Chinasa T. Okolo

It is important to study novice technology users such as CHWs in the Global South due to the critical link they provide between their communities and public health services. As technology and AI in particular shifts to playing a more important role in their work, it will be crucial to understand how XAI can be leveraged to deliver high-quality user experiences and optimal patient outcomes. I have begun this work by surveying XAI literature over the past decade to identify papers that discuss techniques of AI applied in the development, deployment, and evaluation of AI-enabled technologies in the Global South. My future work will involve developing explainable AI prototypes to understand and characterize important aspects of model decision-making for novice technology users. Work accepted to COMPASS 2022 and further work in progress.

As researchers and technology companies rush in to develop AI applications that aid the health of marginalized communities, it is critical to consider the needs and perceptions of the community health workers and other stakeholders involved in integrating these AI applications into the essential healthcare services provided to low-resource communities. For this work, we piloted a 3-month study, the first of its kind, examining CHW perceptions of AI in rural India. Drawing on data from 21 interviews, we characterize (1) CHWs’ knowledge, perceptions, and understandings of AI; and (2) the benefits and challenges that CHWs anticipate as AI applications are integrated into their workflows, including their opinions on automation of their work, possible misdiagnosis and errors, data access and surveillance issues, security and privacy challenges, and questions concerning trust. Accepted to CHI 2021 (Publication).

In healthcare, the role of artificial intelligence is continually evolving and understanding the challenges its introduction poses on relationships between healthcare providers and patients will require a regulatory and behavioural approach that can provide a guiding base for all users involved. Our work proposes a framework to set guidelines for how AI-enabled technologies should be formally introduced to patients in healthcare settings. The core principles of this framework are set into 5 parts: Acceptability, Comfortability, Informed Consent, Privacy, and Security. Preliminary work accepted to the Data4Good: Designing for Diversity and Development Workshop (AVI), expanded work under review. (Publication).