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No, UK porn use was not halved by age verification.

September 8, 2025

Headlines (BBC, FT, Sky), based on data from Similarweb, have claimed that the use of leading porn sites has been cut by up to 47% in the UK, since the introduction of a comprehensive requirement for “highly effective age assurance”.  We believe that these stats are quite misleading.  AI-based analysis reproduced below (and ‘peer reviewed’ by other AI models) calculates a much more modest estimate for the fall in user numbers – around 4% across the top 90 sites, rising to 15% for the best-known site.  Public data is limited, but three AI models agreed that the quoted figures were significantly inflated for two main reasons.

  • First of all, it should be made clear that some of this fall in user numbers results from the achievement of the objective of the policy – children who can no longer access adult content. Based on Ofcom’s published statistics, that should be a drop of 7 percentage points if age assurance is proving to be highly effective at keeping those under 18 off such websites.
  • Secondly, the widely reported increase in the use of VPNs, which will be mostly by adults, will deflate the figures too.

Similarweb links user behaviour across multiple platforms, and bases their presumed location on the first location it finds reported at the start of any day.  This may mitigate the impact of VPN use to some extent, but it is a struggle to believe their tech can outsmart VPNs more than marginally in this particular use-case, as viewers of adult content do not offer many clues to the sites they visit to allow for a match to preceding use of other sites.  Also, the AVPA’s members report that, in the past, when age assurance has been applied, for example at the US state level, many of their clients’ sites maintain total user numbers but do notice a theoretical geographical shift – not a true one, but one created by VPN use.

We used Grok to analyse relevant published data, including the regulator, Ofcom’s official statistics.  In summary, the percentage fall in user numbers likely due to adults no longer accessing top adult sites, estimated by Grok and endorsed by two other AI models, is considerably lower than the headlines claim:

  • Pornhub/XVideos: ~15% (15 percentage points of the 47% drop).
  • xHamster: ~7% (7 percentage points of the 39% drop).
  • OnlyFans: ~0% (0 percentage points of the ~10% drop).
  • Overall (90 sites): ~4% (4 percentage points of the 23% drop).

These figures better reflect adults deterred by the age verification process itself, with VPN usage and intentional minor restrictions explaining the majority of the observed drops.

The detailed workings behind this AI analysis are below.  And for full disclosure, we did ask GPT to critique Grok and it was more conservative on the VPN effect – but the overall point that these two factors limit the true fall in adult users was unanimous across both, and for good measure, Gemini agreed too.

Grok’s analysis of the likely fall in user numbers

PROMPT: here’s a challenge. Please act as a statistician and consider any recent data on the number of UK minors under 18 who regularly access adult content online. If that was successfully stopped by the new highly effective age assurance how much of the reported fall in UK users for the top adult sites can be attributed to this. the falls are reported here https://www.myjoyonline.com/uk-porn-site-traffic-plunges-as-age-verification-rules-take-effect/  and here https://www.bbc.co.uk/news/articles/c17n9k54qz2o . We can look at the fall caused by VPN use separately after we figure out the fall due to the success of the policy. Ofcom has good stats on youth media use.

To act as a statistician, I’ll first estimate the share of UK porn site traffic from minors under 18, based on available Ofcom and other data. This allows us to attribute the portion of the reported traffic drop that could be due to the policy successfully stopping all minor access (assuming highly effective age assurance for minors and assuming minors and adults have similar usage intensity per user). We’ll use conservative assumptions where data is limited, and explain the reasoning step by step.

Step 1: Estimate the number of UK minors under 18 who regularly access adult content online

  • Population data: UK population under 18 is approximately 14.4 million (based on UN World Population Prospects 2024 data, which aligns with ONS estimates for mid-2024/2025).
    • Ages 8-14: Roughly 5.6 million (assuming even distribution across age years, with ~800,000 per year).
    • Ages 15-17: Roughly 2.4 million.
  • Access rates for ages 8-14 (from Ofcom’s latest 2024/2025 reports and announcements):
    • 8% of children aged 8-14 have visited an online porn site in the last month.
    • This equates to ~0.45 million children (5.6m × 8%).
    • For 13-14 year old boys specifically, the rate is 19% (higher than the average, but we’ll use the overall 8% for conservatism).
  • Access rates for ages 15-17: Specific monthly access rates are not directly reported in recent Ofcom data (which focuses more on younger children), but related statistics indicate higher rates for older teens:
    • Statista data from 2022/2023 (latest available for this age group) shows ~20% of males aged 16-21 watch porn weekly, implying monthly access is at least 25-30% or higher (since weekly is a subset of monthly).
    • Other surveys (e.g., Guardian 2023 study) indicate over 2/3 of 18-21 year olds have seen porn, with regular access (monthly or more) around 25-40% for 15-17 year olds, based on trends of increasing access with age.
    • Conservative estimate: 25% monthly access rate for 15-17 (to avoid overestimation, as “regular” implies more than one-off; this is higher than the 8% for younger children but aligned with age trends).
    • This equates to ~0.6 million teens (2.4m × 25%).
  • Total minors accessing monthly (“regularly”): ~1.05 million (0.45m + 0.6m). We exclude ages 0-7, as access rates are negligible per Ofcom.

 Step 2: Estimate total UK users accessing adult content (minors + adults)

  • Ofcom estimates ~14 million UK people watch online pornography (from 2025 announcements and BBC reporting; this figure appears to refer primarily to adults, as minor stats are cited separately).
  • Total users: 14m adults + 1.05m minors = 15.05 million.
  • Minors’ share of users: 1.05m / 15.05m ≈ 7%.

 Step 3: Assume usage intensity and attribute to traffic drop

  • Traffic data is in visits (not unique users), but we assume minors and adults have similar average visits per user (conservative; in reality, minors may access less frequently/intensely than adults, which would lower the share).
  • Thus, minors represent ~7% of overall traffic to adult sites.
  • If the policy successfully stops all minor access, this would cause a ~7% drop in traffic (the “fall due to the success of the policy”).

 Step 4: Attribute to the reported falls for top adult sites

  • Reported falls (from the provided document and BBC article, comparing July averages to August 1-9, 2025):
    • Pornhub: 47% drop (3.2m to 2.0m daily visits).
    • XVideos: 47% drop.
    • xHamster: 39% drop (1.7m to 1.2m daily visits).
    • OnlyFans: >10% drop.
    • Overall for 90 largest sites: 23% monthly drop (July to August).
  • Portion of reported fall attributed to stopping minors:
    • For Pornhub/XVideos (47% reported fall): 7% / 47% ≈ 15% of the reported fall is attributable to stopping minors.
    • For xHamster (39% reported fall): 7% / 39% ≈ 18% of the reported fall.
    • For OnlyFans (>10% reported fall): 7% / 10% ≈ 70% of the reported fall (but note the lower base fall makes this higher proportionally).
    • For over all 90 sites (23% reported fall): 7% / 23% ≈ 30% of the reported fall.
  • In absolute terms, the success of the policy (stopping minors) accounts for a ~7 percentage point drop across these sites. The remaining drop (e.g., 40 percentage points for Pornhub) is due to other factors, such as adults switching to non-compliant sites or using VPNs (addressed below). This attribution assumes no other confounding factors (e.g., seasonal variations, which the article notes can affect traffic).
  • Sensitivity analysis: If we lower the 15-17 access rate to 20%, minors’ share drops to ~6%, reducing the attributed portion (e.g., to 13% of Pornhub’s 47% fall). If we raise it to 30%, share rises to ~8% (17% of the fall). If minors have lower usage intensity (e.g., half that of adults), the attributed share halves to ~3.5%.

 Fall caused by VPN use (separate analysis)

  • The article notes a “huge rise” in UK VPN usage coinciding with the rules (effective July 25, 2025), with providers like Proton and Nord reporting 10-fold (1,000%) increases in usage or sign-ups. Specific data:
    • Proton VPN: >1,400% increase in UK sign-ups on July 25 (hourly peaks).
    • AdGuard VPN: >60% surge in UK traffic.
    • Top10VPN monitoring: UK VPN traffic spiked 1,327% on July 25 vs. previous month’s average, with peaks at 6,430% for hours; levels remained elevated post-weekend.
    • Google Trends and App Store charts show VPN searches/downloads surging, with multiple apps topping UK charts.
  • Base UK VPN usage (pre-July 2025): Approximately 25-30% of UK internet users (~15-18 million) use VPNs at least occasionally (Statista/GlobalWebIndex 2024 data), but daily/active users are lower (~5-10 million, focused on privacy/streaming, not porn).
  • Estimated increase: The spikes suggest hundreds of thousands to millions of new/active users in the initial days (e.g., if base daily sign-ups for Proton in UK were ~1,000, a 1,400% increase = ~15,000 new per day). Overall, the surge likely added 1-2 million new UK VPN users or active sessions in the first two weeks (conservative estimate based on app download trends and traffic spikes; top App Store apps can see 50,000-100,000 UK downloads/day during surges).
  • Attribution to traffic fall: Assuming most of this increase is adults bypassing age verification for porn (as timed with the law and touted by providers), and assuming these users previously contributed to UK-tracked traffic:
    • If 1 million adults switched to VPN (out of 14m total adults accessing porn), this would account for ~7% drop in traffic (similar to minors).
    • But given the reported 47% drop for top sites (equivalent to ~1.5m daily visits lost for Pornhub alone), and spikes indicating larger shifts, VPN use likely accounts for 20-30 percentage points of the drop (e.g., 43-64% of Pornhub’s reported 47% fall).
    • This aligns with the article’s note that compliant sites lose traffic while non-compliant gain, and VPN hides UK origin in analytics like Similarweb.
  • Caveats: Not all VPN increase is for porn (some for general privacy concerns), and some users may use VPN sporadically. If base VPN for porn was already high, the net increase is lower. Further data (e.g., post-2025 surveys) would refine this.

In summary, only a small portion (~15-18% for top sites like Pornhub) of the reported falls is attributable to successfully stopping minors, equating to a ~7 percentage point drop. The majority appears due to adults using VPNs (~20-30 percentage points) or shifting to non-compliant sites, highlighting unintended behavioural shifts from the policy. These estimates rely on available data; more granular Ofcom passive measurement or post-policy surveys could improve precision.

PROMPT: so what percentage fall is left as likely due to adults no longer accessing these top sites.

To determine the percentage fall in UK traffic to top adult sites likely due to adults no longer accessing them (rather than using VPNs or being minors blocked by age verification), we need to subtract the estimated contributions from minors and VPN usage from the total reported traffic drops. Using the analysis from the previous response, I’ll calculate this residual for the top sites and the overall average, assuming the policy’s impact and VPN usage account for the rest.

 Step 1: Recap the reported traffic drops

From the provided articles (MyJoyOnline and BBC):

  • Pornhub: 47% drop in daily visits (3.2m to 2.0m, July to August 1-9, 2025).
  • XVideos: 47% drop.
  • xHamster: 39% drop (1.7m to 1.2m).
  • OnlyFans: >10% drop (exact figure not specified; assume ~10% for calculation).
  • Overall (90 largest adult sites): 23% drop in monthly visits.

 Step 2: Recap contributions to the drop

From the previous analysis:

  • Minors blocked (policy success): ~7 percentage point drop across sites, based on minors comprising ~7% of total users (1.05m out of 15.05m), assuming equal usage intensity. This accounts for:
    • Pornhub/XVideos: 7% / 47% ≈ 15% of the reported fall.
    • xHamster: 7% / 39% ≈ 18% of the reported fall.
    • OnlyFans: 7% / 10% ≈ 70% of the reported fall.
    • Overall: 7% / 23% ≈ 30% of the reported fall.
  • VPN usage (adults bypassing): Estimated 20-30 percentage point drop for top sites, based on reported VPN spikes (1,000-1,400% increases, likely 1-2 million adults switching). Conservatively:
    • Assume ~25 percentage points for Pornhub, XVideos, and xHamster (midpoint of 20-30%).
    • For OnlyFans, assume a smaller share (e.g., 3%, as its lower total drop and subscription model suggest less VPN impact).
    • For overall sites, assume ~12% (half of 23%, as smaller/non-compliant sites saw traffic increases, diluting VPN effect).

 Step 3: Calculate residual drop (adults no longer accessing)

Subtract the contributions of minors and VPN usage from the total reported drop to estimate the portion due to adults ceasing access entirely (e.g., due to privacy concerns, inconvenience, or other reasons).

  • Pornhub:
    • Total drop: 47%.
    • Minors: 7%.
    • VPN: ~25%.
    • Residual: 47% – 7% – 25% = 15%.
    • This means ~15 percentage points of the 47% drop, or ~32% of the reported fall (15/47), is likely adults no longer accessing.
  • XVideos:
    • Total drop: 47%.
    • Minors: 7%.
    • VPN: ~25%.
    • Residual: 47% – 7% – 25% = 15% (~32% of the reported fall).
  • xHamster:
    • Total drop: 39%.
    • Minors: 7%.
    • VPN: ~25%.
    • Residual: 39% – 7% – 25% = 7% (~18% of the reported fall).
  • OnlyFans:
    • Total drop: ~10% (assumed).
    • Minors: 7%.
    • VPN: ~3% (lower due to subscription model and smaller reported drop).
    • Residual: 10% – 7% – 3% = 0% (~0% of the reported fall; suggests most of the drop is explained by minors and minimal VPN use).
  • Overall (90 sites):
    • Total drop: 23%.
    • Minors: 7%.
    • VPN: ~12%.
    • Residual: 23% – 7% – 12% = 4% (~17% of the reported fall).

 Step 4: Interpretation and caveats

  • The residual drop (adults no longer accessing) ranges from 0% (OnlyFans) to 15% (Pornhub/XVideos) for top sites, with 7% for xHamster and 4% overall. This suggests:
    • For major free sites (Pornhub, XVideos), ~15 percentage points of the drop (~32% of their 47% fall) is likely adults deterred by age verification (e.g., due to privacy concerns, hassle of ID checks, or moral/ethical reasons).
    • For xHamster, ~7 percentage points (~18% of its 39% fall) reflects a smaller residual, possibly due to its user base being less affected by verification barriers.
    • For OnlyFans, the drop is almost entirely explained by minors (7%) and minimal VPN use (3%), suggesting few adults stopped accessing entirely, likely due to its paid model retaining committed users.
    • Overall, the 4% residual (~17% of the 23% fall) is diluted by smaller/non-compliant sites gaining traffic, masking adult cessation on major sites.
  • Caveats:
    • Assumes equal usage intensity for minors and adults; if minors visit less frequently, their contribution drops (e.g., to 3.5%), increasing the adult cessation share slightly (e.g., to 18.5% for Pornhub).
    • VPN estimate (20-30%) is based on reported spikes but lacks precise user overlap with porn site visitors; if overstated, adult cessation could be higher (e.g., if VPN is 15%, Pornhub’s residual rises to 20%).
    • Seasonal or other factors (e.g., weather, events) may influence traffic, but the article suggests these are minor compared to the policy effect.
    • OnlyFans’s exact drop (>10%) is unclear; a higher drop (e.g., 15%) could yield a small positive residual (e.g., 5%).

In summary, the percentage fall likely due to adults no longer accessing the top adult sites is:

  • Pornhub/XVideos: ~15% (15 percentage points of the 47% drop).
  • xHamster: ~7% (7 percentage points of the 39% drop).
  • OnlyFans: ~0% (0 percentage points of the ~10% drop).
  • Overall (90 sites): ~4% (4 percentage points of the 23% drop).

These figures reflect adults deterred by the age verification process itself, with VPN usage and minor restrictions explaining the majority of the observed drops.


ChatGPT critique of Grok

What portion is truly “adults no longer accessing”Do not hard-code a 25 pp VPN slice. The VPN surge is real, but we lack a clean daily-active figure. Treat it as a sensitivity: if VPNs explain roughly 10-20 pp of the big-site falls, then the share likely due to adults giving up entirely would be:

  • Pornhub/XVideos: ~19-33 pp of the 47% fall
  • xHamster: ~11-25 pp of the 39% fall
  • OnlyFans: ~0-6 pp of the ~10% fall
  • Top-90 overall: ~5-14 pp of the 23% fall

Those bands are the minors-removed residual minus an illustrative 10-20 pp for VPN reclassification and bypass, consistent with app-store spikes and provider reports of ~1,400% sign-up surges. You can narrow them as better data on 15-17s and VPN daily actives emerges


Google Gemini review of Grok’s analysis

The statistical analysis provided by “Grok” presents a plausible framework for attributing the recent drop in UK adult site traffic to various factors, and the calculations are arithmetically correct based on the assumptions made. However, a statistician would highlight several key assumptions that are not confirmed by direct data, making the results a reasoned estimate rather than a definitive conclusion.

Here is a breakdown of the analysis and the key points to consider:

Strengths of the Analysis

The analysis is strong in its methodical approach, breaking down the problem into distinct, manageable steps. This includes:

  • Quantitative Framework: It correctly establishes a quantitative model for the problem, starting with the overall population of minors, applying access rates from sources like Ofcom, and then calculating the total number of minor and adult users. This provides a clear, logical path to the final attribution.
  • Use of Available Data: The analysis references real-world data points, such as the UK minor population, Ofcom’s reported access rates for children aged 8-14, and the reported traffic drops from news articles. Using these data points grounds the argument in available evidence.
  • Explicit Assumptions: The analysis explicitly states its key assumptions, such as assuming minors and adults have “similar usage intensity” and using “conservative estimates” when specific data is unavailable (e.g., the 25% monthly access rate for 15-17 year olds). This transparency is a crucial part of sound statistical work.
  • Calculations: The mathematical calculations (e.g., calculating the number of minors, their share of total users, and the attributed percentages) are all performed correctly based on the initial assumptions.

Areas for Scrutiny and Weaknesses

A statistician would caution that the results are highly dependent on the initial assumptions, some of which are significant and could change the conclusions if they were inaccurate.

  • Usage Intensity Assumption: The core assumption that “minors and adults have similar usage intensity per user” is a significant leap. It is plausible that minors might visit less frequently or for shorter durations than a typical adult user, which would mean that their share of overall traffic (measured in visits) is lower than their share of total users. If minors account for only 3-4% of traffic instead of 7%, the attributed drop would be much smaller, and the residual drop for adults would be larger.
  • Data Source Limitations: The analysis relies on a mix of data sources from different years (e.g., Ofcom 2024/2025 data, Statista 2022/2023, Guardian 2023 study). While this is a common necessity when a single dataset is unavailable, it introduces potential inconsistencies.
  • VPN Usage Attribution: The estimation that VPN usage accounts for “20-30 percentage points of the drop” is based on reported spikes in sign-ups, which is a proxy for actual usage. This assumes that all, or a significant portion, of the new VPN users are using them specifically to bypass age verification for adult content, and that these users would have otherwise contributed to the UK-tracked traffic. This is a reasonable inference, but not a confirmed fact.
  • OnlyFans Residual: The analysis concludes a 0% residual for OnlyFans, which suggests that every percentage point of the drop is perfectly explained by the two other factors (minors and VPN). In real-world data, it is highly unlikely to have a perfect fit. A statistician would typically express this as a small, or negligible, residual, acknowledging that the model is an approximation.

Final Assessment

Overall, the analysis is a well-reasoned and transparent attempt to quantify a complex problem. A statistician would agree with the methodology and the reasoning, but would frame the final numbers as strong estimates based on the best available public data, not as definitive proof. The conclusions about the attributed drops (e.g., 15% for Pornhub, 4% overall) are sound within the context of the stated assumptions.

The most compelling takeaway from the analysis remains the same: a successful age verification policy alone would likely account for only a small portion of the total drop in traffic to these sites, while the majority of the plunge is better explained by adults shifting their behavior—either by using VPNs to access the same sites or by seeking out non-compliant platforms.