Course curriculum
-
1
Ethnicity, Equity, and AI
-
Abstract and Bio
-
Ethnicity, Equity, and AI
-
-
2
Data Science Against COVID-19
-
Data Science Against COVID-19
-
Abstract and Bio
-
Ethnicity, Equity, and AI
In the field of healthcare, AI can provide solutions as well as be source of bias and therefore inequity. Bias can creep in via algorithmic processes or be inherent in the underlying data. This talk will introduce the audience to challenges in AI for health equity with a particular focus on race and ethnicity data. We will explore real-world ethnicity data collected routinely in healthcare settings in the form of electronic health records. We will examine issues with completeness, correctness, and granularity of these data, implications for healthcare AI, and finally highlight opportunities towards “better data, better models, better healthcare”.
Sara Khalid, Senior Research Fellow in Health Informatics and Biomedical Data Science @ University of Oxford
Data Science Against COVID-19
In the field of healthcare, AI can provide solutions as well as be source of bias and therefore inequity. Bias can creep in via algorithmic processes or be inherent in the underlying data. This talk will introduce the audience to challenges in AI for health equity with a particular focus on race and ethnicity data. We will explore real-world ethnicity data collected routinely in healthcare settings in the form of electronic health records. We will examine issues with completeness, correctness, and granularity of these data, implications for healthcare AI, and finally highlight opportunities towards “better data, better models, better healthcare”.
Nuria Oliver, PhD, Commissioner to the President, AI Strategy and Data Science | Cofounder and Vice President | Chief Data Scientist @ Valencian Government | ELLIS | ELLIS Alicante Unit Foundation | Data-Pop Alliance