vimeo.com/1165640864?s...

If you're interested in scheduling a guest lecture or presentation for your organization, class, or event please reach out.

Thanks to our funders, the Office of the Privacy Commissioner of Canada and the Creative School at Toronto Metropolitan University.

For anyone who wants to learn more: we've produced an educational video and digital literacy primer in English and French. These resources and the full report available at: www.infoscapelab.ca/projects/los...

3. Calls to insurance contact centres have been analyzed to automatically identify customers with Alzheimer’s, Parkinson’s, anxiety, and depression. Pharmaceutical companies are major R&D partners and there are early efforts to use these products to deliver targeted advertisements for drugs.

2. Function creep into workplaces is expanding rapidly. Whether you’re a clinician, call centre agent, corporate employee, Uber driver, or factory labourer—health-related machine listening systems are being promoted to maintain a happy, healthy, and productive workforce.

A few findings that stand out:

1. Infants, children, and youth are targeted. There is a wide array of commercial applications for young people, including respiratory monitoring, learning development tracking, autism detection and mental health applications for use in the home, school, and clinic.

I hope this primer proves useful to you and within your communities. Please consider sharing it to help raise awareness in connection with Data Privacy Day.

The updated primer features an expanded discussion of gaps in privacy protections, as well as new recommendations aimed at engaging civil society organizations in policy-related action.

Some of you may have participated in an earlier event in October as part of Media Literacy Week organized by @mediasmarts.bsky.social , where you shared valuable feedback with the research team.

drive.google.com/file/d/1NVPJ...

This resource offers an overview of this rapidly evolving area of technology and highlights key privacy considerations and rights protections in a Canadian context.

For those interested in this issue, my team and I have prepared a public-facing primer on voice data privacy, which explores these risks and the current gaps in Canadian privacy law.

drive.google.com/file/d/1NVPJ...

At a minimum, a meaningful step forward would be clear and enforceable limits on how voice data is collected, used, and disclosed, including prohibitions on using police call data to train commercial AI systems beyond narrowly defined purposes.

In the wrong contexts, this data could be used to profile people based on their credibility, race, or other variables. Given this sensitivity, commercial uses of voice data likely require explicit consent under PIPEDA.

Voice data is biometric information: it is tied to our bodies and is individually identifying. This raises the risk of re-identification considerably.

Voice also reveal information about emotional state, health conditions, mental health indicators, language background, and race.

Data derived from 811 or 911 calls would be highly valuable to insurance companies and other parties, for example, and could be used to profile individuals or communities.

4) Voice data is highly sensitive biometric data

Yet aggregate and anonymized data still carry real risks of re-identification.

In Canada, under PIPEDA, commercial uses of identifiable personal data require meaningful consent because disclosure to third parties creates downstream risks.

This would position an automated decision-making system at the very front end of emergency response.

3) Serious consent problems

Hyper’s ToC and privacy policy allow broad secondary uses of caller data, including training AI models, developing new products, and creating anonymized datasets.

Data monitoring systems introduced for narrow purposes are routinely expanded over time. This well-documented process is known as function creep.

A plausible future scenario is the use of Hyper as a triage system for 911 calls.

This could lead to under-reporting of non-emergency incidents, and potentially even emergency situations, due to privacy and surveillance fears.

2) Function creep from non-emergency to emergency calls

Toronto Police have stated that Hyper will only be used for 811 calls. For now.