Category: Law
The Tyranny of the Complainers
Some years ago, Dourado and Russell pointed out a stunning fact about airport noise complaints: A very large number come from a single individual or household.
In 2015, for example, 6,852 of the 8,760 complaints submitted to Ronald Reagan Washington National Airport originated from one residence in the affluent Foxhall neighborhood of northwest Washington, DC. The residents of that particular house called Reagan National to express irritation about aircraft noise an average of almost 19 times per day during 2015.
Since then, total complaint volumes have exploded—but they are still coming from a tiny number of now apparently more “productive” individuals. In 2024, for example, one individual alone submitted 20,089 complaints, accounting for 25% of all complaints! Indeed, the total number of complainants was only 188 but they complained 79,918 times (an average of 425 per individual or more than one per day.)
What I learned recently is that it’s not just airport noise complaints. We see the same pattern in data from the US Department of Education’s Office for Civil Rights which enforces federal civil rights laws related to education funding. In 2023, for example, 5059 sexual discrimination complaints came from a single individual–from a total of 8151 complaints. Thus, one individual accounted for 68.5% of all sexual discrimination complaints in that year.
In the annual reports for 2022-2024 the OCR identifies what type of complaint the single-individual with multiple complaints was making, a sex discrimination complaint, while in previous years they just give data on the number of complaints from single individuals compared to the total of all types of complaints. I’ve collated this data in this graph which presents totals compared to multiple complaints from a single individual without regard to the type of complaint. Do note, that there are also single individuals filing hundreds of other types of complaints such as age discrimination complaints so the data from more recent years may actually be an underestimate.
In any case, it’s clear that a single individual often accounts for 10-30% of all complaints! These complaints have to be investigated so this single individual may be costing taxpayers millions. It’s as if a single individual were pulling a fire alarm thousands of times a year, mobilizing emergency services on demand, and never facing repercussions.
Does this strategy work? Probably. When complaints are summarized for Congress or reported in the media, are totals presented as-is, or adjusted for spam?
Increasingly, public institutions seem to exist to manage the obsessions of a tiny number of neurotic—and possibly malicious—complainers.
My excellent Conversation with Brendan Foody
Here is the audio, video, and transcript. Here is the episode summary:
At 22, Brendan Foody is both the youngest Conversations with Tyler guest ever and the youngest unicorn founder on record. His company Mercor hires the experts who train frontier AI models—from poets grading verse to economists building evaluation frameworks—and has become one of the fastest-growing startups in history.
Tyler and Brendan discuss why Mercor pays poets $150 an hour, why AI labs need rubrics more than raw text, whether we should enshrine the aesthetic standards of past eras rather than current ones, how quickly models are improving at economically valuable tasks, how long until AI can stump Cass Sunstein, the coming shift toward knowledge workers building RL environments instead of doing repetitive analysis, how to interview without falling for vibes, why nepotism might make a comeback as AI optimizes everyone’s cover letters, scaling the Thiel Fellowship 100,000X, what his 8th-grade donut empire taught him about driving out competition, the link between dyslexia and entrepreneurship, dining out and dating in San Francisco, Mercor’s next steps, and more.
And an excerpt:
COWEN: Now, I saw an ad online not too long ago from Mercor, and it said $150 an hour for a poet. Why would you pay a poet $150 an hour?
FOODY: That’s a phenomenal place to start. For background on what the company does — we hire all of the experts that teach the leading AI models. When one of the AI labs wants to teach their models how to be better at poetry, we’ll find some of the best poets in the world that can help to measure success via creating evals and examples of how the model should behave.
One of the reasons that we’re able to pay so well to attract the best talent is that when we have these phenomenal poets that teach the models how to do things once, they’re then able to apply those skills and that knowledge across billions of users, hence allowing us to pay $150 an hour for some of the best poets in the world.
COWEN: The poets grade the poetry of the models or they grade the writing? What is it they’re grading?
FOODY: It could be some combination depending on the project. An example might be similar to how a professor in English class would create a rubric to grade an essay or a poem that they might have for the students. We could have a poet that creates a rubric to grade how well is the model creating whatever poetry you would like, and a response that would be desirable to a given user.
COWEN: How do you know when you have a good poet, or a great poet?
FOODY: That’s so much of the challenge of it, especially with these very subjective domains in the liberal arts. So much of it is this question of taste, where you want some degree of consensus of different exceptional people believing that they’re each doing a good job, but you probably don’t want too much consensus because you also want to get all of these edge case scenarios of what are the models doing that might deviate a little bit from what the norm is.
COWEN: So, you want your poet graders to disagree with each other some amount.
FOODY: Some amount, exactly, but still a response that is conducive with what most users would want to see in their model responses.
COWEN: Are you ever tempted to ask the AI models, “How good are the poet graders?”
[laughter]
FOODY: We often are. We do a lot of this. It’s where we’ll have the humans create a rubric or some eval to measure success, and then have the models say their perspective. You actually can get a little bit of signal from that, especially if you have an expert — we have tens of thousands of people that are working on our platform at any given time. Oftentimes, there’ll be someone that is tired or not putting a lot of effort into their work, and the models are able to help us with catching that.
And:
COWEN: Let’s say it’s poetry. Let’s say you can get it for free, grab what you want from the known universe. What’s the data that’s going to make the models, working through your company, better at poetry?
FOODY: I think that it’s people that have phenomenal taste of what would users of the end products, users of these frontier models want to see. Someone that understands that when a prompt is given to the model, what is the type of response that people are going to be amazed with? How we define the characteristics of those responses is imperative.
Probably more than just poets that have spent a lot of time in school, we would want people that know how to write work that gets a lot of traction from readers, that gains broad popularity and interest, drives the impact, so to speak, in whatever dimension that we define it within poetry.
COWEN: But what’s the data you want concretely? Is it a tape of them sitting around a table, students come, bring their poems, the person says, “I like this one, here’s why, here’s why not.” Is it that tape or is it written reports? What’s the thing that would come in the mail when you get your wish?
FOODY: The best analog is a rubric. If you have some —
COWEN: A rubric for how to grade?
FOODY: A rubric for how to grade. If the poem evokes this idea that is inevitably going to come up in this prompt or is a characteristic of a really good response, we’ll reward the model a certain amount. If it says this thing, we’ll penalize the model. If it styles the response in this way, we’ll reward it. Those are the types of things, in many ways, very similar to the way that a professor might create a rubric to grade an essay or a poem.
Poetry is definitely a more difficult one because I feel like it’s very unbounded. With a lot of essays that you might grade from your students, it’s a relatively well-scoped prompt where you can probably create a rubric that’s easy to apply to all of them, versus I can only imagine in poetry classes how difficult it is to both create an accurate rubric as well as apply it. The people that are able to do that the best are certainly extremely valuable and exciting.
COWEN: To get all nerdy here, Immanuel Kant in his third critique, Critique of Judgment, said, in essence, taste is that which cannot be captured in a rubric. If the data you want is a rubric and taste is really important, maybe Kant was wrong, but how do I square that whole picture? Is it, by invoking taste, you’re being circular and wishing for a free lunch that comes from outside the model, in a sense?
FOODY: There are other kinds of data they could do if it can’t be captured in a rubric. Another kind is RLHF, where you could have the model generate two responses similar to what you might see in ChatGPT, and then have these people with a lot of taste choose which response they prefer, and do that many times until the model is able to understand their preferences. That could be one way of going about it as well.
Interesting throughout, and definitely recommended. Note the conversation was recorded in October (we have had a long queue), so a few parts of it sound slightly out of date. And here is Hollis Robbins on LLMs and poetry.
Yes, Western Europe will survive recent waves of migration
Over 1.2mn people came to the EU seeking protection in 2015, many displaced by worsening conflict in Syria. There were bitter political feuds in Brussels over asylum, border and relocation policies. January 2016 set a grim record for the number of migrants dying while attempting to cross the Mediterranean.
Now things have changed, as European Commission president Ursula von der Leyen made clear in December when she took the stage at a conference on migrant smuggling. After a major policy overhaul over the past two years, “Europe is managing migration responsibly,” she said. “The figures speak for themselves.”
Irregular arrivals of migrants to the EU recorded by its border agency Frontex dropped by 25 per cent in the 11 months to November 2024, and have been continuously declining since a recent peak of 380,000 arrivals registered in 2023.
New asylum applications have also decreased by around 26 per cent in the first nine months of last year, according to Eurostat data, as fewer Syrians are applying for protection since the fall of the authoritarian regime of Bashar al-Assad in late 2024.
Why Some US Indian Reservations Prosper While Others Struggle
Our colleague Thomas Stratmann writes about the political economy of Indian reservations in his excellent Substack Rules and Results.
Across 123 tribal nations in the lower 48 states, median household income for Native American residents ranges from roughly $20,000 to over $130,000—a sixfold difference. Some reservations have household incomes comparable to middle-class America. Others face persistent poverty.
Why?
The common assumption: casino revenue. The data show otherwise. Gaming, natural resources, and location explain some variation. But they don’t explain most of it. What does? Institutional quality.
The Reservation Economic Freedom Index 2.0 measures how property rights, regulatory clarity, governance, and economic freedom vary across tribal nations. The correlation with prosperity is clear, consistent, and statistically significant. A 1-point improvement in REFI—on a 0-to-13 scale—correlates with approximately $1,800 higher median household income. A 10-point improvement? Nearly $18,000 more per household.
Many low-REFI features aren’t tribal choices—they’re federal impositions. Trust status prevents land from being used as collateral. Overlapping federal-state-tribal jurisdiction creates regulatory uncertainty. BIA approval requirements add months or years to routine transactions. Complex jurisdictional frameworks can deter investment when the rules governing business activity, dispute resolution, and enforcement remain unclear.
This is an important research program. In addition to potentially improving the lives of native Americans, the 123 tribal nations are a new and interesting dataset to study institutions.
See the post for more details amd discussion of causality. A longer paper is here.
Three that Made a Revolution
Another excellent post from Samir Varma, this time on the 1991 reforms in India that launched India’s second freedom movement:
Three men you’ve probably never heard of—P.V. Narasimha Rao, Manmohan Singh, Montek Singh Ahluwalia—may be the three most important people of the late 20th century.
Bold claim. Audacious, even. Let me defend it.
Here are the numbers. In 1991, over 45% of Indians lived below the poverty line—roughly 400 million people. By 2024, extreme poverty in India had fallen to under 3%.
That’s 400 to 500 million people lifted out of poverty.
The largest democratic poverty alleviation in human history.
….So there they stood.
The precipice was visible. A Hindu politician from a dusty village in Telangana who spoke 17 languages and wrote novels nobody wanted to read. A Sikh economist from a village that no longer existed, who took cold showers at Cambridge and kept dried fruits in his pockets. Another Sikh economist who’d been the youngest division chief in World Bank history and wrote a memo that would change a country.
Three men. All products of a civilization that absorbs contradictions—that somehow fits Hindus and Sikhs and Muslims and Christians and Jains and Buddhists and Parsis into one impossibly diverse democracy. A civilization where, as I’ve written before, any statement you make is true, AS IS its opposite.
India was bankrupt. The gold was gone. The Soviet model they’d followed for forty years was collapsing in real time. Every assumption that had guided Indian economic policy since independence was being revealed as catastrophically wrong.
The intelligentsia still believed in socialism. The party cadres still worshipped Nehru’s memory. The opposition would scream about selling out to foreign powers. The bureaucracy would resist losing its control. The protected industries would fight to keep their monopolies.
But the three men had something their opponents didn’t: a plan. The M Document—the years of thinking—the technocratic expertise accumulated across decades. They had political cover—Rao’s tactical genius, his willingness to let Singh take the heat while he worked the back channels. They had credibility—Singh’s Cambridge pedigree, Ahluwalia’s World Bank experience, Rao’s decades of political survival.
And they had something else: the crisis itself. The one thing that could break through forty years of socialist inertia. The emergency that made the previously impossible suddenly necessary.
Varma tells the story well. For the full history consult the indispensable The 1991 Project, full of documents, oral histories and interviews.
Hat tip: Naveen Nvn.
*38 Londres Street*
The author is Philippe Sands and the subtitle is
So recommended, and added to my own list. And yes I did buy another book by Philippe Sands, the acid test of whether I really liked something.
Bring Back the Privateers!
Senator Mike Lee has a new bill that encourages the President to authorize letters of marque and reprisal against drug cartels:
The President of the United States is authorized and requested to commission, under officially issued letters of marque and reprisal, so many of privately armed and equipped persons and entities as, in the judgment of the President, the service may require, with suitable instructions to the leaders thereof, to employ all means reasonably necessary to seize outside the geographic boundaries of the United States and its territories the person and property of any individual who the President determines is a member of a cartel, a member of a cartel-linked organization, or a conspirator associated with a cartel or a cartel-linked organization, who is responsible for an act of aggression against the United States.
SECURITY BONDS.—No letter of marque and reprisal shall be issued by the President without requiring the posting of a security bond in such amount as the President shall determine is sufficient to ensure that the letter be executed according to the terms and conditions thereof.
My paper on privateers explains how privateers were historically very successful. During the War of 1812, roughly 500 privateers operated alongside a tiny U.S. Navy. The market responded swiftly—privateers like the Comet were commissioned within days of war’s declaration and began capturing prizes within weeks. Sophisticated institutional design combined combined profit incentives with regulatory constraints:
- Security bonds ensured compliance with license terms
- Detailed instructions protected neutral vessels and required civilized conduct
- Prize courts adjudicated captures and distinguished privateers from pirates
- Share-based compensation created good incentives for crews
- Markets emerged where crew could sell shares forward (with limits to maintain work incentives)
Privateers cost the government essentially nothing compared to building and maintaining a navy. Private investors financed vessels , bore the risks, and operated on profit-seeking principles. Moreover, privateers unlike Navy vessels had incentives to capture enemy ships, particularly merchant ships, not just blow them and their occupants out of the water. Of course, capturing the drugs isn’t very useful but it’s quite possible to go after the money on the return journey–privateers as hackers–which is just as good.
Here is my paper on privateering, here is the time I went bounty hunting in Baltimore, here is work on the closely related issue of whistleblowing rewards and here is the excellent historian Mark Knopfler on privateering:
What should I ask Joanne Paul?
Yes I will be doing a Conversation with her. From the Google internet:
Joanne Paul is a writer, broadcaster, consultant, and Honorary Senior Lecturer in Intellectual History at the University of Sussex. A BBC/AHRC New Generation Thinker, her research focuses on the intellectual and cultural history of the Renaissance and Early Modern periods…
She has a new book out Thomas More: A Life.
Here is her home page. Here is Joanne on Twitter. She has many videos on the Tudor period, some with over one million views.
So what should I ask her?
Markets in everything?
If you don’t yet have a REAL ID, you can continue to fly, but it’s going to cost you. Beginning Feb. 1, 2026, the Transportation Security Administration (TSA) will start collecting a $45 fee from travelers using non-compliant forms of identification at airport security checkpoints.
The agency previously proposed a fee of $18 to cover the administrative and IT costs of ID verification for those traveling without a REAL ID or passport but increased the total to $45 in an announcement released earlier this month.
Here is the full story, via the excellent Samir Varma.
Is involuntary hospitalization working?
From Natalia Emanuel, Valentin Bolotnyy, and Pim Welle:
The involuntary hospitalization of people experiencing a mental health crisis is a widespread practice, as common in the US as incarceration in state and federal prisons and 2.4 times as common as death from cancer. The intent of involuntary hospitalization is to prevent individuals from harming themselves or others through incapacitation, stabilization and medical treatment over a short period of time. Does involuntary hospitalization achieve its goals? We leverage quasi-random assignment of the evaluating physician and administrative data from Allegheny County, Pennsylvania to estimate the causal effects of involuntary hospitalization on harm to self (proxied by death by suicide or overdose) and harm to others (proxied by violent crime charges). For individuals whom some physicians would hospitalize but others would not, we find that hospitalization nearly doubles the probability of being charged with a violent crime and more than doubles the probability of dying by suicide or overdose in the three months after evaluation. We provide evidence of housing and earnings disruptions as potential mechanisms. Our results suggest that on the margin, the system we study is not achieving the intended effects of the policy.
Here is the abstract online at the AEA site. I am looking forward to seeing more of this work.
Origins and persistence of the Mafia in the United States
This paper provides evidence of the institutional continuity between the “old world” Sicilian mafia and the mafia in America. We examine the migration to the United States of mafiosi expelled from Sicily in the 1920s following Fascist repression lead by Cesare Mori, the so-called “Iron Prefect”. Using historical US administrative records and FBI reports from decades later, we provide evidence that expelled mafiosi settled in pre-existing Sicilian immigrant enclaves, contributing to the rise of the American La Cosa Nostra (LCN). Our analysis reveals that a significant share of future mafia leaders in the US originated from neighborhoods that had hosted immigrant communities originating in the 32 Sicilian municipalities targeted by anti-mafia Fascist raids decades earlier. Future mafia activity is also disproportionately concentrated in these same neighborhoods. We then explore the socio-economic impact of organized crime on these communities. In the short term, we observe increased violence in adjacent neighborhoods, heightened incarceration rates, and redlining practices that restricted access to the formal financial sector. However, in the long run, these same neighborhoods exhibited higher levels of education, employment, and social mobility, challenging prevailing narratives about the purely detrimental effects of organized crime. Our findings contribute to debates on the persistence of criminal organizations and their broader economic and social consequences.
That is a new paper in the works by Zachary Porreca, Paolo Pinotti, and Masismo Anelli, here is the abstract online.
Gans and Doctorow on AI Copyright
Josh Gans had written what I think is the first textbook of AI. Instead of the “big issues” like will AI result in the singularity or the end of the human race, Gans treats AI as a tool for improving predictions. What will better predictions do in legal markets, economic markets, political markets? He generally avoids conclusions and instead explores models of thinking.
I especially enjoyed the chapter on intellectual property rights which maps out a model for thinking about copyright in training and in production, how they interact and the net costs and benefits.
Gans’s chapter usefully pairs with Cory Doctorow’s screed on AI. It’s a great screed despite being mostly wrong. I did like this bit, however:
Creative workers who cheer on lawsuits by the big studios and labels need to remember the first rule of class warfare: things that are good for your boss are rarely what’s good for you.
…When Getty Images sues AI companies, it’s not representing the interests of photographers. Getty hates paying photographers! Getty just wants to get paid for the training run, and they want the resulting AI model to have guardrails, so it will refuse to create images that compete with Getty’s images for anyone except Getty. But Getty will absolutely use its models to bankrupt as many photographers as it possibly can.
…Demanding a new copyright just makes you a useful idiot for your boss, a human shield they can brandish in policy fights, a tissue-thin pretense of “won’t someone think of the hungry artists?…
We need to protect artists from AI predation, not just create a new way for artists to be mad about their impoverishment.
And incredibly enough, there’s a really simple way to do that. After 20+ years of being consistently wrong and terrible for artists’ rights, the US Copyright Office has finally done something gloriously, wonderfully right. All through this AI bubble, the Copyright Office has maintained – correctly – that AI-generated works cannot be copyrighted, because copyright is exclusively for humans. That’s why the “monkey selfie” is in the public domain. Copyright is only awarded to works of human creative expression that are fixed in a tangible medium.
And not only has the Copyright Office taken this position, they’ve defended it vigorously in court, repeatedly winning judgments to uphold this principle.
The fact that every AI created work is in the public domain means that if Getty or Disney or Universal or Hearst newspapers use AI to generate works – then anyone else can take those works, copy them, sell them, or give them away for free. And the only thing those companies hate more than paying creative workers, is having other people take their stuff without permission.
The US Copyright Office’s position means that the only way these companies can get a copyright is to pay humans to do creative work. This is a recipe for centaurhood. If you’re a visual artist or writer who uses prompts to come up with ideas or variations, that’s no problem, because the ultimate work comes from you. And if you’re a video editor who uses deepfakes to change the eyelines of 200 extras in a crowd-scene, then sure, those eyeballs are in the public domain, but the movie stays copyrighted.
AI should not have to pay to read books any more than a human. At the same time, making AI created works non-copyrightable is I think the right strategy at the present moment. Moreover, it’s the most practical suggestion I have heard for channeling AI in a more socially beneficial direction, something Acemoglu has discussed without much specificity.
GDPR is worse than you had thought
We examine how data privacy regulation affects healthcare innovation and research collaboration. The European Union’s General Data Protection Regulation (GDPR) aims to enhance data security and individual privacy, but may also impose costs to data collection and sharing critical to clinical research. Focusing on the pharmaceutical sector, where timely access and the ability to share patient-level data plays an important role drug development, we use a difference-in-differences design exploiting variation in firms’ pre-GDPR reliance on EU trial sites. We find that GDPR led to a significant decline in clinical trial activity: affected firms initiated fewer trials, enrolled fewer patients, and operated at fewer trial sites. Overall collaborative clinical trials also declined, driven by a reduction in new partnerships, while collaborations with existing partners modestly increased. The decline in collaborations was driven among younger firms, with little variation by firm size. Our findings highlight a trade- off between stronger privacy protections and the efficiency of healthcare innovation, with implications for how regulation shapes the rate and composition of subsequent R&D.
That is from Jennifer Kao and Sukhun Kang, here is the online abstract for the AEA meetings.
Mass Incarceration and Mass Crime
In our Marginal Revolution Podcast on Crime in the 1970s, I pointed out that blacks were often strongly in favor of tough on crime laws:
Tabarrok: [P]eople think that mass incarceration is a peculiarly American phenomena, or that it came out of nowhere, or was due solely to racism. Michelle Alexander’s, The New Jim Crow, takes this view.
…[But] back then, the criminal justice system was also called racist, but the racism that people were pointing to was that black criminals were let back on the streets to terrorize black victims, and that black criminals were given sentences which were too light. That was the criticism back then. It was black and white victims together who drove the punishment of criminals. I think this actually tells you about two falsehoods. First, the primary driver of mass imprisonment was not racism. It was violent crime.
Second, this also puts the lie, sometimes you hear from conservatives, to this idea that black leaders don’t care about black-on-black crime. That’s a lie. Many Black leaders have been, and were, and are tough on crime. Now, it’s true, as crime began to fall in the 1990s, many blacks and whites began to have misgivings about mass incarceration. Crime was a huge problem in the 1970s and 1980s, and it hit the United States like a brick. It seemed to come out of nowhere. You can’t blame people for seeking solutions, even if the solutions come with their own problems.
A new paper The Racial Politics of Mass Incarceration by Clegg and Usmani offer more evidence challenging the now conventional Michelle Alexander view:
Public opinion data show that not just the white but also the black public became more punitive after the 1960s. Voting data from the House show that most black politicians voted punitively at the height of concern about crime. In addition, an analysis of federally mandated redistricting suggests that in the early 1990s, black political representation had a punitive impact at the state level. Together, our evidence suggests that crime had a profound effect on black politics. It also casts some doubt on the conventional view of the origins of mass incarceration.
As the authors note, the fact that blacks supported tough-on-crime laws doesn’t mean racism was absent. Racial overtones surely influenced the specific ways fear of crime was translated into policy. But the primary driver of mass incarceration wasn’t racism—it was mass crime.
Australia should not ban under-16s from internet sites
YouTube in particular, and sometimes X, are among the very best ways to learn about the world. To the extent that the law is effectively enforced, targeting YouTube will have a terrible effect on youth science, and the ability of young scientists and founders to get their projects off the ground will take a huge and possibly fatal hit. If you are only allowed to learn from the internet at age 16, you are probably not ready for marvelous achievements at age 18 or perhaps not even at 20. The country may become more mediocre.
The more serious concern is that this represents a major expansion of government control over tech services and also speech. Over time the government has to decide which are the approved tech companies and services and which are not. That becomes a politicized decision, as any chosen lines will be arbitrary, especially as online services evolve in their functionality. For instance, if excess video usage is what is problematic, it is possible for videos to be embedded more seamlessly into some future version of WhatsApp, an exempt service. Or Australian youth, even under the new law, will be able to access video on a laptop, simply by viewing it and not signing into their accounts…
I predict that either this law stops being effectively enforced, or the controls on companies and users have to become much, much tighter and more oppressive. In a large poll of Australian 9 to 16-year-olds, only 6 percent of them thought the new ban was going to work.
That is true for yet another reason. With gaming and messaging exempt from the ban, we can expect old-style “social media” to move into those areas. It already was the case that Fortnite and other gaming services served as social media networks, and that trend will be accelerated. Discord, for instance, is exempt from the ban, a glaring hole, and in a fast-changing market there probably will be some significant loopholes most of the time. For the ban to continue to work, it will have to spread. It is hard to think of an area of internet services that could not, in principle, serve social media–like functions, or produce the harms being attributed to online life. Regulation of artificial intelligence services is perhaps the next logical albeit misguided move here.
Who is in charge of the family anyway? If I have decided that my 15-year-old should be free to follow Magnus Carlsen on X and YouTube, should we have the boot of the state tell me this is forbidden? This is a big move in the direction of what Socrates advocated in The Republic, namely that the state takes priority over the family in deciding which stories can be told to the youth.
Over time, I expect this ban, again assuming it is kept and enforced, to become one of the biggest free speech restrictions on the internet. It is the incentive of government agencies to boost their budgets, spread their mandates, and enforce their dictates. What starts with a nation’s youth rarely ends there.
You might think that Australia’s regulatory guardians can be trusted to uphold free speech ideals, but has that been the case to date? Under Australian law, it is permissible to restrict free speech for reasons of public order, national security, and protection from harm. That includes limits on “hate speech,” prompting Elon Musk to exaggerate and call the country fascist. Nonetheless the country does not have anything comparable to America’s First Amendment free speech protections.
So why should we empower Australian regulators and restrict free speech further?
It is very defensible to worry that your kid is on his or her phone too much. Furthermore, school bans or limits on smartphone usage are likely to bring some measurable but small gains.
But if you think a massive expansion of state authority over online content is the answer, you ought to know that the associated gains from that decision will at best be modest. You will not be saving civilization or our youth; rather you will be joining the ever-growing parade against free speech.
Recommended, and in this recent piece Ben Yeoh surveys the research-based literature on social media and teen harm.