Hello everyone, this is my first post in a while as school got off to a busy start, but I will be posting more frequently in the future, so stay tuned for more anthropology articles.
I recently participated in a guided research program where I wrote my first research paper. Choosing a topic was slightly hard, but I eventually settled on medical anthropology. I had the most difficult task to deal with next: finding a research question. After looking into many different areas in which medical anthropology could be applied, my mentor and I looked into the development of artificial intelligence (AI) healthcare models and applications of anthropology to them.
The concept of healthcare AI models is a relatively new one, as the technology needed to produce something effective enough to be worth developing has only just recently become available. Though experimental research could only be performed on existing prototype models (the soonest beta releases are years away), I wanted to look into issues that could arise in a fully functional healthcare model, specifically in regards to cultural differences. These theoretical issues would occur (most likely) primarily by way of cross-cultural differences in semantics or communication style.
In terms of methodology, I interviewed six participants: a man and a woman each from Walnut Creek, USA; Istanbul, Turkiye; and Develi, Turkiye. The interviews were conducted as series of questions over international encrypted messaging app WhatsApp.
Image credit: National Cancer Institute
Semantic Differences
Fortunately, there exists some research that looks into cultural differences in semantics of illness. Acclaimed Harvard professor Byron J Good’s The Heart of What’s the Matter: Semantics of Illness in Iran examines the Persian folk illness “heart distress” and its perceived causes in Iranian culture. The paper draws on observed semantic networks to trace how people describe their illness, and the result was that Iranians understand their illnesses very differently than Americans understand theirs. While outdated (it was published in 1977), Good’s study provided a strong theoretical basis for me to do more research. In a theoretical healthcare AI model, misdiagnoses could stem from semantic differences, resulting in an unintentionally biased model. This potential harm, should it become an issue, would be classified as structural violence, a form of social harm that prevents groups of people from having their essential needs met (Read more in the paper linked below).
The first two interview questions were oriented towards semantic differences. The first asked participants to describe symptoms of a common cold to a doctor, and the second asked them to describe symptoms to an AI model. In theory, these two questions would reveal differences across cultures in both how patients interacted with physicians and how they interacted with AI. Provided symptoms were compared in a table (included below), and the style of descriptions (symptom vs biomedical, list vs na
Cultural Comfort Differences
The other two questions were less important to the study; these dealt with contextual differences in communication across cultures. The participants were asked to honestly give any sensitive or embarrassing symptoms that they would not feel comfortable sharing with an in-person physician. They were then asked if they would be more comfortable sharing these symptoms with an AI doctor. The purpose of these questions was to evaluate two things. First, if patients felt more comfortable sharing symptoms with a doctor and, consequently, omitted certain symptoms from a report to an AI model, misdiagnosis could occur from a skewed description. Second, if patients felt more comfortable sharing details with an AI model, they would be more likely to share full details and receive an accurate diagnosis as a result.
Results
It was hypothesized based on existing theory and assumptions that there would be a good deal of cultural differences in semantics of illness and comfortability interacting with an AI model. The results, however, showed minimal differences across the three cultures (see tables in the paper). There were little to no differences within the country of Turkey, and Turks tended to describe their symptoms and comfortability with in relatively similar ways. The only major difference within Turkey was that rural Turks tended to describe their illness in a symptomatic hybrid difference, while urban Turks tended to describe their illnesses in a list fashion. American and Turkish responses displayed similar levels of variation, as the only major difference between the countries was the symptoms of the common flu that they provided (more detail in the paper).
There are many potential explanations for the high level of similarity between cultures, but experimental research is needed to verify any one of these explanations. A possible and likely reason that the results of my study were so different from Dr. Good’s is that globalization has made the world a much smaller place since 1977. With the technological revolution putting internet access into the hands of almost all people, information can be spread much more easily, and as a result, cultural mannerisms and ways of interacting bleed into each other more than they used to.
This study was non-experimental and hypothesis-generating, so no conclusions can be drawn from the results. It does, however, raise interesting questions about how important cultural differences really are to the development of healthcare AI models.
I would like to thank the team at Lumiere education for providing excellent services and making the experience of writing a paper much easier than it would have been if I had attempted to do it myself. I highly recommend them to anyone who needs guidance in writing and publishing their first paper.
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