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Integrating ethics and governance into the design of artificial intelligence tools for health. Case study: Cervical cancer screening

Offered by OpenWHO
Integrating ethics and governance into the design of artificial intelligence tools for health. Case study: Cervical cancer screening

This course builds upon the WHO guidance and adapted introductory online course Ethics and Governance of Artificial Intelligence for Health, aiming to guide programmers, designers, data scientists and principal investigators in integrating ethical considerations and effective governance frameworks throughout the full artificial intelligence (AI) lifecycle. The course follows a case-based approach focusing on a use case that explores enhancing access to cervical cancer screening for undocumented migrant women using an AI tool. Modules cover ethical considerations from data collection to the deployment and maintenance of the AI tool. The course emphasises the significance of informed consent, explores strategies to implement risk-based approaches, and delves into the notions of autonomy and accountability. Through interactive learning, participants gain practical insights into responsible AI design, development, deployment, and maintenance, ensuring the right balance between innovation and healthcare benefits.

Photo credit: Getty Images / miriam-doerr & WHO / Blink Media - Etinosa Yvonne

Self-paced
Language: English
English
Health topic

Course information

Overview

Artificial intelligence (AI) has enormous potential for strengthening the delivery of healthcare and medicine and helping countries achieve universal health coverage. For AI to have a beneficial impact on public health and medicine, considerations of ethics and human rights must guide decisions made in all phases of the design, development, deployment, and maintenance of AI tools for health. New approaches to software engineering arising in the past decade have moved beyond an appeal to abstract moral values, and improvements in design methods are not merely upgraded programming techniques. Methods have been developed to support the effective, systematic, and transparent integration of ethical values in tool design.

This is a follow-on course to the WHO introductory online course Ethics and governance of artificial intelligence for health, which builds upon the guidance published by WHO in 2021 under the same name.

This course aims to (a) trace steps that should be taken to ensure that AI tools designed, developed and tested are used for the benefit of patients and providers when implemented, (b) facilitate learning through a case-based approach to elicit participants to make, support and defend value-based decisions in all phases of the AI lifecycle and (c) ensure that participants are aware of the broader ethical obligations that must be satisfied by other individuals and entities that participate in the AI tool lifecycle.

This new curriculum offers the flexibility of being pursued independently or in conjunction with the introductory online learning already available. For a comprehensive and enriching educational journey, we recommend completing the introductory course before enrolling in this one.

Throughout this course, we will present a case study that focuses on demonstrating how an AI tool has the potential to increase access to cervical cancer screening for undocumented migrant women facing limited access to care in the fictional high-income country Profectus, as well as for women across other high or middle- to low- income countries and areas with similar limitations. By adopting a case-based methodology, we will systematically explore ethical considerations and emphasise challenges and ways to address them.

Course Duration

The course will take approximately 2.5 hours to complete.

Certificates

A Confirmation of Participation certificate is offered at the end of the course.

A Record of Achievement certificate will also be available to participants who score at least 80% in the final assessment.

Participants who receive a Record of Achievement can also download an Open Badge for this course. Click here to learn how.


What you'll learn

  • Identify and describe the ethical challenges and risks that can materialise during the AI lifecycle.
  • Assess the ethical challenges and risks by raising relevant issues or questions throughout the decision-making process in all phases of the AI lifecycle.
  • Mitigate ethical challenges and risks by making informed decisions while integrating ethical, medical, epistemic, societal, and political considerations and values.

Who this course is for

  • The target audience for this course comprises individuals involved in data creation, data acquisition, model development, model evaluation, and model deployment of AI tools for health applications, whether they work in public, private or not-for-profit sectors.
  • It is expected to be of interest to (a) full stack developers, (b) software engineers, (c) data scientists, (d) front and back-end specialists, and (e) principal investigators and/or site investigators, along with healthcare professionals who engage in the design development, deployment, and implementation of AI tools.

Course contents

  • Course Introduction:

    Welcome to this course on Integrating Ethics and Governance into the Design of Artificial Intelligence Tools for Health. Case Study: Cervical Cancer Screening.
  • Module 1: Introduction to the Case Study and Associated General Considerations:

    In this module, we will present a case study using a fictional country as an example, in which we will illustrate how an AI tool can enhance cervical cancer screening accessibility for undocumented women while addressing key general considerations.
  • Module 2: Before Designing an AI Tool:

    In this module, we will examine ethical considerations surrounding the data used in algorithm training and strategies for preserving human rights in AI tool design using a case study as a focal point guided by the ethical and practical guidance developed.
  • Module 3: Developing an AI Tool:

    In this module, we will delve into the principle of autonomy, stress the importance of obtaining informed consent from data subjects, and examine strategies for integrating a risk-based approach into AI tool development.
  • Module 4: Deploying and Maintaining an AI Tool:

    In this module, we will explore the principle of accountability in AI tool development and introduce refined ethical and practical guidance through our case study.
  • Course Assessment

  • Course Credits:

    This online course is a collaboration between the WHO Department of Digital Health and Innovation (DHI) AI team, Strategy and Governance unit, and the Department of Research for Health (RFH), Health Ethics and Governance unit. The course development was coordinated by Denise Schalet (DHI) and Rohit Malpani (RFH), under the guidance of Andreas Alois Reis (RFH), Sameer Pujari and Ursula (Yu) Zhao (DHI), with support from (in alphabetical order) Shada AlSalamah (DHI), Ana Mafalda Dancante (WHO Learning and Capacity Development (LCD)), Jose Diaz Mendoza, Kanika Kalra (DHI), Corentin Piroux and Heini Utunen (LCD). Additional substantial technical inputs were received from Maribel Almonte Pacheco (WHO Cervical Cancer Elimination Initiative, NCD Department). The course curriculum and learning materials were developed by the research team at the Institute of Biomedical Ethics and History of Medicine, University of Zurich, Switzerland (a WHO Collaborating Centre for Bioethics), under the guidance of the project leads, Nikola Biller-Andorno and Julian W. März. Fayez Abdulrazeq and Jan Niklas Schwarz served as research associates. Fayez Abdulrazeq developed the case study and the ethical guidance and acted as the lead writer. All team members participated in reviewing and finalising the course contents. The course learning content was reviewed by the following external experts (in alphabetical order): Andrea Ferrario, Davy van de Sande, Emmanuel Awuni Kolog, Finale Doshi-Velez, Gennady Roshchupkin, Giorgia Pozzi, Jeroen van den Hoven, Jerome Amir Singh, Juan Manuel Duran, Karin Bogdanova, Kingsley Ofosu-Ampong, Leong Tze Yun, Manuel Schneider, Roli Mathur, Samantha Copeland, and Simão Campos.

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Certificate Requirements

  • Gain a Record of Achievement by earning at least 80% of the maximum number of points from all graded assignments.
  • Gain a Confirmation of Participation by completing at least 80% of the course material.
  • Gain an Open Badge by completing the course.