14 resources on artificial intelligence, ethics, and governance


This is a practical, useful collection of articles assembled by one of our amazing fellows, Dr. Jay Shaw.  Jay’s work aims to clarify the implications of artificial intelligence (AI) and related technologies in healthcare policy and practice. The linked articles below offer a rich overview of the issues that arise when we use  AI in healthcare, including big data management. 

AI is being used in a wide variety of ways, most of which revolve around massive amounts of data being used to train algorithms to achieve two broad aims:

  • Decision support in which advanced analytics lead to more accurate predictions that can inform human decisions
  • Automation, whereby predictive algorithms are connected to the execution of a task

In healthcare, AI’s data can target the health of individual people and entire populations. Since AI can transform many of healthcare’s tasks, it’s raising important questions about how these changes should be governed. Ensuring the ethical governance of AI in healthcare leads to important questions:

  • How accurate are our diagnostic strategies, and could they be better? 
  • How might new technologies interfere with the abilities of healthcare providers to demonstrate compassion with their patients? 
  • How should the health system decide which risks are tolerable and which aren’t when deploying AI?

In Canada, a rich ecosystem of people pay attention to these issues. Stay tuned for more deep thinking about this topic from AMS.

From What to How: An Overview of AI Ethics Tools, Methods and Research to Translate Principles into Practices

Artificial Intelligence: the global landscape of ethics guidelines

This is a synthesis of global considerations and guidelines related to ethics and artificial intelligence.

The Doctor Just Won’t Accept That!

An interesting paper that explores how explainability in AI enhances implementability… with a healthcare focus!

Big Data, precision medicine and private insurance: A delicate balancing act

This paper discusses health-related big data, precision medicine, and private insurance.

Ethics and Epistemology in Big Data Research

Learn about the ethics and epistemology of big data research. This work includes specific suggestions for ethics researchers and institutional review boards.

Canadian Association of Radiologists White Paper on Ethical and Legal Issues Related to Artificial Intelligence in Radiology

This position statement from the Canadian Association of Radiologists shares advanced thinking about the ethical and legal issues related to the use of AI in radiology.

Digital health at fifteen: More human (more needed)

This paper highlights the link between the current state of digital health and a future state of health-related AI.

Machine Learning and AI Research for Patient Benefit: 20 Critical Questions on Transparency, Replicability, Ethics and Effectiveness

This paper is a valuable step towards considering and implementing best practices for AI applications in health.

Artificial Intelligence and the ‘Good Society’: the US, EU, and UK approach

Learn about different policy approaches for ‘a good AI society’ in the USA, UK, and EU.

Understanding the care.data conundrum: New information flows for economic growth

A useful analysis of the UK’s care.data initiative, where health data was shared in order to fuel economic growth.

‘Hypernudge’: Big Data as a mode of regulation by design

See the insidious ways that our data is used to “nudge” our actions. While this paper is not directly about healthcare, it shows that there are clear implications for the health field.

Towards international standards for evaluating machine learning

This article is technical and really worth digging into. It presents international standards for evaluating machine learning.

Google DeepMind and healthcare in an age of algorithms

This is a case study exploring lessons learned from sharing population-derived health datasets with large, private companies.

Dangers of the digital fit: Rethinking seamlessness and social sustainability in data-intensive healthcare 

See how data sharing was halted in Denmark because of conflicting views about its legitimate use.