Considerations in assessing trustworthy AI - Quality and integrity of data

“Compliance with this assessment list is not evidence of legal compliance, nor is it intended as guidance to ensure compliance with applicable law. Given the application-specificity of AI systems, the assessment list will need to be tailored to the specific use case and context in which the system operates. In addition, this chapter offers a general recommendation on how to implement the assessment list for Trustworthy AI though a governance structure embracing both operational and management level.” (High-Level Expert Group on AI, 2019, p. 24)“TRUSTWORTHY AI ASSESSMENT LIST (PILOT VERSION) “Privacy and data governance Respect for privacy and data Protection: “Quality and integrity of data: Did you align your system with relevant standards (for example ISO, IEEE) or widely adopted protocols for daily data management and governance? Did you establish oversight mechanisms for data collection, storage, processing and use? Did you assess the extent to which you are in control of the quality of the external data sources used? Did you put in place processes to ensure the quality and integrity of your data? Did you consider other processes? How are you verifying that your data sets have not been compromised or hacked?” (High-Level Expert Group on AI, 2019, p. 28)