Thank you, Mr. Chair.

Thank you, Mr. Chair and members of the Standing Committee on Access to Information, Privacy and Ethics, for giving me the opportunity to speak with you today about artificial intelligence in radiology, specifically in relation to ethical and legal issues in the implementation of this technology in medical imaging.

My name is Dr. An Tang and I am here representing the Canadian Association of Radiologists (CAR), as chair of the Artificial Intelligence Committee within the CAR.

The CAR AI working group is composed of more than 50 members who have a keen interest in technology advancement in radiology as it pertains to AI. The composition of this working group is varied, from predominantly radiologists to physicists, computer scientists and researchers. It also includes a philosopher specialized in the ethics of AI and an academic lawyer.

Under the CAR board of directors' leadership we have been entrusted with taking a global look at AI and the impact it will have on radiology and patient care in Canada.

I believe I speak for most of my colleagues in thinking that this is a good-news story and that AI can dramatically impact the way radiologists practise, in a positive way. Through the collection of data and simulation, using mathematical algorithms, we can help reduce wait times for patients, thus expediting diagnosis and positively affecting patient outcomes.

AI software analyzing medical images is becoming increasingly prevalent. Unlike early generations of AI software, which relied on expert knowledge to identify image features, machine learning techniques can automatically learn to recognize these features with the use of training datasets.

AI can be used for the purpose of detecting disease, establishing diagnosis and optimizing treatment selection. However, for this to be performed accurately, access to large quantities of medical data from patients will be required. This, of course, brings the privacy question into the equation. How do we collect this data while still guaranteeing we are collecting this information in an ethical way that protects the privacy of our patients?

Because of the transition from film to digital imaging that occurred two decades ago in radiology, and because of the availability of digital records for each imaging examination, radiology is well positioned to lead the development and implementation of AI and to manage associated ethical and legal challenges.

CAR believes that the benefits of AI can outweigh risks when institutional protocols and technical considerations are appropriately implemented to safeguard or remove the individually identifiable components of medical imaging data.

Technology advancements are occurring so quickly that they are outpacing current radiology procedures. We need to establish regulations pertaining to data collection and ownership to ensure that we are safeguarding patients and not infringing on ethical or privacy guidelines.

The CAR is advocating for the federal government to take a leadership role in the implementation of an ethical and legal framework for AI in Canada. Despite health care being a provincial priority, AI is a global issue. We feel the government is well positioned to lead the provinces in the regulation of the implementation of such a framework. Similar examples are the federal government's leadership in the national medical imaging equipment fund in the early 2000s.

The CAR can help, and the AI working group, under the CAR board's leadership, has published two white papers on AI, the first published in 2018 on AI in radiology, and a general overview of machine learning and implementation in radiology. This second paper, published in May 2019, focused on ethical and legal issues related to AI in radiology.

We have provided copies of the white papers, with our recommendations, for each of you. For the purpose of the discussion, I would like to highlight the more prevalent ones as they relate to the federal government's role in this capacity.

The first is the implementation of a public awareness campaign regarding consent and patient sharing of anonymized health data and harm reduction strategies. This information is essential for helping to identify disease and treatment for future AI applications.

Second is the general adoption of broad consent by default, with the right to opt out.

Third is developing a system for ensuring data security and anonymization of radiology data for secondary use, and implementing system standards to ensure that this criterion is being met.

Fourth, train radiology data custodians and establish clear guidelines for their role in the implementation of data sharing agreements for common AI-related scenarios and third parties.

The CAR has to work with the federal government and provincial ministries of health, including the Canadian Medical Protective Association, or CMPA, to develop guidelines for appropriate deployment of AI assistive tools in hospitals and clinics, while looking at minimizing harm and liability for malpractice for errors involving AI. We need to educate radiologists and other health care professions on the limitations of AI and reiterate the use of the tool in supplementing the work rather than replacing radiologists.

AI is not going away. Sharing medical data is a complex issue that balances individual privacy rights versus collective societal benefits. Given the potential of AI in helping to improve patient care and medical outcomes, I believe we will start to see a paradigm shift from patient's rights to near absolute data privacy through the sharing of anonymized data for the good of society.

We need to work together to implement a framework to ensure that we can move forward with this technology, while respecting the patient's anonymity and privacy. AI in healthcare is going to happen sooner or later; let's make sure it is implemented in an ethical way.

Thank you for your time. I'm happy to answer your questions in either French or English.

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