Documentation standard and transparency reporting
Using Saidot, you will be able to
Create a comprehensive documentation for your AI system and ensure transparency and accountability.
Prove regulatory compliance by maintaining clear and traceable records of your AI system.
Help relevant stakeholders understand your AI system and its functions while building trust in your AI system.
Documentation standards
Creating comprehensive documentation for your AI system ensures transparency, accountability, and auditability. It helps stakeholders understand the system's purpose, development process, and operational details. Furthermore, documentation addresses legal and regulatory requirements, mitigates risks, and facilitates effective maintenance and updates.
The AI system technical documentation can include, but is not limited to, the following elements:
General description, f.e. intended purpose
Usage instructions
Technical assumptions about deployment and operation
Technical limitations
Monitoring capabilities and functions
Documentation elements related to all AI system life cycle stages can include, but are not limited to, the following elements:
Design and system architecture
Design choices and quality measures during system development
Data use during development and data quality measures
Management activities, f.e. risk management process
Verification and validation records
Changes to the AI system during operation
Impact assessment documentation
Documentation elements related to the responsible operation of the AI system can include, but are not limited to, the following elements:
Failure management plan
Health monitoring process
Standard operating procedures
Personnel roles and accountability
System updates
Adapted based on ISO/IEC 42001 item B.6.2.7.
We apply research and regulation-based AI documentation standards to maintain clear and traceable records of AI design choices, development processes, and compliance efforts. With Saidot, your organisation can effortlessly generate comprehensive documentation for relevant aspects of your AI system. Our platform enables you to document diverse components, including system type and capabilities, models, suppliers, datasets, risk management practices, and policy templates. The amount of documentation required can vary depending on the AI system and its context, as different systems have different regulatory requirements. Additionally, it supports the attachment of any additional documents your organisation deems relevant, ensuring a thorough and customisable documentation trail.
Transparency reporting
The primary purpose of transparency in AI is to help stakeholders understand the system’s workings, decision-making process, and to contest its behaviours. This enables accountability for those affected and allows responsible parties, auditors, and civil society activists to evaluate the system. Transparency reporting facilitates the sharing of information to enhance explainability and accountability, ultimately helping to build trust and ensure responsible AI usage.