Otter.ai Notetaker Allegedly Recorded Meeting Conversations Without Participants' Informed Consent and Used Data for AI Training

In February 2025, Otter.ai's Notetaker reportedly recorded and transcribed a Zoom conversation involving Justin Brewer, a San Jacinto, California resident who was not an Otter account holder, without his informed consent. Brewer later alleged that Otter obtained and retained his meeting communications and used captured data to train its speech-recognition and machine-learning systems.

Risk classification

• Primary risk domain: 2 Privacy & Security
• Primary risk subdomain: 2.1 Compromise of privacy by obtaining, leaking or correctly inferring sensitive information

The incident involves Otter.ai obtaining and recording private, non-public conversations of meeting participants without their consent to train its AI models.

Additional risk subdomains

• 7.4 Lack of transparency or interpretability: The lawsuit highlights a lack of transparency regarding Otter's de-identification process and its failure to notify participants of recording.

Causal factors

• Entity: Human
• Intent: Intentional
• Timing: Post-deployment

The privacy risks and unauthorized recordings were caused by human design decisions and corporate policies of Otter.ai. These actions were intentional as the system was designed to collect data to train its models post-deployment.

EU AI Act risk tier

• Risk tier: 3 Limited Risk

Level 3: Limited Risk. The system is an AI transcription and note-taking assistant that requires specific transparency obligations, such as notifying participants when they are being recorded and when their data is being processed by an AI.

AI system and alleged parties

• AI system: Otter Notetaker (Otter.ai)
• AI purpose: Voice Recognition; Writing Assistant
• Behaviour type: Assistant
• Alleged developer: Otter.ai, AI transcription technology developers
• Alleged deployer: Otter.ai users, Otter.ai, AI transcription tool users
• Alleged harmed parties: Privacy, People recorded without consent, Otter.ai users, Justin Brewer, Employees

Harm severity

Severity ratings are based on this scale.

Highest direct severity in any category: Minor. Severity is scored from Negligible to Catastrophic in each harm category, for harm the reports describe as caused directly or indirectly by the AI system.

• Physical: direct Negligible, indirect Negligible
• Infrastructure: direct Negligible, indirect Negligible
• Property: direct Negligible, indirect Negligible
• Financial: direct Negligible, indirect Minor
• Environmental: direct Negligible, indirect Negligible
• Malicious content: direct Negligible, indirect Negligible
• Differential treatment: direct Negligible, indirect Negligible
• Civil rights: direct Negligible, indirect Negligible
• Democracy: direct Negligible, indirect Negligible
• Privacy: direct Minor, indirect Negligible
• Psychological: direct Negligible, indirect Negligible
• Epistemic: direct Negligible, indirect Negligible
• Child sexual exploitation and abuse: direct Negligible, indirect Negligible

Financial

Reported: The report mentions a business deal being killed due to an unauthorized recording, and the lawsuit seeks damages exceeding 5,000,000 dollars, but specific direct financial losses are not quantified.

Indirectly caused: An AI researcher's business deal was reportedly killed after Otter shared a transcript containing confidential details discussed after he left the meeting.

Inferred additional harm: It is likely that other businesses or individuals suffered unquantified financial losses or lost business opportunities due to leaked confidential meeting details.

Privacy

Reported: Yes, the report explicitly describes widespread privacy violations caused by the unauthorized recording and transcription of meetings.

Directly caused: Otter.ai recorded and transcribed a confidential Zoom meeting attended by Justin Brewer on February 24, 2025, without his consent, using his voice data to train its models.

Inferred additional harm: Given Otter's 25 million users, it is highly likely that millions of other non-consenting meeting participants have had their private conversations recorded and used for AI training.

People affected

• Occurrences reported: 1
• People reportedly harmed: 1
• People reportedly exposed: 25000000

Potential causes

Management

• Prioritizing Growth Over Privacy: Company focused on rapid user growth and revenue over robust privacy safeguards.
• Lack of Transparency on Data Use: Management failed to provide public details on de-identification processes.

Technology

• Default Settings Disable Notifications: Pre-recording email alerts to participants are turned off by default.
• Unreliable De-identification: AI training data de-identification lacks transparency and may be unreliable.
• No Participant Recording Control: Unlike competitors, non-users cannot stop Otter from recording the meeting.

Data Inputs

• Non-Consensual Voice Harvesting: Voice and meeting data of non-consenting participants are used for training.
• Indefinite Data Retention: Otter retains captured conversational data indefinitely for model training.
• Lack of Training Data Extraction: Once data is incorporated into the AI model, it cannot be easily extracted.

Human Factors

• User Neglect of Notice Rules: Users fail to manually notify or get consent from other meeting participants.
• Overreliance on Default Settings: Users do not enable optional pre-meeting notification settings.

Process and Methods

• Shifting Consent Burden to Users: Otter's terms outsource legal consent obligations entirely to the accountholder.
• Automatic Calendar Integration: Software automatically joins and records meetings linked to workplace calendars.
• Host-Only Consent Mechanism: The system only requests consent from the host, ignoring other participants.

Regulatory Environment

• Inadequate Wiretap Law Enforcement: Ambiguity in whether AI transcription tools constitute third-party eavesdroppers.
• Varying Multi-Party Consent Laws: Jurisdictional differences in consent requirements complicate compliance.

Information quality

• Classification confidence: High
• Reason for confidence: The reports provide consistent and detailed information regarding the class-action lawsuit against Otter.ai, including specific dates, legal claims, and the technical mechanisms of the Otter Notetaker tool. The legal arguments and company responses are well-documented across multiple sources.
• Ambiguities identified: There is some ambiguity regarding the exact technical process Otter uses to 'de-identify' voice and transcript data, as well as the exact number of non-users affected.
• Alternative interpretations: None. The incident is clearly a privacy-related legal dispute over unauthorized data collection for AI training.

Otter.ai faces a class-action lawsuit alleging unauthorized recording of virtual meetings to train its AI models. While representing a significant privacy concern and an evolved method of automated data harvesting, the national security impact remains minor and is manageable through standard legal and regulatory channels.

• Overall national security impact: Minor
• Scope: Single nation
• Primary target: United States
• Alleged perpetrator: Otter.ai

Threat characteristics

• Imminence: Long-term. The incident involves ongoing corporate data collection practices and legal proceedings rather than an active, fast-moving national security crisis.
• Autonomy: Human-supervised. The AI tool operates with automated features like auto-joining calendars and transcribing, but is initiated and supervised by human users.
• Novelty: Evolved capability. Represents an evolved privacy threat where automated transcription tools are systematically leveraged to harvest proprietary voice data for AI model training.

Impact by dimension

• Physical security: Negligible. No physical security threats, kinetic impacts, or critical infrastructure disruptions are reported in connection with this incident.
• Information security: Minor. Unauthorized transcription of private meetings poses a minor intelligence risk regarding the exposure of confidential business or organizational information, though no state-sponsored espionage is indicated.
• Sovereignty: Negligible. The incident does not impact state authority, border control, or core government decision-making processes.
• Economic security: Minor. Minor economic impact is demonstrated by a reported business deal being disrupted due to leaked transcripts, but there is no systemic threat to strategic national industries.
• Societal stability: Minor. The unauthorized recording of meetings represents a notable privacy violation affecting potentially millions of users, but the threat is manageable within standard legal and regulatory frameworks.