234 incidents on record · 2026HeadlightsIncident reports by Ellie Harris · Melbourne
5 new this weekLibrary last updated 14 October 2026
← The incident library
HD-INC-196
Healthcare · Canada · 2024 · An AI transcription tool joined a clinical meeting through a departed physician's retained invitation and sent patient information to the meeting's recipient list

An Otter.ai Transcription Tool Joined Hospital Rounds Through a Former Doctor's Old Invite

By Ellie Harris · Filed Meeting recorded on 23 September 2024

Alleged: Ontario hospital (not named by the regulator); Otter.ai developed or deployed the AI system implicated in this incident. Details are drawn from public reports; parties are presumed innocent of any wrongdoing not established by an official finding.

An Otter.ai Transcription Tool Joined Hospital Rounds Through a Former Doctor's Old Invite

What happened

The Information and Privacy Commissioner of Ontario reported in October 2025 that Otter.ai, an AI transcription tool, joined and recorded an online hepatology rounds meeting at an Ontario hospital on 23 September 2024.

According to the commissioner’s letter, a doctor had left the hospital in June 2023, but his personal email address was still on the meeting invitation. The letter records that he installed Otter.ai on a personal device in September 2024. When the hospital meeting took place, the tool joined using the meeting link saved in his personal calendar.

After the meeting, Otter.ai automatically emailed a meeting summary and access to a transcript, addressed to 65 users on the recipient list. Staff had discussed personal health information about seven patients during the meeting.

The letter records that some recipients confirmed they had deleted the information or had not received it. Others appeared to have left the hospital without confirming whether they had deleted it. The former doctor did not respond when asked to contact Otter.ai to request deletion of the information.

The hospital had not approved Otter.ai for use in its meetings.

What an auditable version would have shown

The commissioner’s letter reported what the hospital was able to establish after the incident, including who was sent the email, who confirmed deletion or non-receipt, and which patients had been discussed. The recording came to light when Otter.ai sent its email after the meeting.

In this entry’s reading, the hospital needed a record of who had access to the meeting and what happened while it was taking place, rather than having to piece everything together afterwards.

A record made at the time would have shown who was on the invitation, whether they still worked at the hospital and who was admitted to the meeting. It would also have identified any AI tools that joined, whose accounts they were using, what they recorded and where they sent the information.

The hospital could then have used those records to establish who had received the patient information and whether it had been deleted.

The sources reviewed do not report whether the meeting platform logged that a transcription tool had joined, or whether anyone in the meeting noticed it before the email arrived.

Where the gap was

The letter reported that Otter.ai joined through the meeting link in the former doctor’s personal calendar and then sent information through his account.

In this entry’s reading, the doctor had left the hospital more than a year earlier, but he was still on the invitation to a meeting where confidential patient information was discussed. The tool he installed was able to use that invitation to join the meeting.

The published record does not identify an admission control that stopped an automated participant joining on his behalf.

An EgressGate is designed to check whether information contains sensitive data and whether it is being sent outside the trust boundary. In this case, Otter.ai was running through the former doctor’s personal account. The hospital needed to control who could enter the meeting before patient information could be recorded.

A ConductRecord keeps a record of each action an AI tool takes, including whose account it used, what information it captured and where it sent that information.

EgressGate and ConductRecord are Headlights designs.

What governance should have looked like

The commissioner reportedly recommended that the hospital contact Otter.ai directly to request deletion of the information. The recommendations also included reviewing how access is removed when staff and doctors leave, enforcing meeting lobbies whenever health information is discussed, clarifying the rules on personal devices and aligning the hospital’s AI governance framework with the commissioner’s presentation on AI in Ontario’s health sector.

Where clinical meetings are held online, best practice would be to remove former staff from meeting invitations when they leave the organisation. Every participant, whether a person or an AI tool, should be checked before being allowed into a meeting, with a record of who admitted them.

Failure Pattern: a physician who had left the hospital more than a year earlier remained on a clinical meeting invitation, and an AI transcription tool he later installed joined through it and sent patient information to the recipient list.

Governance Principle: an organisation that discusses health information in online meetings should be able to show who was admitted to each meeting, human or automated, on whose authority, and that people who have left can no longer be admitted through invitations they kept.

The reference implementation of EgressGate and ConductRecord is open source. It lives at github.com/saffronandindia/headlights-oss, Apache 2.0 licensed and free to install. The repository is public now.

Sources

The mailing list

Fresh incident reports every week. One email to match.

We add new incidents to the library regularly, and send a single short email each week with what's new. The library stays free and open; this is just how you keep up with it.

Sent through Substack. Unsubscribe in one click.

The record

An auditable system would have produced a signed, tamper-evident record the moment this happened: what the system did, the version that did it, the basis it acted on, and the action taken, and Ontario hospital (not named by the regulator); Otter.ai could have produced it on demand.

This is the record the system as deployed did not produce in a signed, auditable form.

What this teaches
Capture what happened when it happens
What the system did, the version that did it, the basis it acted on, and the action taken, recorded at the moment, not reconstructed after.
Sign it, so no one has to trust the record-keeper
A tamper-evident entry. Edit it later and the signature breaks. The record does not ask for the benefit of the doubt.
Make it verifiable by anyone
A court, a regulator, a customer's lawyer can check the record themselves, without taking the company, or us, at our word.

Headlights summarises publicly reported AI incidents. All summaries are independently written, attributed to their original sources, and intended for research and educational purposes. Allegations are identified as such until established through official findings.

Last reviewed September 2026. This report is based on the sources listed above and reflects information available at the time of review; later developments may not be captured. Where a person is described as charged with or alleged to have done something, that allegation is unproven unless a conviction or a court or regulatory finding is stated. Headlights publishes journalism and commentary, not legal advice.

Want to write back?

Direct to my inbox.

ellie@useheadlights.com →