Capitalogix

The Most Hyped Technologies of the 00s

The Gartner Group’s Hype Cycle research provides the raw material for some of my favorite posts every year.

It is a graphical and conceptual presentation used to represent the maturity, adoption, and social application of popular technologies.

Here is a link to a Gartner research note on understanding Hype Cycles.

I’ve found that they are an excellent source of well-researched tech and business analysis. As another example, here is a video of their Top Ten Tech Trends for 2024.

 

via YouTube

Humans are famously bad at predicting the future of technologies. We tend to overestimate technology’s abilities in the near term and massively underestimate what it can do in the long term.

The shape of that curve has come to be known as the Gartner Hype Cycle, and the five stages of that curve are important for any entrepreneur or investor to understand.

via Gartner

In general, as technology advances, it is human nature to get excited about the possibilities and disappointed when those expectations aren’t met. 

At its core, the Hype Cycle tells us where we are in the product’s timeline and how long it will likely take the technology to hit maturity. It attempts to tell us which technologies will survive the hype and have the potential to become a part of our daily lives. 

Gartner’s Hype Cycle Report is a considered analysis of market excitement, maturity, and the benefit of various technologies. It aggregates data and distills more than 2,000 technologies into a succinct and contextually understandable snapshot of where various emerging technologies sit in their hype cycle.

Here are the five regions of Gartner’s Hype Cycle framework:

1. Innovation Trigger (potential technology breakthrough kicks off),
2. Peak of Inflated Expectations (Success stories through early publicity),
3. Trough of Disillusionment (waning interest),
4. Slope of Enlightenment (2nd & 3rd generation products appear), and
5. Plateau of Productivity (Mainstream adoption starts). 

Understanding this hype cycle framework enables you to ask important questions like “How will these technologies impact my business?” and “Which technologies can I trust to stay relevant in 5 years?”

If you are curious, here is Perplexity’s explanation of Gartner’s Hype Cycle and related research. 

Another methodology uses frequency analysis to identify the “most hyped” concepts and technologies.  

VisualCapitalist recently put together an infographic highlighting the most hyped technologies of each year. They call it the “Peak of Inflated Expectations”.

 

(Click To See Full Infographic) via VisualCapitalist

Here’s a Summary of the most hyped technologies, by year, since 2000.

• 2000 - Wireless Web, ASPs, Bluetooth
• 2001 - Web Services, Enterprise IM, m-Commerce
• 2002 - Biometrics, Grid Computing
• 2003 - Process Portals
• 2004 - Micro Portals, Virtual Content Repositories
• 2005 - P2P VOIP, Biometric ID Documents, BPM Suites
• 2006 - Mashup, Web 2.0 
• 2007 - Legal P2P, Digital Video Broadcasting
• 2008 - Green IT
• 2009 - Cloud Computing, e-Book Readers, Social Software Suites
• 2010 - 4G Standard, Activity Streams
• 2011 - Internet TV, NFC Payment, Augmented Reality
• 2012 - BYOD, 3D Printing, Complex Event Processing
• 2013 - Big Data, Gamification, Wearable User Interfaces
• 2014 - IoT, Natural-Language Question Answering, Cryptocurrencies
• 2015 - Speech-To-Speech Translation, Advanced Analytics, Autonomous Vehicles
• 2016 - Blockchain, Cognitive Expert Advisors, Machine Learning
• 2017 - Virtual Assistants, Connected Home, Deep Learning
• 2018 - Biochips, Digital Twin, Deep Neural Networks
• 2019* - 5G, AI PaaS, Graph Analytics
  *Missing from the infographic, but updated by Gartner

As we take our smartphones for granted, it’s hard to imagine Bluetooth, wireless web, or e-book readers as emerging technologies at this point - but at one point in time, the lightbulb was an emerging technology. 

It’s also interesting to look at which technologies peaked in a hype cycle ... and which now popular technologies no longer appear on this list. For example, despite Virtual Reality being around since the 80s, I still expected to see it on this list. 

Cryptocurrencies, “smart homes”, and several older examples are in a recession - but that doesn’t mean they won’t have resurgences. 

As a reminder, the hype cycle and the innovation adoption cycle are often on very different time scales. It’s very possible that technologies from the early 2000s may still have their heyday. 

What are you surprised wasn’t on the list? And, what do you think is about to get added?

We live in interesting and exciting times!

Cultivating An Innovator's Mindset

To some, new technology is a good thing. To others, less is more.

Most people simply “tolerate” technology transitions, some people drive them, and others crave them and use them as a catalyst for growth or strategic advantage.

The description begins with resistance and progresses towards compulsion. Reversing this sequence allows us to illustrate the innovation adoption process.

Here is a visualization of the innovation adoption model and market share.

In the image above, the blue line represents consumer adoption (taken from Geoffrey Moore’s “Crossing the Chasm,” while the yellow line represents market share. 

As you can see, only 2.5% of the population drive innovation (or adopt it early enough to help drive the Alpha & Beta versions of emerging technologies). 13.5% make up the Early adopters, who help get it ready for the mainstream. Then, the early and late majorities are the groups that ultimately consume (or use) the mature product. Meanwhile, Laggards are often forced kicking and screaming into “new” technologies as the early adopters are well on their way to subsequent iterations. 

Here is a link to Perplexity’s description of Crossing the Chasm’s innovation-adoption model and other key concepts from the book.

Even if you are not an innovator, here are a few Innovator Mindsets that I find useful. 

1. You Believe There’s A Better Way
   • Wherever you are, you know that there is a best next step, and you are eager to find it and take it.
   • You recognize that the opportunity for more (or better) often lies just beyond the constraints or problems of the current way.
   • The bigger future fuels your efforts. When initial excitement fades, understanding what the bigger future can bring helps you power through.
2. You Are Comfortable Being Uncomfortable
   • You understand that Pioneers sometimes take arrows in the back.
   • When creating a new reality, you expect some resistance as a result of the law of averages. Escaping the status quo takes a lot of momentum, but it’s worth it. 
   • You recognize when victory is near. In a quirk of human nature, too many people quit just before they would have won. Don’t make that mistake.
3. You Know Where You’re Going, Even If You Are Not Sure How You’re Going To Get There
   • Your goal should be your North Star. A clear direction is essential to ensure that activity leads to progress.
   • Measure progress and momentum rather than the distance from your goal.
   • It is easier to course-correct while in motion.
   • If you’re too committed to a path that isn’t leading in the right direction, you might find what Blockbuster, RadioShack, and Kodak found.
4. You Are Married To Questions (Not Necessarily Answers)
   • Everything works until it doesn’t; and nothing works forever.
   • It’s easy to find an answer (and think it’s correct), but there’s always a best next step or a better way.
   • Figure out what you want and how to get it. This is much more empowering than focusing on what you don’t want ... or why you can’t get it.
   • Ask questions that focus on opportunities or possibilities rather than challenges ... or what you want to avoid.
   • Energy flows where focus goes.
   • Commit to finding a way!

I plan on sharing more Innovator Mindsets. Let me know what you think.

The 2.9 Trillion Dollar Drop

Last Friday was the stock market’s worst day since COVID. 

The media says weak job reports and recessionary fears fueled it.  Geopolitics might have played a part, too.

Over 2.9 Trillion Dollars got wiped out. 

To visualize what happened, here is a market heatmap of the S&P 500 index stocks categorized by sectors and industries.  Size represents market cap.  There was very little green in a sea of red.

 

via FinViz

Last year, I asked if we would see a recession in 2024?  Here is an excerpt from that post:

 

I want to remind people that the U.S. is resilient, and it seems like public sentiment is moving in a positive direction. 

That said, 84% of CEOs and 69% of consumers think we're headed toward a recession. Meanwhile, the Fed is positive we won't ... and banks are almost positive we won't. 

It seems like they know something we don't ... or maybe vice versa. 

To lend some credence to the bullish sentiment, consumer spending is still high despite inflation and interest rates. In addition, Retailers are still posting solid earnings.

Unfortunately, we're increasingly seeing consumers resort to borrowing (including short-term lending options) to pay for goods. Household debt has hit a record high of $17 trillion in March.

— Are We Going To See A Recession In 2024?, October 2023

Yes, last week was potentially alarming.  Even the ordinarily resilient tech giants took a hit. 

With the unemployment rate reaching 4.3% in July, the three-month moving average is at least 0.5 percentage points above the minimum of the previous 12 months’ averages.  This triggers the Sahm rule, which supposedly signals a recession.  According to the rule, reaching the 0.5% threshold indicates a recession.  When the jobless rate rises quickly, it suggests the economy is slumping.

But, even the inventor of the rule, Claudia Sahm, says the doomsday narrative may be overblown. 

I’m not here to tell you that everything is sunshine and roses, but I am here to remind you that no indicator exists in a vacuum.  While the negative performance is real, household income is still growing, and consumer spending and business investment remain resilient.

Not to mention that with graduation, there’s a massive increase in the workforce, which also impacts the numbers. 

Recessions can build slowly - but come quickly - but as they build, there is time to react ... and even better - there is time to not ‘react’ but ‘respond’. 

AI will likely impact the workforce, business, and eventually ... the economy. 

I’ve learned that the market often feels random because you can’t predict events like global pandemics, threats, assassinations, or cybersecurity outages.

Over time, I’ve focussed less on guessing what will happen and more on responding faster and better to what happens.

With that said, I do have an opinion here.  It’s an election year, and I suspect the government will push every button and pull every lever to boost the market leading into November.  Even though markets and the economy are not the same thing, many voters believe they are.  So, I would say this correction is perfectly timed ... and I anticipate a steady ramp-up so that people feel as good as possible about the economy when they vote.

What do you think is going to happen?

The Power Of Assessments

Over the years, I've used a number of different assessment tests on myself and our team. It's a great way to help people better understand each other and the various forms of communication and problem-solving styles we use.

Here are several of the tests that have proven themselves time and again:

1. Kolbe measures how individuals naturally approach problem-solving and execute tasks when free to be themselves.
2. Predictive Index (PI) - helps organizations make data-driven, objective hiring decisions by providing insights into a candidate's personality traits and cognitive abilities in relation to their perceived role.
3. StrengthsFinder: helps people discover their natural talents and develop them into strengths they can leverage for personal and professional success.

On top of these, it's always fun to see what else is available and how it might provide new and useful insights. 

For example, Ray Dalio recently created a personality assessment called PrinciplesYou that you can take for free. This tool breaks down personality traits into three areas: how you think, engage with others, and apply yourself. I've seen several articles praising PriciplesYou and its insights.

Less meaningful, perhaps (but still fun), I also found a website called Human Benchmark that lets you test your performance on various reaction and memory tests. I'm unsure how scientific it is, but it was an interesting use of 10 minutes nonetheless. Here are my son's results from that one.

via Human Benchmark

Progress starts by telling the truth ... most often to yourself.  

What assessments have you found particularly helpful?

Thoughts On Conversing With AI

A few weeks ago, I shared an article about a tool I've been enjoying called Dot.  I use it as an AI journal that acts somewhat like a sounding board and counselor for me.

Since writing that article, I have continued to enjoy and appreciate the tool.  I've used Dot to help me plan and prepare for a substantial business transaction.  It assists me in processing and evaluating significant life decisions.  Sometimes, I even use it just because I'm bored. 

Dot sometimes responded to my thoughts with probing questions which pushed me to consider why I said what I said. These prompts helped me think about my thinking in ways that I hadn't before. The result was more valuable than simply coming up with a strategy or a list of potential answers. It actually helped me articulate and identify what I really wanted. 

It's clear to me that I increasingly rely on the tool and have made it part of my daily routine.  I've even noticed that I sometimes refer to it as "she" or "her."

Dot remembers my discussions with it, prompts me to stick with things we've discussed, and can even tell when I'm trying to change the subject or end a conversation.

It's fascinating to think about how AI creates a programmatic version of empathy.  It makes me question the distinction between artificial and real empathy (and whether that distinction even matters).  Perhaps, instead, we should focus simply on the utility and benefits of the responses.  

If you're into comparisons, you might want to check out Pi, one of the pioneering personal AI tools designed to blend EQ and IQ.

If you like variety, try Poe, developed by Quora.  It gives you access to the latest AI models and millions of user-created AI chatbots and even lets you create your own custom bots.

I'm also a fan of TalkTastic, which lets you record your rough ideas and then distill them into thoughtful and articulate language.  I use it frequently throughout the day to create short messages, emails, and even some of the sentences in articles like this.  As I use voice more, I love the idea of a digital editor that declutters and refines what I say into what I mean.

Things Are Getting Better Fast! 

As a thought experiment, imagine how advanced AI will be by the end of your lifespan.

Assign the number 100 to that level of capability.  Where are we now?

Based on my life expectancy, I would guess that AI is currently only at a 3 out of 100.

Where we are today is incredible compared to the past.  Likewise, it's astounding how fast things are getting better.  But compared to what's coming ... it's virtually nothing.

The most exciting part is that (considering the rapid pace of exponential technological improvements) we likely can't even imagine how advanced AI will become or the benefits and insights it will be capable of producing for us. 

While my first article focused on the tool and its capabilities, I think it's also helpful to think more globally about mindsets around these types of tools and the proliferation of AI. 

Technology Adoption Model 

To start, I've built a model I call the Technology Adoption Model. This model explains how ideas transform from a Capability into a Product and then once again into a platform that spawns new capabilities. 

Before you start considering new capabilities, the first thing you should do is assess whether this new tool helps us better accomplish what we already do. To answer that, we often use three simple measures: efficiency, effectiveness, and certainty. This means getting things done in less time, with less effort, or with a greater chance of success.

Once you know that you can do what you already did—just better—you naturally get greedy for more. That means you start thinking about what you could or should do to improve further.

This applies to adopting new tools - and also to building them.

I've also built a worksheet around the model that you can use in your own business. 

As you start using new AI tools, you will gain new capabilities.  Don't concentrate on mastering the tool itself; instead, focus on getting better at using it to enhance your life.

A great place to start is simply making your life easier or more enjoyable.  Use new tools in fun and low-friction ways.  The impact of tools like these will increase as you become more proficient at thinking about using them better ... and as you improve your ability to imagine new possibilities. 

From Inconceivable To Unavoidable

Your mindset creates your reality.

It's natural to feel resistance to new and powerful capabilities.  It's a safety mechanism because humans are wired to think locally and linearly - and to avoid danger. 

Realize, however, that linear thoughts don't often lead to exponential results.

The more I play around with these tools, the more I anthropomorphize them.  Human thought and connection are ultimately chemicals and electricity firing within a system, not too different from a computer.  If AI can become such a reasonable facsimile that it's indistinguishable, is the difference worth thinking about?  Or is it better to focus on what and how you will use the new capabilities? 

As entrepreneurs, our job is to get the rock up that hill.  We can spend time thinking about whether the tool is 'artificial' or how we can better harness it. 

I've said this before, but it's worth echoing …  Some of what was once Impossible becomes Possible.  Some of what became Possible becomes Probable.  And, and some of what became Probable becomes Inevitable.  Here is a way to visualize that scale.

And, our limitations are often only in our ability to conceive of a bigger future.

Speed Matters

AI isn't just valuable because of what it can do; its deeper value comes from enabling you to achieve more.

I like to use a simple model to illustrate this: Crawl, Walk, Jog, Run, Sprint.  As you think about your day or week, what percent of the time are you sprinting?

Chances are you sprint less than you initially thought.  Why?  Because, when you really sprint, it's hard to breathe ... and you can't talk.  And because of all our other burdens and responsibilities, we don't tend to push ourselves that hard.

However, as AI eliminates frustration and bother, it frees you up to do and be more and focus on the things that create the most value and really matter.

The real benefit of AI is that it gives you back those time cycles to really sprint towards what you truly want.

A tool like Dot can also help you better clarify what you want while also helping you accomplish those things.

Too much of our day is spent thinking about what we don't want or how to avoid feeling angry, frustrated, or uncertain.

Your life can improve quickly by focusing on becoming more clear about what you want, how you can achieve it, and the best ways to measure progress toward those goals.

The next step is to use the traction, progress, and momentum to determine what else is possible and what you should plan to do next.

When you think about it this way, a tool like Dot can be a powerful alignment tool and a way to help you and your company move faster. 

Just make sure you're heading in the right direction!

Buying a Computer in 1994 ...

We take for granted a lot of the technology we have today.  Computers and phones have evolved so fast that it's hard to remember that they haven't been around for many years. 

When my youngest son was born in 1993, cassette tapes and the Sony Walkman were popular.  I had a brick-sized phone hardwired into my car, and we had a Macintosh-II in the study.

Here is a throwback picture showcasing the cool tech we had back then. 

 

Everything in that photo now exists in the cheapest of smartphones.  And the features and functions available now far exceed my wildest expectations back then.

For a blast from the past and a look back at what used to be top-of-the-line ... here's a video of people buying a computer in 1994. 

 

via David Hoffman

Video transfer and playback.  160-megabyte hard drive.  32 megahertz.  All for the low price of $2,000. 

I can remember back further than 1993, because I'm old enough that I didn't have my first computer until after I graduated college.  My first Macintosh had floppy disks measured in K, not megs or gigs.  For context, my first job out of school was at a law firm where the only people who used computers were in the typing pool.  And when I said I wanted a computer, the lawyers said "No!" because it would look bad.

It's pretty cool to see how far we've come! 

Still, someday soon, they will look back at the tech we have now as "primitive" and "quaint".

I can't wait!

Cognitive Biases & The Consequences of Labeling

“Words can be twisted into any shape. Promises can be made to lull the heart and seduce the soul. In the final analysis, words mean nothing.
They are labels we give things in an effort to wrap our puny little brains around their underlying natures,
when ninety-nine percent of the time the totality of the reality is an entirely different beast.
The wisest man is the silent one. Examine his actions. Judge him by them.”
― Karen Marie Moning

Continuing with the theme of cognitive biases, the upcoming election has me thinking about the consequences of labeling things, creating boxes, and simplifying ideas into news-ready headlines.

With more news sources than ever and less attention span, you see ideas packaged into attention-grabbing parts.  The focus isn't on education or the issues, but on getting the click, making your stay on their page longer, and sending you to a new article utterly unrelated to why you clicked on the page.

Complex issues are simplified – not even into their most basic forms – but instead into their most divisive forms ... because there's no money in the middle.

via Quote Investigator

The amplified voices are those on the fringe of the average constituents' beliefs – precisely because those are the ones who are often the most outspoken.  We might think that because they're the voices we hear, these fringe messages fairly represent what people like us believe or think ... but they rarely do. 

Issues that should be bipartisan have been made "us" versus "them," "liberal" versus "conservative," or "right" versus "wrong." The algorithms many of our information sites use create echo chambers that increase radicalization and decrease comprehension. 

Identity politics have gotten so strong that you see families breaking apart and friend groups disintegrating ... because people can't imagine sharing a room with someone with whom they don't share the same values. 

In psychology, heuristics are mental models that help you make decisions easier.  They're a starting point to save mental bandwidth, allowing you to spend more brain cycles on the important stuff.

That's a great use of "boxes" and "simplification"… but it shouldn't eliminate deeper and more nuanced thought on important issues. 

Most situations are nuanced, and the "correct" answer changes as you change your vantage point.

In an ideal world, we'd consider every angle.  I recognize that's not realistic.

Instead, I encourage you to remember to continue to think and learn ... even about things you already know.  And, if you become familiar with the most common cognitive biases, you can hopefully identify them in your thinking and decision-making.

Confirmation Bias is one of the more common forms of cognitive bias.  Here is an infographic that lists 50 common cognitive biases.  Click to explore further.

 

via VisualCapitalist

Important issues deserve more research.  New insights happen between the boundaries of what we know and don't.  Knowledge comes from truly understanding the border between what you are certain and uncertain about. 

I challenge you to look beyond the headlines, slogans, and talking points you like most.  Look for dissenting opinions and understand what's driving their dissent.  Are they really blind or dumb (or are their value systems just weighted differently)?

Not everything needs to be boxed.  Not everything needs to be simple.  You should explore things and people outside of your comfort zone and look to see things from their point of view ... not your own. 

Recently, I've started using a website and news app called Ground News.  They claim to be a news platform that makes it easy to compare news sources, read between the lines of media bias, and break free from algorithms. 

As discussed above, online news and ad-driven algorithms have made it profitable for news outlets to embrace a position on the bias spectrum to target specific consumers.   That bias in the media affects everything from what events receive coverage to how a news outlet frames those events in their reporting.

As media outlets narrow their perspective and range of coverage, I use Ground to help me get a well-rounded view of important issues and become aware of my blind spots.

Applying This Lesson  

“I am ashamed to think how easily we capitulate to badges and names, to large societies and dead institutions.”
― Ralph Waldo Emerson, Self-Reliance

I love learning a lesson in one space and applying it to other spaces.  It's one of the cool things about AI.  An algorithm can learn rules in the construction space that may help in the medicine or trading space.  Everything's a lesson if you let it be.

In that vein, the lesson on labeling also applies to yourself and your business.  Don't get me wrong - naming things is powerful.  It can help make the intangible tangible.  However, don't let the label (or your perception of the label) stop you from achieving something greater. 

Many things are true because we believe them to be, but when we let go of past beliefs, the impossible becomes possible, and the invisible becomes visible.  

Hope that helps. 

“Words can be twisted into any shape. Promises can be made to lull the heart and seduce the soul. In the final analysis, words mean nothing.
They are labels we give things in an effort to wrap our puny little brains around their underlying natures,
when ninety-nine percent of the time the totality of the reality is an entirely different beast.
The wisest man is the silent one. Examine his actions. Judge him by them.”
― Karen Marie Moning

Continuing with the theme of cognitive biases, the upcoming election has me thinking about the consequences of labeling things, creating boxes, and simplifying ideas into news-ready headlines.

With more news sources than ever and less attention span, you see ideas packaged into attention-grabbing parts.  The focus isn't on education or the issues, but on getting the click, making your stay on their page longer, and sending you to a new article utterly unrelated to why you clicked on the page.

Complex issues are simplified – not even into their most basic forms – but instead into their most divisive forms ... because there's no money in the middle.

via Quote Investigator

The amplified voices are those on the fringe of the average constituents' beliefs – precisely because those are the ones who are often the most outspoken.  We might think that because they're the voices we hear, these fringe messages fairly represent what people like us believe or think ... but they rarely do. 

Issues that should be bipartisan have been made "us" versus "them," "liberal" versus "conservative," or "right" versus "wrong." The algorithms many of our information sites use create echo chambers that increase radicalization and decrease comprehension. 

Identity politics have gotten so strong that you see families breaking apart and friend groups disintegrating ... because people can't imagine sharing a room with someone with whom they don't share the same values. 

In psychology, heuristics are mental models that help you make decisions easier.  They're a starting point to save mental bandwidth, allowing you to spend more brain cycles on the important stuff.

That's a great use of "boxes" and "simplification"… but it shouldn't eliminate deeper and more nuanced thought on important issues. 

Most situations are nuanced, and the "correct" answer changes as you change your vantage point.

In an ideal world, we'd consider every angle.  I recognize that's not realistic.

Instead, I encourage you to remember to continue to think and learn ... even about things you already know.  And, if you become familiar with the most common cognitive biases, you can hopefully identify them in your thinking and decision-making.

Confirmation Bias is one of the more common forms of cognitive bias.  Here is an infographic that lists 50 common cognitive biases.  Click to explore further.

 

via VisualCapitalist

Important issues deserve more research.  New insights happen between the boundaries of what we know and don't.  Knowledge comes from truly understanding the border between what you are certain and uncertain about. 

I challenge you to look beyond the headlines, slogans, and talking points you like most.  Look for dissenting opinions and understand what's driving their dissent.  Are they really blind or dumb (or are their value systems just weighted differently)?

Not everything needs to be boxed.  Not everything needs to be simple.  You should explore things and people outside of your comfort zone and look to see things from their point of view ... not your own. 

Recently, I've started using a website and news app called Ground News.  They claim to be a news platform that makes it easy to compare news sources, read between the lines of media bias, and break free from algorithms. 

As discussed above, online news and ad-driven algorithms have made it profitable for news outlets to embrace a position on the bias spectrum to target specific consumers.   That bias in the media affects everything from what events receive coverage to how a news outlet frames those events in their reporting.

As media outlets narrow their perspective and range of coverage, I use Ground to help me get a well-rounded view of important issues and become aware of my blind spots.

Applying This Lesson  

“I am ashamed to think how easily we capitulate to badges and names, to large societies and dead institutions.”
― Ralph Waldo Emerson, Self-Reliance

I love learning a lesson in one space and applying it to other spaces.  It's one of the cool things about AI.  An algorithm can learn rules in the construction space that may help in the medicine or trading space.  Everything's a lesson if you let it be.

In that vein, the lesson on labeling also applies to yourself and your business.  Don't get me wrong - naming things is powerful.  It can help make the intangible tangible.  However, don't let the label (or your perception of the label) stop you from achieving something greater. 

Many things are true because we believe them to be, but when we let go of past beliefs, the impossible becomes possible, and the invisible becomes visible.  

Hope that helps. 

The Law (And Flaw) Of Averages

The law of averages is a principle that supposes most future events are likely to balance any past deviation from a presumed average.

Take, for example, flipping a coin.  If you happen to get 5 "Heads" in a row, you'd most likely assume the next one should be "Tails" ... even though each flip has a 50/50 chance of landing on either. 

Even from this example, you can tell it's a flawed law.  While there are some reasonable mathematical uses of the law of averages, in everyday life, this "law" mostly represents wishful thinking. 

It's also one of the most common fallacies succumbed to by gamblers and traders. 

The concept of "Average" is more confusing and potentially damaging than you might suspect.

Perhaps you heard the story about how the U.S. Air Force discovered the 'flaw' of averages by creating cockpits based on complex mathematics surrounding the average height, width, arm length, etc., of over 4,000 pilots.  Despite engineering the cockpit to precise specifications, pilots crashed their planes on a too-regular basis. 

The reason?  With hindsight, they learned that very few of those 4,000 pilots were actually "average".  Ultimately, the Air Force re-engineered the cockpit and fixed the problem. 

It's a good reminder that 'facts' can lie, and assumptions and interpretations are dangerous.  It's why I prefer taking decisive action on something known, rather than taking tentative actions about something guessed. 

via ReasonTV

Our Brains and the Illusion of Balance

Our brains are wired to find patterns, even in random events.  This tendency, known as apophenia, can lead us to see connections where none exist.

The Misleading Law of Averages

It's this very tendency that fuels the misconception of the law of averages.  We expect randomness to "even out" because we see patterns in short sequences.  This can be tempting to believe, especially when dealing with chance events.

The law of averages is a common idea that suggests future events will even out past results to reach some average outcome.  For instance, going back to our earlier coin-flipping example,  after getting five heads in a row, it's natural to assume the next flip is "due" to be tails.  However, that's not how probability works.  Each coin flip is an independent event (with a 50% chance of landing on heads or tails), regardless of previous flips.  The coin doesn't "remember" what happened before.

Apophenia isn't limited to coin flips.  For instance, you might see your lucky number appearing repeatedly throughout the day, leading you to believe it has a special meaning – even though each instance is completely independent.

This natural desire for order and predictability can lead us astray when dealing with chance events.

Why is it Flawed?

The law of averages often leads to a misconception called the gambler's fallacy.  This fallacy is the belief that random events can somehow "correct" themselves to reach an average.  In reality, every coin flip, roll of the dice, or spin of the roulette wheel is a fresh start with its own discrete probabilities.  The odds remain the same no matter how long the losing streak persists.

Are there ever times when it applies?

It's important to distinguish the law of averages from the law of large numbers, a well-established statistical principle.  The law of large numbers states that as the number of random events increases, the average outcome gets closer to the expected probability.  This applies in situations where many trials happen, and while past results of individual events are independent, the law describes the behavior of averages over a large number of trials.  For instance, the average weight of a large sample of apples will likely be close to the expected average weight of an apple, even if some individual apples are heavier or lighter than expected.

However, in everyday situations (with a limited number of events), the law of averages is generally not a helpful way to think about chance or probabilities.

Understanding these misconceptions can help us make better decisions and avoid false expectations based on flawed reasoning.

Psychological Reasons Behind the Belief

Human decision-making suffers from a range of tendencies and biases.

Earlier, we discussed the tendency to find patterns, even where none exist.  Next, we will consider cognitive bias.  In our coin-flipping example, it is the representativeness heuristic that makes us assume that small samples should resemble the larger population they come from.

Emotional factors also play a role.  The desire for control in uncertain situations can make us latch onto the law of averages as a comforting notion.  Believing that things will "even out" gives us a sense of predictability and fairness in an otherwise random world.

Additionally, social influences can reinforce these beliefs.  Stories and anecdotes about streaks ending or luck changing often circulate among friends and family, further embedding the misconception into our collective consciousness.

Understanding these psychological reasons helps explain why the law of averages persists despite its flaws.  Recognizing these biases can empower us to think more critically about probability and chance events.

Improving Decision-Making in Gambling and Investing

Recognizing the fallacy of the law of averages can significantly enhance decision-making, particularly in gambling and investing.  Understanding that each event is independent can help participants make more rational choices.  Instead of chasing losses with the hope that a win is "due," savvy speculators understand their odds remain constant and may choose to walk away or set strict limits on their betting behavior.

In investing, this knowledge is equally crucial.  Many factors influence markets.  Nonetheless, believing that a stock "must" rebound after a series of declines too often leads to poor investment decisions.  Investors who grasp that past performance does not dictate future results are better equipped to evaluate investments based on fundamentals rather than emotions or flawed expectations.

By dispelling these misconceptions, you can approach gambling or investing with a clearer mindset, reducing the risk of substantial losses driven by erroneous beliefs about probability and chance.

You can also eliminate fear, greed, and discretionary mistakes by relying on algorithms to calculate realtime expectancy scores and take the road less stupid.  Take a different kind of chance.  Just ask our AI Overlords; they'll tell you what to expect!

Correlation Between Market Crashes & Oreos?!

During the Robinhood & Gamestop debacle in 2021, I wrote an article about r/WallStreetBets where I essentially said that most of the retail investors that frequent the site don’t know what they’re doing ... Occasionally, however, there are posts that present the type of solid research or insights you might see from a respected Wall Street firm.

With Gamestop and AMC both surging recently, I thought this was a topic worth revisiting. 

As an example of good research done by the subreddit, here’s a link to a post where a user (nobjos) analyzed 66,000+ buy and sell recommendations by financial analysts over the last 10 years to see if they had an edge.  Spoiler: maybe, but only if you have sufficient AUM to justify the investment in their research. 

Some posts demonstrate a clear misunderstanding of markets, and the subreddit certainly contains more jokes than quality posts.  Nevertheless, I saw a great example of a post that pokes fun at the concept that correlation does not equal causation. 

I’ve posted about the Super Bowl Indicator and the Big Mac Index in the past, but what about Oreos?  Read what’s next for mouth-watering market insights.

The increasingly-depraved debuts of Oreos with more stuffing indicate unstable amounts of greed and leverage in the system, serving as an immediate indicator that the makings of a market crash are in place. Conversely, when the Oreo team reduces the amount of icing in their treats, markets tend to have great bull runs until once again society demands to push the boundaries of how much stuffing is possible.

1974: Double Stuf Oreo released. Dow Jones crashes 45%. FTSE drops 73%.

1987: Big Stuf Oreo released. Black Monday, a 20% single-day crash and a following bear market.

1991: Mini Oreo introduced. Smaller icing ratios coincide with the 1991 Japanese asset price bubble, confirming the correlation works both ways and a reduction of Oreo icing may be a potential solution to preventing a future crash.

2011: Triple Double Oreo introduced. S&P drops 21% in a 5-month bear market

2015: Oreo Thins introduced. A complete lack of icing causes an unprecedented bull run in the S&P for years

2019: The Most Stuf Oreo briefly introduced. Pulled off the shelf before any major market damage could occur.

2021: The Most Stuf Oreo reintroduced. Market response: ???

 - LehmanParty via Reddit

It’s surprisingly good due diligence, but it’s also clearly just meant to be funny.  It resonates because we crave order and look for signs that make markets seem a little bit more predictable.

The problem with randomness is that it often appears meaningful. 

Many people on Wall Street have ideas about how to guess what will happen with the stock market or the economy.  Unfortunately, they often confuse correlation with causation.  At least with the Oreo Indicator, we know that the idea was supposed to be thought-provoking (but silly) rather than investment advice to be taken seriously.

More people than you would hope or guess attempt to forecast the market based on gut, ancient wisdom, and prayers.

While hope and prayer are good things ... they aren’t reliably good trading strategies.

Consider this a reminder that even if you do the work, you’ll likely get a bad answer if you use the wrong inputs. 

Garbage in, garbage out. 

Onwards!

Some Timeless Wisdom From Socrates

Small distinctions separate wise men from fools ... Perhaps most important among them is what the wise man deems consequential. 

This post discusses Socrates' Triple Filter Test, which involves checking information for truth, goodness, and usefulness.  It also explores how this concept applies to decision-making in business and life by focusing on important information and filtering out the rest.  The key to making better choices and staying focused is to avoid damaging or irrelevant information.

Socrates' Triple Filter

In ancient Greece, Socrates was reputed to hold knowledge in high esteem.  One day an acquaintance met the great philosopher and said, "Do you know what I just heard about your friend?"

"Hold on a minute," Socrates replied. "Before telling me anything, I'd like you to pass a little test. It's called the Triple Filter Test."

"Triple filter?"

"That's right," Socrates continued.  "Before you talk to me about my friend, it might be a good idea to take a moment and filter what you're going to say. That's why I call it the triple filter test.

The first filter is Truth.  Have you made absolutely sure that what you are about to tell me is true?"

"No," the man said, "Actually I just heard about it and…"

"All right," said Socrates. "So you don't really know if it's true or not. Now let's try the second filter, the filter of Goodness.  Is what you are about to tell me about my friend something good?"

"No, on the contrary…"

"So," Socrates continued, "You want to tell me something bad about him, but you're not certain it's true.  You may still pass the test though, because there's one filter left.  The third filter is Usefulness.  Is what you want to tell me about my friend going to be useful to me?"

"No, not really."

"Well," concluded Socrates, "If what you want to tell me is neither true, nor good, nor even useful … then why tell it to me at all?"

With all the divisiveness in both media and in our everyday conversations with friends, family, and strangers ... this is a good filter for what you say, what you post, and even how you evaluate markets, the economy, or a business opportunity. 

How Does That Apply to Me or Trading?

The concept of Socrates' Triple Filter applies to markets as well.

When I was a technical trader, rather than looking at fundamental data and scouring the news daily, I focused on developing dynamic and adaptive systems and processes to look at the universe of trading algorithms to identify which were in phase and likely to perform well in the current market environment.

That focus has become more concentrated as we've transitioned to using advanced mathematics and AI to understand markets. 

Filter Out What Isn't Good For You.

In contrast, there are too many ways that the media (meaning the techniques, graphics, music, etc.), the people reporting it, and even the news itself appeal to the fear and greed of human nature.

Likewise, I don't watch the news on TV anymore.  It seems like story after story is about terrible things.  For example, during a recent visit with my mother, I listened to her watch the news.  There was a constant stream of "oh no," or "oh my," and "that's terrible".  You don't even have to watch the news to know what it says.

These concepts also apply to what you feed your algorithms.  Garbage in, garbage out.  Just because you can plug in more data doesn't mean that data will add value.  Deciding what "not to do" and "what not to listen to" is equally as important as deciding what to do. 

Artificial intelligence is exciting, but artificial stupidity is terrifying. 

What's The Purpose of News for You?

My purpose changes what I'm looking for and how much attention I pay to different types of information.  Am I reading or watching the news for entertainment, to learn something new, or to find something relevant and actionable?

 

 

One of my favorite activities is looking for new insights and interesting articles to share with you and my team.  If you aren't getting my weekly reading list on Fridays - you're missing out.  You can sign up here. 

By the way, I recently found a site, Ground News, that makes it easy to compare news sources, read between the lines of media bias, and break free from the blinders the algorithms put on what we see.  I'd love to hear about tools or sites you think are worth sharing.

Getting back to Socrates' three filters and business, I often ask myself: is it important, does it affect our edge, or can I use it as a catalyst for getting what we want?

There's a lot of noise out there competing for your attention.  Stay focused. 

Onwards!