On June 25, 2019, as part of their continuing work on the AI Auditing Framework, the UK Information Commissioner’s Office (ICO) published a blog setting out their views on human bias and discrimination in AI systems. The ICO has also called for input on specific questions relating to human bias and discrimination, set out below.

The ICO explains in its blog how flaws in training data can result in algorithms that perpetuate or magnify unfair biases. The ICO identifies three broad approaches to mitigate this risk in machine learning models:

  1. Anti-classification: making sure that algorithms do not make judgments based on protected characteristics such as sex, race or age, or on proxies for protected characteristics (e.g., occupation or post code);
  2. Outcome and error parity: comparing how the model treats different groups. Outcome parity means all groups should have equal numbers of positive and negative outcomes. Error parity means all groups should have equal numbers of errors (such as false positives or negatives). A model is fair if it achieves outcome parity and error parity across members of different protected groups.
  3. Equal calibration: comparing the model’s estimate of the likelihood of an event and the actual frequency of said event for different groups. A model is fair if it is equally calibrated between members of different protected groups.

The guidance stresses the importance of appropriate governance measures to manage the risks of discrimination in AI systems. Organizations may take different approaches depending on the purpose of the algorithm, but they should document the approach adopted from start to finish. The ICO also recommends that organizations adopt clear, effective policies and practices for collecting representative training data to reduce discrimination risk; that organizations’ governing bodies should be involved in approving anti-discrimination approaches; and that organizations continually monitor algorithms by testing them regularly to identify unfair biases. Organizations should also consider using a diverse team when implementing AI systems, which can provide additional perspectives that may help to spot areas of potential discrimination.

The ICO seeks input from industry stakeholders on two questions:

  • If your organisation is already applying measures to detect and prevent discrimination in AI, what measures are you using or have you considered using?
  • In some cases, if an organisation wishes to test the performance of their ML model on different protected groups, it may need access to test data containing labels for protected characteristics. In these cases, what are the best practices for balancing non-discrimination and privacy requirements?

The ICO also continues to seek input from industry on the development of an auditing framework for AI; organizations should contact the ICO if they wish to provide feedback.

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Photo of Lisa Peets Lisa Peets

Lisa Peets leads the Technology Regulatory and Policy practice in the London office and is a member of the firm’s Management Committee. Lisa divides her time between London and Brussels, and her practice embraces regulatory counsel and legislative advocacy. In this context, she…

Lisa Peets leads the Technology Regulatory and Policy practice in the London office and is a member of the firm’s Management Committee. Lisa divides her time between London and Brussels, and her practice embraces regulatory counsel and legislative advocacy. In this context, she has worked closely with leading multinationals in a number of sectors, including many of the world’s best-known technology companies.

Lisa counsels clients on a range of EU law issues, including data protection and related regimes, copyright, e-commerce and consumer protection, and the rapidly expanding universe of EU rules applicable to existing and emerging technologies. Lisa also routinely advises clients in and outside of the technology sector on trade related matters, including EU trade controls rules.

According to the latest edition of Chambers UK (2022), “Lisa is able to make an incredibly quick legal assessment whereby she perfectly distils the essential matters from the less relevant elements.” “Lisa has subject matter expertise but is also able to think like a generalist and prioritise. She brings a strategic lens to matters.”

Photo of Sam Jungyun Choi Sam Jungyun Choi

Sam Jungyun Choi is an associate in the technology regulatory group in the London office. Her practice focuses on European data protection law and new policies and legislation relating to innovative technologies such as artificial intelligence, online platforms, digital health products and autonomous…

Sam Jungyun Choi is an associate in the technology regulatory group in the London office. Her practice focuses on European data protection law and new policies and legislation relating to innovative technologies such as artificial intelligence, online platforms, digital health products and autonomous vehicles. She also advises clients on matters relating to children’s privacy and policy initiatives relating to online safety.

Sam advises leading technology, software and life sciences companies on a wide range of matters relating to data protection and cybersecurity issues. Her work in this area has involved advising global companies on compliance with European data protection legislation, such as the General Data Protection Regulation (GDPR), the UK Data Protection Act, the ePrivacy Directive, and related EU and global legislation. She also advises on a variety of policy developments in Europe, including providing strategic advice on EU and national initiatives relating to artificial intelligence, data sharing, digital health, and online platforms.