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Generative artificial intelligence is altering the methods through which individuals compose, read, articulate, contemplate, empathize, and respond within and across various languages and cultures. In the healthcare sector, breakdowns in communication between patients and healthcare providers can exacerbate patient outcomes and hinder advancements in treatment and care. The Language/AI Incubator, made feasible through financing from the MIT Human Insight Collaborative (MITHIC), presents a possible solution to these issues.

The initiative envisions a research community anchored in the humanities that will encourage interdisciplinary cooperation across MIT to enhance comprehension of generative AI’s influence on multilingual and multicultural communication. The project’s emphasis on healthcare and communication aims to create connections across varied socioeconomic, cultural, and linguistic landscapes.

The incubator is jointly led by Leo Celi, a medical doctor and the research director and senior research scientist at the Institute for Medical Engineering and Science (IMES), and Per Urlaub, a practice professor in German and second language studies and the director of MIT’s Global Languages program.

“The cornerstone of healthcare delivery is the understanding of health and illness,” Celi states. “We’re witnessing poor outcomes despite significant investments because our knowledge framework is flawed.”

A serendipitous partnership

Urlaub and Celi first crossed paths at a MITHIC launch gathering. Discussions throughout the event uncovered a mutual interest in enhancing medical communication and practice through AI.

“We’re aiming to integrate data science into healthcare provision,” Celi mentions. “We’ve been enlisting social scientists [at IMES] to help propel our initiatives, as the knowledge we generate is not neutral.”

The team believes that language serves as a non-neutral facilitator in healthcare delivery, acting as either an asset or an obstacle to effective treatment. “Later, after we met, I became part of one of his working groups focused on metaphors for pain: the terminology we utilize to describe it and its evaluation,” Urlaub elaborates. “One inquiry we explored was how effective communication can happen between physicians and patients.”

They contend that technology influences casual communication, and its effects vary based on both users and creators. As AI and large language models (LLMs) gain influence and prominence, their applications are expanding to encompass areas like healthcare and wellness.

Rodrigo Gameiro, a physician and researcher at MIT’s Laboratory for Computational Physiology, is another participant in the program. He emphasizes that the laboratory’s work prioritizes responsible AI development and implementation. Designing systems that effectively utilize AI, especially in considering challenges related to communication across linguistic and cultural divides in healthcare, necessitates a nuanced approach.

“When we create AI systems that engage with human language, we’re not simply teaching machines how to process words; we’re instructing them to traverse the intricate web of significance embedded in language,” Gameiro states.

The intricacies of language can affect treatment and patient care. “Pain can only be conveyed through metaphor,” Urlaub continues, “yet metaphors don’t always align, linguistically and culturally.” Smileys and one-to-10 scales – pain assessment tools that English-speaking medical professionals often use to evaluate their patients – may not translate effectively across racial, ethnic, cultural, and linguistic borders.

“Science must embody compassion”

LLMs may enable researchers to enhance healthcare, although there are systemic and educational challenges that need addressing. Science can often emphasize results to the detriment of the individuals it aims to assist, Celi suggests. “Science must embody compassion,” he asserts. “Evaluating students’ effectiveness solely by counting the quantity of papers they publish or patents they secure misses the essence.”

The essence, Urlaub notes, is to investigate thoroughly while simultaneously recognizing what we do not know, referencing what philosophers term Epistemic Humility. The investigators argue that knowledge is tentative and perpetually incomplete. Deeply held convictions may require adjustment in light of new discoveries.

“No one’s cognitive framework of the world is exhaustive,” Celi states. “It is essential to cultivate an environment in which individuals are at ease acknowledging their biases.”

“How can we communicate concerns between language educators and others engaged in AI?” Urlaub questions. “How do we pinpoint and explore the relationship between medical professionals and language educators interested in AI’s capabilities to bridge the communication gaps between doctors and patients?”

Language, in Gameiro’s view, is more than a mere instrument for communication. “It manifests culture, identity, and power dynamics,” he asserts. In scenarios where a patient may feel uneasy about articulating pain or discomfort due to the physician’s authority or due to cultural expectations to yield to perceived authority figures, miscommunications can pose significant risks.

Transforming the dialogue

AI’s proficiency with language can assist medical professionals in navigating these complexities more adeptly, supplying digital frameworks that provide valuable cultural and linguistic contexts enabling patients and practitioners to rely on data-driven, research-backed tools to enhance communication. Institutions must reevaluate how they educate medical professionals and involve the communities they serve in the dialogue, the team advises.

“We must question what we genuinely desire,” Celi mentions. “Why are we measuring what we measure?” The biases we bring into these interactions – doctors, patients, their families, and their communities – present challenges to enhanced care, Urlaub and Gameiro argue.

“We aim to connect individuals who think differently and ensure AI serves everyone,” Gameiro adds. “Technology lacking purpose results in widespread exclusion.”

“Collaborations like this can facilitate profound processing and generate better ideas,” Urlaub remarks.

Establishing environments where concepts concerning AI and healthcare can conceivably translate into actions is a crucial aspect of the project. The Language/AI Incubator conducted its inaugural colloquium at MIT in May, led by Mena Ramos, a physician and co-founder and CEO of the Global Ultrasound Institute.

The colloquium also included presentations by Celi, alongside Alfred Spector, a visiting scholar in MIT’s Department of Electrical Engineering and Computer Science, and Douglas Jones, a senior staff member in the MIT Lincoln Laboratory’s Human Language Technology Group. A second Language/AI Incubator colloquium is scheduled for August.

Greater harmony between the social sciences and hard sciences could significantly enhance the potential for developing feasible solutions and minimizing biases. Allowing alterations in how patients and doctors perceive their relationship, while granting each shared ownership of the interaction, can lead to improved outcomes. Facilitating these discussions with AI may accelerate the integration of these viewpoints.

“Community advocates should be included in these discussions,” Celi emphasizes.

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says, “AI and statistical modeling cannot gather all the information necessary to support all individuals who require it.”

Community requirements and enhanced educational prospects and practices should consistently align with interdisciplinary methods for knowledge acquisition and dissemination. The perspectives people hold are confined by their interpretations and various influences. “Whose language are we emulating?” Gameiro poses regarding the development of LLMs. “Which dialects are being integrated or disregarded?” Since significance and purpose can vary among those contexts, it’s crucial to keep these considerations in mind when creating AI tools.

“AI presents an opportunity to redefine the guidelines”

Although the collaboration holds considerable promise, there are substantial obstacles to navigate, such as developing and expanding the technological solutions to enhance communication between patients and providers using AI, creating chances for collaboration with marginalized and underserved populations, and reevaluating and overhauling patient care.

However, the team remains undeterred.

Celi perceives chances to bridge the growing divide between individuals and practitioners while tackling deficiencies in healthcare. “Our goal is to reconnect the thread that has been severed between society and science,” he states. “We can empower researchers and the community to explore the world collaboratively while also recognizing the limitations that arise from navigating their biases.”

Gameiro passionately champions AI’s potential to revolutionize our understanding of medicine. “As a medical professional, I don’t think I’m exaggerating when I assert that AI presents us with the opportunity to redefine the parameters of what medicine can achieve and who we can assist,” he expresses.

“Education transforms individuals from mere objects into engaged subjects,” Urlaub contends, illustrating the distinction between indifferent observers and proactive participants in the new care paradigm he envisions. “We must deepen our comprehension of technology’s influence on the boundaries between these states of existence.”

Celi, Gameiro, and Urlaub advocate for MITHIC-like environments throughout healthcare—spaces where innovation and collaboration can thrive without the arbitrary standards institutions typically apply to measure achievement.

“AI will revolutionize all these fields,” Urlaub asserts. “MITHIC is a comprehensive framework that enables us to embrace uncertainty with adaptability.”

“We aim to harness our influence to foster a community among diverse audiences while acknowledging that we lack all the solutions,” Celi remarks. “If we stumble, it will be due to our failure to envision a sufficiently ambitious reimagined world.”


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