Capitalogix

Are Your AI Fears Valid? What Experts Say

It's no surprise that there is often a disparity between what experts believe and what the average adult feels. It's even more pronounced in industries like AI that have been lambasted by science fiction and popular media.

Even just a few years ago, many of my advisors and friends told me to avoid using the term "AI" in our materials because they thought people would respond negatively to it. Back then, people expected AI to be artificial and clunky ... yet, somehow, it also reminded them of dystopian stories about AI Overlords and Terminators. An incompetent superpower is scary ... so is a competent superpower you can't trust!

As AI integrates more heavily into our everyday lives, people's hopes and concerns are intensifying... but should they be? 

Pew Research Center surveyed over 5,000 adults and 1,000 experts about their concerns related to AI. The infographic shows the difference in concern those groups had regarding specific issues.

 

Statista via VisualCapitalist

Half of experts (47%) report being more excited than concerned about AI’s future. Among U.S. adults, just 11% say the same.
Instead, 51% of adults say they’re more concerned than excited — more than triple the rate of experts (15%).

 

The most common—and well-founded—fears center on misinformation and the misappropriation of information. Experts and the average adult are in alignment here. 

I am consistently surprised by the lack of media literacy and skepticism demonstrated by otherwise intelligent people. Images and articles that scream "fake" or "AI" to me are shared virally and used to not only take advantage of the most susceptible but also to create dangerous echo chambers. 

Remember how bad phishing e-mails used to be, and how many of our elderly or disabled ended up giving money to a fake Prince from various random countries? Even my mother, an Ivy League-educated lawyer, couldn't help but click on some of these e-mails. Meanwhile, the quality of these attacks has risen exponentially.

And we're seeing the same thing now with AI. Not only are people falling for images, videos, and audio, but you also have the potential for custom apps and AI avatars that are fully focused on exploitation. 

AI Adoption Implications

Experts and the average adult have a significant disparity in beliefs about the long-term ramifications of AI adoption, such as potential isolation or job displacement. 

I'm curious, how concerned are you that AI will lead to fewer connections between people or job loss? 

I often say that technology adoption has very little to do with technology and much more to do with human nature.

That obviously includes AI adoption as well. 

Career growth often means abandoning an old role to take on something new and better. It's about delegating, outsourcing, or automating tasks so you can free up time to work on things that matter more.

It may sound like a joke, but I don't believe most people will lose jobs to AI. Instead, they'll lose jobs to people who use AI better. The future of work will be about amplifying human intelligence ... making better decisions, and taking smarter actions. If your job is about doing those things – and you don't use AI to do them – you will fall behind, and there will be consequences.

It's the same way that technology overtook farming. Technology didn't put people out of work, but it did force people to work differently.

Innovation has always created opportunity and prosperity in the long term. Jobs may look different, and some roles may be phased out, but new jobs will take their place. Think of it as tasks being automated, not jobs. 

Likewise, COVID is not why people have resisted returning to the office. COVID might have allowed them to work remotely in the first place, but their decision to resist going back to the office is a natural part of human nature.

When people found that technology enabled them to meet expectations without a commute, opportunities and possibilities expanded.

Some used the extra time to learn and grow, raising their expectations. Others used that time to rest or focus on other things. They're both choices, just with different consequences.

Choosing to Contract or Expand in the Age of AI 

AI presents us with a similar inflection point. I could have easily used AI to write this article much faster, and it certainly would have been easier in the short term. But what are the consequences of that choice?

While outreach and engagement are important, the primary benefit of writing a piece like this, for me, is to take the time and to go through the exercise of thinking about these issues ... what they mean, what they make possible, and how that impacts my sense of the future. That wouldn't happen if I didn't do it.  

I often say, "First bring order to chaos ... then wisdom comes from making finer distinctions." Doing work often entails embracing the chaos and making finer distinctions over time as you gain experience. With repetition, the quality of those results improves. As we increasingly rely on technology to do the work, to learn, and to grow, the technology learns and grows. If you fail to also learn and grow, it's not the technology's fault. It is a missed opportunity.

The same is true for connection. AI can help you connect better with yourself and others... or it can be another excuse to avoid connection.

You can now use an AI transcription service to record every word of an interaction, take notes, create a summary, and even highlight key insights. That sounds amazing! But far too many people become accustomed to the quality of that output and fail to think critically, make connections, or even read and process the information.

It could be argued that our society already has a connection problem (or an isolation epidemic), regardless of AI. Whether you blame it on social media, remote work, or COVID-19, for a long time, how we connect (and what we consider "connection") has been changing. However, many still have fulfilling lives despite the technology ... again, it's a choice. Do you use these vehicles to amplify your life, or are they a substitute and an excuse to justify failing to pursue connection in the real world?.

As said, actions have consequences ... and so do inactions.

I'm curious to hear your thoughts on these issues. Are you focused on the promise or the perils of AI?

Why Don't We See Aliens?

So, if the math says it's likely that there are aliens ... why don't we see them?

In 2020, I mentioned Israeli officials who claimed they had been contacted by Aliens from a Galactic Federation - and that not only is our government aware of this, but they are working together.

There are many stories (or theories) about how we have encountered aliens before and just kept them secret. Here are some links to things you might find interesting if you want to learn more about this.

• NewsNation Segment: UFO Whistleblower Jake Barber Shares Allegations and Will Testify to Congress About Nonhuman Craft Retrievals.
• NewsNation Segment: UFO whistleblower David Grusch: 'We are not alone.'
• Dr. Diana Walsh Pasulka, Professor of Religious Studies, bridges the gap between religious studies, technological advancements, and the realm of UFO phenomena.
• Trailer for a film called "The Phenomenon."

So, while some may still believe aliens don't exist - I think it's a more helpful thought experiment to wonder why we haven't seen them. 

For example, the Fermi Paradox considers the apparent contradiction between the lack of evidence for extraterrestrial civilizations and the various high-probability estimates for their existence. 

To simplify the issue, billions of stars in the Milky Way galaxy (which is only one of many galaxies) are similar to our Sun. Consequently, there must be some probability that some of them will have Earth-like planets. It isn't hard to conceive that some of those planets should be older than ours, and thus some fraction should be more technologically advanced than us. Even if you assume they're only looking at evolutions of our current technologies, interstellar travel isn't absurd. 

Thus, based on the law of really large numbers (both in terms of the number of planets and length of time we are talking about) ... it makes the silence all the more deafening and curious. 

If you are interested in the topic "Where are all the aliens?"  Stephen Webb, a particle physicist, tackles that in his book and this TED Talk.   

via TED

In the TED talk, Stephen Webb covers a couple of key factors necessary for communicative space-faring life. 

1. Habitability and stability of their planet
2. Building blocks of life 
3. Technological advancement
4. Socialness/Communication technologies

But he also acknowledges the numerous confounding variables, including things like imperialism, war, bioterrorism, fear, the moon's effect on climate, etc. 

Essentially, his thesis is that there are numerous roadblocks to intelligent life, and it's entirely possible we are the only planet that has gotten past those roadblocks. Even if there were others, it's entirely possible that they're extinct by now. 

What do you think?

Here are some other links I liked on this topic. There is some interesting stuff you don't have to be a rocket scientist to understand or enjoy. 

• 75 Reasons We Don't See Aliens 
• Wait But Why: The Fermi Paradox
• A New Theory on Why We Haven't Found Aliens Yet
• A List of Solutions to The Fermi Paradox
• Dissolving the Fermi Paradox, Future of Humanity Institute, Oxford University

To Infinity and Beyond!

Here Are Some Links For Your Weekly Reading - April 20th, 2025

Here are some of the posts that caught my eye recently. Hope you find something interesting.

Lighter Links:

• OpenAI's Most Impressive Move Has Nothing to Do With AI. (ZDNet)
• AI Stuns Researchers by Rewriting Its Own Code to Overcome Limitations. (TalkAndroid)
• Meta’s New AI Tech Can Read Your Mind at Work…What Could Possibly Go Wrong? (AllWork)
• How to Enter a ‘Flow State’ on Command: Peak Performance Mind Hack Explained in 7 Minutes. (OpenCulture)
• British Anthropologist Claims Jesus' Tomb and Ark of the Covenant are Beneath the Great Pyramid. (JPost)

 

 

Trading Links:

• Trump’s Knives Are Out for Jerome Powell, Setting Up a Supreme Court Showdown Over the Fed’s Independence. (Fortune)
• First Shockwaves of Trump’s Tariffs are About to Hit the World Economy. (Bloomberg)
• America is Losing the Robot Wars. (Insider)
• The Only Way Some Manufacturing Jobs Will Return Stateside is If AI-Empowered Robots Do Them—And That’s a Good Thing. (Fortune)
• ‘China’s Elon Musk’ Uses Just Two Numbers to Demonstrate Why His Country’s Auto Industry is Now Outcompeting the U.S. And Europe. (Fortune)

Are We Alone In The Universe?

Last week, Astronomers announced the discovery of the most promising "hints" of life on an exoplanet, K2-18, 124 light years away. 

While it would only be signs of phytoplankton and other microscopic marine life, it would still be a massive finding. 

I tend to read a lot across a wide variety of sources. Recently, I've noticed a significant uptick in stories about aliens, UFOs, non-human intelligence, and non-human technology. In addition, several of my seemingly sane friends claim to have direct knowledge of projects and groups (funded by well-known billionaires) close to making very public announcements about missions, research, and discoveries in these areas, they hope will result in discontiguous innovations and asymmetric capabilities.

While I believe it's naive to assume that there's no other form of life in a universe as vast as what we understand ... I'm also highly skeptical of anyone who claims that they have specific knowledge or proof. With that said, I have seen enough stuff from people I trust to expect that our beliefs about these issues will shift massively in the very near future. As an example, check out Skywatch.ai, some of its videos, or this NewsNation broadcast.

Since we live in a time where technologies are rapidly advancing, I thought it might be interesting to test out an AI-powered chatbot designed to debunk conspiracy theories through evidence-based conversations. It is a spin-out project with roots at MIT and other top universities. Research shows that many people doubted or abandoned false beliefs after a short conversation with the DebunkBot. 

I first heard of this tool through these two articles: Meet DebunkBot, The AI Chatbot that Will Debunk Any Conspiracies You Believe and AI Chatbot Shows Promise in Talking People Out of Conspiracy Theories.

Here is a link to the conversation I had with it about the belief  "Life likely exists elsewhere in the Universe due to its vastness and the repeated conditions that can give rise to life."  To my surprise, this tool concluded that the belief is not a conspiracy theory and reminded me that:

Science for the sake of knowing is one thing. Belief for the sake of hope, curiosity, or imagination is another. The search for "life" might actually help us discover something more valuable than what we thought we were searching for in the first place.

You can test your beliefs against DebunkBot's AI. Let me know how it goes and whether you changed your mind.

Meanwhile, Information Is Beautiful has an interactive data visualization to help you decide if we're alone in the Universe. 

As usual, it's well done, fun, and informative. 

For the slightly geeky amongst us, the model lets you adjust the estimate by playing with the Drake and Seager equations.

The Drake equation estimates the number of detectable extraterrestrial civilizations in our galaxy and the universe. It factors in variables such as habitable planets, the likelihood of life, intelligent life, and the duration of time a civilization sends signals into space. 

The Seager equation is a modern take on the equation, focusing on bio-signatures of life that we can currently detect - for example, the number of observable stars/planets, the % have life, and the % chance of detectable bio-signature gas. 

Click here to play with the Are We Alone in the Universe infographic. 

 

via Information Is Beautiful

For both equations, the infographic lets you look at various default options, but also enables you to change the variables based on your beliefs. 

For example, the skeptic's default answer for Drake's equation shows 0.0000062 communicating civilizations in our galaxy, which is still 924,000 in the universe. The equivalent for Seager's equation shows 0.0009000 planets with detectable life in our "galactic neighborhood" and 135,000,000 planets in our universe. 

Even with the "lowest possible" selection chosen, Drake's equation still shows 42 communicating civilizations (Douglas Adams, anyone?) in the universe.

 

via Information Is Beautiful

One of the most interesting numbers (and potentially influential numbers for me) is the length of time a civilization sends signals into space. Conservative estimates are 420 years, but optimistic estimates are 10,000 or more. 

One other thing to consider is that some scientists believe that life is most likely to grow on planets with very high gravity, which would also make escaping their atmosphere for space travel nigh impossible.

If any aliens are reading this ... don't worry, I won't tell. But we will find out who you voted for in the last election.

Last week, Astronomers announced the discovery of the most promising "hints" of life on an exoplanet, K2-18, 124 light years away. 

While it would only be signs of phytoplankton and other microscopic marine life, it would still be a massive finding. 

I tend to read a lot across a wide variety of sources. Recently, I've noticed a significant uptick in stories about aliens, UFOs, non-human intelligence, and non-human technology. In addition, several of my seemingly sane friends claim to have direct knowledge of projects and groups (funded by well-known billionaires) close to making very public announcements about missions, research, and discoveries in these areas, they hope will result in discontiguous innovations and asymmetric capabilities.

While I believe it's naive to assume that there's no other form of life in a universe as vast as what we understand ... I'm also highly skeptical of anyone who claims that they have specific knowledge or proof. With that said, I have seen enough stuff from people I trust to expect that our beliefs about these issues will shift massively in the very near future. As an example, check out Skywatch.ai, some of its videos, or this NewsNation broadcast.

Since we live in a time where technologies are rapidly advancing, I thought it might be interesting to test out an AI-powered chatbot designed to debunk conspiracy theories through evidence-based conversations. It is a spin-out project with roots at MIT and other top universities. Research shows that many people doubted or abandoned false beliefs after a short conversation with the DebunkBot. 

I first heard of this tool through these two articles: Meet DebunkBot, The AI Chatbot that Will Debunk Any Conspiracies You Believe and AI Chatbot Shows Promise in Talking People Out of Conspiracy Theories.

Here is a link to the conversation I had with it about the belief  "Life likely exists elsewhere in the Universe due to its vastness and the repeated conditions that can give rise to life."  To my surprise, this tool concluded that the belief is not a conspiracy theory and reminded me that:

Science for the sake of knowing is one thing. Belief for the sake of hope, curiosity, or imagination is another. The search for "life" might actually help us discover something more valuable than what we thought we were searching for in the first place.

You can test your beliefs against DebunkBot's AI. Let me know how it goes and whether you changed your mind.

Meanwhile, Information Is Beautiful has an interactive data visualization to help you decide if we're alone in the Universe. 

As usual, it's well done, fun, and informative. 

For the slightly geeky amongst us, the model lets you adjust the estimate by playing with the Drake and Seager equations.

The Drake equation estimates the number of detectable extraterrestrial civilizations in our galaxy and the universe. It factors in variables such as habitable planets, the likelihood of life, intelligent life, and the duration of time a civilization sends signals into space. 

The Seager equation is a modern take on the equation, focusing on bio-signatures of life that we can currently detect - for example, the number of observable stars/planets, the % have life, and the % chance of detectable bio-signature gas. 

Click here to play with the Are We Alone in the Universe infographic. 

 

via Information Is Beautiful

For both equations, the infographic lets you look at various default options, but also enables you to change the variables based on your beliefs. 

For example, the skeptic's default answer for Drake's equation shows 0.0000062 communicating civilizations in our galaxy, which is still 924,000 in the universe. The equivalent for Seager's equation shows 0.0009000 planets with detectable life in our "galactic neighborhood" and 135,000,000 planets in our universe. 

Even with the "lowest possible" selection chosen, Drake's equation still shows 42 communicating civilizations (Douglas Adams, anyone?) in the universe.

 

via Information Is Beautiful

One of the most interesting numbers (and potentially influential numbers for me) is the length of time a civilization sends signals into space. Conservative estimates are 420 years, but optimistic estimates are 10,000 or more. 

One other thing to consider is that some scientists believe that life is most likely to grow on planets with very high gravity, which would also make escaping their atmosphere for space travel nigh impossible.

If any aliens are reading this ... don't worry, I won't tell. But we will find out who you voted for in the last election.

To Rebirth & Spring Cleaning

Next Sunday is Easter, but yesterday was the first night of Passover - an 8-day long Jewish holiday that recounts the story of Exodus. 

The overlap can be seen in DaVinci's Last Supper, depicting a Passover Seder and Jesus's last meal before his crucifixion. 

 

 

Part of the Passover Seder tradition involves discussing how to share the story in ways that connect with different types of people, recognizing that everyone understands and relates to things differently.

To do this, we examine the Passover story through the lens of four archetypal children — the Wise Child, the Wicked Child, the Simple Child, and the Child Who Does Not Know How to Ask.

The four children reflect different learning styles — intellectual (Wise), skeptical (Wicked), curious (Simple), and passive (Silent) — and highlight how we must adapt communication to the diverse personalities and developmental stages of our audience.

This seems even more relevant today, as we struggle to come to a consensus on what to believe and how to communicate with people who think differently. 

 

On a lighter note, one of the memorable phrases from Exodus is when Moses says, "Let my people go!"  For generations, people assumed he was talking to the Pharoah about his people's freedom.  But after a week of eating clogging food like matzoh, matzoh balls, and even fried matzoh … for many Jews, "Let my people go" takes on a different meaning.

After Passover, and as we enter a new season, it's a great time for a mental and physical 'Spring Cleaning,' and delve into your experiences to cultivate more of what you desire and less of what you don't.

Here is to Spring, Re-Birth, and Spring Cleaning.

Hope you had a great weekend.

Understanding the Shape of Change

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 Shape of Change via the World Government Summit

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 Shape of Change via the World Government

The second part of the experiment lets you explore the year-over-year changes in key statistics regarding health, education, economy, and other topics.

 

The Shape of Change via the World Government

If you want to explore this further, I asked Perplexity to give me a broad overview of the project and its key insights. Here is the link.

The data is interesting. But, perhaps, your reaction to the data is more important. 

Were there any numbers that surprised you?

Taking Lessons on AI from my Grandmom

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.

Onwards!

Mad About March Madness

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. 

Before 24/7 sports channels, people watched the weekly show "The Wide World of Sports."  Its opening theme promised "The thrill of victory and the agony of defeat!" and "The human drama of athletic competition." That defines March Madness.

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.

via Duke University

Here's some more crazy March Madness Stats: 

• Companies expect $4 Billion of corporate losses due to employees tracking games
• The highest-paid NCAA coach, Kansas's Bill Self, makes a salary of $8.8 Million
• 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

The data is there. Over 100,000 NCAA regular-season games were played over the last 25+ years, and we generally have plenty of statistics about the teams for each season. There are plenty of questions to be asked about that data that may add an extra edge. 

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:

1. People aren't as good at prediction as they predict they are.
2. Machine Learning isn't a one-size-fits-all answer to all your problems.

Something to think about.

 

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

The data is there. Over 100,000 NCAA regular-season games were played over the last 25+ years, and we generally have plenty of statistics about the teams for each season. There are plenty of questions to be asked about that data that may add an extra edge. 

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:

1. People aren't as good at prediction as they predict they are.
2. Machine Learning isn't a one-size-fits-all answer to all your problems.

Something to think about.

The Psychology of Gamblers

March Madness, Vegas, and Wall Street share a lot in common. 

Over Time ... The House Wins

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. 

Here is an infographic that lays it out for you. 

Bojoko via DailyInfographic

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.

Are you playing the right game?

Starting With Why

Ideas don’t have to be complex to be valuable. 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." Here's the article I wrote in 2009 after that visit:

___________________

Inspiration is stronger than persuasion.  It gives people a sense of purpose and belonging that has little to do with external incentives or benefits.

Simon Sinek, who is quite charismatic and well-spoken, is delivering this message to a rapidly growing fan base. 

My team thought Simon was inspiring, engaging, and insightful.

You can watch a short video that introduces his material below. 

In addition, you can explore more of his ideas in his book, Start with Why: How Great Leaders Inspire Everyone to Take Action.

 

An Example of Finding the Right Person for a Job.

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.)
• Here is a link to Videos of Simon.
• Here is a link to an article on why to know someone else's Why.  (PDF Version)
• Here is a link to Simon's Book: Start with Why.

_____________________

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.

If you haven't read any of his books, they're all good, but I suggest "Start With Why" and "The Infinite Game."

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."

Here's the article I wrote in 2009 after that visit: