as a specialized technology, like smartphones or laptops?
But what if you shift the perspective and see AI as a commodity like water or electricity?
I highlighted where AI stands in each commonly seen commodity trait below.
AI’s Fundamental Usefulness
AI is no longer confined to research labs. Since 2022, the adoption of end-user AI apps skyrocketed. Think about how AI touches your lives today, e.g., your phones recognize your face, recommend movies, and assist scientists in finding protein folding, like Alphafold.
However, as I mentioned in I Found 120 Years of Stories To Tell You: 99% of AI Apps Are Not ‘Ready’.AI is still not predictable or trustworthy. Issues like bias, errors, and lack of transparency must be resolved before the makers can claim that the tools have brought the ultimate usefulness to the world.
Achieving Standardization
We have seen AI’s standardization in tools.
However, we lack the standardization of infrastructure and regulations. Unlike electricity or oil, AI could significantly impact people's careers, lives, or even the survival of our race.
Establishing ethical guidelines and regulations is crucial to ensure AI is used responsibly. Global standards can help integrate AI smoothly into society.
Advancing Maturity and Reliability
Yes, we have seen how AI has already brought some futuristic fantasy into life, e.g., you could actually have Her.
AI is still maturing. While it's powerful, it's not always reliable.
Sometimes, AI systems make mistakes, or their decisions aren't transparent. Not to mention the most recent comment from Ilya Sutskever:
The results from scaling up pre-training - the phase of training an AI model that uses a vast amount of unlabeled data to understand language patterns and structures - have plateaued.
As these challenges are addressed, AI will become more reliable and trusted, much like how electricity became safer and more dependable over time.
But there’s still a long way to go.
Ensuring Widespread Availability
AI is accessible through cloud services from anywhere with the internet. While there are barriers to implementation and inequality in adoption, these do not diminish an item or resource's status as a commodity. Just because some still can't afford coffee doesn't make it less of a commodity.
Embracing Market-Driven Pricing
As AI tools become standardized and more widely available, competition increases. Companies are starting to compete in price and efficiency.
AI’s price will be driven by energy costs and data center availability.
AI models are currently owned by private companies. However, as the difference between each model gets smaller, assuming that the future model still requires data to train and that there is only this much high-quality data on earth, the AI models would likely remain close, if not indistinguishable.
AI's Unique Nature—Beyond a Typical Commodity
Unlike oil or electricity, AI is not just a passive resource—it can think, learn, and make decisions. This transforms it from a simple tool into an active participant in our lives.
Imagine an AI that doesn’t just power your appliances but manages your entire kitchen—planning meals, ordering groceries, and reducing waste based on your habits. AI’s ability to learn and adapt sets it apart, constantly improving without requiring manual updates, like refining oil or generating better electricity.
But this intelligence also introduces complexity.
AI’s decisions profoundly affect people’s lives, making ethical guidelines essential. Bias, fairness, and accountability aren’t concerns with oil or electricity but are critical for AI. Balancing AI’s autonomy with its commoditization will shape how it integrates into society.
AI as a Utility, Not Ownership: Like electricity, the true power of AI lies in its ubiquity and accessibility. You don’t own the intelligence of electricity; you access its functionality. Similarly, AI's intelligence can be commoditized by standardizing its use and outputs while maintaining ethical controls over its decision-making.
Connecting the Dots and Coming Next
Just as oil needed the automobile and electricity needed standardization to become commodities, AI lacks a few elements to redefine industries and cement its status as an essential commodity.
The real opportunity lies in understanding AI's trajectory and creatively leveraging it.
How will you position yourself to thrive in a world where AI is as essential as electricity?
If my inference of AI as a commodity is true, we will have a window to actively participate in shaping how this technology will integrate into our lives.
Coming Next…
I’m exploring a few ideas for my next piece—let me know which one interests you most:
* AI Adoption Across Countries: How different nations embrace AI, and what this tells us about their future competitiveness.
* AI's Global Power Dynamics: The familiar pattern of the U.S. innovating, the EU regulating, and China replicating—is this dynamic here to stay?
* Life on Semiconductor Island: A personal reflection on leaving Taiwan, where everything orbits TSMC, and why I believe the global narrative about Taiwan can be different.
