Responsible Digital Health Speaker Series #4 - Responsible AI for health
The digital revolution continues to change the face of health systems the world over. At the 71st World Health Assembly (WHA), the World Health Organisation (WHO) recognised the full potential of the digital health revolution to enhance health service capacities and accelerate progress towards achieving health and wellbeing related Sustainable Development Goals (SDGs), especially SDG 3. They also recognised that the responsible and appropriate use of digital health solutions remains a great challenge. The potential for positive impacts through the application of digital health tools are clear, and it is often cited that they will be a key vehicle on the road to achieving Universal Health Coverage. However, poorly designed, unsustainable, unsafe and irresponsible digital health products can be a waste of time, energy and physical and financial resources, and more importantly can risk the wellbeing for those whose lives they were supposed to improve. Along this continuum of negative outcomes due to badly designed digital health tools, the perpetuation of stereotypes, the widening of the digital divide and the abuse of personal data are also key concerns.
The Digital Health Initiative aims to:
- Encourage and facilitate the sustainable, safe and responsible development and adoption of digital health products amongst international organisations, NGOs, the private sector and government organisations;
- Build capacity among health care workers, local governments, publics, and other end users;
- Ensure uptake and use of strong digital health tools and guidelines.
The age of Artificial intelligence and machine learning is upon us.
In this webinar we will take a look not just at the promise that these data analytics tools hold for the future of health care, but also highlight some of the key challenges and common pitfalls in developing ethically sound and fair AI for health. We will focus in on the ethical and societal impact of AI applications, particularly on issues of gender bias and racial discrimination caused by machine learning algorithms.
At the end of this session, participants should be able to:
- Describe what bias in AI means
- Identify some of the key groups most vulnerable to poorly designed AI
- Describe some steps that can be taken to make AI for health more responsible
This Responsible Digital Health Speaker Series will feature experts from healthcare, academia, public and private sector.
Participation is open to government officials, diplomats, staff of international organizations, development practitioners, faculty members, and administrators of educational institutions.