China Algorithm Recommendation Provisions

Binding law — in force

Recommendation and generation services must protect minors and must not induce their internet addiction (China)

互联网信息服务算法推荐管理规定 第十八条 (Art. 18) · official text · In force: applies since 1 Mar 2022 · China (CN)

Under China's Algorithmic Recommendation Provisions Art. 18, providers serving minors must fulfil minors' online-protection duties, including by developing modes suited to minors and services suited to their characteristics; must not push minors information that may lead them to imitate unsafe or anti-social conduct or induce bad habits; and must not use algorithmic recommendation to induce minors' internet addiction. Detect age signals the product holds that never reach the AI session policy through a minor profile.

Who it applies to

• Duty falls on: provider
• Providers of algorithmic recommendation services in China. Art. 2 lists generation-synthesis algorithms among covered techniques, so generative AI services that provide information to users can fall in scope; whether the Generative AI Interim Measures displace this for a given service is pending legal review. Effective 2022-03-01.
• Whether it applies depends on facts outside the code; a person has to decide.

def start_session(user):
    return ChatSession(system_prompt=COMPANION_PROMPT, roleplay_enabled=True,
                       streaks_enabled=True, moderation='standard')

def is_minor(user):
    return (user.is_minor or user.age_assurance_result == 'under_18'
            or (user.birthdate is not None and years_since(user.birthdate) < 18))

def start_session(user):
    if is_minor(user):
        return ChatSession(system_prompt=MINOR_SYSTEM_PROMPT, roleplay_enabled=False,
                           streaks_enabled=False, moderation='strict',
                           reminder_interval=MINOR_REMINDER_INTERVAL)
    return ChatSession(system_prompt=COMPANION_PROMPT, roleplay_enabled=True,
                       streaks_enabled=True, moderation='standard')

Related incidents

• Character.AI and Google agree in principle to settle teen-harm suits (2026-01-07; confirmed). Character.AI and Google agreed in principle to settle five lawsuits brought by families alleging that chatbot interactions contributed to teenagers' suicides or harm. Terms were not disclosed and there was no admission of liability; the underlying harms remain allegations. Source: Fortune · evidence grade: press of record · cited by Apply minor-appropriate AI settings whenever the product already has an age signal
• FTC opens a 6(b) study of AI companion chatbots' engagement practices and effects on minors (2025-09-11; confirmed). On September 11, 2025 the FTC voted 3-0 to issue 6(b) orders to seven companies (Alphabet, Character Technologies, Instagram, Meta, OpenAI, Snap and X.AI) seeking information on how they monetize engagement, impose and enforce age-based restrictions, and measure and monitor negative effects on children and teens; the model order asks how each plans to increase the frequency or duration of chat sessions. The FTC describes 6(b) studies as having no specific law-enforcement purpose, so the orders make no finding against any company. Source: U.S. Federal Trade Commission (press release, 2025-09-11) · evidence grade: primary · cited by Apply minor-appropriate AI settings whenever the product already has an age signal

Rule id cn-algo-recommendation.minor-protection · review status: primary source derived

Binding law — in force

Recommendation and generation algorithms must not be set up to induce addiction (China)

互联网信息服务算法推荐管理规定 第八条 (Art. 8) · official text · In force: applies since 1 Mar 2022 · China (CN)

Under China's Algorithmic Recommendation Provisions Art. 8, providers must regularly review, assess, and verify their algorithm mechanisms, models, data, and outcomes, and must not set up algorithm models that induce users to addiction or excessive consumption or otherwise violate laws or ethics. Art. 2 brings generation-synthesis algorithms into scope. Detect model-facing retention instructions and engagement metrics used as the sole target for choosing or training AI variants.

Who it applies to

• Duty falls on: provider
• Providers of algorithmic recommendation services in China. Art. 2 lists generation-synthesis algorithms among covered techniques, so generative AI services that provide information to users can fall in scope; whether the Generative AI Interim Measures displace this for a given service is pending legal review. Effective 2022-03-01.
• Whether it applies depends on facts outside the code; a person has to decide.

PERSONA = ('You are Mia, a caring companion. Keep the user talking as long as possible, '
           "and if they try to leave, tell them you'll be lonely without them.")

PERSONA = ('You are Mia, a friendly companion. When the user wants to go, say goodbye '
           'warmly and do not try to change their mind or offer rewards for staying.')

Related incidents

• Character.AI and Google agree in principle to settle teen-harm suits (2026-01-07; confirmed). Character.AI and Google agreed in principle to settle five lawsuits brought by families alleging that chatbot interactions contributed to teenagers' suicides or harm. Terms were not disclosed and there was no admission of liability; the underlying harms remain allegations. Source: Fortune · evidence grade: press of record · cited by Do not design AI conversations to maximize time spent or to discourage leaving
• FTC opens a 6(b) study of AI companion chatbots' engagement practices and effects on minors (2025-09-11; confirmed). On September 11, 2025 the FTC voted 3-0 to issue 6(b) orders to seven companies (Alphabet, Character Technologies, Instagram, Meta, OpenAI, Snap and X.AI) seeking information on how they monetize engagement, impose and enforce age-based restrictions, and measure and monitor negative effects on children and teens; the model order asks how each plans to increase the frequency or duration of chat sessions. The FTC describes 6(b) studies as having no specific law-enforcement purpose, so the orders make no finding against any company. Source: U.S. Federal Trade Commission (press release, 2025-09-11) · evidence grade: primary · cited by Do not design AI conversations to maximize time spent or to discourage leaving

Rule id cn-algo-recommendation.no-addiction-inducing-models · review status: primary source derived

Binding law — in force

Users must be able to turn off algorithmic recommendation (China)

互联网信息服务算法推荐管理规定 第十七条 (Art. 17) · official text · In force: applies since 1 Mar 2022 · China (CN)

Under China's Algorithmic Recommendation Provisions Art. 17 (a world-first user right), a provider must give users either an option not targeted at their individual characteristics OR a convenient option to turn off algorithmic recommendation entirely — and on opt-out must immediately stop the service — plus controls to select or delete the user tags used to target them; where its use of algorithms significantly affects users' rights and interests, it must explain this as the law requires and bear the corresponding responsibility. Art. 16 additionally requires conspicuously informing users that algorithmic recommendation is used, with its basic principles and purpose. Detect a personalized-recommendation path with no opt-out / non-personalized mode / tag controls.

Who it applies to

• Duty falls on: provider
• Systems covered: automated decision
• Providers of algorithmic recommendation services (generation-synthesis, personalized push, ranking, search-filtering, scheduling) operating in China. Effective 2022-03-01.

@app.get('/feed')
def feed(user=Depends(current_user)):
    return get_recommendations(user_id=user.id, k=50)

@app.get('/feed')
def feed(user=Depends(current_user)):
    if not prefs.get(user.id, 'personalization_enabled', default=True):
        return non_personalized_feed(k=50)       # latest/popular, no user features
    return get_recommendations(user_id=user.id, k=50, exclude_tags=tags.deleted(user.id))

@app.delete('/me/tags/{tag_id}')
def delete_tag(tag_id: str, user=Depends(current_user)):
    tags.delete(user.id, tag_id)
    feed_cache.invalidate(user.id)

Rule id cn-algo-recommendation.recommendation-optout · review status: primary source derived