The next best thing since the last best thing! Some tech hype models to live by

Lately, colleagues Jon Reed and Stuart Lauchlan (among countless others) have been experimenting with and commenting on ChatGPT – an AI tool that is garnering considerable, outsized attention of late. This technology has been in the news a lot with some of the more hyperbolic headlines telling us that: 

What generally happens at this stage of new product is that more and more pundits, politicians, media types and more see an opportunity to either pile on with headline grabbing concerns or rush to the defense of the new but so misunderstood technology. Regardless of which side these players take, the new tech continues to amass headlines and attention. 

For the creators and investors in this new tech, the publicity, good or bad, is usually helpful. P.T. Barnum is often cited as the source of the idiom “All publicity is good publicity”. And don’t forget his corollary piece of wisdom “There’s no such thing as bad publicity”. New tech often follows this guidance.

Whenever a new technology comes out, market watchers and others start whipping up the potential concerns that the new tech will inflict on people, businesses, the environment and more. You can almost always predict that someone will claim that a new innovative technology will:

• Cause large numbers of people to lose their jobs
• Allow criminals to steal more of a person’s wealth or identity 
• Trigger adverse health consequences
• Will create a societal gap between users/owners of the new tech and those that don’t have access to it 
• Eventually get weaponized
• Destroy wealth
• Create wealth

Don’t believe me? ChatGPT is far from the first technology that’s generated serious hype and concern. Just go back a couple of years ago and remember how: 

• Smart phones were going to cause all kinds of brain cancers
• Self-driving cars were going to cause all kinds of mayhem (okay, there’s some truth to this)
• Process automation tools were going to eliminate most accounting jobs
• The ‘Cloud’ was going to transform businesses, reduce IT costs, etc.
• The world was going paperless
• We’ll all soon be in a cashless world
• Cryptocurrencies will replace country-specific currencies
• Second Life (a precursor to the metaverse) will replace traditional commerce and entertainment

And, of course, 

• Broadband internet access would empty workers out of offices and almost all work would occur virtually

Creators or investors of a radically new tech know that the easiest way to get attention is follow a hype formula. That formula usually includes:

• Tying a new technology (or concept) to a radical reimagination of work, pleasure, business, etc.  
• Getting some non-tech celebrity or politician to talk up the new tech even if they have no idea what it really can or can’t do. This is perfect for big concepts with no real proof points. Bonus points if you can get a rapper, jock and/or Hollywood star to endorse the tech. 
• Making the early investors a huge part of the story. In fact, the more the founders hype who is investing in the new tech vs. what value the new tech is actually delivering, then the greater the overhype risk is. 
• Attacking anyone who would dare demand proof of value delivered. Hype-sters are quick to brand anyone who doesn’t fully embrace the hype as ‘ignorant’, ‘technically slow’, a ‘laggard’ or worse. These founders make it seem that only they, the omniscient inventors/investors, know more than anyone else on this earth. 

When the new tech starts to show visible cracks in its armor, the founders often double down on their support for the new tech and their disgust for any critic or naysayer.  When this overhyped/underdelivered phase passes, the crash can be heard ‘round the world.

The enablers

The laziest, click-baiting writers/influencers/tech marketers out there don’t do a lot of research. They see a headline or a press release about a new tech product or category and figure “Hey, I can get some press out of this new tech!”  And, the worst of these are the ones who blindly accept and repeat the claims of the new tech founders/investors. 

Parroting and/or amplifying founder claims without verification is, at a minimum, ethically challenged and intellectually weak. And yet, bloggers, influencers and traditional media aid and abet the continued hyping of these new tech products simply because the articles on these new technologies attract readers and are easy to produce (especially when the founder/investor spoon feeds them copy and soundbites). These enablers may think they are merely reporting what others are saying but to do so without applying any effort to verify the claims is likely negligent. 

What often gets underreported at this stage are the product’s and founders’ bona fides. It is astonishing that people get burned when a new technology company:

• Has no customers in production yet.
• Gets a massive unicorn valuation (i.e., $1 billion or more valuation) without actually shipping a real product yet.
• Is being run by kids with no business background (i.e., where’s the adult supervision?).
• Fails to account: where it’s spending its venture capital money, what its burn rate really is, how long it can continue to burn cash, etc. 

But the surest way to spot a future flameout is to see if the firm is holding its company or sales meetings in some exotic island hotel or a major Vegas casino with all kinds of bad behavior on full display. Blowing through mountains of cash should never be a tech company core competency and it never should be a source of pride. Anytime a reporter or influencer sees this kind of activity, it should be loudly reported and denounced – not celebrated. 

When hype re-orients

When a new technology category/segment appears, the initial flurry of speculative hype (above) may begin to wane as new data points emerge and more considered and thoughtful analyses are prepared. Real case studies will replace the speculative and overly optimistic claims of yore. 

Analyst firm, Gartner, saw this yo-yo effect of technology hype and coined a model, the Hype Cycle, to illustrate it. (See: Gartner Hype Cycle Research Methodology | Gartner or Gartner hype cycle - Wikipedia).  The Hype Cycle has five stages. The first is the technology trigger. Immediately thereafter, the hype and market awareness of the new technology rises to a very high ‘peak of inflated expectations’. After that, the hype turns negative until the technology experiences its ‘trough of disillusionment’. After all of that up and down, the product goes through a period Gartner calls the ‘slope of enlightenment’ until it eventually reaches its ‘plateau of productivity’. 

Colleague Jon Reed has this to say about the plateau of productivity: 

Not every technology achieves that plateau, and some do it far better than others. It's not like all tech comes out useful and productive on the other side. For example, I don't think blockchain and the Metaverse are going to emerge in some meaningful way that dramatically changes the enterprise. They'll have their use cases to be sure. Sometimes it takes a long, long time to hit this plateau. I suspect Quantum Computing will have some very useful scenarios but not for years.

Jon makes a good point. I’ve seen some products or categories experience a massive run-up in hype and then crash and burn. They never get out of the trough of disillusionment. I actually wrote an entire book manuscript on this (and related) phenomena. 

That Gartner model and its stages often parallel many real-world situations involving new technologies. 

The Gartner hype cycle isn’t the only model, though. If a new technology has a particularly jarring or disquieting profile, then a new kind of hype may pop up. In a very recent Wired magazine article, Kevin Kelly noted the Tech Panic Cycle. 

In looking at the Tech Panic Cycle, a writer/influencer/marketer can see 7 or more ways to spin a story about a new kind of technology. It’s like the cycle can define an editorial calendar.  

To illustrate, the current mix of stories re: ChatGPT seem to be a mix of phases 1 and 2 for now. Some people are sounding potential alarm bells (#2) while others not convinced of the tool’s abilities so far (#1). We can expect new articles coming soon that will focus on phase 3.

Readers should always expect a correction to the initial hype of a new technology or segment. The euphoria of the early days will need to be updated with new, better, real-world data points. That’s what the real story should be. 

And while the real story could be correct, it may not be as headline grabbing as the fear-mongering stories one could generate. It’s the latter that makes the trough of disillusionment so compelling from a click-bait perspective and often deeper than it need be. 

Armchair visionaries/savants

I’m sure most of you have a relative, in-law or friend who has a deeply-felt (not necessarily fact-based) opinion on most every subject including technology.  It’s a shame that these self-proclaimed experts are given platforms on social media to render their perspectives given the lack of rigor that goes into their assessments. But, write they will. 

The effect of so many pseudo-experts in social media creates an amplifying and distorting effect. The truth can get drowned out by people who don’t want to hear it. They’d rather stand in the echo chamber with others of a similar philosophy.  This amplifies one aspect of the hype and obliterates another.  It can also distort the reality of the situation when lots of speculation, opinion and cheerleading skews casual readers to think this is the way things really are.  One classic situation of this occurs every year-end when press releases about predictions become more numerous than holiday greeting cards. We need to be asking why should we give credence to the technology predictions of an out-of-work tech person whose biggest claim to fame was that they created their own blog? 

If readers and publications were truly discriminating, they’d exercise more care in selecting which sources they consider in formulating their decisions and pieces. For me, I don’t want just anyone’s opinion, I prefer the ones who have well researched data, fact-based, defensible materials.  

Just because someone has a soapbox or can draft a press release doesn’t mean that their content is really worth sharing. Remember, there is content and content that matters. 

Tech and the 'Dark Side'

History is full of technologies being appropriated for use by the less stellar members of the human race. Show me a new technology category, and I’ll bet someone’s looking to use it for less than honorable purposes. For example, several sources state that 30% of internet content is porn. There are dark web sites that trade in stolen identities. You name it and someone’s likely thinking of ways to move a cool new tech to the dark side.  (see this piece on Twitter’s porn problem) 

Pundits, arm-chair or real professionals, talk about this. And, I almost never see these matters discussed in their annual predictions or market forecast estimates. The unwillingness to discuss this fact of life is disingenuous.  

One last model - Fubini’s Law

If you’re feeling compelled to say or write something about a new technology, you might want to ponder Fubini’s Law. It states:

“1. People initially use technology to do what they do now – but faster.
2. Then they gradually begin to use technology to do new things.
3. The new things change lifestyles and work-styles.
4. The new lifestyles and work-styles change society
… and eventually change technology.”

In the context of AI and machine learning, we can already see where this technology is being used to do traditional tasks (like accounts payable invoice vouching and entry) in a fully automated manner. Since that works, AI/ML is being used to do new things (e.g., park a car without human input). And when enough driverless capabilities come together, it can then change how we work and live. 

Fubini’s model is circular but it reminds us that new technology goes through a flow. New technology is rarely a destination in and of itself. It’s part of the journey. That’s how we should be looking at it. And, if the PR flacks, marketers, crooks, bad investors and intellectually bankrupt hype-aholics out there only realized that, they’d craft more intelligent copy with a more refined long-view of the space. 

That would be really nice.   

Additional (recommended) reading

All readers who are interested in AI generally and ChatGPT specifically should really check out Gary Marcus’ piece:   24 Seriously Embarrassing Hours for AI - by Gary Marcus (substack.com). It’s an eye-opening review of numerous AI technologies and the less than perfect results that are being generated (or how the models are being trained). One thing that captured my attention is that his piece is looking at some of the big AI/ChatGPT stories that have broken in just a 24-hour window. When a new technology is starting its hype phase, the quantity and velocity of stories about it can be tremendous.   

Specific to ChatGPT, you should check out a a recent piece by Stuart Lauchlan.  Stuart has some nice observations from an Accenture executive that bring a measure of caution to the discussion. 

And, finally, readers should check out this piece by Jeffrey Sonnenfeld in Chief Executive magazine. The article is titled “The Problem With Prophets” and it concludes with five common forecasting failings. One soundbite I really liked was: “The only function of economic forecasting is to make astrology look respectable.” Clearly, that’s the QOTD (quote of the day)!