Welcome to Stuff I Thought About Last Week, a personal collection of topics on tech, innovation, science, the digital economic transition, the finance industry, and whatever else made me think last week.

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In today’s post: your driving activity may be secretly increasing your insurance rates, just one of the many insidious ways data will be used against us as analytics becomes AI's child's play; software priced per conversation; demonstrations of advanced AI replacing information and physical-world jobs are proliferating, creating a growing sense of human inferiority; bubble gum demand pops; Pi and I discuss the controversy around the Hubble constant; the diverging wages between high and low income earners; and, much more below.

Stuff about Innovation and Technology
Auto Espionage
While the US frets about Chinese cars spying on Americans, it turns out the real threat is American car companies spying on us for profit. The NYT has a detailed exposé on the data your car maker is selling without your knowledge to your insurance company, which is using it in some cases to dramatically raise your premiums. There are two things that I think heighten the righteous indignation of this situation: 1) this data sharing is happening without people realizing it or actively opting in with awareness of the potential costs; and 2) it appears to be asymmetric: insurers are using your driving data to raise rates but not lower them. It turns out that both of our cars have data agreements in place to sell our driving behavior to insurance companies, and I have no recollection of opting in or agreeing to it. Driver behavior monitoring is another example of data and algorithms talking to each other secretly in the background causing prices to rise, like we’ve seen in other industries such as apartment rentals. As AI increasingly scores an individual’s risks, whether it be for a job application, apartment rental, insurance, mortgage, etc., disparate pools of previously disconnected data are going to be used far more often, and consumers are likely to be blindsided by more negative impacts.
 
The Long Answer
Microsoft’s new Security Copilot is priced on a consumption-based model at $4/hour. I’ve been talking for a while about the potential challenges of cloud software moving from seat-based to value-based pricing, especially if that software is going to replace some of those “seats” (aka humans). So, charging per conversation (using “security compute units”) should be an interesting experiment. However, at first pass, this pricing strategy would seem misaligned with customers, who generally want answers as quickly as possible, which is at odds with service providers incentivized to take longer to solve customer needs. 
 
You Are Special?
An array of recent, compelling examples of AI and robots catching up to (or surpassing) humans at various tasks has me thinking about that inevitable moment coming for us all when we see, for the first time, technology accomplish a task we thought we were uniquely good at. As I reflect on the dazzling new examples, I am reminded of the poignant aftermath of AlphaGo beating Lee Se-dol, as portrayed in this documentary (see also #221 from 2019). Se-dol retired from the game in 2019 declaring AI “invincible”. The AlphaGo matches were in 2016, so the writing has been on the wall for a while. Now, eight years later, the stomach dropping moments of AI’s feats are coming faster than we can process. Software engineering has of course been an early example of AI proficiency; and, recently, a demo of Devin (Cognition Labs) shows what appears to be a fully functioning AI programmer. We were not the only ones wowed by OpenAI’s Sora video generator, with the president of Hollywood’s Animation Guild saying that “the future is foggy” (WSJ). A combination of AI programmers, engines like Epic’s Unreal, and video generators like Sora suggests a near future of video game development and immersive media that is largely, if not entirely, AI driven. But, in addition to all these AI creators, there are also AI players. Google’s DeepMind recently demonstrated SIMA, an AI agent capable of navigating virtual 3D environments. SIMA can play complex video games like humans. It’s surely an AlphaGo-like moment when you realize a machine can beat you at any game. Does this loss of specialness cause you to put the controller down and never pick it back up? This reminds me of something Jaron Lanier said about VR gaming recently: “There are many reasons why V.R. and gaming don’t quite work, and I suspect that one is that gamers like to be bigger than the game, not engulfed by it. You want to feel big, not small, when you play.” When AI is “bigger” than humans, will we want to keep playing? Perhaps even the joy of watching a movie will fade when we learn that AI agents can have the same nuanced, emotional takeaways as humans. How much of what we do is motivated by the pride of being able to do something well that others (whether they be human, machine or animal) cannot? The thrill and adrenaline of playing a great video game or getting sucked into a director’s world might still be enough to drive our experiential desire. But, knowing a trillion AI agents can do the same might also take away from our enjoyment, driving us to seek even more complex and/or esoteric activities that remain uniquely within the human skillset.
 
Of course, there is an even bigger leap coming as AI is embedded in form factors capable of interacting with the world. Last week’s demo of the Figure robot, featuring OpenAI’s GPT4 and very human-like speech rendering, offers a glimpse into the physical awareness and responsiveness coming to AI. The Figure robot sees and physically reacts to its environment in real time while conversing with a human. Embedding an LLM in the physical world like that, with context and continuity in the form of long-term memory, creates a sense of “self”, and is, for all practical (and perhaps transcending practical) purposes, a new type of being. The main difference between us and AI-enhanced bots' minds will be our lifetime of experiential learning. While a simulated “childhood” could be embedded into the memory of an AI, the lack of feedback from years of mistakes and experiments – all which underpin our understanding of our environment and the social/emotional dynamics of the creatures that inhabit it – would presumably create a different type of conscious awareness. Similar to Thomas Nagel’s “What Is It Like To Be a Bat”, it may be just as hard for us to perceive what it’s like to be a bipedal AI wired from birth (so to speak). 
 
All of these new examples of AI’s human-equivalent prowess, in both information-based and real-world physical tasks, makes me wonder whether their form of consciousness is also human-like, or perhaps as incomprehensible to us as a bat’s awareness. The more self-aware embedded AI becomes, the more we may feel in opposition with it, and thus feel defeated when it surpasses our own capabilities. I discussed this theme of humans vs. technology at length in John Henry vs. Lee Se-dol back in 2022. Technology taking over human jobs – whether it’s the steam-engine-powered drill that John Henry was up against, or the Figure robot loading a dishwasher – is nothing new. Each leap has reduced a previously uniquely human skill to something replicable by machines or software. John Henry fought the technology and collapsed, according to folklore. Could AI write a song as enduring as “The Ballad of John Henry” and create a voice as captivating as that of Tennessee Ernie Ford to sing it? Will AI feel what I feel when I hear Tom Jones belt out “Elvis Presley Blues”, speculating how Elvis, on the precipice of death, might have pondered how happy John Henry must have been when he fell down and died? But, no need to get depressed, there’s still a bit of time yet before humans face an existential AI reckoning en masse. Afterall, the majority of the examples above are betas and demos, and we all know how well Silicon Valley excels at vaporware – touting the premiere of revolutionary technologies that won’t be ready for five to ten years, if ever! Entire companies are faked all the way through (e.g., Theranos); so, there could easily be a wizard behind the curtain pulling the strings on these demos. But, still, the glimpse of this next technological wave inspires more fear of change than what we saw during the techno-optimist dotcom bubble. Further down in the newsletter, you’ll see a section written by Pi.ai that I am relatively happy with and that did not leave me feeling devoid of specialness (it does seem to lack a certain something...special). Working alongside AI is still a net positive experience, at least for now. 

Miscellaneous Stuff
Addiction-Driven Sales
Chewing gum volumes have dropped 32% since 2018 to 1.2B units. However, with the average pack price increasing by $1 to $2.71, overall US gum revenues are stable. Although this trend is unrelated to GLP-1s, this is a good example of price overcoming declining volumes, particularly in habit-forming products (see Can Advertising Stomach GLP-1s?). Gen Z eschewing gum chewing is implicated in the slowdown. The gum industry is adding ingredients like vitamins and trying to reposition gum as a stress reliever vs. its traditional image as a breath freshener. Meanwhile, Philip Morris, owner of Zyn nicotine pouches, reports that US sales grew 62% in 2023, with a forecast for 35% growth in 2024. There's always a bubble somewhere.
 
Pi Explains Hubble Heresy
The following was written by Pi.ai based on a detailed outline and source articles (here and here) that I provided to it:
About a century ago, Edwin Hubble made the groundbreaking discovery that distant objects in space were receding from us at a faster rate than closer ones, pointing to an accelerating expansion of the universe. This phenomenon is described by Hubble's Law, with the rate of expansion quantified by the Hubble constant (H0). Hubble's initial estimate for H0 was around 70 km/s/Mpc. The Hubble Space Telescope later provided a refined value of 74, which was recently confirmed by the James Webb Space Telescope (JWST). Interestingly, the Planck satellite's observations of the cosmic microwave background (CMB) suggest a lower Hubble constant of around 70, implying a slower expansion rate following the Big Bang. This discrepancy between the CMB-based and telescope-based measurements has been a source of debate and investigation in the field of cosmology. The disagreement might be an indication that our current understanding of the universe's expansion history is incomplete or that some unknown physical processes are at play. As scientists continue to investigate the discrepancy between the CMB-based and telescope-based measurements, the pursuit of a precise and consistent Hubble constant value may not only resolve this tension but could also challenge or refine our current models of cosmic evolution and shed new light on the elusive nature of dark energy, the mysterious force driving the universe's accelerating expansion.

Stuff About Demographics, the Economy, and Investing
White Collar Wage Deflation
One way to parse the economy is to compare how low-wage vs. high-wage earners are faring. For example, BI recently compared managerial vs. non-managerial wages in the US, which have had strikingly divergent trajectories over the past couple of decades. Since 2006, managerial wages have been flat in real terms (inflation adjusted), while non-managerial wages have risen 15%. The recent difference is even more stark, with non-managerial earnings rising about 4% in real terms since pre-pandemic 2019 (despite high inflation), while managerial real earnings are down about 8%. Of course, higher wage earners have fared better in other areas of wealth with home price and stock market increases. Even some workers at Google are seeing stagnating and falling pay packages after years of robust increases. It’s far too early to assume that AI-driven productivity gains have driven wages down (there is no evidence of that); but, if advances in technology continue, the wage trend for white collar workers could continue on its downward trajectory.

✌️-Brad

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