{"id":556,"date":"2026-07-13T16:29:26","date_gmt":"2026-07-13T15:29:26","guid":{"rendered":"https:\/\/schools.stem.open.ac.uk\/knowledge-media-institute\/?page_id=556"},"modified":"2026-07-13T16:29:26","modified_gmt":"2026-07-13T15:29:26","slug":"enhancing-fairness-in-machine-learning-identifying-and-mitigating-bias-with-a-focus-on-gender-bias-in-finance","status":"publish","type":"page","link":"https:\/\/schools.stem.open.ac.uk\/knowledge-media-institute\/enhancing-fairness-in-machine-learning-identifying-and-mitigating-bias-with-a-focus-on-gender-bias-in-finance\/","title":{"rendered":"Enhancing Fairness in Machine Learning: Identifying and Mitigating Bias with a Focus on Gender Bias in Finance"},"content":{"rendered":"\n
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\"Dr.<\/figure>\n\n\n\n

Dr. \u00c1ngel Pav\u00f3n P\u00e9rez – KMi, The Open University
This event took place on Tuesday 14 October 2025 at 11:30<\/small><\/p>\n<\/div>\n\n\n\n


Machine Learning systems increasingly shape critical decisions\u2014who gets a loan, who receives healthcare support, who\u2019s flagged for risk. However, the data behind these systems often reflects historical and societal biases, leading to unfair and potentially harmful outcomes, particularly for marginalised groups. In this talk, I\u2019ll explore three core challenges in addressing bias in machine learning, drawing from my thesis research in the financial domain where gender bias is particularly embedded:

1. Hidden bias in the data \u2013 Sensitive attributes are often not explicitly included in datasets, but bias creeps in through proxy variables. Detecting and mitigating these hidden proxies is a major challenge, requiring methods that go beyond standard fairness checks.
2. Fairness without sensitive attributes \u2013 In many real-world scenarios, we don\u2019t have access to information like gender or race due to privacy or legal concerns. This makes it difficult to audit or mitigate bias, raising the question: how do we build fair systems when we can’t measure unfairness directly?
3. Conflicting fairness definitions \u2013 Fairness isn\u2019t one-size-fits-all. There are multiple, sometimes incompatible definitions of fairness, and addressing one can worsen another.

Understanding how to navigate and balance these trade-offs remains an open and complex problem. I\u2019ll share how my work tackles each of these challenges\u2014through proxy detection, knowledge transfer methods, and a large-scale study of bias mitigation strategies. The aim is to offer practical tools and insights for anyone working toward more responsible, equitable AI systems.

Apologies – last minute network issues have prevented Live streaming of this event.<\/p>\n\n\n\n


Watch the webcast replay >><\/a><\/p>\n\n\n\n

View all past events<\/a><\/p>\n\n\n\n

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Maven of the Month<\/a><\/h3>\n\n\n\n

We are also inviting top experts in AI and Knowledge Technologies to discuss major socio-technological topics with an audience that comprises both members of the Knowledge Media Institute, as well as the wider staff at The Open University. Differently from our seminar series, these events follow a Q&A format.<\/p>\n<\/div>\n<\/div>\n","protected":false},"excerpt":{"rendered":"

Dr. \u00c1ngel Pav\u00f3n P\u00e9rez – KMi, The Open UniversityThis event took place on Tuesday 14 October 2025 at 11:30 Machine Learning systems increasingly shape critical decisions\u2014who gets a loan, who receives healthcare support, who\u2019s flagged for risk. However, the data behind these systems often reflects historical and societal biases, leading to unfair and potentially harmful […]<\/p>\n","protected":false},"author":13,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"unity_related_person":[],"unity_sdg":[],"unity_research_theme":[],"unity_strategic_priority":[],"unity_enabler":[],"unity_general_category":[],"unity_stem_unit":[],"unity_related_project":[],"unity_related_archived_project":[],"unity_related_event":[],"class_list":["post-556","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/schools.stem.open.ac.uk\/knowledge-media-institute\/wp-json\/wp\/v2\/pages\/556","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/schools.stem.open.ac.uk\/knowledge-media-institute\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/schools.stem.open.ac.uk\/knowledge-media-institute\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/schools.stem.open.ac.uk\/knowledge-media-institute\/wp-json\/wp\/v2\/users\/13"}],"replies":[{"embeddable":true,"href":"https:\/\/schools.stem.open.ac.uk\/knowledge-media-institute\/wp-json\/wp\/v2\/comments?post=556"}],"version-history":[{"count":1,"href":"https:\/\/schools.stem.open.ac.uk\/knowledge-media-institute\/wp-json\/wp\/v2\/pages\/556\/revisions"}],"predecessor-version":[{"id":557,"href":"https:\/\/schools.stem.open.ac.uk\/knowledge-media-institute\/wp-json\/wp\/v2\/pages\/556\/revisions\/557"}],"wp:attachment":[{"href":"https:\/\/schools.stem.open.ac.uk\/knowledge-media-institute\/wp-json\/wp\/v2\/media?parent=556"}],"wp:term":[{"taxonomy":"unity_related_person","embeddable":true,"href":"https:\/\/schools.stem.open.ac.uk\/knowledge-media-institute\/wp-json\/wp\/v2\/unity_related_person?post=556"},{"taxonomy":"unity_sdg","embeddable":true,"href":"https:\/\/schools.stem.open.ac.uk\/knowledge-media-institute\/wp-json\/wp\/v2\/unity_sdg?post=556"},{"taxonomy":"unity_research_theme","embeddable":true,"href":"https:\/\/schools.stem.open.ac.uk\/knowledge-media-institute\/wp-json\/wp\/v2\/unity_research_theme?post=556"},{"taxonomy":"unity_strategic_priority","embeddable":true,"href":"https:\/\/schools.stem.open.ac.uk\/knowledge-media-institute\/wp-json\/wp\/v2\/unity_strategic_priority?post=556"},{"taxonomy":"unity_enabler","embeddable":true,"href":"https:\/\/schools.stem.open.ac.uk\/knowledge-media-institute\/wp-json\/wp\/v2\/unity_enabler?post=556"},{"taxonomy":"unity_general_category","embeddable":true,"href":"https:\/\/schools.stem.open.ac.uk\/knowledge-media-institute\/wp-json\/wp\/v2\/unity_general_category?post=556"},{"taxonomy":"unity_stem_unit","embeddable":true,"href":"https:\/\/schools.stem.open.ac.uk\/knowledge-media-institute\/wp-json\/wp\/v2\/unity_stem_unit?post=556"},{"taxonomy":"unity_related_project","embeddable":true,"href":"https:\/\/schools.stem.open.ac.uk\/knowledge-media-institute\/wp-json\/wp\/v2\/unity_related_project?post=556"},{"taxonomy":"unity_related_archived_project","embeddable":true,"href":"https:\/\/schools.stem.open.ac.uk\/knowledge-media-institute\/wp-json\/wp\/v2\/unity_related_archived_project?post=556"},{"taxonomy":"unity_related_event","embeddable":true,"href":"https:\/\/schools.stem.open.ac.uk\/knowledge-media-institute\/wp-json\/wp\/v2\/unity_related_event?post=556"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}