# Envisioning Possibilities and Challenges of AI for Personalized Cancer Care

arXiv: https://arxiv.org/abs/2408.10108 · HTML: https://mlsanity.com/paper/2408.10108/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 4 of its 53 references that are in the map.
- First posted on arXiv 19 Aug 2024.

## Builds on (most cited first, 4 of 4)

- [Power to the People? Opportunities and Challenges for Participatory AI](https://mlsanity.com/paper/2209.07572/) (2022)
- [The Participatory Turn in AI Design: Theoretical Foundations and the Current State of Practice](https://mlsanity.com/paper/2310.00907/) (2023)
- [Reconfiguring Participatory Design to Resist AI Realism](https://mlsanity.com/paper/2406.03245/) (2024)
- ["It's Sink or Swim'': Exploring Patients' Challenges and Tool Needs for Self-Management of Postoperative Acute Pain](https://mlsanity.com/paper/2401.14972/) (2024)

## Built on by (most cited first, 1 of 1)

- [Balancing Efficiency and Empathy: Healthcare Providers' Perspectives on AI-Supported Workflows for Serious Illness Conversations in the Emergency Department](https://mlsanity.com/paper/2506.00241/) (2025)

## Abstract (arXiv)

The use of Artificial Intelligence (AI) in healthcare, including in caring for cancer survivors, has gained significant interest. However, gaps remain in our understanding of how such AI systems can provide care, especially for ethnic and racial minority groups who continue to face care disparities. Through interviews with six cancer survivors, we identify critical gaps in current healthcare systems such as a lack of personalized care and insufficient cultural and linguistic accommodation. AI, when applied to care, was seen as a way to address these issues by enabling real-time, culturally aligned, and linguistically appropriate interactions. We also uncovered concerns about the implications of AI-driven personalization, such as data privacy, loss of human touch in caregiving, and the risk of echo chambers that limit exposure to diverse information. We conclude by discussing the trade-offs between AI-enhanced personalization and the need for structural changes in healthcare that go beyond technological solutions, leading us to argue that we should begin by asking, ``Why personalization?''