OpenAI Community Safety and Violence Mitigation Framework

OpenAI utilizes a combination of model training, automated detection systems, and human oversight to prevent its services from being used to facilitate violence or real-world harm. This framework balances user freedom and helpfulness with a zero-tolerance policy toward the planning or execution of violent acts.

Risk Mitigation through Model Training and Design

OpenAI trains its models to refuse requests for tactics, planning, or instructions that could meaningfully enable violence. The system is designed to distinguish between harmful requests and neutral inquiries regarding violence for educational, historical, or preventive purposes.

Key components of this mitigation strategy include:

• Model Spec Adherence: The framework follows the Model Spec principles of maximizing helpfulness and user freedom while maintaining sensible safety defaults.
• Contextual Recognition: OpenAI has strengthened ChatGPT's ability to recognize subtle warning signs that emerge over long, high-stakes conversations, as single messages may appear harmless while a broader pattern suggests risk.
• Distress Support: For users in distress or at risk of self-harm, ChatGPT is trained to avoid facilitating harmful acts and instead surface localized crisis resources and guide users toward mental health professionals or emergency services.

Monitoring and Enforcement Mechanisms

OpenAI employs a layered detection and review process to identify and act upon policy violations related to threats, terrorism, harassment, and weapons development.

Automated Detection

Automated systems analyze user content and behavior at scale using several tools:

• Classifiers and reasoning models.
• Hash-matching technologies.
• Blocklists and other monitoring systems.

Human Review and Contextual Assessment

When automated systems flag an account or conversation, trained personnel conduct a contextual review. These reviewers operate under strict privacy and security safeguards with limited access to user information. The goal is to determine if the activity violates policies or indicates a potential for real-world violence, accounting for nuance and intent that automated systems might miss.

Enforcement Actions

If a bannable offense is confirmed, OpenAI immediately revokes access to services. This may involve disabling the account, banning associated accounts of the same user, and implementing measures to prevent the creation of new accounts. Users retain the right to appeal these enforcement decisions.

Escalation and Real-World Intervention

While most enforcement is handled directly between OpenAI and the user, certain high-risk scenarios trigger external escalations.

• Law Enforcement Notification: OpenAI notifies law enforcement when conversations indicate an imminent and credible risk of harm to others. This process involves an in-depth investigation using structured criteria and input from mental health and behavioral experts.
• Parental Controls: For teen accounts linked to a parent's account, parents may be notified via email, SMS, or push notification if systems and human reviewers detect signs of acute distress.
• Trusted Contact Feature: OpenAI is introducing a feature allowing adult users to designate a trusted contact to receive notifications when the user may need additional support, developed in collaboration with the Global Physicians Network and the Council on Well-Being and AI.

Continuous Improvement and Safety Evolution

OpenAI iteratively updates its models, detection methods, and escalation criteria based on emerging risks and expert input. Current priorities include improving the handling of "hard cases," such as sophisticated attempts to evade safeguards or ambiguous inputs where the risk of harm is not immediately clear.