OpenAI has begun rolling out an age prediction feature across ChatGPT consumer plans to automatically estimate whether an account likely belongs to someone under 18, and to apply age-appropriate protections as part of its broader safety strategy.
According to OpenAI, the age prediction system works by analysing a combination of behavioural and account-level signals, such as the length of an account’s existence, typical activity times, usage patterns over time, and any stated age, to help indicate whether the account may belong to a minor. At the same time, the company says the model is designed to be refined over time as more signals are learned and accuracy improves.
If the system estimates that an account belongs to someone under 18, ChatGPT automatically applies additional safeguards to reduce exposure to sensitive content. These include restrictions on graphic violence or gory material, viral challenges that could encourage risky behaviour, sexual, romantic, or violent role play, depictions of self-harm, and content that promotes extreme beauty standards or unhealthy dieting.
However, users whom the system wrongly places in the under-18 experience can dispute the decision and restore full access by verifying their age through Persona, a secure identity verification service, using a selfie.
Notably, this decision comes after a wrongful death lawsuit in the United States linked to the death of 16-year-old Adam Raine, whose parents alleged ChatGPT failed to prevent or appropriately intervene in his prolonged discussions of self-harm and suicide with the chatbot before he took his own life in April 2025.
After the Raines family’s suit, OpenAI added stronger parental controls and age-based safety features, enabling guardians to monitor teen accounts, receive alerts if the system detects the child is in severe distress, and enforce blackout hours.
How accurate can age verification be?
Age verification systems still struggle to deliver exact precision in real-world applications, with industry experts and platform deployments underscoring key limitations. In an interview with MediaNama, Bureau Chief Technology Officer (CTO) Sandesh GS explained that many current technologies are better at identifying broad age bands than precise ages, saying that “if you want a band, it works reasonably well, but when we want a point in time, it does not work as well.” He added that models simply are not calibrated for “decimal-level accuracy,” meaning systems can sometimes group a user into a general age bracket yet misestimate their specific age.
This limitation is visible in large-scale platform rollouts. Roblox, one of the world’s most popular gaming platforms, now requires users to complete age checks, typically through facial age estimation using Persona or ID-based verification, before accessing chat features. The platform then places users into specific age groups, allowing them to interact in-game within those…
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