Snap AI Ethical Guidelines

1. Fairness and Non-Discrimination

• Avoid Bias : Ensure that AI models used in the platform do not reinforce harmful biases related to race, gender, age, ethnicity, religion, or other protected characteristics.
• Equal Access : The AI-driven features must be designed and deployed to provide equal opportunities for all users, irrespective of their background or demographic information.

2. Privacy and Data Security

• AI Disclosure : Users must be informed when AI is being used in their applications, and they must be provided with clear explanations of how the AI system makes decisions.
• Data Privacy : Ensure all AI-driven functionalities comply with data protection regulations, such as GDPR, and prioritize the protection of personal data.
• Informed Consent: Users must be clearly informed about how their data is used and must give explicit consent for the collection and processing of their data for AI purposes.
• Data Minimization : AI systems should only collect and use the minimal amount of data necessary for their functioning, and all user data must be securely stored and protected

3. Accountability

• Human Oversight : Users must have the ability to override AI decisions or opt-out from AI-driven automation when necessary.
• Responsibility for Outcomes : Developers using the platform should take responsibility for the outcomes of AI-driven applications and ensure they align with ethical standards.
• Regular Audits : Periodically audit AI systems to ensure compliance with ethical guidelines and continuously improve systems based on feedback and new research.

4. Safety and Reliability

• Robustness : AI models should be regularly tested for accuracy and reliability to ensure they perform as expected across different contexts and environments.
• Error Handling : Ensure that AI systems have error-handling mechanisms that notify users when problems arise and provide alternative solutions where applicable.
• Avoid Harm : AI should be designed to avoid causing physical, emotional, or financial harm to users or other individuals impacted by its use.

5. Sustainability

• Energy Efficiency : Aim to develop and deploy AI solutions that are energy-efficient and minimize the environmental impact of training and using AI models.
• Long-Term Impact : Consider the long-term societal and environmental impact of AI-driven solutions developed on the platform.

6. User Empowerment

• AI Literacy : Provide resources and education to help users understand the capabilities and limitations of AI.
• Control and Autonomy : Give users control over how AI features are integrated into their applications, allowing them to customize and disable AI features as needed.

8. Ethical Innovation

• Continuous Improvement : Encourage the development of AI that improves over time, focusing on ethical innovations that benefit users and society at large
• Inclusive Design : Ensure that AI-driven tools and features are accessible and useful for a diverse range of users, including those with disabilities.

These guidelines promote the responsible and ethical use of AI within the platform while fostering trust, transparency, and fairness for all users and stakeholders.