Bridging Gaps, Empowering Communities

Lucy Family Institute for Data & Society

Available on-demand

AI holds immense promise, yet Ketan Paranjape warns the “last mile” remains a formidable barrier. From rural Indiana to India, infrastructure gaps and cultural nuances challenge the scalability of digital health. Explore how we can bridge this divide by prioritizing human kinship and ethical innovation over mere algorithmic speed.

Over the past two years, the Lucy Family Institute has invited a variety of business, government, academic, and non-profit partners to campus as part of the Health Equity Data Forum. Each year, this has led to impactful research and data analysis questions. In fall 2025, the Health AI track was a part of the larger RISE AI Conference, allowing attendees to meet and collaborate with researchers, industry partners, and other stakeholders.

This year’s focal topic was Rural Healthcare; exploring the issues of first and last mile challenges of data acquisition and application to dispersed communities, and the possibilities of AI and data models to address these communities. Rural healthcare topics included the mental health, transportation, availability/location of specialists, food accessibility, and availability/accessibility of people for clinical trials. Addressing these factors can significantly change outcomes for rural populations.

By analyzing the intersection of rural health and artificial intelligence, we move from theoretical innovation to an ethical application that ensures progress serves the common good, particularly for those historically marginalized by the digital revolution.

I. The Global-Local Paradox

Dr. Kaitton Parapp, Chief Operating Officer at Optum and World Health Organization expert, challenges the “one size fits all” mentality inherent in global health scaling. He critiques the assumption of universality by comparing the Highway 31 corridor in Kokomo, Indiana, to villages 600 kilometers from Bombay. While both share geographic isolation, their “pain points” differ fundamentally. Dr. Parapp argues that strategic success requires pivoting from emergency-room-centric models to localized needs, such as tracking anemia in maternal care or monitoring post-surgical recovery in environments where dirt roads make bi-weekly hospital visits impossible.

II. Infrastructure Before Algorithms

The keynote adopts a “not yet” stance on immediate AI deployment, identifying trust and infrastructure as non-technical prerequisites for algorithmic adoption. Dr. Parapp analyzes the persistent “literacy gap,” noting that while rural populations may be digitally literate (using TikTok for social engagement), they often remain medically illiterate regarding how to query a chatbot without falling victim to “hallucinations.” Furthermore, connectivity remains volatile; 4G often degrades to “no G” in the field. To address this, we must prioritize “light operating systems”—like the Rural Health Operating System (RHOS)—and low-memory software capable of running on legacy devices, rather than assuming the availability of high-bandwidth environments.

III. AI as Augmentation, Not Replacement

A central theme of the panel involves synthesizing technology with the “human touch.” Dr. Emily Hoe, a Quantitative Psychologist, differentiates between objective social isolation and the subjective, painful experience of loneliness. The panel advocates for the “PACE” model (Program of All-inclusive Care for the Elderly), examining the tension between traditional “bricks and mortar” centers and “digital projections” into the home.

Strategic augmentation is illustrated by the Taiwanese Fisherman cardiology case: technology tracked the recovery of fishermen who, defying medical advice for rest, returned to sea immediately after heart surgery. By utilizing Holter monitors and satellite phones, the system tracked “digital biomarkers” where human supervision was impossible. However, the panel warns against over-automation; a meal-delivery drone must not replace the only human interaction a senior has that week. The goal is to reduce “time toxicity”—the administrative burden on caregivers—freeing them to return to the bedside.

IV. The Ethical Imperative (RISE)

The “Responsible, Inclusive, Safe, and Ethical” (RISE) framework demands that community members be “compensated investigators from day zero.” Dr. Hoe emphasizes the ethos of “nothing about us without us” to prevent exacerbating disparities, such as the Lancet-documented link between untreated hearing loss and dementia. Bakata Hayes of Blue Cross Blue Shield of Minnesota illustrates “Inclusion” through the Ghanaian mobile clinics (ODM), which built trust during the COVID-19 pandemic and now provide mobile mammography across sixteen rural counties. This proves that the community already possesses the answers; the technologist’s role is to provide the resources and autonomy to implement them.

These strategic insights reveal that the power of AI lies in its ability to act as a catalyst for “kinship health,” reinforcing the social fabric of rural communities.

Solving the “Last Mile” Through Local Specificity: Success in rural health is determined not by the complexity of the AI, but by its alignment with local pain points like maternal anemia or post-surgical monitoring. Strategies must prioritize the “last inch” of delivery over broad, unrefined scale.
Infrastructure as a Non-Negotiable Prerequisite: Advanced LLMs cannot function in power-starved environments. Innovation must focus on “light operating systems” (RHOS) and solar-powered hardware that can bridge the gap between 2G connectivity and modern diagnostic needs.
The Ethical Mandate of “Nothing About Us Without Us”: Building trust is a strategic investment, not a technical feature. Communities must be involved as stakeholders and compensated investigators from the project’s inception to ensure cultural validity and long-term adoption.
Augmenting Caregivers to Reduce “Time Toxicity”: AI’s primary value in senior care is the automation of administrative tasks. By reducing the time spent on documentation and eligibility forms, technology restores the caregiver to the bedside, addressing the root of patient loneliness.
Leveraging Kinship Health and Social Capital: Health outcomes are intrinsically linked to “kinship health”—the web of mutual aid within a community. Future interventions should use technology to enhance these existing social ties, such as coordinating church volunteers or mobile clinics like the Ghanaian ODM initiative.

“Rural Indiana versus rural India are two different worlds… one size will not fit all.” — Ketan Paranjape

“We’re not talking about replacing human beings on the issue of loneliness and social connection; we’re talking about augmenting them.” — Erwin Tan

“One of the core beliefs we have is that community has the answers.” — Bukata Hayes

“We think that AI can also help us by helping caregivers spend more time at the bedside with the older adult rather than documenting all of the time.” — Shelley Kendrick

“There’s a sort of ethos of ‘nothing about us without us’ that has to be—we have to start from day zero.” — Dr. Emily Ho