Scenario: Fixing Racial Bias in EEG Research

[CatTruxillo]

This is a discussion forum for the activities in the Inclusivity module of the Free SAS e-learning course, Responsible Innovation and Trustworthy AI.

Scenario: Fixing Racial Bias in EEG Research

Consider This: 

What is the impact of ignoring inclusivity on health and well-being?

[RichardH_CVS]

Many conditions and activities are studied with EEG. For example, trying to predict epilepsy, sickle cell, creativity. My son and I have dreadlocks. I am a scientist in public health (outcomes research). I play in both a jazz band and steel pan (drum) group. I am a long time SAS user (mostly SAS/STATS). I have had a successful Fulbright Scholarship. My interest and activities indicate that I am at least proficient in quantitative and 'creative' areas. My son plays guitar, enjoys classical music and dub step. He's planning to pursue an MD/PhD in radiation oncology. However, I am not  sure that the surface or swim cap electrodes would capture our brain activity clearly. Imagine if an AI algorithm was being used to map and score our brain activity for an important role. We might score low (if at all). Our cultural heritage would not be subsumed in the training data. Dreadlocks are not just coarse of curly hair. Dreadlocks is more like wearing a turban. While a turban (in principle) can be removed for the investigation, dreadlocks can't be taken off and put back on.

I don't know what is a fair solution. I do know asking us to cut off our dreadlocks is not an equitable solution.

[jomana-khatib]

Ignoring inclusivity in healthcare technology and research can lead to misdiagnosis, mistreatment, and unequal access to care, which directly impacts the health and well-being of underrepresented populations. In the EEG scenario, traditional electrode designs that don’t account for coarse or curly hair types result in inaccurate brain readings for individuals with such hair textures. This not only skews neuroimaging research findings but also delays or misguides clinical decision-making, potentially putting patients at greater health risk.

Furthermore, these biases reinforce systemic inequities and reduce trust in healthcare systems among marginalized groups. If people believe that medical tools and procedures are not designed with them in mind, they may be less likely to seek care or participate in medical research, thereby widening health disparities.