Blog

AI is helping healthcare organisations determine care management programs and treatment plans – who gets what care – but these models and algorithms can be biased and introduce discrimination in the allocation or denial of care.

This guest panel series examines the use of AI in assisting healthcare, with a particular focus on automating tasks, communicating diagnoses and allocating resources. It examines the sources of bias in AI integrated systems and what we can do to eliminate it.

The double-edged sword of AI with bias; on the one hand it could treat every patient objectively and reduce bias, and on the other could impact certain patient populations adversely by using non-representative data. This video examines the potential of AI in reducing biases within medical diagnosis, by using AI technologies to understand how diseases […]

The advent of AI promises to revolutionise the way we think about medicine and healthcare, but who do we hold accountable when automated procedures go awry? In this talk, Varoon focuses on the lack of affordable medicines within healthcare and the concerns over racial bias being brought into the healthcare system.

Using the example of machine learning in medicine as an example, Rachel Thomas examines examples of racial bias within the AI technologies driving modern-day medicines and treatments. Rachel Thomas argues that whilst the diversity of your data set, and performance of your model across different demographic groups is important, this is only a narrow slice […]

Talk by Rachel Thomas on the prevalence of bias within AI-based technology used in medicine. AI has the potential to remove human biases in the healthcare system, however its integration within medicine could also amplify the existing biases.

A short video examining the lack of inclusion within clinical biomedical research, and the consequence this has on the effectiveness of the treatments and medicines for non-white patients. Lack of research on minority patients means that we do not understand the racial differences in drug response, and so approved medical treatments are excluding a huge […]

This video is an in depth panel discussion of the issues uncovered in the ‘Unmasking Facial Recognition’ report from WebRootsDemocracy. This report found that facial recognition technology use is likely to exacerbate racist outcomes in policing and revealed that London’s Metropolitan Police failed to carry out an Equality Impact Assessment before trialling the technology at […]

In 2018, Amazon’s use of AI for hiring was discovered to favour male job candidates, because its algorithms had been trained on 10 years’ worth of internal data that heavily skewed male. The algorithm was trained, in effect, to believe that male candidates were better than female candidates.

This video argues that hiring is largely analogue and broken. This leads to major problems such as inefficiency, ineffectiveness (50% of first-year hires fail), poor candidate experience, and lack of diversity. The hiring process is plagued by gender bias, age bias, socioeconomic bias, and racial bias. Pymetrics intentionally audits algorithms to weed out unconscious human […]

The Misinformation Edition of the Glass Room is an online version of a physical exhibition that explores different types of misinformation, teaches people how to recognise it and combat its spread.

A video overview of a report advocating for the use of edtech, or education technology, which includes many AI solutions, in order to close the “Opportunity Gap” between marginalised and “mainstream” pupils.