The FIPs: where all of this started
AI ethics frameworks descend from the FIPs (Fair Information Practices), originated in 1980 by the OECD Guidelines on the Protection of Privacy and Transborder Flows of Personal Data. The eight principles cover data collection, use, protection and individual rights.
Decades of privacy, security and data governance design are rooted in the Fair Information Practices. AI ethics frameworks are their descendants.
Originated in 1980 by the OECD Guidelines on the Protection of Privacy and Transborder Flows of Personal Data. Echoed by international organisations and US agencies such as the Department of Homeland Security and the FTC. The FIPs focus on data collection, use, protection and individual rights → follow-on principle sets (like AI governance principles) build on them.
- Collection limitation → collect only what is necessary, obtained by lawful and fair means.
- Use limitation → use data only as specified, unless the data subject consents or a legal exception applies.
- Purpose specification → disclose specific purposes up front, then use data only for those compatible purposes.
- Data quality → data should be relevant to its purpose and accurate, complete and timely to be fair to data subjects.
- Security safeguards → reasonable safeguards established to protect personal data.
- Openness → be clear and open, to the extent required by law, about practices and policies for personal data.
- Individual participation → appropriate access so a person can understand their data and obtain, amend, correct or challenge it.
- Accountability → companies are accountable for complying with the principles and obligations in the other FIPs.