Posts Tagged ‘artificial intelligence’
“The remedy is worse than the disease”*…
Your correspondent is a co-founder and director of Common Sense Media, an organization devoted to understanding the fraught media environment in which we live, to helping children, their families, and educators navigate it, and to advocating for “common sense” protections for kids. When we began, over 20 years ago, the terrain was largely TV, movies, books, and video games. They remain, of course, but the spotlight moved to social media, and now, to AI.
Advocacy, as it turns out, can be a tricky needle to thread. As Francis Bacon (and following him, a stream of others) observe, sometimes “the cure can be worse that the disease.” And that’s especially true when the “disease” one is fighting is the province of a powerful, richly funded cabal who market their moves as cures, even though, through their lens, disease is the desired state.
By way of one (chilling) example, Joe Wilkins outlines one dimension of the current state-of-play…
The White House and Congress are working on a deal to clamp down on what US citizens are allowed to say online. According to new reporting by Axios, the Trump administration is negotiating with key senators in an effort to shoehorn a massive legislation package which would limit states’ abilities to regulate AI in exchange for placing broad federal limits on digital speech.
Plenty of ink has been spilled about the Trump administration’s push to revoke AI regulation from individual states. Though the White House and its allies frame this as a matter of “safety” and “national security,” the timing is telling, coming as progressive state governments move to restrict the building of AI data centers and hold tech companies liable for harms their AI systems cause.
What makes this deal particularly insidious is the trade-off at its core. Per Axios, congressional lawmakers lead by Republican Marsha Blackburn are essentially offering to surrender their ability to regulate AI in exchange for three federal censorship bills: the Kids Online Safety Act, the NO FAKES Act, and a federal age verification mandate.
While the language around these three measures suggests common-sense cyber regulation, activists say they really amount to a massive censorship regime that is fundamentally anti-democratic.
In a blistering statement, the first amendment group Foundation for Individual Rights and Expression (FIRE) warns that “taken together, these bills would fundamentally change the internet as we know it.” That’s especially striking because FIRE is funded by conservative private interests like billionaire Charles Koch, meaning its opposition highlights the degree to which Trump is butting heads against fellow members of the US ruling class.
The Kids Online Safety Act (KORA) for example, would force social media giants to restrict lawful speech based on Federal Trade Commission regulations. FIRE complains that this would give the federal government too much power to hold platforms like Meta accountable for their harms — which, many would argue, is long overdue. But given that just a few corporations own the vast majority of web infrastructure and social media, KORA would give the Trump-controlled FTC major power to bend the internet to its will.
To put this power into perspective, just regulating Meta’s Instagram would impact about 71 percent of US citizens who say they regularly use the app.
It’s a powerful weapon, in other words — and like any weapon, it matters a great deal who wields it. Should the White House and Congress push KORA through, it’s likely it would functionally end the possibility of surfing the internet anonymously, while supercharging Trump’s efforts to criminalize left wing opposition groups in the US.
Whether it passes will depend on some shrewd maneuvering on the Trump administration’s part to secure Congressional support. But it all underscores a frustrating reality of AI regulation in the US: Americans overwhelmingly support stricter regulation on AI — but with the current cabal running the Oval Office, there’s no guarantee that the cure won’t be worse than the disease…
Common Sense Media continues to fight– both overt malignancies and the faux remedies that promise to be as bad or worse. So, I would argue, should we all.
Pending federal bills would fundamentally change the internet as we know it: “Trump Moves to Deeply Censor the Entire Internet,” from @joeonhere.bsky.social in @futurism.com.
A resonant reminder of the poisonous program to be resisted: “The Side That Won the Civil War is Now Banning Books About Why the Civil War Was Fought.”
And a look at the politicial economics that may drive it.
(Image above: source)
###
As we seek sanity, we might recall that it was on this date in 1788, with the ratification of the ninth state (New Hampshire), that the Constitution of the United States came into effect. It was, of course, briskly amended to include what we call the Bill of Rights— the first 10 of 27 amendments (so far).
“Common sense is not so common”*…
The Enlightenment is under attack by the Left and the Right. It can only be “saved,” Eliane Glaser argues, through use of its greatest legacy: permanent critique. And then there’s AI. After summarizing the critiques from both sides, she continues…
In consequence of this pincer-movement attack, the Enlightenment’s legacy is existentially vulnerable. It makes me deeply worried as someone whose entire career has been built on trying to understand and analyse the world around me – especially a world that still tries to confine thinking women to the realms of emotion and ‘personal experience’.
I believe that Enlightenment values are essential, but that we have largely forgotten how to make a good case for them: we need to rely on shared facts, tested by experiment; a public sphere where open discussion can take place; and the belief that discussion should be founded on reasoned argument. We need, moreover, to cherish the more political values of tolerance, freedom, human rights and the common good. Advocates for artificial intelligence have the temerity to claim that large language models are ushering in a ‘second Enlightenment’ (a claim that was uncritically echoed in a paper published by the World Economic Forum last year) when what we are in fact seeing is the destruction of the Enlightenment legacy under the false banner of its name. As the historian David Bell argued in The New York Times in 2025, AI is actually ‘shedding Enlightenment values’ by simply reinforcing ‘what we already think we know.’ In The Guardian,the journalist and geopolitical risk consultant Joseph de Weck warned that ‘AI is taking us back to the dark ages’, making us lazy, and stymying independent thinking.
The evidence suggests that we are going through a rapid de-enlightenment. Newspaper circulations, attention spans, and trust in forms of agreed knowledge are in freefall. Misinformation, disinformation and deepfakes are gaining ground. If we let go of the valuable aspects of the Enlightenment project, we open ourselves up to a world of AI blather, ‘my truth’ pronouncements, wobbly sentiment and unchecked power.
My unease with this parlous state of affairs has provoked me to go back and rethink the Enlightenment and what it has to offer. But, rather than unthinkingly recouping it as a mission, I want instead to tease out and weigh up its merits, to discern with nuance what is still fit for our times. I want to ask if it is possible to rescue the Enlightenment’s rallying power, and if it’s worth defending what the combined forces of Left and Right are coming together to attack. Are the Enlightenment’s deficiencies barnacles on an old ship, or integral to its design?…
And so she does. Do read on: “Flickering Enlightenment,” from @elianeglaser.bsky.social in @aeon.co.
* Voltaire
###
As we reclaim reason, we might spare a thought for a glorious product of the Enlightenment, Joseph Haydn; he died on this date in 1809. A composer of the Classical period, he was pivotal in the evolution of chamber music forms like the string quartet and piano trio, and is known as the “Father” of both the symphony and sonata forms. Haydn was a friend and mentor of Mozart, and a teacher of Beethoven; indeed, the Haydn, Mozart and Beethoven trio are sometimes referred to as the “First Viennese School.”
Schonberg wrote that Haydn “was the Classic performer par excellence, and in his long life, from 1732 to 1809, he grew up with the new musical ideas and, more than any one man, shaped them.”
“Gambling is a tax on ignorance”*…
And as Einstein observed, “two things are infinite: the universe and human stupidity; and I’m not sure about the universe.”
Gambling– and related specualtive investments– have always been, for the vast majority of punters, a sucker’s bet. But, as Paul Kedrosky explains, the growing prevalence of AI and the emergence of prediction markets have amplified that painful reality…
The return skew in prediction markets’ returns is startling. It is partly a function of their nature, but also of vibe-coding script kiddies attacking every market anomaly as quickly as it arises. Check a recent WSJ article for examples.
The same dynamic is now spreading across retail-dominated markets. A driver is how AI lowers the cost of systematic exploitation and exploration to near zero. What used to require infrastructure, data pipelines, and bearded quants is now accessible via off-the-shelf models, APIs, and loosely stitched “agent” workflows doing … stuff that even their users don’t fully understand.
The result isn’t democratization of returns. It is wider participation, of a sort, alongside the rapid re-concentration of profits. A small subset of users—those willing to iterate fastest, monitor continuously, and deploy capital programmatically—capture gains, with everyone else just liquidity.
They scrape sentiment, parse new information, and reprice positions in seconds, compressing the half-life of mispricings. That doesn’t eliminate inefficiency, but changes who harvests it. The edge shifts from insight to speed, coverage, and execution discipline—areas where even modest automation compounds quickly, and edges disappear overnight.
Prediction markets are simply the cleanest expression of this trend because they combine thin liquidity, discrete outcomes, and high retail participation. But the same pattern is visible in options flow, single-stock volatility events, and even online poker, which AI increasingly dominates.
As AI tools continue to scale, expect this to get worse: a small cohort running semi-automated strategies extracting semi-consistent edge, and a much larger base supplying them returns. Under the pressure of AI prevalance, markets don’t flatten, the return gradient steepens to a cliff…
Fewer and fewer winners take more and more of the pot. The mechanics of concentration: “AI is Eating Markets” from @paulkedrosky.com.
* Warren Buffett
###
As we contemplate concentration, we might note that today is Mother’s Day. As noted yesterday, the observance became official on that date in 1914. But the quest to honor moms began a good bit earlier. On this date in 1908, Anna Jarvis held a memorial for her mother at St. Andrew’s Methodist Church in Grafton, West Virginia, the location of the International Mother’s Day Shrine. But her quest to create Mother’s Day had begun three years earlier when her mother Ann, a lifelong activist, died.
Ann had tried to start a “Mother’s Remembrance Day” in the mid-19th century. On her passing, Anna enlisted the support of retailer extraordinaire John Wanamaker, who knew a merchandising opportunity when he saw one, and who hosted the first Mother’s Day ceremonies in his Philadelphia emporium’s auditorium. In 1912, Anna trademarked the phrases “second Sunday in May” and “Mother’s Day”, and created the Mother’s Day International Association. By 1914, she and Wanamaker had built sufficient support in Congress to score the Congressional Resolution noted yesterday. (President Wilson, who was by current accounts uninterested in the move– distracted as he was by the beginnings of his ultimately unsuccessful effort to keep the U.S. out of the troubles in Europe that became World War I– nonetheless knew better than to take a stand against moms.)
“Always look on the bright side of life”*…
The estimable economic historian Louis Hyman has been engaged in an on-going “friendly debate” with his equally-estimable friend and Johns Hopkins colleague Rama Chellappa on “what AI means”…
… As I see this debate, this question of our age, there are two main questions that history can shed some light on.
- Is AI a complement or a substitute for labor? That is, will it increase demand for and the productivity of workers, or decrease it?
- Will AI be controlled by the few or be accessible to the many?
A Complement or a Substitute?
Consider a some of the most important technologies of the past 200 years.
When I am asked about what automation might look like, I inevitably discuss agriculture. Roughly all of our ancestors were farmers and approximately none of us today are. Yet we still eat bread made from wheat. That shift is possible because of automation.
The mechanical thresher, used to process wheat, was a substitute for the most backbreaking work of the harvest. But it also enabled more land to be cultivated, and that land was cultivated more efficiently, allowing for greater harvests. Mechanization of the farm, like the thresher, turned the American Midwest into the breadbasket of the world.
Those displaced farmers found work on railroads, moving all that. And those jobs, according to people at the time, were a kind of liberation from the raw animal labor of threshing. On net, it created demand for more workers at better wages in work more fit for people than beasts. For those that remained farmers, they found other higher-value work to be done. On a farm, there is always more work to do.
The failure, then and now, is to think farmers were only threshers. That was one part of their jobs. Today, our work, for most people, is also a bundle of tasks. Workers then and now could and can focus on parts of their job that are of higher value. And in a new economy, new tasks in new industries will be created. Many of the jobs that we do today (web designer, UI expert) were simply unimaginable in 1850. That is a good thing.
Consider now the assembly line. I’m sure you all know about the staggering increases in productivity that come from the division of labor. If you take my class in industrial history, you would learn deeply about the story of the automobile. With the assembly line, and no other change in technology, car assembly went from 12 and a half hours to about 30 minutes (once they worked out the kinks). Did this reduce the demand for workers? No. It reduced the price of cars. And that increased the demand for workers, who eventually could demand even higher wages through unionization.
It is important here to realize that better tools don’t make us get paid worse. They generally make us get paid more. Why? Because the tool, without the person, is useless. Even for today’s most cutting-edge AIs, that is true. It can code, but it can only code what I imagine it to code. It can draw, but only what I imagine it to draw. That is true for AIs as it was true for the thresher.
So, I would offer that AI will create more growth, more abundance. In the long run, all growth comes from higher productivity.
I would add one more piece to this story. Economic inequality has worsened since roughly 1970. It has worsened, therefore, not in the industrial era, but the digital era. I have argued elsewhere that this happened because for decades we did not use computers as tools of automation but as glorified typewriters (and then as televisions). Our productivity did not increase, especially to justify the expense of computers. Economists have debated for decades now over the lack of increase in productivity that came with the “digital age” of computing, but it is simple. We don’t use them as computers. Now we can.
For the first time now, normal people with their normal problems can use their computers to solve and automate their problems. AI can write code. AI can automate their tedium. The digital age did not bring any gains because it had no yet arrived. We were living through the last gasp of the industrial economy.
It is now here.
This technology will unleash unimaginable productivity gains. It will level the playing field between coders and the rest of us. Coders will lose their jobs, to be sure, but for the rest of us, the bundle of workplace tasks will become much better.
And truthfully, the demand for real computer scientists will probably increase in the era of vibe-coding. Computer science itself is a bundle of skills, of which coding is just one. The more important skill – software and data architecture – will only increase in demand as the usefulness of software expands…
[Hyman goes on to explore the dangers of monopolization (which, for reasons he explains, he believes are overstated); the future of softward (which, he believes, will skew to open-sorce), and of hardware (which, he believes will not be a bottleneck). He concludes…]
… Put together we come to a very different picture of what the digital age will be. The industrial age required massive investments to build the factories to make the products that were in demand. In the digital age, in contrast, the factories to build digital products will be made by the AI on your laptop. That is not inequality. That is equality.
The physical products of the Fordist industrial age were made for the mass market. In contrast, the digital products of the post-fordist digital age will be long-tail products. I don’t need to make mass market products; I can make them for a small niche, or just for myself.
Rather than fostering inequality, AI, then, is a great equalizer. To make products for a global market you don’t need a billion-dollar factory. You just need a laptop. That is astonishing.
That said, it will not be all sunshine and rainbows. Will AI solve the inequities of capitalism or its reliance on externalities as a source of primitive accumulation? Probably not.
But at the same time, AI is not a normal technology in that it has the potential to radically undermine many of the tendencies to concentrate capital that we have seen in the industrial age. We have been automated out of work before, that is nothing new, but it has always concentrated capital in the hands of the few. For the first time, there is potentially an alternative path forward.
AI will bring the digital age out of the hands of the coders. AI will not widen the gap—it will bridge it. Its ubiquity will mean that AI will be a tool that nearly all of us will be able to use in our daily work, which will make ordinary people more productive and prosperous…
Eminently worth reading in full: “Hooray! Post-Fordism Is Finally Here!“
Even as Hyman’s message is reassuring in the context of the flood of jeremiads in which we’re awash, it’s worth remembering that eerily-similar points were made a couple of decades ago about the threat/promise of digital publishing/commerce. Given the then-current conditions and then-plausible futures, those predictions might have come true… but in the event, they didn’t pan out as projected. That said, things are changing, so maybe this time things are different?
(Image above: source)
* song (by Eric Idle) from Monty Python’s Life Of Brian
###
As we resolve to remain rosy, we might send productive birthday greetings to Andrew Meikle; he was born on this date in 1719. A Scottish millwright, he invented the threshing machine (for removing the husks from grain, as mentioned above). One of the key developments of the British Agricultural Revolution in the late 18th century., it was also one of the main causes of the Swing Riots— an 1830 uprising by English and Scottish agricultural workers protesting agricultural mechanization and harsh working conditions.
“The present is pregnant with the future”*…
The estimable Tim O’Reilly uses scenario planning to create an insightful look at AI, our futures, and the choices that will define them…
We all read it in the daily news. The New York Times reports that economists who once dismissed the AI job threat are now taking it seriously. In February, Jack Dorsey cut 40% of Block’s workforce, telling shareholders that “intelligence tools have changed what it means to build and run a company.” Block’s stock rose 20%. Salesforce has shed thousands of customer support workers, saying AI was already doing half the work. And a Stanford study found that software developers aged 22 to 25 saw employment drop nearly 20% from its peak, while developers over 26 were doing fine.
But how are we to square this news with a Vanguard study that found that the 100 occupations most exposed to AI were actually outperforming the rest of the labor market in both job growth and wages, and a rigorous NBER study of 25,000 Danish workers that found zero measurable effect of AI on earnings or hours?
Other studies could contribute to either side of the argument. For example, PwC’s 2025 Global AI Jobs Barometer, analyzing close to a billion job ads across six continents, found that workers with AI skills earn a 56% wage premium, and that productivity growth has nearly quadrupled in the industries most exposed to AI.
This is exactly the kind of contradictory, uncertain landscape that scenario planning was designed for. Scenario planning doesn’t ask you to predict what the future will be. It asks you to imagine divergent possible futures and to develop a strategy that improves your odds of success across all of them. I’ve used it many times at O’Reilly and have written about it before with COVID and climate change as illustrative examples. The argument between those who say AI will cause mass unemployment and those who insist technology always creates more jobs than it destroys is a debate that will only be resolved by time. Both sides have evidence. Both are probably right at some level. And both framings are not terribly helpful for anyone trying to figure out what to do next…
[O’Reilly explains the scenario approach, then applies it to our future with AI (see the image above), astutely assessing the conflicting signals that we’ve experiencing; he explores the “robust strategy” for our uncertian future (strategic choices that make sense regardless of which future unfolds); then he concludes…
… I’ll return to the theme that I sounded in my book WTF? What’s the Future and Why It’s Up To Us.
Every time a company uses AI to do what it was already doing with fewer people, it is making a choice for the lower half of the scenario grid. Every time a company uses AI to do something that wasn’t previously possible, to serve a customer who wasn’t previously served, to solve a problem that wasn’t previously solvable, it is making a choice for the upper half. These choices compound, for good or ill. An economy that uses AI primarily for efficiency will slowly hollow itself out.
Looking at the news from the future, both sets of signals are present. The question is which will dominate. AI will give us both the Augmentation Economy and the Displacement Crisis, in different measures in different places, depending on the choices we make.
Scenario planning teaches us that we don’t have to predict which future we’ll get. We do have to prepare for a very uncertain future. But the robust strategy, the one that works across every quadrant, is to focus on doing more, not just doing the same with less, and to find ways that human taste still matters in what is created. As long as there is unmet demand, as long as there are problems we haven’t solved and people we haven’t served, AI will augment human work rather than replacing it. It’s only when we stop looking for new things to do that the machines come for the jobs…
Eminently worth reading in full. Indeed, speaking as a long-time scenario planner, your correspondent can only wish that everyone who wields “scenarios” applies the approach as appropriately, adriotly, and acutely as Tim has: “Scenario Planning for AI and the ‘Jobless Future‘,” from @timoreilly.bsky.social.
* Voltaire
###
As we take the long view, we might send formative birthday greetings to Mark Pinsker; he was born on this date in 1923. A mathematician, he made impoprtant contributions to the fields of information theory, probability theory, coding theory, ergodic theory, mathematical statistics, and communication networks. This work, which helped lay the foundation for AI-as-we-know-it, earned him the IEEE Claude E. Shannon Award in 1978, and the IEEE Richard W. Hamming Medal in 1996, among other honors.
You must be logged in to post a comment.