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Generative AI as Enabler of Culturally Competent Care-The HSB Blog 5/26/23

Our Take:

Differences in language,culture and inaccurate descriptions can cause patients to refuse help from other races (ex: black patients/white doctors, Chinese patients/English-speaking doctors) technology like generative AI may help by employing appropriate language which would help narrow the gap. Using generative AI to process natural language, developing language models and chatbots to understand and respond to patients of all backgrounds in a culturally appropriate way, generative AI can be trained on data sets containing cultural backgrounds, dialects, and linguistic nuances allowing it to understand a variety of accents and dialects. This would enable individuals from different cultural backgrounds to interact effectively with the technology. Giving patients the ability to engage with technology in a way that respects their cultural traditions and language preferences promotes a sense of dignity, respect, and empowerment. By working towards cultural inclusion, technology has the potential not only to reduce differences, but to promote understanding, empathy, and harmony in our increasingly interconnected world.

Key Takeaways:

  • African Americans and Latinos experience 30% to 40% poorer health outcomes than White Americans

  • Research shows poor care for the underserved is because of fear, lack of access to quality healthcare, distrust of doctors, and often dismissed symptoms and pains

  • One study found that black patients were significantly less likely than white patients to receive analgesics for extremity fractures in the emergency room (57% vs. 74%), despite having similar self-reports of pain

  • Each additional standard deviation improvement score that hospitals received in cultural competency, translated into an increase of 0.9% in nurse communication and 1.3% in staff responsiveness on patient satisfaction surveys

The Problem:

While culturally appropriate language is important to promote inclusiveness and reduce disparities, there are challenges and potential problems with its implementation. Because of the cultural diversity of the United States, cultural norms and practices do not ensure that everyone living in the United States will be culturally respected and vary greatly between communities and regions. Because of differences in tradition, religion, society, language, and socialization, individuals within various communities may not feel respected or secure.

With literally thousands of languages and dialects in the world, each having its own unique cultural background, dealing with linguistic diversity and ensuring culturally appropriate language can become quite a complex task. In health care this has been shown to lead to neglect or underservice in certain communities through intentional and unintentional slights.

As society continues to change, social inclusiveness cannot be overlooked as an integral component of care. Inclusiveness is not only an important but necessary element of care so that patients feel respected and valued in a system that recognizes the cultural practices and identities of different communities. Research has demonstrated that this leads to improved clinician-patient interactions, compliance, and data sharing by patients. More recently the health care system has come to recognize the impact the unique cultural needs of often overlooked groups such as people with disabilities, lesbian, gay, bisexual, and transgender (LGBT) people have on the quality and effectiveness of care as well (while not a racial or ethnic group these provide further evidence of the need for culturally competent care).

The Backdrop:

According to “Understanding Cultural Differences in the U.S.”, from the U.S.A.Hello, website cultures can differ in 18 different ways including, communication, physical contact (shaking hands, personal space), manners, political correctness, family, treatment of women & girls (men and women going to school/work together, sharing tasks), elders (multigenerational homes), marriage (traditions, views on same-sex marriage), health, education, work, time, money, tips religion, holidays, names and language. Recognizing and understanding cultural differences is important to create trust and security with patients.

Generative AI can help bridge language and cultural barriers that often prevent non-English speakers from accessing essential health services. According to Marcin Frąckiewicz, “generative AI can serve as a virtual health assistant, providing accurate and personalized health advice to users. By making health information more accessible, individuals can make better-informed decisions about their health and well-being.” Different cultural backgrounds interact effectively with technology. Similarly, speech synthesis can provide text-to-speech capabilities in a variety of languages, enabling technology to communicate with users in their preferred language. This can often be done more rapidly and more efficiently than when having to locate and find an appropriate translator.

Using generative AI can carry out multicultural expression, according to the product and service integration of multicultural expression. A variety of visual depictions, avatars, and characters of different racial, ethnic, and cultural backgrounds. Inclusion can be promoted through such technologies, allowing users to feel represented and valued. In addition, generative AI can help identify and correct potential instances of cultural insensitivity or technological bias. Moreover, since generative AI is iterative it allows for continuous improvement, ensuring that culturally appropriate language and experience are prioritized.


While still in the developmental stages, generative AI can be one tool to assist healthcare organizations in delivering culturally competent care for patients. At its most fundamental level, generative AI models can provide translation services to help overcome language barriers and help communicate between healthcare providers and patients who speak different languages. It can enhance doctor-patient interaction, improve patient satisfaction and reduce misunderstanding.

Although communications created with generative AI will likely lack nuance

and will have difficulty creating empathetic emotional connections with patients, it will be a step in the right direction. Over time we expect generative AI and other generative AI models to be able to provide up-to-date information about medical conditions, treatment guidelines, medications, and research results. By collecting and analyzing patient data through remote monitoring, facilitating virtual consultations, and providing real-time information and guidance. Moreover, technologies like generative AI can contribute to remote monitoring and telemedicine initiatives to improve access to health care services, particularly for those living in remote areas or with limited mobility.

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