💬 Discussion
Two Greek figures examine a social-media phone, protective gate and school satchel.

A Minimum Age Online

Platforms already forbid accounts for young children in their terms of service and do almost nothing to enforce it. Senators Brian Schatz and Ted Cruz want to make that limit law and switch off the algorithmic feed for teenagers, with parents', teachers' and medical groups behind them [2]. The platforms' trade group NetChoice and digital rights organisations oppose the bill.

  • 38 percent of American children aged 8 to 12 already use social media [16]
  • 4.7 million accounts were closed or restricted within days of Australia's stricter ban for under-16s [11]
  • 42 percent of Australian 10-to-15-year-olds still held an account three months after the ban, down from 52 percent [12]

The proposal

Bar under-13s from social media accounts and switch off algorithmic feeds for everyone under 17.

The debate

Supporters say social media is making children more depressed and anxious, that platforms profit from feeds built to hold them, and that parents have asked for help for years. Opponents warn that the bill pushes platforms toward age checks on everyone and cuts young people off from learning and community. They also argue that it limits the speech of minors. The Commerce Committee approved the bill on 5 February 2025, and since 30 June 2025 it has waited for a vote of the full Senate.

  • “The growing evidence is clear: social media is making kids more depressed, more anxious, and more suicidal.”

    argues for: Brian Schatz, Democrat, Hawaii Press release, 5 February 2025

  • “Under the current proposal, a blanket ban on social media access for those under 13 would prevent young people from accessing even age-appropriate platforms like YouTube Kids, while broad content recommendation restrictions for users under 17 would limit access to valuable educational resources and community support networks that many young people rely on for learning and development.”

    argues against: Amy Bos, NetChoice Letter to the Senate Commerce Committee, 4 February 2025

  • “By banning social media for kids under 13, KOSMA violates First Amendment rights and pressures platforms into invasive age verification and data collection practices—putting all users’ privacy at risk.”

    argues against: Sydney Saubestre, Open Technology Institute Press release, 4 February 2025

The analysis

A Minimum Age Online

85% of the weight is for, 15% against.

An argument's weight combines three questions: how big the effect is, how certain it is and how much the good at stake matters. The larger the slice, the more the argument weighs.

For

Against

A minimum age online is a good proposal on the current analysis, and a narrower one than its critics' picture of it.

Very likely better

Very likely better: Under the assumptions used, the proposal brings more than it costs in 93 of 100 model runs.

 Overall effect: medium

How strongly the proposal works overall, in five steps from very small to very large, comparable across all debates. The ring is always full, even when the overall effect is small; this step says how large it is.

The analysis sides with the sponsors, but its main reason is school rather than mental health. The study of Facebook's arrival at colleges found more students saying their work suffered, and that gain alone outweighs every cost in the debate. The critics' strongest point holds: platforms must rebuild their feeds at their own expense, whether or not the rule works. The loss of community support that the trade group warns about adds nothing, because the study measured students' health net of what the platform gave them. What could still change the result is the unmeasured step from students saying their work suffered to learning actually lost.

In detail

All arguments

Arguments for2 arguments

Better years at school

13points

The same study that found worse mental health found more students reporting that it interfered with their academic work. That is a second consequence rather than the same one told twice: what a person learns between thirteen and seventeen shows up in their earnings for forty years.

Value 8 · Life chancesImpact 4.6Plausibility 3.5
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Value

The stream is what a young person learns and what that is worth to them later: qualifications gained, courses not dropped, the difference between finishing and not. This site places it in the class it uses for subsistence and life chances, above economic output and below life and health. It is genuinely separate from the mental health counted above — a student can be unhappy and still learn, or content and still fall behind — and it is counted only to the extent the evidence links the two. What the schooling is worth to the wider economy rather than to the person is not counted, because it would be the same hours twice. The value sits in the upper part of the scale, at the level this site uses for subsistence and life chances.

Impact

About 17 million Americans are aged 13 to 16, and the same effective reach as in the previous argument applies, about 38 percent: those who lose the feed, plus a quarter for those who get it back and only use less. The study behind that argument found that Facebook's arrival raised the share of students reporting that poor mental health had impaired their academic work from 13 to 16 percent [4][9]; 30 percent of that is carried across for a feed switched off rather than a platform removed, so about 0.9 percent of pupils, roughly 57,000, are newly spared such impairment each year, in a range from 0.3 to 1.8 percent. What an impaired pupil loses is a construction: a tenth of a school year's learning is assumed, in a range from a twentieth to a quarter. A year of American schooling is worth roughly eight percent of lifetime earnings, and lifetime earnings are taken at about 2.3 million dollars — forty working years at 58,000 — without discounting, as this site does everywhere; a tenth of a year is therefore worth about 19,000 dollars to the pupil concerned, and the 5,700 pupil-years a year come to about 1.1 billion dollars. The figure counts each year's pupils once and follows their earnings for a working life, which is how this site books schooling everywhere. The Impact is the largest in this debate, and it is large because a small share of a school year, followed through forty years of earnings, is worth a great deal — the one step that carries it, from self-reported impairment to learning lost, is the one nobody has measured.

▸ Show calculation ▾ Hide calculation
Americans aged 13 to 16 17 million students
× Teenagers effectively reached by the feed rule the same effective reach as in the first argument: known to the platform and staying without the feed, plus a quarter for those who get it back and use less [6] [6] 37.5 % 6.38 million students
× Pupils newly spared mental-health impairment of their school work Setting, range 0.3 to 1.8 percent: Facebook's arrival raised the share reporting such impairment from 13 to 16 percent, and 30 percent of that is carried across for a feed switched off rather than a platform removed [4][9] 0.9 % 57,375 students
× Learning lost by an impaired pupil Setting, range 5 to 25 percent: the source reports impairment, not grades 10 % of a school year 5,738 student-years
× Lifetime earnings from a year of schooling a year of American schooling is worth roughly eight percent of lifetime earnings; forty working years at 50,000 euro-equivalent (about 58,000 dollars), undiscounted as everywhere on this site 8 % × 2 million euro-equivalent (about 2.3 million dollars at 1.16 dollars to the euro) 918 million euro-equivalent
÷ Normalised Impact scale of this evaluation 200 million euro-equivalent a point 4.59
Score 4.59 Impact × 8 Value × 3.5 Plausibility ÷ 10 = 13 of 100

Plausibility

The link is real in the source and thin in the application. The counterfactual is the same students at colleges without Facebook, and the academic finding rests on the same staggered rollout that carries the mental health result, so its identification is equally good [4]. What is much weaker is everything after it. The study measures students saying their work suffered, not grades or completion, and self-reported impairment and actual learning are not the same quantity. The step from there to lifetime earnings runs through a return-to-schooling figure estimated on whole years of education rather than on marginal quality within a year, which is a different object. The counter-mechanism is unaddressed: a student who spends less time on a feed does not necessarily spend it studying, and the American time-use evidence on what displaces what is not settled. Reverse causation does not arise in the underlying design. Read as a statement about the world: about a third of the time, switching off the feed improves a school year by roughly the amount assumed here. The Plausibility is well below the middle: the finding it starts from is identified, the step from reported impairment to learning lost is unmeasured, and what replaces the time on the feed is unanswered.

Evidence: Study · plausibility at most 8 Evidence of effect: Quasi-experimental · at most 8 Placement: Chain open · plausibility 3–3.5

Open: Australia's ban applies to a whole cohort at one date. Comparing school outcomes for Australian 15-year-olds against a comparable country over three years would measure this directly and could carry P to 6.

Adolescents in better mental health

6.9points

The best causal evidence on this question comes from Facebook's arrival at American colleges one at a time between 2004 and 2006. Where it arrived, symptoms of depression and anxiety rose, and the mechanism the authors identify is unfavorable comparison with other people. The bill removes the part of the product that does the comparing.

Value 9 · HealthImpact 2.2Plausibility 3.5
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Value

The stream is the mental health of people between about eleven and seventeen: how much they sleep, whether they are anxious in a way that interferes with school, how they feel about their own life against everyone else's. This site places it in the class it uses for life and health, one step below the top because adolescent low mood is generally recoverable and because what is measured is a symptom index rather than a diagnosis. The weight does not rise because the people concerned are young; what youth changes is how long the consequences run, and that belongs to the Impact. The academic consequences are counted separately in the next argument. The value sits one step below the maximum: the stream is health, and health that can be regained.

Impact

About 17 million Americans are aged 13 to 16 [15], and of the roughly 20 million aged 8 to 12, 38 percent use social media [16]; about half of those are taken to hold an account of their own, roughly 4 million. The bill requires no age check: a platform acts on the age it already holds or on what the circumstances make obvious [6], and a teenager who wants the personalized feed back only needs an adult date of birth on the account. Around a third of British children with a profile already carry one [7], and in Australia, where platforms must check, 37 percent of children who kept an account had listed their age as 16 or older, while the share holding an account fell only from 52 to 42 percent in three months [12]. So about 60 percent of 13-to-16-year-olds are taken as known to their platform, and half of those as staying without the feed rather than getting it back under a new date of birth: 30 percent lose it outright. The other half of the known teenagers are counted at a quarter of the effect, for using less rather than not at all — in Australia daily use among 14- and 15-year-olds fell from 78 to 69 percent [13] and fewer children said they were missing out, 36 against 43 percent [12] — which gives an effective reach of about 38 percent, in a range from 15 to 65. The upper part of that range is the pull of the network: when fewer classmates are on the feed, staying on is worth less to everyone, and in an experiment with American college students most would need paying to quit a platform alone while many would rather it were gone for all of them together [17]; nothing has yet measured that pull weakening among Australian teenagers, and by the sixth month most of those who had left were back [14]. For under-13 accounts, 10 percent are taken as closed and staying closed, in a range from 2 to 25, because under Australia's stricter law use of the platforms fell only from 86 to 82 percent and time per day at ages 12 and 13 did not change [12][13]. The size of what a feed does comes from the one clean measurement available: Facebook arrived at American colleges at different dates, and where it arrived, an index of poor mental health rose by 0.085 standard deviations — about 22 percent of the effect of losing one's job [4][9]. Removing algorithmic recommendation is not the same as removing the platform, so 30 percent of that effect is used, in a range from 10 to 60 percent: about 0.025 standard deviations across the 6.4 million teenagers this reach amounts to. For an under-13 whose account goes, 0.06 standard deviations is set rather than measured, about 70 percent of the full effect, because a child without an account can still watch without one; a standard deviation on such an index is worth roughly 0.06 quality-adjusted years, in a range from 0.03 to 0.12, which gives about 11,000 quality-adjusted years a year. The Impact is the largest health figure in this debate and rests on the feed rule for teenagers: it is little more than a third of what it would be if every teenager lost the feed, because the rule reaches only those a platform knows to be young, and many of them can have the feed back under a different date of birth.

▸ Show calculation ▾ Hide calculation
Americans aged 13 to 16 [15] 17 million people
× Teenagers effectively reached by the feed rule Setting, range 15 to 65 percent: about 60 percent are known to their platform [6][7]; half of them stay without the feed, the other half get it back under an adult date of birth and count at a quarter for using less — in Australia 37 percent of children who kept an account had listed an age of 16 or more and account holding fell only by a fifth [12], daily use at 14 and 15 fell from 78 to 69 percent [13]; the upper part of the range is the weaker pull of a network with fewer peers on it [17], not yet measured, against most returning by the sixth month [14] [6][7][12][13][14][17] 60 % × (50 % + 50 % × ¼) = 37.5 % 6.38 million people
× Improvement in symptoms of poor mental health Setting, range 10 to 60 percent of the measured effect: Facebook's arrival at a college raised the index by 0.085 standard deviations, and this measure removes one feature rather than the platform [4][9] 0.025 standard deviations 159,375 standard-deviation-people
+ Under-13s who actually lose their accounts Setting, range 2 to 25 percent closed for good: 38 percent of 8-to-12-year-olds use social media [16], about half through an account of their own; under Australia's law, which obliges platforms to check, account holding among 10-to-15-year-olds fell by a fifth in three months while use fell from 86 to 82 percent [12], time per day at ages 12 and 13 did not change [13] and compliance fell further by the sixth month [14] — a bill without a duty to check closes fewer; 0.06 standard deviations a head is set at about 70 percent of the full measured effect [6][12][13][14][16] 4 million × 10 % × 0.06 standard deviations 183,375 standard-deviation-people
× Quality-adjusted years per standard deviation Setting, range 0.03 to 0.12 0.06 11,003 quality-adjusted years
× Value of the years the value of a healthy life year used across this site 40,000 euro-equivalent each 440 million euro-equivalent
÷ Normalised Impact scale of this evaluation 200 million euro-equivalent a point 2.2
Score 2.2 Impact × 9 Value × 3.5 Plausibility ÷ 10 = 6.9 of 100

Plausibility

This is the most contested empirical question in the area and the evidence divides by design rather than by conclusion. The counterfactual in the study carrying this figure is colleges that had not yet received Facebook, compared against those that had, on the same survey instrument before and after [4]. The confounder that would otherwise dominate — that early colleges differ from late ones — is what the staggered rollout absorbs, and reverse causation cannot arise, since a student's mood did not determine when Facebook expanded. Against that, meta-analyses of the wider literature repeatedly find effects near zero, and they are right to: most of that literature is cross-sectional and measures who uses social media rather than what it does. Two things limit the transfer here. The study is about college students in 2004 and this measure concerns adolescents in 2026, whose product is a video recommendation engine rather than a list of friends' profiles. And the study measures a platform arriving, while this measure removes one feature of it — which is why only 30 percent of the effect is carried across. A third limit concerns reach and is carried in the range, not here: Australia closes accounts while this bill switches off one feature for users who stay, so the Australian figures on who stays and who returns bound the reach only loosely [12][13][14]. Read as a statement about the world: about a third of the time, switching off algorithmic feeds for the teenagers it reaches improves their mental health by roughly the amount assumed here. The Plausibility is well below the middle: the design behind the number is sound, but the two steps that carry it to today's product, a feed switched off rather than a platform arriving and adolescents now rather than students then, have never been measured.

Evidence: Study · plausibility at most 8 Evidence of effect: Quasi-experimental · at most 8 Placement: Chain open · plausibility 3–3.5

Open: Australia's law took effect on December 10, 2025; platforms reported 4.7 million under-16 accounts deactivated, removed or restricted within days [11], yet three months on four in five under-16s were still using the platforms [12]. No survey so far reports minutes per day before and after. The official evaluation runs to 2028: a measurement of time spent, and of adolescent mental health against a similar country over three years, would replace the whole transfer with a direct reading and could carry P to 7 — or show that a ban of this kind changes too little use to move health at all.

Arguments against4 arguments

Platforms rebuild at their own expense

2.8points

Closing every account a platform knows belongs to a child, deleting its data within ninety days, and running a second, unpersonalized feed for every user it knows to be under seventeen is engineering, legal review and moderation staff. The large platforms can pay for it easily, which does not make it free: the hours and the machines are spent either way.

Value 5 · Compliance costImpact 1Plausibility 5.5
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Value

The stream is money spent by companies on compliance: engineers' time, legal review, moderation staff, the servers that run a second feed. This site places corporate spending at the middle of the scale, at the weight it gives to money as such — neither raised because the platforms are large nor lowered because they can afford it. That the platforms can carry the cost does not remove it: who pays and whether anything is spent are separate questions. What the spending buys — the protection of adolescents — is counted on the other side and is not netted here. The value sits at the middle of the scale: the stream is corporate money, and money is money whoever holds it.

Impact

The bill takes effect a year after enactment and reaches every service that collects personal data, lives primarily on advertising and hosts a community forum [6]. For each of them it means three pieces of work: finding and closing the accounts it knows belong to under-13s and deleting their data within 90 days; building and running a recommendation system for known teenagers that uses nothing about them but device, language, location and age; and the legal and moderation apparatus to show a regulator that it did not know what it should have known. The largest platforms have already built parts of this — teen accounts, age estimation, a chronological feed option — so what is counted is the increment. Ten large platforms at about 17 million dollars a year each, in a range from 6 to 46, and a long tail of a thousand mid-sized services at about 58,000 dollars a year give about 230 million dollars a year over the five years, in a range from 70 to 700 million. That is a price set rather than found: no platform publishes what its teen-safety engineering costs. The Impact is less than half of the health gain, and it is the one cost in this debate that arrives whether or not the law achieves anything.

▸ Show calculation ▾ Hide calculation
Large covered platforms [6] 10 platforms
× Yearly increment for closing known child accounts, an unpersonalized teen feed and compliance Setting, range 5 to 40 million: teen accounts, age estimation and a chronological option already exist, so only the increment counts 15 million euro-equivalent each (about 17 million dollars at 1.16 dollars to the euro) 150 million euro-equivalent
+ Long tail of mid-sized covered services Setting: legal review and account closures without a dedicated team 1,000 × 50,000 euro-equivalent (about 58,000 dollars) 200 million euro-equivalent
÷ Normalised Impact scale of this evaluation 200 million euro-equivalent a point 1
Score 1 Impact × 5 Value × 5.5 Plausibility ÷ 10 = 2.8 of 100

Plausibility

That a legal duty of this shape costs engineering and legal time is not a prediction; what is uncertain is the size, and that sits in the range rather than here. The counterfactual is the current position, in which the same platforms already spend on teen accounts and age estimation voluntarily, so part of the work is done and would be done without the law — which is why the increment rather than the whole is counted, and why the range runs low. The one thing that could make the figure vanish is a platform simply switching every user under seventeen to a chronological feed it already offers, at almost no cost; the bill's exceptions are written to allow that, and a platform whose product is the personalized feed will not do it. No behavioral step carries the quantity, and reverse causation does not arise. The Plausibility is just above the middle: the spending is certain, the increment over what platforms already do is assumed.

Evidence: Projection · plausibility at most 6 Evidence of effect: Definitional

Some people must prove who they are

0.57points

The bill requires no age check and no new data: a platform acts on what it already knows. But a platform that must not know is a platform that will want to be sure, and the ones that already run age estimation on accounts that look young will ask more people for a document. For those people, an account that never required an identity now has one attached.

Value 9 · Basic rightsImpact 0.2Plausibility 3.5
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Value

The stream is two things that arrive together for the people asked: the time spent proving their age, and the end of anonymous participation for anyone whose account is now tied to a document. This site places the second in the class it uses for the constitutional core and treats the first as time under compulsion, which sits near the top of the scale as well; the combination is priced just below life and health. The point is not that identity checks are wrong — banks do them daily — but that a social platform is where a great deal of political speech now happens, and an account connected to a document changes what can be said on it. Nothing here is counted for the risk of that record leaking, which is real and unquantified. The value is high because the stream is anonymity in public speech alongside hours of compelled time, not a convenience — and it is priced per person asked, however many that turns out to be.

Impact

Roughly 250 million Americans hold at least one social media account. The bill does not make anyone check them: it says in terms that nothing in it requires age verification or the collection of any age data a platform does not already hold, and it lets a platform be found to know a user's age only from what the circumstances make obvious [6]. What remains is the platforms' own response to that standard: a platform that is liable for what it should have known will want to be sure, and Meta already routes accounts its models flag as younger than declared into a verification step [10]. Ten percent of account holders are taken as asked to prove their age at some point in the five years, in a range from 2 to 40 — flagged adults, people whose accounts change hands or devices, users of platforms that decide to check everyone rather than argue about what was obvious. Spread over the five years, that is 5 million checks a year. Each is put at 12 minutes including retries, in a range from 4 to 30, which is 1 million hours of compelled time a year. A person checked once stays identified to the platform for the rest of the horizon, so the loss of anonymity grows from 5 million people in the first year to 25 million in the fifth, 15 million on average; it has no market price and is valued as if it cost each of them about 2.30 dollars a year, in a range from 0.60 to 12, the order of magnitude that surveys of willingness to pay for privacy return. Together that is a Normalised Impact of 0.18 on this scale, of which the hours carry 0.03 and the anonymity 0.15. Repeated checks would raise the time; how often a platform re-checks is not known and sits in the upper part of the range. Varying every setting across its own range at once, each most likely at its central value, the middle eight in ten outcomes run from a third of this figure to nearly three times it. The Impact is under a twentieth of what it would be if everyone had to be checked every year, which the bill does not require.

▸ Show calculation ▾ Hide calculation
Americans holding at least one social media account 250 million people
× Share asked to prove their age within five years Setting, range 2 to 40 percent: the bill requires no check and no new data [6]; what is counted is platforms hedging a knowledge-fairly-implied standard — flagged adults, changed devices, platforms that decide to check everyone [10] [6][10] 10 % 25 million people
÷ Checks a year, spread over the five years each person is checked once in the horizon; retries are inside the minutes per check ÷ 5 5 million checks
× Time verifying, including retries Setting, range 4 to 30 minutes: uploading a document, waiting, retrying when a face scan fails 12 minutes a check 1 million hours
× Value of forced time the rate this site uses for time a person must spend with nothing in return 6.85 euro-equivalent an hour (about 7.90 dollars) 6.85 million euro-equivalent
+ Value set on the end of anonymous participation Setting, range 0.5 to 10 euro-equivalent a person a year (about 0.60 to 12 dollars): the identified group grows from 5 to 25 million over the horizon; the order of magnitude surveys of willingness to pay for privacy return, set here rather than found 15 million identified on average × 2 euro-equivalent (about 2.30 dollars at 1.16 dollars to the euro) 30 million euro-equivalent
= Time and anonymity together 36.85 million euro-equivalent
÷ Normalised Impact scale of this evaluation 200 million euro-equivalent a point 0.18
Score 0.18 Impact × 9 Value × 3.5 Plausibility ÷ 10 = 0.6 of 100

Plausibility

That some people will be asked to prove their age is a prediction about how platforms answer a liability standard, not arithmetic. The counterfactual is the current position, in which platforms act on a self-declared date of birth and, increasingly, on their own age estimation. The bill's text is the strongest evidence against a large figure: it excludes any duty to verify and any duty to collect new data [6]. What carries the figure is a mechanism — the standard of knowledge fairly implied from the circumstances makes it costly not to know, and the commentary on the bill expects platforms to build verification steps for that reason [10] — plus the observed fact that the largest platform already sends flagged accounts to a check. The confounder is that this would happen anyway: Meta's age estimation predates the bill, and part of the checking counted here would occur under no law at all, which would cut the figure. The privacy half of the quantity is a stated price rather than a measurement. Reverse causation does not arise. Read as a statement about the world: about a third of the time, the bill leads platforms to check roughly one account holder in ten more than they would have checked anyway. The Plausibility is well below the middle: the mechanism is named and partly visible already, how far platforms go beyond what the bill demands is assumed, and the checking that would run without any law has not been separated out.

Evidence: Projection · plausibility at most 6 Evidence of effect: Mechanistic · at most 6 Placement: Chain open · plausibility 3–3.5

Open: Once the law is in force, the platforms' transparency reports would show how many accounts were sent to a verification step and how many adults were misclassified; that would replace the assumed share with a count and could carry P to 6.

Small sites close rather than comply

0.25points

When the United Kingdom imposed online safety duties in 2025, a number of small British forums shut down rather than carry the legal and compliance load. The American bill asks far less of them — no age checks, no risk assessments, and no duty at all unless a site lives mainly on advertising — but a volunteer-run board that is covered still faces a federal liability it cannot price.

Value 7 · Public debateImpact 0.1Plausibility 3.5
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Value

The stream is places for people to talk to each other that stop existing: a forum for a rare disease, a local history board, a community that never had a business model. This site places that in the class it uses for participation and the conditions of public debate, above money and below health. What is priced is the loss of the venue rather than any particular conversation, and no attempt is made to weigh a small forum against a large platform by size — the argument is about the ones for whom no substitute exists. The compliance cost to large platforms is not counted here; it stands in the next argument. The value sits in the upper middle of the scale, at the level this site uses for the conditions of public debate.

Impact

The British experience since 2025 is the closest precedent: hobby forums such as the London fixed-gear cycling board closed rather than meet the Online Safety Act's requirements, and support communities put government-ID checks in front of their doors [8]. Very little of that regime is in this bill. It requires no age assurance and no new data [6]; it covers only a service that collects personal data, lives primarily on advertising or data sales, and hosts a community forum — so a board with no advertising is outside it, as are wikis, review sites, gaming, email and direct messaging; and what a covered board must do is close accounts it knows belong to under-13s and not run a personalized recommendation system for known teenagers, which a plain forum does not run. What remains is liability under a standard of knowledge fairly implied from the circumstances, enforced by the Federal Trade Commission and state attorneys general, for an operator with no lawyer. A Normalised Impact of 0.1 on the scale of this evaluation is used for the value of what closes on that account, in a range from 0.03 to 0.75 if boards close at all; whether they do is a question of plausibility. The top of that range is what scaling the British closures would give if the duties were alike. The Impact is the smallest in this debate, and it is small because the bill's definition of a covered platform and its refusal to mandate checks leave most small venues untouched.

▸ Show calculation ▾ Hide calculation
Value of small forums and community sites that close rather than carry the liability Setting, range 6 to 150 million euro-equivalent if boards close at all, whether they do being a question of plausibility; the top is the British closures scaled as if the duties were alike. British boards closed under a regime with risk assessments, complaint systems and age assurance [8]; this bill imposes none of those, requires no checks, and covers only ad-funded services with a community forum [6] — what remains is an unpriceable federal liability for volunteer operators [6][8] 20 million euro-equivalent
÷ Normalised Impact scale of this evaluation 200 million euro-equivalent a point 0.1
Score 0.1 Impact × 7 Value × 3.5 Plausibility ÷ 10 = 0.3 of 100

Plausibility

The mechanism has a documented precedent under a different law and no measurement under this one. British forums did close after online safety duties took effect, which establishes that small venues do shut rather than carry compliance they cannot price [8]. The counterfactual there is the same forums before the duty, which is weak — several were already struggling and the duty was the occasion rather than the cause for some of them, and nobody has separated the two. The transfer is the larger problem: the British regime imposed risk assessments, complaint systems and age assurance; this bill imposes none of those and covers only ad-funded services with a community forum [6], so the chain that closed British boards mostly does not exist here. What is left is fear of a federal liability, and the precedent for that — the children's privacy law of 1998, which also turns on knowledge — did not close forums; it produced a line in their terms of service. Reverse causation is a live concern for the British closures. The Plausibility is well below the middle: the effect is documented under a heavier law, and under this one the closest precedent says it mostly does not happen.

Evidence: Precedent · plausibility at most 6 Evidence of effect: Mechanistic · at most 6 Placement: Load-bearing link disputed · plausibility 3.5–4

Open: The bill's definition of a covered platform is now in the text [6]; what would settle the rest is a count of American forums that close or geoblock within a year of the law taking effect, against the British count under the Online Safety Act.

Teenagers lose what they get from it

0points

The same feed that produces unfavorable comparison also produces the group chat, the club, the person who has the same rare illness, and for teenagers who are isolated where they live, the only people who are like them. Removing it removes both. Nobody has measured the second half — but the measurement the first argument rests on is a net one, and the loss is already inside it.

Value 9 · HealthImpact 0Plausibility 4
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Value

The stream is the same one the first argument counts, running the other way and on the same people: connection, belonging and support, and their absence. It would carry the same weight for the same reason — what is at stake is adolescent mental health, one step below the top of the scale because it is recoverable. Nothing here is counted for what parents gain or lose, which is a different stream on different people and is not priced anywhere in this evaluation. The argument is kept on the page because readers reach for it first, and because the reason it carries no figure of its own is the most important thing to understand about this debate. The value would sit one step below the maximum; it is not applied, because the stream is already netted inside the first argument.

Impact

The same adolescents are affected, and the effect runs the other way. Its size cannot be booked here, because the figure in the first argument is not the harm of a feed but the net of harm and benefit: the study measured how students' mental health changed when Facebook arrived, with everything the platform gave them — the friends kept, the groups found — already inside the number [4][9]. The net was negative, which is what says the harm outweighed the benefit; subtracting the benefit again on this side would count it twice. What is not inside the measurement is the distribution: the loss falls hardest on adolescents who are isolated offline — in rural areas, with rare conditions, with an identity unwelcome where they live — for whom the feed is not one social channel among many. Whether the average net effect measured on college students holds for them is an open question, not a figure. The Impact is zero by construction: what this argument describes has already been taken off the other side's number, and the one thing it might add — a different balance for isolated teenagers — has never been measured.

▸ Show calculation ▾ Hide calculation
Health gain in the first argument, measured net of what the platform gave [4][9] from the first argument 440 million euro-equivalent
× Share of the lost connection still to be subtracted the college measurement is a net effect: what the platform gave students is already inside it, so nothing remains to be taken off a second time [4][9] 0 0 million euro-equivalent
÷ Normalised Impact scale of this evaluation 200 million euro-equivalent a point 0
Score 0 Impact × 9 Value × 4 Plausibility ÷ 10 = 0 of 100

Plausibility

This argument is grounded in the same study as the first one and reads it from the other side. The counterfactual is identical: colleges before and after Facebook arrived [4]. What that study measures is a net effect, so the benefit side is inside it rather than separate from it, and no design isolates the two components — which is why nothing can be added here without counting the benefit twice. The confounder in the qualitative literature that does examine the benefits is severe: teenagers who say social media helps them are describing their own experience, and the ones most likely to say so are the ones most attached to the product. Reverse causation is unresolvable there. What can be said is that the net effect being negative bounds the benefit from above — it cannot exceed the harm, or the measured sign would flip. The Plausibility is below the middle and is not applied: the stream certainly exists, and it has already been netted where the measurement was made.

Excluded (axis = 0): Already inside pro-1: the college measurement that carries the health gain is a net effect — what the platform cost students after what it gave them — so the connection lost is subtracted there once and cannot be subtracted again here.

Evidence: Mechanism · plausibility at most 6 Evidence of effect: Mechanistic · at most 6 Placement: Chain closed, unevidenced · plausibility 4–5

Open: Within days of Australia's law taking effect on December 10, 2025, platforms had deactivated, removed or restricted 4.7 million under-16 accounts [11]. A comparison of loneliness and support measures for Australian 14-year-olds against a comparable country would give the first direct reading of this side of the ledger.

How robust the result is

Under the assumptions used, the proposal brings more than it costs in 93 of 100 model runs.

gains more than it costscosts more than it gains

Each dot stands for 200 of the 20,000 model runs.

The two largest figures rest on one measurement, what Facebook's arrival did to college students twenty years ago, carried across to today's feeds at 30 percent. Both are cut to the teenagers a platform actually knows to be young and who do not get the feed back under an adult date of birth, because the bill requires no age check. The measurement is a net one: what the feed gave those students is already inside it, which is why the loss of connection stands on this page without a figure of its own. A year of American schooling is valued at roughly eight percent of lifetime earnings, without discounting, as everywhere on this site. The second title of the bill, which makes subsidized schools block social media on their networks, is left out of the count, because those schools already filter under the Children's Internet Protection Act. Counted so, the bill lies ahead in 93 of 100 runs.

Show the distribution of the model runs

20,000 simulated futures

Very likely better · 93 %

In 93 of 100 simulated futures the proposal brings more than it costs.

No effect is known exactly; every argument has a range. The calculation draws a possible size for each argument from its range 20,000 times and counts how often the benefits exceed the costs.

Net effect in points per future. Left of zero the drawbacks outweigh the benefits, right of zero the benefits win. Eight in ten futures fall between +1.0 and +38 points.
Scale and assessment

Scale of this evaluation: Normalised Impact, unitless and calibrated to this topic. For comparison, one point here corresponds to about 200 million euro-equivalent a year.

Size class:small

Effect medium (+3.2) · 85 % of the effect is positive

Areas show individual argument weights. The positive share of the effect nets out money transfers between the two sides; the probability of a positive net effect is determined separately.

How we score →

Review and sources

Last reviewed by Claude Opus 5.5 · October 29, 2026 · 12× AI, 2× human
  1. October 29, 2026AI reviewClaude Opus 5.5record updated

    Page texts for the new page layout (draft G) with quotes from primary sources; numbers unchanged.

  2. October 21, 2026AI reviewClaude Fable 5.1record updated

    Money amounts in argument texts stated in dollars per style-en.md; scores, chains and balance unchanged

  3. October 20, 2026AI reviewClaude Fable 5.1record updated

    Summary and scale note rewritten to the style of 20 Oct 2026; numbers unchanged

  4. October 16, 2026AI reviewClaude Opus 5.5record updated

    Small-forum closure range no longer starts at zero (6 to 150 million euro if boards close; whether they do stays in P 3.5); balance unchanged.

  5. October 14, 2026AI reviewClaude Opus 5.5re-scored

    v6 nach Prüfbericht 11.10.: con-1 Prüfungen auf fünf Jahre verteilt (5 Mio. je Jahr), Anonymitätsverlust über den Ø-Bestand von 15 Mio. Identifizierten, I 0,084 → 0,037, Spanne neu; Titel II (Schulnetz-Filter) ausdrücklich aus dem Bewertungsumfang genommen. P(D>0) 0,476 → 0,535, ausgeglichen.

  6. October 14, 2026Assessed by a human, implemented by AIClaude Opus 5.5re-scored

    v5 nach Julians Entscheidung vom 14.10.: Feed-Reichweite 70 % in zwei Kanäle zerlegt (60 % bekannt, davon die Hälfte ohne Feed, Rest mit einem Viertel für weniger Nutzung = 37,5 %, Spanne 15 bis 65 mit Netzwerkeffekt oben), pro-1 auf kette_offen P 3,5, Bilanz-Block geschrieben.

  7. October 12, 2026Assessed by a human, implemented by AIClaude Opus 5.5re-scored

    v4 nach Julians Entscheidung vom 12.10.: Australien-Befunde (eSafety Drei-Monats-Bericht, BMJ, NBER w35162) zeigen kaum gesunkene Nutzung trotz Prüfpflicht — Kontoverlust unter 13 von 40 % auf 10 % (2 bis 25), pro-1 I 0,944 → 0,772, r 0,909 → 0,902; Belege für 17 Mio. und 4 Mio. nachgetragen, 0,06 SD als Setzung benannt, Summary um den Australien-Satz ergänzt.

  8. October 12, 2026AI reviewClaude Opus 5.5re-scored

    v3 nach Prüfbericht 12.10.: Befundbänder pro-2 und con-1 auf kette_offen (P 4 → 3,5 und 4,5 → 3,5), Revisions-Narration und britische Schreibweise entfernt, Rechenweg con-2 ergänzt, Australien-Zahl nach der Regierungsmitteilung vom 16.01.2026 korrigiert und als Quelle [11] belegt; r 0,908 → 0,909.

  9. September 14, 2026AI reviewClaude Fable 5.1re-scored

    v2 nach Gesamtprüfung 08.09.: Gesetzestext S. 278 verlangt keine Altersprüfung — con-1 0,84 → 0,084, con-3 0,15 → 0,02; con-2 (40 % des Netto-Effekts) als Doppelzählung auf 0; pro-1 mit Reichweite 1,6 → 0,94; pro-2 Lebenseinkommen korrekt 0,68 → 1,71; con-4 Plattformkosten neu. r 0,56 → 0,91.

  10. September 6, 2026AI reviewClaude Opus 5record updated

    i_spanne an allen 5 Argumenten aus den englischen Ketten, kein Transfer im Record. Kategorie kippt von Ausgeglichen (r 0,56) auf Schlechter (P(D>0) 0,15).

  11. September 6, 2026AI reviewClaude Opus 5record updated

    i_spanne an allen 5 Argumenten aus den englischen Ketten, kein Transfer im Record. Kategorie kippt von Ausgeglichen (r 0,56) auf Schlechter (P(D>0) 0,15).

  12. September 6, 2026AI reviewClaude Opus 5First evaluation

    Created for the English side: the harm is taken from the staggered Facebook college rollout, the benefit is booked as a share of it because nothing measures it.

Evaluations are produced with AI support and reviewed on a schedule for new developments; human passes are marked separately.How we review →

Show all 17 sourcesHide sources
  1. Route Fifty: How would proposed age restrictions on social media use actually work?. route-fifty.com
  2. Senator Brian Schatz: Kids Off Social Media Act. schatz.senate.gov
  3. eSafety Commissioner, Australia: Social media age restrictions. esafety.gov.au
  4. Braghieri, Levy and Makarin, American Economic Review 112(11): Social Media and Mental Health. aeaweb.org
  5. Pew Research Center: Teens, Social Media and AI Chatbots 2025. pewresearch.org
  6. U.S. Government Publishing Office: S. 278 — Kids Off Social Media Act (119th Congress), bill text. govinfo.gov
  7. Ofcom: A third of children have false social media age of 18+. ofcom.org.uk
  8. Techdirt: Didn't Take Long To Reveal The UK's Online Safety Act Is Exactly The Privacy-Crushing Failure Everyone Warned About. techdirt.com
  9. Braghieri, Levy and Makarin, CEPR VoxEU: Social media and mental health. cepr.org
  10. Truth on the Market: Can You Actually Keep Kids Off Social Media Without Age Verification?. truthonthemarket.com
  11. Prime Minister of Australia: 4.7 million accounts deactivated, removed or restricted (media release, 16 January 2026). pm.gov.au
  12. eSafety Commissioner, Australia: Early days, early insights: Understanding experiences of social media age restrictions at the three-month follow-up (July 2026). esafety.gov.au
  13. BMJ Group: Little evidence that Australia's under-16 social media restrictions have curbed use among adolescents (The BMJ, doi 10.1136/bmj-2026-363695). bmjgroup.com
  14. Bursztyn, Duckworth, Jiménez-Durán, Leonard, Milojević, Roth and Sunstein, NBER Working Paper 35162: Tipping Points and Australia's Social Media Ban. nber.org
  15. U.S. Census Bureau: National Population by Characteristics 2020–2024: resident population by single year of age. census.gov
  16. Common Sense Media: The Common Sense Census: Media Use by Tweens and Teens, 2021 (press release). commonsensemedia.org
  17. Bursztyn, Handel, Jiménez-Durán and Roth, Becker Friedman Institute: When Product Markets Become Collective Traps: The Case of Social Media. bfi.uchicago.edu

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