We live in an interesting time. Many billionaires aren’t just business leaders - they’re also influencers, personalities, and public figures.
While countless billionaires go under the radar, several of today’s billionaires have become controversial figures - like Elon Musk. So, how do the top 10 richest Americans rank in this so-called “popularity contest?”
It’s interesting how many of the 10 wealthiest people in America are still flying relatively under the radar. In my head, names like Sergey Brin or Larry Page should still be household names.
On the other side of this scale, the three richest billionaires have primarily unfavorable ratings ... with Mark Zuckerburg being the most disliked of the bunch.
Meanwhile, Warren Buffett and Bill Gates have predominantly positive ratings - though Bill is more polarizing than Buffett.
As an aside, the world’s richest lost over $200 billion in a single day as news of Trump’s tariffs rocked markets. For context, that drop is the fourth-largest one-day decline in the Bloomberg Billionaires Index’s 13-year history.
My take: Actions Have Consequences. More importantly, we don't know all the actions ... and we certainly haven't recognized all the consequences. This is the beginning of something bigger than it seems, and many of the outcomes are beyond our current expectations or comprehension.
Sure, we saw some fundamental shifts last week ... but know that we are in for more.
The moves were big and fast enough that most people I know haven't had the time or brain cells to ponder things long and deep enough to form a well-reasoned opinion.
The only thing I "know" is that I expect more volatility and big moves.
With that in mind, here are some charts to help keep you informed as the consequences unfold.
Chart #1 - Global Stock Market Returns in Q1 of 2025
Looking at the first chart, it's clear that prior to this announcement, there was a U.S. sell-off, perhaps caused by concerns about inflation and slower GDP growth. As a result, more investment was moving toward Chinese and European stocks.
After Trump's announcement, many things happened, including a joint response from China, Japan, and Korea - something I never thought I'd see. Also, many internet netizens started to plug questions into AI LLMs and receive similar results as Trump's tariffs. Contrary to a more complex equation, it appeared as if the tariff rates were calculated by dividing the deficit and imports of a country. Ultimately, this math was confirmed by the White House Deputy Press Secretary, Kush Desai.
It will be interesting to see what is walked back and what is doubled down on over the next few weeks.
Do you have faith? Do you have an opinion? I'd love to hear it!
Change is the only constant in life, yet it rarely unfolds in ways we expect. While we sense its approach, its shape — whether sudden and disruptive or slow and subtle — often defies our predictions. As the pace and scale of change accelerate, understanding its patterns becomes more crucial than ever.
The World Government Summit put together a helpful interactive website where you can test your knowledge on the trajectory of key statistical indicators for the development of society over the past decade. Here is the text from their opening screen.
Can we estimate how much the world has changed in a decade? Or do our own experiences impact the perception of progress? This work challenges the assumptions we make about how key statistical indicators regarding Health, the Environment, or Education evolve through the years.
The first part of the process was designed to be like a guessing game where you try to predict the direction and the rate of change of key issues shaping the world (like oil dependency, pollution, literacy, economic freedom, etc.) by answering some questions at "The Shape of Change." It is simple, easy-to-use, and has a nice interface ... but answering the questions was more challenging than expected. Try it here.
The second part of the experiment lets you explore the year-over-year changes in key statistics regarding health, education, economy, and other topics.
Almost every event I go to nowadays ends up focused on AI. At a recent event, conversations ranged from use cases for generative AI (and the ethics of AI image creators) to the long-term effects of AI and its adoption.
Before I could chime in, the conversation had gone to the various comparisons from past generations. When electricity was harnessed, articles claimed that it would never catch on, it would hurt productivity – and woe be unto the artisans it would potentially put out of business if it were to gain traction.
When the radio or TV was released, the older generation was sure it would lead to the death of productivity, have horrible ramifications, and ultimately lead to the next generation's failure.
People resist change. We're wired to avoid harm more than to seek pleasure. The reason is that, evolutionarily, you have to survive to have fun.
On the other hand, my grandmother used to say: "It's easy to get used to nice things."
Here's a transcript of some of my comments during that discussion:
With AI, getting from "Zero-to-One" was a surprisingly long and difficult process. Meaning, getting AI tools and capabilities to the point where normal people felt called to use it because they believed it would be useful or necessary was a long and winding road. But now that everybody thinks it's useful, AI use will no longer be "special". Instead, it will become part of the playing field. And because of that, deciding to use AI is no longer a strategy. It becomes table stakes.
But that creates a potential problem and distraction. Why? Because, for most of us, our unique ability is not based on our ability to use ChatGPT or some other AI tool of the day. As more people focus on what a particular tool can do, they risk losing sight of what really matters for their real business.
Right now, ChatGPT is hot! But, if you go back to the beginning of the Internet, MySpace or Netscape (or some other tools that were first and big) aren't necessarily the things that caught on and became standards.
I'm not saying that OpenAI and ChatGPT aren't important. But what I believe is more important is that we passed a turning point where, all of a sudden, tons of people started to use something new. That means there will be an increase of focus, resources, and activity concentrated on getting to next in that space.
You don't have to predict the technology; it is often easier and better to predict human nature instead. We're going to find opportunities and challenges we wouldn't because of the concentration of energy, focus, and effort. Consequently, AI, business, and life will evolve.
For most of us, what that means is that over the next five years, our success will not be tied to how well we use a tool that exists today, but rather on how we develop our capabilities to leverage tools like that to grow our business and improve our lives.
Realize that your success will not be determined by how well you learn to use ChatGPT. It will be determined by how well you envision your future and recognize opportunities to use tools to start making progress toward the things you really want and to become more and more of who you really are. Right?
So, think about your long-term bigger future. Pick a time 5, 10, or even 20 years from now. What does your desired bigger future look like? Can you create a vivid vision where you describe in detail what you'd like to happen in your personal, professional, and business life? Once you've done that, try to imagine what a likely midpoint might look like. And then, using that as a directional compass, try to imagine what you can do in this coming year that aligns your actions with the path you've chosen.
Ultimately, as you start finding ways to use emerging technologies in a way that excites you, the fear and gloom fade.
The best way to break through a wall isn't with a wide net ... but with a sharp blow. You should be decisive and focused.
Commit to using AI in ways that give you energy, which may be entirely different from how you use it now.
So much of what we do now is anchored in the past. This is an opportunity to transcend the old ways you did things and to shape and transform your future (and perhaps even what you believe is possible).
I was an entrepreneur in the late 90s (during the DotCom Bubble). And I remember watching people start to emulate Steve Jobs ... wearing black faux-turtlenecks and talking about how they were transforming their business to be in an Internet company – or which Internet company would be the "next big thing." Looking back, an early sign that a crash was coming was that seemingly everybody had an opinion about what would be hot, and too many people were overly confident in their views because seemingly everyone was saying the same things.
Human nature has remained stubbornly consistent through many waves of technology.
The point is that almost nobody talks about the Internet with the focus and intensity they did in the late 90s ... in part because the Internet is now part of the fabric of society. At this point, it would be weird if somebody didn't use the Internet. And you don't really even have to think about how to use the Internet anymore because there's a WHO to do almost all those HOWs (and many of them are digital WHOs that do those HOWs for you without you even knowing they were needed or being done).
The same is going to be true for AI. Like with any technology, it will suffer from all the same hype-cycle blues of inflated expectations and then disillusionment. But, when we come out the other side, AI will be better for it ... and so will society.
Understanding the Possibility Scale
It helps to understand how we bring things into existence. To start, it's nearly impossible to manifest something you can't first imagine. And there is a moment just before something happens - when it becomes inevitable.
I created this Possibility Scale to help envision the stages of becoming.
As an aside, before today, I would not have attempted to create an image for a post like this. While I love thinking and writing, image creation was outside my area of expertise or unique ability. But now things are different. Today, I simply asked ChatGPT to create that image. Yes, it took me four tries ... each retry starting with "that was great, now help me improve the prompt to (fix the thing I wanted done differently)." At the end, I asked it to give me the complete prompt I could reuse. Contact me if you want the prompt.
Earlier, I mentioned how long it took to get from "Zero-to-One" with AI. But don't fret; things are speeding up, and we're just at the beginning of the process. If I created a scale to show the capabilities of AI, and set the endpoint at 100 to represent AI's potential when I die - even though I'm in my early 60s, I'd put us at only a 3 or 4 on that 100-point scale. Meaning, we are at the beginning of one of the biggest and most asymptotic curves that you can imagine. That also means that you're not late. You're early! Even the fact that you're thinking about stuff like this now means that you are massively ahead of most.
The trick isn't to figure out how to use AI or some AI tool. The trick is to keep the main thing the main thing. Build your ability to recognize when and how to use these new capabilities to bring the future forward faster.
Investing resources into your company is one thing. Realize that there are 1000s of these tools out there, and many more coming. You don't have to build something yourself. It is often faster and better to acquire a tool than it is to spend money on developing and building it.
Think of the Medici family. They invested in people, which in turn triggered the Renaissance. A key to moving forward in the Age of AI will be to invest in the right WHOs, seeking to create the kind of world you want to see or the types of capabilities you desire. Think of this as a strategic investment into creators and entrepreneurs with a vision or who are on a path that aligns with yours.
As you get better and better at doing that, you'll see increasing opportunities to use tools to engage people to collaborate with and create joint ventures. Ultimately, you will collaborate with technology (like it's your thought partner and then your business partner). We are entering exciting times where AI, automation, and innovation will make extraordinary things possible for people looking for opportunities to do extraordinary things.
As my grandmother said, it's easy to get used to nice things.
March Madness is in full swing and will have the world's attention for a few more days. As you can guess, almost no one has a perfect bracket anymore. McNeese beat Clemson, Drake beat Mizzou, and Arkansas handed Kansas its first first-round loss since 2006. On Friday, the NCAA said that of the over 34 million brackets submitted at the start of March Madness, approximately 1,600 remained perfect. That's less than .1% after the first day. The first game of the tournament - Creighton vs. Louisville - busted over half of the brackets.
The holy grail is mighty elusive in March Madness (as in most things). For example, the odds of getting the perfect bracket are 1 in 9,223,372,036,854,775,808 (that is 1 in 9.223 quintillion if that was too many zeros count). If you want better odds, then you can have a 1 in 2.4 trillion chance based on a Duke Mathematician's formula that takes into account ranks). It's easier to win back-to-back lotteries than picking a perfect bracket. Nonetheless, I bet you felt pretty good when you filled out your bracket.
In 2018, it was estimated that March Madness generated $10 Billion in gambling (twice as much as the Super Bowl)
Feeding the Madness
"Not only is there more to life than basketball, there's a lot more to basketball than basketball." - Phil Jackson
In 2017, I highlighted three people who were (semi) successful at predicting March Madness: a 13-year-old who used a mix of guesswork and preferences, a 47-year-old English woman who used algorithms and data science (despite not knowing the game), and a 70-year-old bookie who had his finger on the pulse of the betting world. None of them had the same success even a year later.
Finding an edge is hard - Maintaining an edge is even harder.
That's not to say there aren't edges to be found.
Bracket-choosing mimics the way investors pick trades or allocate assets. Some people use gut feelings, some base their decisions on current and historical performance, and some use predictive models. You've got different inputs, weights, and miscellaneous factors influencing your decision. That makes you feel powerful. But knowing the history, their ranks, etc., can help make an educated guess, and they can also lead you astray.
The allure of March Madness is the same as gambling or trading. As sports fans, it's easy to believe we know something the layman doesn't. We want the bragging rights for the sleeper pick that went deeper than most expected, our alma mater winning, and for the big upset we predicted.
You'd think an NCAA analyst might have a better shot at a perfect bracket than your grandma or musical-loving co-worker.
In reality, several of the highest-ranked brackets every year are guesses.
The commonality in all decisions is that we are biased. Bias is inherent to the process because there isn't a clear-cut answer. We don't know who will win or what makes a perfect prediction.
Think about it from a market efficiency standpoint. People make decisions based on many factors — sometimes irrational ones — which can create inefficiencies and complexities. It can be hard to find those inefficiencies and capitalize on them, but they're there to be found.
In trading, AI and advanced math help remove biases and identify inefficiencies humans miss.
Can machine learning also help in March Madness?
“The greater the uncertainty, the bigger the gap between what you can measure and what matters, the more you should watch out for overfitting - that is, the more you should prefer simplicity” - Tom Griffiths
That said, people have tried before with mediocre success. It's hard to overcome the intangibles of sports—hustle, the crowd, momentum—and it's hard to overcome the odds of 1 in 9.2 quintillion.
Two lessons can be learned from this:
People aren't as good at prediction as they predict they are.
Machine Learning isn't a one-size-fits-all answer to all your problems.
Casinos only offer to play games that they expect to win. In contrast, gambling customers play even though they know the odds are against them.
Why does this happen? The rush of a win, the chance of a big win, and random reinforcement are common factors that incentivize people to play the lotto, go to a casino, or try to trade.
Chemicals like adrenaline and dopamine play a part as well. Even in a sea of losses, your body can't help but crave the chemical reward of even a small win.
The "House" knows this and engineers an experience that takes advantage of it.
In the case of casinos, every detail is meticulously crafted to extract you from your money - from carpet patterns to the labyrinthian layouts, the music, the lights, and even the games themselves.
Most people aren't gamblers ... the fear of losing big inhibits them. However, when people were instructed to "think like a trader," they showed considerably less risk aversion when gambling. And I bet you have no problem filling out a March Madness bracket, even if you put money on the line.
The illusion of control convinces us we can overcome the statistics.
When you almost get it right - when you guess the first round of March Madness correctly, when you miss the jackpot by one slot on a slot machine, when you just mistime a trade to get a big win - you're more likely to play longer, and place bigger bets ... because you're "so close."
It's human nature to want to feel in control.
This is why you find a lot of superstitious traders & gamblers. If you wear this lucky item of clothing ... if you throw the dice in this particular way ... if you check your holdings at this time every day ... you have control.
There is a big difference between causation and correlation.
It is not hard to imagine that, for most traders, the majority of their activities do little to create a real and lasting edge.
Skill vs. Luck
There are games of skill, and there are games of chance.
In a casino, poker, and blackjack are considered games of skill. In contrast, slot machines are considered a game of chance.
In trading, predicting markets is much different than using math and statistics to measure the performance of a technique.
Much of what we do is to figure out how to eliminate the fear, greed, and discretionary mistakes humans bring to trading.
In trading, "Alpha" is the measure of excess return attributed to manager skill, rather than luck or taking on more risk.
We believe in Alpha-by-Avoidance ... Meaning much of what we do is figure out what to ignore or avoid so that more of the games we play are games of skill rather than games of chance.
Twice this week, I heard someone say, “Start with Why.”
As a tech entrepreneur, I often ignore that aphorism.
Someone who embodies it (and made it famous) is Simon Sinek. He is a motivational speaker and organizational consultant who gained widespread recognition after his 2009 TED Talk, “How Great Leaders Inspire Action,” which remains one of the most-viewed TED Talks ever, with almost 70 million views.
This talk introduced his core framework: The Golden Circle, the concept that catapulted him to fame. It is a simple but powerful model for understanding why some leaders and organizations inspire while others don’t. It consists of three concentric circles, like a bullseye. At the center is Why, the middle ring is How, and the outermost ring is What.
Most people and organizations focus on the outermost circle first—what they do—and then work inward. Sinek flips this approach, arguing that great leaders and companies start from the inside out: start with Why.
Why Start with Why?
Here’s an analogy: Think of a magnet. The strongest force comes from its core. Similarly, in leadership and business, the Why is your core—it’s what attracts people to you. It’s not just about selling a product; it’s about sharing a belief or vision that resonates emotionally with others.
For example:
Apple doesn’t just sell computers (What). They believe in challenging the status quo and thinking differently (Why). Their How—innovative design and user-friendly technology—flows naturally from this belief.
Martin Luther King Jr. didn’t say, “I have a plan.” He said, “I have a dream.” His Why inspired millions because it connected with their values and emotions.
The Biological Connection
Sinek ties this idea to how our brains work. The outer layer of the brain (the neocortex) processes logical information like facts and figures (What), but decisions are driven by the limbic brain, which controls emotions and instincts (Why). When you lead with Why, you speak directly to people’s feelings, inspiring trust and loyalty.
Simplified Takeaway
Think of it like this: If you want people to join your cause or buy into your vision, don’t just tell them what you’re selling or how great it is. Tell them why it matters—to you and to them. Starting with Why connects hearts before minds, creating a lasting impact.
In short, the Golden Circle isn’t just a business strategy; it’s a way to inspire action by leading with purpose.
I met Simon through friends before his first book came out.
Then, in 2009, he gave a speech to the Dallas Chapter of EO, and then visited my office to speak with our team afterwards. I still remember how well-received he was. It was right at the beginning of his meteoric rise, two short months after the release of his famous book "Start With Why."
Who do you believe will do a better job, someone who takes a job because of the salary and benefits ... or someone truly inspired to accomplish the job's purpose?
Phrased that way, of course, you know the answer. Still, how can you leverage this to better select customers and employees?
For example, Simon uses the story of Sir Ernest Shackleton to illustrate this concept. Shackleton was preparing to lead the first expedition across Antarctica in 1914. Legend has it that when seeking crew members for his journey, Shackleton placed the following ad in a newspaper:
"MEN WANTED FOR HAZARDOUS JOURNEY. SMALL WAGES, BITTER COLD, LONG MONTHS OF COMPLETE DARKNESS, CONSTANT DANGER, SAFE RETURN DOUBTFUL. HONOUR AND RECOGNITION IN CASE OF SUCCESS. - SIR ERNEST SHACKLETON"
When the expedition became stuck in the ice and could not be rescued for 22 months, not a single man was lost. The reason Simon gave for their unlikely survival was that Shackleton hired survivors that could deal with the situation and were aligned with the mission and purpose.
Can you imagine writing an ad like that to attract the right people to your cause?
Watch This Video.
Here is a video of Simon speaking at a TED Conference. It is an excellent intro to his stuff.
Other Resources:
Here is a link to Simon's Blog. (2023 Note: this now links to his old blog, which is poorly formatted but interesting to see. His new website/blog can be found here.)
It's now more than ten years later, and Simon is one of the most prominent leaders in leadership development and has published five books, to much acclaim.
Part of his success is the charisma and pith with which Simon speaks and writes - but a large part is his focus on what makes humans human. He's not preaching a leadership mantra focused on the bottom line and revenue; he's focused on the aspects of human nature that don't change. He's focused on purpose and the elements of leadership that apply to everyone - not just CEOs.
As we move into an era of increased volatility – both in markets and business - these leadership principles will become more important.
Understanding your "WHY" is vital if you want to make a difference (and not be replaced by an AI). It’s also vital in making discipline the easier choice.
Are Billionaires Popular?
We live in an interesting time. Many billionaires aren’t just business leaders - they’re also influencers, personalities, and public figures.
While countless billionaires go under the radar, several of today’s billionaires have become controversial figures - like Elon Musk. So, how do the top 10 richest Americans rank in this so-called “popularity contest?”
via visualcapitalist
It’s interesting how many of the 10 wealthiest people in America are still flying relatively under the radar. In my head, names like Sergey Brin or Larry Page should still be household names.
On the other side of this scale, the three richest billionaires have primarily unfavorable ratings ... with Mark Zuckerburg being the most disliked of the bunch.
Meanwhile, Warren Buffett and Bill Gates have predominantly positive ratings - though Bill is more polarizing than Buffett.
As an aside, the world’s richest lost over $200 billion in a single day as news of Trump’s tariffs rocked markets. For context, that drop is the fourth-largest one-day decline in the Bloomberg Billionaires Index’s 13-year history.
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