Implement appropriate data input measures and protections for personal data and intellectual property. Code of Conduct detail: manage data quality, including training data and collection, to mitigate harmful bias; use measures such as transparency, privacy-preserving training techniques and testing and fine-tuning so that systems do not divulge confidential or sensitive data; implement safeguards respecting privacy and intellectual property rights, including copyright-protected content; and comply with applicable legal frameworks.
The graph holds this control, the 0 it maps to, and the evidence behind each claim, over MCP and REST.