TL;DR:
- Patients facing cancer increasingly engage with AI for healthcare support.
- Dana-Farber Cancer Institute calls for ethical guidelines in patient-facing AI.
- Concerns about depersonalization and erosion of patient-caregiver relationships.
- AI applications in telehealth, remote monitoring, and health coaching.
- Ethical challenges include confidentiality risks and diminishing human oversight.
- Guiding principles emphasize human dignity, patient autonomy, equity, and justice.
- Transparency in AI-generated recommendations is crucial.
- Market implications: AI in oncology must prioritize ethics for patient trust and satisfaction.
Main AI News:
The realm of oncology is undergoing a transformative shift as artificial intelligence (AI) increasingly becomes a prominent player in the patient care landscape. Patients facing the daunting journey of cancer diagnosis and treatment now find themselves in the company of AI technologies, poised to facilitate scheduling, health monitoring, disease education, and more. In an exclusive report featured in JCO Oncology Practice, the bioethics experts at Dana-Farber Cancer Institute put forth a compelling call to action. They urge medical societies, government bodies, clinicians, and researchers to collaboratively steer the course of AI-driven healthcare, safeguarding patient autonomy and upholding human dignity as paramount values.
The potential of AI in enhancing access to cancer care, revolutionizing cancer detection, diagnosis, and treatment is undeniable. However, the authors of this groundbreaking paper emphasize that the time to act is now, lest we risk the depersonalization of patient care and the erosion of the precious bonds between patients and caregivers. While previous discussions have predominantly centered on the impact of AI in oncology from the perspective of clinicians and researchers, this paper is among the pioneers to scrutinize the ethical implications of AI technology embedded within the patient experience.
Dr. Amar Kelkar, the lead author of this paper and a distinguished stem cell transplantation physician at Dana-Farber Cancer Institute, highlights the urgency of addressing the ethical challenges posed by patient-facing AI in cancer care. “To date, there has been little formal consideration of the impact of patient interactions with AI programs that haven’t been vetted by clinicians or regulatory organizations,” says Dr. Kelkar. “We wanted to explore the ethical challenges of patient-facing AI in cancer, with a particular concern for its potential implications for human dignity.”
While oncology professionals have begun to harness the power of AI for purposes such as cancer diagnosis, tumor monitoring, treatment outcome prediction, and pattern recognition, direct patient interaction with AI has remained relatively limited. However, this landscape is poised for transformation.
This comprehensive report focuses on three key areas where patients are likely to engage with AI—telehealth, remote health monitoring, and health coaching. Telehealth, traditionally a platform for patient-clinician interactions, is set to benefit from AI in streamlining appointment scheduling, reducing wait times, and collecting patient data efficiently. Remote health monitoring may be revolutionized with AI systems capable of analyzing data reported by patients or collected through wearable devices. Furthermore, AI-driven health coaching, facilitated by natural language models mimicking human interactions, can offer personalized health advice, education, and psychosocial support.
Despite the promise of AI in these domains, the authors emphasize a range of ethical challenges that demand urgent attention. Confidentiality risks loom large in the context of telehealth and remote monitoring when patient data are entrusted to AI. Additionally, as AI-driven health coaching programs evolve to resemble human interactions, there is a looming concern about the diminishing oversight by actual humans, potentially eroding the interpersonal connections that have long defined cancer care.
The report proposes a set of guiding principles to shape the development and adoption of AI in patient-facing scenarios, underscoring the principles of human dignity, patient autonomy, equity and justice, regulatory oversight, and collaborative efforts. “No matter how sophisticated, AI cannot achieve the empathy, compassion, and cultural comprehension possible with human caregivers,” the authors assert. “Overdependence on AI could lead to impersonal care and diminished human touch, potentially eroding patient dignity and therapeutic relationships.”
To safeguard patient autonomy, the report emphasizes the need for patients to fully understand the origin and basis of AI-generated recommendations. Dr. Kelkar underscores this point, stating, “The opacity of some patient-facing AI algorithms can make it impossible to trace the ‘thought process’ that leads to a treatment recommendation. It needs to be clear whether a recommendation came from the patient’s physician or from an algorithmic model raking through a vast amount of data.”
Furthermore, justice and equity demand that AI models be trained on data representative of the diverse racial, ethnic, and socioeconomic landscape of the entire population, countering the bias often inherent in AI models trained on historical data skewed towards majority groups.
The imperative for oncology stakeholders to unite to ensure that AI technology serves as a force for promoting patient autonomy and preserving human dignity cannot be overstated. As aptly put by senior author Dr. Gregory Abel, director of the older adult hematologic malignancy program at Dana-Farber, “It is important for oncology stakeholders to work together to ensure AI technology promotes patient autonomy and dignity rather than undermining it.” This ethical voyage into the realm of patient-facing AI in oncology is not just necessary—it is an ethical mandate.
Conclusion:
The rise of patient-facing AI in oncology underscores the importance of ethical considerations. Ensuring patient autonomy, preserving human dignity, and addressing confidentiality risks are paramount. The market for AI in oncology must prioritize ethical guidelines to build trust and maintain strong patient-caregiver relationships, ultimately enhancing the quality of care and patient satisfaction.
