Discord has been using ML to determine the gender and age of some of its users

Business and Product Motives

• Many see the main driver as advertising: age/gender inference improves ad targeting, pricing, and partner pitches (e.g., “we have X 18–24-year-olds”).
• Some think Discord is building an ad network / platform, especially after announcing in-app ads and “quests.”
• Demographic inference can also support market research and customer segmentation offerings at different price points (self‑reported vs inferred data).

Regulatory and Child Safety Arguments

• Several argue ML age detection may be used to identify under‑13 or otherwise underage users for compliance with laws like the UK Online Safety Act, EU child‑protection rules, and similar.
• Counterpoint: if the sole aim is age‑gating, you only need “too young vs old enough,” not fine‑grained age bands and gender.

Privacy, Consent, and Legal Concerns

• Strong pushback that users never explicitly gave age/gender to Discord, yet these are being inferred from behavior and text.
• Under frameworks like GDPR/CCPA (as described by commenters), users should know what is collected, how it’s used/shared, and be able to have it corrected or deleted; “inference” is seen by many as equivalent to collecting.
• Disagreement over whether probabilistic scores for gender/age legally count as personal data.
• Some worry that inferred traits (e.g., sexuality, gender) could be dangerous if accessed by governments or hostile actors.

Targeting, Segmentation, and ML Use

• Debate over whether demographic targeting adds value beyond pure behavioral targeting; some argue behavior alone is superior, others say demographics remain a key axis advertisers demand.
• Discussion of “person type” / persona clustering vs explicit demographics; advertisers often still want human‑readable categories.

User Trust, Enshittification, and Alternatives

• Many view this as part of the broader “enshittification” of Discord as it moves to an ad‑driven model.
• Some users discuss migrating to alternatives (Matrix, Revolt, Mattermost, P2P systems) to regain control and avoid surveillance.

Other ML Uses and Concerns

• Reports that Discord also uses ML to infer voice‑channel topics and surface them to others in the server, which some find intrusive.
• A minority defends such ML as necessary for combating child exploitation, scams, and other abuses; others see this as overstated or as cover for monetization.