Tag Archives: technology

The Tesla Cybertruck’s Branding Blow-Up

The inexact science of branding is nowhere more evident that in the case of the Tesla Cybertruck, which looks like it might usurp the Edsel’s title as the biggest automotive flop in history.

First, a little of the Tesla backstory. No, it wasn’t founded by Elon Musk. It was founded in 2003 by Martin Eberhard and Marc Tarpenning. Musk came in a year later as a money man. Soon, he had forced Eberhard and Tarpenning out of the company. But their DNA remained, notably in the design and engineering of the hugely popular Tesla Model S, Model X and Model 3. These designs drove Tesla to capture over 50% of the electric car market and are straight line extensions of the original technology developed by Eberhard, Tarpenning and their initial team

Musk is often lauded as an eccentric genius in the mold of Steve Jobs, who had his fingers in every aspect of Tesla. While he was certainly influential, it’s not in the way most people think. The Model S, Model X and Model 3 soon became plagued by production issues, failed software updates, product quality red flags and continually failing to meet to meet Musk’s wildly optimistic and often delusional predictions, both in terms of sales and promised updates. Those things all happened on Musk’s watch.  Even with all this, Tesla was the darling of investors and media, driving it to be the most valuable car company in the world.

Then came the Cybertruck.

Introduced in 2019, the Cybertruck did have Musk’s fingerprints all over it. The WTF design, the sheer impracticality of a truck in name only, a sticker price nearly double of what Musk originally promised and a host of quality issues including body panels that have a tendency to fall off have caused sales to not even come close to projections.

In its first year of sales (2024), the Cybertruck sold 40,000 units, about 16% of what Musk predicted annual sales could be. That makes it a bigger fail than the Edsel, which sold 63,000 units against a target of 200,000 sales in its introductory year – 1958. The Edsel did worse in 1959 and was yanked from the market in 1960. The Cybertruck is sinking even faster. In the first quarter of this year, only 6406 Cybertrucks were sold, half the number sold in the same quarter a year ago. There are over 10,000 Cybertrucks on Tesla lots in the U.S., waiting for buyers that have yet to show up.

But it’s not just that the Cybertruck is a flawed product. Musk has destroyed Tesla’s brand in a way that can only be marvelled at. His erratic actions have managed to generate feelings of visceral hate in a huge segment of the market and that hate has found a visible target in the Cybertruck. It has become the symbol of Elon Musk’s increasingly evident meltdown.

I remember my first reaction when I heard that Musk had jumped on the MAGA bandwagon. “How the hell,” I thought, “does that square with the Tesla brand?” That brand, pre-Musk-meltdown and pre-Cybertruck, was a car for the environmentally conscious who had a healthy bank account – excitingly leading edge but not dangerously so. Driving a Tesla made a statement that didn’t seem to be in the MAGA lexicon at all. It was all very confusing.

But I think it’s starting to make a little more sense. That brand was built by vehicles that Musk had limited influence over. Sure, he took full credit for the brand, but just like company he took over, it’s initial form and future direction was determined by others.

The Cybertruck was a different story. That was very much Musk’s baby. And just like his biological ones (14 and counting), it shows all the hallmarks of Musk’s “bull in a China shop” approach to life. He lurches from project to project, completely tone-deaf to the implications of his actions. He is convinced that his genius is infallible. If the Tesla brand is a reflection of Musk, then the Cybertruck gives us a much truer picture. It shows what Tesla would have been if there had never been a Martin Eberhard and Marc Tarpenning and Musk was the original founder.

To say that the Cybertruck is “off brand” for Tesla is like saying that the Titanic had a tiny mishap. But it’s not that Musk made a mistake in his brand stewardship. It’s that he finally had the chance to build a brand that he believed in.

Curation is Our Future. But Can You Trust It?

 You can get information from anywhere. But the meaning of that information can come from only one place: you. Everything we take in from the vast ecosystem of information that surrounds us goes through the same singular lens – one crafted by a lifetime of collected beliefs and experiences.

Finding meaning has always been an essentially human activity. Meaning motivates us – it is our operating system. And the ability to create shared meaning can create or crumble societies. We are seeing the consequences of shared meaning play out right now in real time.

The importance of influencing meaning creates an interesting confluence between technology and human behavior. For much of the past two decades, technology has been focusing on filtering and organizing information. But we are now in an era where technology will start curating our information for us. And that is a very different animal.

What does it mean to “curate” an answer, rather than simply present it to you? Curation is more than just collecting and organizing things. The act of curation is to put that information in a context that provides additional value by providing a possible meaning. This crosses the line that delineates just disseminating information from attempting to influence individuals by providing them a meaningful context for that information. 

Not surprisingly, the roots of curation lie – in part – with religion. It comes from the Latin “curare” – “to take care of”. In medieval times, curates were priests who cared for souls. And they cared for souls by providing a meaning that lay beyond the realms of our corporal lives. If you really think about religion, it is one massive juxtaposition of a pre-packaged meaning on the world as we perceive it.

In the future, as we access our world through technology platforms, we will rely on technology to mediate meaning. For example, searches on Google now include an “AI Overview” at the top of the search results The Google Page explaining what the Overview is says it shows up when “you want to quickly understand information from a range of sources, including information from across the web and Google’s Knowledge Graph.” That is Google – or rather Google’s AI – curating an answer for you.

It could be argued that this is just another step to make search more useful – something I’ve been asking for a decade and a half now. In 2010, I said that “search providers have to replace relevancy with usefulness. Relevancy is a great measure if we’re judging information, but not so great if we’re measuring usefulness.” If AI could begin to provide actionable answers with a high degree of reliability, it would be a major step forward. There are many that say such curated answers could make search obsolete. But we have to ask ourselves, is this curation something we can trust?

With Google, this will probably start as unintentional curation – giving information meaning through a process of elimination. Given how people scan search listings (something I know a fair bit about) it’s reasonable to assume that many searchers will scan no further than the AI Overview, which is at the top of the results page. In that case, you will be spoon-fed whatever meaning happens to be the product of the AI compilation without bothering to qualify it by scanning any further down the results page. This conveyed meaning may well be unintentional, a distillation of the context from whatever sources provided the information. But given that we are lazy information foragers and will only expend enough effort to get an answer that seems reasonable, we will become trained to accept anything that is presented to us “top of page” at face value.

From there it’s not that big a step to intentional curation – presenting information to support a predetermined meaning. Given that pretty much every tech company folded like a cheap suit the minute Trump assumed office, slashing DEI initiatives and aligning their ethics – or lack of – to that of the White House, is it far-fetched to assume that they could start wrapping the information they provide in a “Trump Approved” context, providing us with messaged meaning that supports specific political beliefs? One would hate to think so but based on Facebook’s recent firing of its fact checkers, I’m not sure it’s wise to trust Big Tech to be the arbitrators of meaning.

They don’t have a great track record.

The World vs Big Tech

Around the world, governments have their legislative cross hairs trained on Big Tech. It’s happening in the US, the EU and here in my country,  Canada. The majority of these are anti-trust suits. But Australia has just introduced a different type of legislation, a social media ban for those under 16. And that could change the game – and the conversation -completely for Big Tech.

There are more anti-trust actions in the queue in the US than at any time in the previous five decades. The fast and loose interpretation of antitrust enforcement in the US is that monopolies are only attacked when they may cause significant harm to customers through lack of competition. The US approach to anti-trust since the 1970s has typically followed the Chicago School of neoclassical economy theory, which places all trust in the efficiency of markets and tells government to keep their damned hands off the economy. Given this and given the pro-business slant of all US administrations, both Republican and Democratic, since Reagan, it’s not surprising that we’ve seen relatively few anti-trust suits in the past 50 years.

But the rapid rise of monolithic Big Tech platforms has raised more discussion about anti-trust in the past decade than in the previous 5 decades. These platforms suck along the industries they spawn in their wake and leave little room for upstart competitors to survive long enough to gain significant market share.

Case in point: Google. 

The recent Canadian lawsuit has the Competition Bureau (our anti-trust watchdog) suing Google for anti-competitive practices selling its online advertising services north of the 49th parallel. They’re asking Google to sell off two of its ad-tech tools, pay penalties worth up to 3% of the platform’s global gross revenues and prohibit the company from engaging in anti-competitive practices in the future.

According to a 3-year inquiry into Google’s Canadian business practices by the Bureau, Google controls 90% of all ad servers and 70% of advertising networks operating in the country. Mind you, Google started the online advertising industry in the relatively green fields of Canada back when I was still railing about the ignorance of Canadian advertisers when it came to digital marketing. No one else really had a chance. But Google made sure they never got one by wrapping its gigantic arms around the industry in an anti-competitive bear hug.

The recent Australian legislation is of a different category, however. Anti-trust suits are – by nature – not personal. They are all about business. But the Australian ban puts Big Tech in the same category as Big Tobacco, Big Alcohol and Big Pharma – alleging that they are selling an addictive product that causes physical or emotional harm to individuals. And the rest of the world is closely watching what Australia does. Canada is no exception.

The most pertinent question is how will Australia enforce the band? Restricting social media access to those under 16 is not something to be considered lightly.  It’s a huge technical, legal and logistical hurdle to get over. But if Australia can figure it out, it’s certain that other jurisdictions around the world will follow in their footsteps.

This legislation opens the door to more vigorous public discourse about the impact of social media on our society. Politicians don’t introduce legislation unless they feel that – by doing so – they will continue to get elected. And the key to being elected is one of two things; give the electorate what they want or protect them against what they fear. In Australia, recent polling indicates the ban is supported by 77% of the population. Even those opposing the ban aren’t doing so in defense of social media. They’re worried that the devil might be in the details and that the legislation is being pushed through too quickly.

These types of things tend to follow a similar narrative arc: fads and trends drive widespread adoption – evidence mounts about the negative impacts – industries either ignore or actively sabotage the sources of the evidence – and, with enough critical mass, government finally gets into the act by introducing protective legislation.

With tobacco in the US, that arc took a couple of decades, from the explosion of smoking after World War II to the U.S. Surgeon General’s 1964 report linking smoking and cancer. The first warning labels on cigarette packages appeared two years later, in 1966.

We may be on the cusp of a similar movement with social media. And, once again, it’s taken 20 years. Facebook was founded in 2004.

Time will tell. In the meantime, keep an eye on what’s happening Down Under.

The Political Brinkmanship of Spam

I am never a fan of spam. But this is particularly true when there is an upcoming election. The level of spam I have been wading through seems to have doubled lately. We just had a provincial election here in British Columbia and all parties pulled out all stops, which included, but was not limited to; email, social media posts, robotexts and robocalls.

In Canada and the US, political campaigns are not subject to phone and text spam control laws such as our Canadian Do Not Call List legislation. There seems to be a little more restriction on email spam. A report from Nationalsecuritynews.com this past May warned that Americans would be subjected to over 16 billion political robocalls. That is a ton of spam.

During this past campaign here in B.C., I noticed that I do not respond to all spam with equal abhorrence. Ironically, the spam channels with the loosest restrictions are the ones that frustrate me the most.

There are places – like email – where I expect spam. It’s part of the rules of engagement. But there are other places where spam sneaks through and seems a greater intrusion on me. In these channels, I tend to have a more visceral reaction to spam. I get both frustrated and angry when I have to respond to an unwanted text or phone call. But with email spam, I just filter and delete without feeling like I was duped.

Why don’t we deal with all spam – no matter the channel – the same? Why do some forms of spam make us more irritated than others? It’s almost like we’ve developed a spam algorithm that dictates how irritated we get when we deal with spam.

According to an article in Scientific American, the answer might be in how the brain marshalls its own resources.

When it comes to capacity, the brain is remarkably protective. It usually defaults to the most efficient path. It likes to glide on autopilot, relying on instinct, habit and beliefs. All these things use much less cognitive energy than deliberate thinking. That’s probably why “mindfulness” is the most often quoted but least often used meme in the world today.

The resource we’re working with here is attention. Limited by the capacity of our working memory, attention is a spotlight we must use sparingly. Our working memory is only capable of handling a few discrete pieces of information at a time. Recent research suggests the limit may be around 3 to 5 “chunks” of information, and that research was done on young adults. Like most things with our brains, the capacity probably diminishes with age. Therefore, the brain is very stingy with attention. 

I think spam that somehow gets past our first line of defence – the feeling that we’re in control of filtering – makes us angry. We have been tricked into paying attention to something that was unsuspected. It becomes a control issue. In an information environment where we feel we have more control, we probably have less of a visceral response to spam. This would be true for email, where a quick scan of the items in our inbox is probably enough to filter out the spam. The amount of attention that gets hijacked by spam is minimal.

But when spam launches a sneak attack and demands a swing of attention that is beyond our control, that’s a different matter. We operate with a different mental modality when we answer a phone or respond to a text. Unlike email, we expect those channels to be relatively spam-free, or at least they are until an election campaign comes around. We go in with our spam defences down and then our brain is tricked into spending energy to focus on spurious messaging.

How does the brain conserve energy? It uses emotions. We get irritated when something commandeers our attention. The more unexpected the diversion, the greater the irritation.  Conversely, there is the equivalent of junk food for the brain – input that requires almost no thought but turns on the dopamine tap and becomes addictive. Social media is notorious for this.

This battle for our attention has been escalating for the past two decades. As we try to protect ourselves from spam with more powerful filters, those that spread spam try to find new ways to get past those filters. The reason political messaging was exempt from spam control legislation was that democracies need a well-informed electorate and during election campaigns, political parties should be able to send out accurate information about their platforms and positions.

That was the theory, anyway.

The Adoption of A.I.

Recently, I was talking to a reporter about AI. She was working on a piece about what Apple’s integration of AI into the latest iOS (cleverly named Apple Intelligence) would mean for its adoption by users. Right at the beginning, she asked me this question, “What previous examples of human adoption of tech products or innovations might be able to tell us about how we will fit (or not fit) AI into our daily lives?”

That’s a big question. An existential question, even. Luckily, she gave me some advance warning, so I had a chance to think about it.  Even with the heads up, my answer was still well short of anything resembling helpfulness. It was, “I don’t think we’ve ever dealt with something quite like this. So, we’ll see.”

Incisive? Brilliant? Erudite? No, no and no.

But honest? I believe so.

When we think in terms of technology adoption, it usually falls into two categories: continuous and discontinuous. Continuous innovation simply builds on something we already understand. It’s adoption that follows a straight line, with little risk involved and little effort required. It’s driving a car with a little more horsepower, or getting a smartphone with more storage.

Discontinuous innovation is a different beast. It’s an innovation that displaces what went before it. In terms of user experience, it’s a blank slate, so it requires effort and a tolerance for risk to adopt it. This is the type of innovation that is adopted on a bell curve, first identified by American sociologist Everett Rogers in 1962. The acceptance of these new technologies spreads along a timeline defined by the personalities of the marketplace. Some are the type to try every new gadget, and some hang on to the tried and true for as long as they possibly can. Most of us fall somewhere in between.

As an example, think about going from driving a tradition car to an electric vehicle. The change from one to the other requires some effort. There’s a learning curve involved. There’s also risk. We have no baseline of experience to measure against. Some will be ahead of the curve and adopt early. Some will drive their gas clunker until it falls apart.

Falling into this second category of discontinuous innovation, but different by virtue of both the nature of the new technology and the impact it wields, are a handful of innovations that usher in a completely different paradigm. Think of the introduction of electrical power distribution in the late 19th century, the introduction of computers in the second half of the 20th century, or the spread of the internet in the 21st Century.

Each of these was foundational, in that they sparked an explosion of innovation that wouldn’t have been possible if it were not for the initial innovation. These innovations not only change all the rules, they change the very game itself. And because of that, they impact society at a fundamental level. When these types of innovations come along, your life will change whether you choose to adopt the technology or not. And it’s these types of technological paradigm shifts that are rife with unintended consequences.

If I was trying to find a parallel for what AI means for us, I would look for it amongst these examples. And that presents a problem when we pull out our crystal ball and try to peer ahead at what might be. We can’t know. There’s just too much in flux – too many variables to compute with any accuracy. Perhaps we can project forward a few months or a year at the most, based on what we know today. But trying to peer any further forward is a fool’s game. Could you have anticipated what we would be doing on the Internet in 2024 when the first BBS (Bulletin Board System) was introduced in Chicago in 1978?

A.I. is like these previous examples, but it’s also different in one fundamental way. All these other innovations had humans at the switch. Someone needed to turn on the electrical light, boot up the computer or log on to the internet. At this point, we are still “using” A.I., whether it’s as an add-on in software we’re familiar with, like Adobe Photoshop, or a stand-alone app like ChatGPT, but generative A.I.’s real potential can only be discovered when it slips from the grasp of human control and starts working on its own, hidden under some algorithmic hood, safe from our meddling human hands.

We’ve never dealt with anything like this before. So, like I said, we’ll see.