The University of Glasgow Tackles Gender Bias in Healthcare artificial intelligence: A Pioneering Framework for Unbiased ai Models
The University of Glasgow, a prestigious Scottish institution known for its significant contributions to scientific research and innovation, is set to address the issue of gender bias in healthcare artificial intelligence (ai) over the next 18 months. This groundbreaking project will focus on rectifying gender-related discrepancies in ai systems used to assess data collected by remote monitoring technologies (RMTs).
Led by Dr. Nour Ghadban, the principal investigator, this research initiative will involve collecting data from 60 study volunteers (30 males and 30 females) using radar sensors. By training separate ai models on male and female data, the team aims to identify any biases embedded in the ai functions, allowing for subsequent adjustments and improvements.
The potential impact of this research extends beyond just healthcare ai development; integrating new sensors with ai can significantly enhance patient monitoring, leading to more accurate diagnoses and personalized care. However, it’s crucial that these innovations are free from biases related to race, class, and, notably, gender.
Funding and ai-supported sensing technology developments:
The Women and Science Chair at Université Paris Dauphine-PSL generously supports this research. Recently, there have been significant strides in ai-supported sensing technology, and the University of Glasgow is at the forefront of institutions developing cutting-edge sensors to monitor heart and lung rhythms without wearable technology or video cameras.
The £5.5 million Healthcare QUEST system at the University of Glasgow exemplifies its commitment to advancing healthcare technology. This remote monitoring system offers personalized advice and alerts, suggesting lifestyle improvements and rehabilitation programs for patients recovering from illness at home. With the potential to improve independence for older individuals and provide valuable insights into patients’ well-being in hospital wards, Healthcare QUEST represents a promising leap forward in healthcare technology.
Addressing historical concerns: Mitigating gender bias in ai systems:
Growing concerns about gender bias in ai systems within the healthcare landscape have become increasingly apparent. A notable example emerged in 2019 when a chatbot employed by the remote NHS GP at Hand displayed disparate diagnoses for identical symptoms between male and female patients. Men were warned of potential heart attacks, while women were advised they might be experiencing depression or panic attacks. This instance underscores the need for extensive efforts to eliminate biases that could impact healthcare outcomes.
The University of Glasgow’s commitment to eliminating gender bias in healthcare ai holds significant implications for the future. As ai plays a vital role in patient monitoring and diagnosis, it is essential that unbiased decision-making tools are employed to ensure accurate diagnoses and optimal patient care. The gender-specific ai model training approach adopted by the university sets a precedent for meticulous scrutiny and adjustment, serving as an invaluable example for other institutions navigating the complex realm of ai in healthcare.
In conclusion, the University of Glasgow’s initiative represents a bold step towards a future where ai in healthcare is devoid of gender bias. By investing in meticulous data collection, analysis, and model training, the university is setting the stage for a revolution in healthcare technology that could significantly impact patient outcomes while fostering a more inclusive and equitable healthcare landscape.
