AI Ethics & Responsible Development

3.1 Model Selection & Training: We carefully select and evaluate third-party LLM providers based on their ethical practices, data handling policies, and commitment to responsible AI development.

3.2 Bias Detection & Mitigation: We actively work to identify and mitigate potential biases in AI processing. This includes regular audits of our systems and continuous monitoring of processing results.

3.3 Safety & Security: We implement comprehensive safety measures to prevent misuse of our AI systems and protect against potential security vulnerabilities.

3.4 Continuous Improvement: We regularly review and update our AI ethics practices based on new research, user feedback, and evolving industry standards.

4.1 Informed Consent: We ensure that users provide informed consent before their data is processed by AI systems. Users are clearly informed about how their data will be used and have the right to opt out.

4.2 Data Minimization: We collect and process only the minimum amount of data necessary to provide our services effectively.

4.3 Secure Processing: All data processing is conducted through secure, encrypted channels with strict access controls and monitoring.

4.4 Third-Party Provider Standards: We partner only with AI providers who share our commitment to ethical practices and responsible data handling.

We empower users with the following rights and controls:

• Transparency: Clear information about how AI processes their data
• Consent: Ability to provide or withdraw consent for AI processing
• Access: Right to access and review AI-generated results
• Correction: Ability to request corrections to AI-generated content
• Deletion: Right to request deletion of their data and AI processing results
• Human Review: Option to request human review of AI-generated results

6.1 AI Accuracy: While we strive for high accuracy, AI systems may occasionally produce errors or unexpected results. Users should always verify AI-generated content and not rely solely on automated processing for critical decisions.

6.2 Context Understanding: AI systems may not always fully understand the context or nuances of complex documents. Users should exercise judgment when interpreting AI-generated summaries and analysis.

6.3 Evolving Technology: AI technology is rapidly evolving. Our systems and practices will continue to improve, but users should be aware that current limitations exist.

7.1 Regular Audits: We conduct regular audits of our AI systems to ensure compliance with ethical standards and identify potential issues.

7.2 User Feedback: We actively solicit and incorporate user feedback to improve our AI systems and address ethical concerns.

7.3 Incident Response: We have established procedures for responding to AI-related incidents, including bias detection, security breaches, or other ethical concerns.

7.4 External Review: We welcome external review of our AI ethics practices and are committed to transparency in our development processes.

We align our AI ethics practices with established industry standards and frameworks, including:

• OECD AI Principles
• IEEE Ethically Aligned Design
• EU AI Act guidelines
• NIST AI Risk Management Framework
• Industry-specific best practices