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This policy ensures our Flora chatbot and text analysis products meet safety and quality standards while operating within our resource constraints as a growing company. All AI products at Bloomfilter are powered by OpenAI models and benefit from their underlying framework for safety and bias mitigation. Additional information about OpenAI's comprehensive policies and safety measures can be found in their public documentation.
Bloomfilter's AI products have been specifically designed and rigorously tested to address particular use cases within the Bloomfilter platform, ensuring our AI systems make appropriate decisions within their intended scope. When we implement changes to our AI systems, we apply thorough testing protocols to maintain consistent accuracy in all responses. We validate data from reliable sources and conduct periodic assessments to ensure data quality and accuracy remain high, with continual updates and risk reviews to address evolving challenges.
We maintain comprehensive logging of all AI responses within Bloomfilter, including full stack traces that enable detailed investigation of any decision or judgment made by our AI agents when accuracy concerns arise. We treat accuracy issues with utmost seriousness, and users can report concerns through Bloomfilter support channels or by contacting ai_safety@bloomfilter.ai directly.
Our AI products utilize proven analytics technology that undergoes rigorous testing before any code changes are deployed. We maintain strict data source verification protocols to ensure all training and operational data originates from reliable, documented sources with validated integrity and correctness. During our customer integration process, we conduct thorough data validation procedures to ensure all data within the system is handled correctly and meets our quality standards throughout the pipeline.
We implement regular data quality assessments to validate data integrity, accuracy, and continued relevance for our AI systems. Access to training and operational datasets is restricted to authorized personnel only, with audit logging to prevent unauthorized manipulation. Our data integrity controls include automated validation checks for completeness, consistency, and format compliance before any data is used in AI model training or inference.
Given that Bloomfilter primarily processes software development execution data, we anticipate minimal risk of our AI systems encountering prompts that could lead to bias or fairness concerns. Nevertheless, we implement specific mechanisms to prevent unfair identification, profiling, or statistical singling out based on race, religion, gender identity, national origin, disability, or other protected characteristics.
Our bias prevention measures include pre-deployment testing across diverse scenarios and periodic monitoring of AI outputs for discriminatory patterns. We maintain a bias incident reporting system and conduct regular reviews to assess whether our AI systems exhibit any unfair treatment of different user groups. Should any Bloomfilter AI agent exhibit unfair or biased behavior, we commit to swift action to understand the root cause and implement appropriate corrective measures to prevent recurrence. Users with concerns can contact ai_safety@bloomfilter.ai.
We ensure strict adherence to privacy regulations by implementing purpose limitation controls that prevent data collected for specific AI training or operational purposes from being utilized for unrelated objectives such as user profiling or personalized marketing. Before any data collection occurs, we document the specific purpose and establish the lawful basis for processing under applicable privacy regulations including GDPR.
Our privacy compliance framework includes transparency standards that clearly communicate to users how their data is used in our AI systems. We provide mechanisms for users to exercise their rights including data access, correction, and deletion requests. Where required, we obtain explicit user consent before processing personal data for AI model training or inference. All data processing activities are logged and auditable to demonstrate compliance with privacy regulations. Users can contact security@bloomfilter.ai for any privacy-related concerns or to exercise their data rights.
We maintain comprehensive documentation covering our AI model development processes, including detailed records of dataset sources, data combination methodologies, and model training procedures. Our AI systems are designed to provide sufficiently transparent operations that enable users to interpret system outputs and utilize them appropriately within their intended context.
We provide clear documentation to users regarding the capabilities and limitations of our AI systems, including guidance on interpreting results and recommendations. Where technically feasible, we implement explainability features that help users understand the reasoning behind AI-generated outputs. Our model development documentation includes version control, change logs, and performance metrics to ensure full traceability of AI system evolution and decision-making processes.
Our security and robustness approach focuses on essential protections while ensuring comprehensive system resilience. We implement HTTPS encryption across all systems without exception, as this represents a fundamental security requirement. We employ rate limiting to prevent system abuse and designate responsible team members to handle security updates and patches promptly. Our monitoring system provides effective oversight through automated alerts when the system experiences downtime, significant response time degradation, or other performance anomalies.
Our AI systems are designed to withstand unexpected events, maintain functionality during system changes, and degrade gracefully when necessary while preserving core security controls. We implement logging mechanisms to detect and counter unauthorized access attempts and system misuse. Regular security assessments ensure our systems remain resilient against errors, faults, inconsistencies, and malicious actions that could compromise system security or data integrity.
For emergency situations, we maintain clear response procedures that prioritize user safety and system integrity. In the event of a system compromise, we immediately take the affected systems offline to prevent further damage and protect user data. When harmful content is generated by our AI systems, we document the incident thoroughly, implement fixes where possible, and refine our prompts to prevent similar occurrences. We commit to responding to security or privacy concerns within 24 hours to address issues and maintain trust in our platform.
