Founding Principles of AI at Magnet Forensics
We are committed to developing AI tools that uphold the highest standards of transparency, fairness, and ethical responsibility. We build and integrate AI into our solutions in ways that safeguard privacy and maintain the integrity of investigations, while ensuring that AI remains a powerful ally in the pursuit of justice.
01
Design AI to enhance—never replace—human judgment
Principle
Our AI features must be developed as tools that accelerate analysis while never undermining human oversight.
Implementation
Design AI features to assist the user, while presenting clear means to build confidence in outputs, and mechanisms for users to identify, confirm, modify, or reject AI suggestions whenever possible.
02
Prioritize demonstrated reliability in AI-enabled features
Principle
AI feature outputs must be presented in a manner that is easy to evaluate by the end user to demonstrate reliability.
Implementation
Implement features and support mechanisms that give users context about how an AI result is reached. This may include noting the type of AI employed, annotated references, citations to specific source data, attestation(s) about testing and accuracy, or published empirical research on the reliability of the AI-enabled feature.
03
Incorporate bias mitigation and objectivity from the ground up
Principle
AI systems must be built to minimize bias and promote fairness, ensuring all individuals and evidence are treated impartially.
Implementation
Design AI features to be equally accurate across a wide array of datasets. AI features will not be trained using user submitted data.
04
Facilitate proper user training and education
Principle
Ensure AI systems are intuitive and accompanied by educational resources for users.
Implementation
Design AI-driven features that users can easily navigate, understand, and interact with. Provide built-in training modules, tutorials, and documentation to help users understand both the capabilities and limitations of the AI system.
05
Ensure ethical use and data privacy protections
Principle
Develop AI systems with robust ethical safeguards and data privacy protections, operating strictly within legal requirements.
Implementation
Incorporate mechanisms that enforce data privacy standards and prevent misuse of the AI system. Ensure compliance with all relevant privacy laws and regulations and implement auditing tools to track data use.