AI note-takers
Attention only · Discussion moved +0.0%; no adoption series is mapped for it. (as of 2026·08·12)
Distinct voices per mention. 1.00 means every mention came from a different person; a low number means a handful of people are driving the volume. Authors are counted once per day, so someone who posts across several days counts more than once over the whole window. The figure can overstate breadth, never understate it.
A wave of praise on a forum and a rapidly filling issue tracker both show up as “mentions up” until you see where they came from.
Most opinion points the same way, so the average sentiment reads as a verdict rather than two sides cancelling out.
SRC: 12 mentions in window · net sentiment −0.04 · 0 adoption series · derived aggregates only
Interactive chart. Arrow keys step through the series, Home and End jump to its ends, and Escape closes the readout.
| Period | mentions |
|---|---|
| 2026-05-15 | 5 |
| 2026-05-28 | 1 |
| 2026-06-01 | 1 |
| 2026-06-05 | 1 |
| 2026-07-02 | 1 |
| 2026-07-03 | 1 |
| 2026-07-27 | 1 |
| 2026-08-10 | 1 |
Interactive chart. Arrow keys step through the series, Home and End jump to its ends, and Escape closes the readout.
| Period | net sentiment |
|---|---|
| 2026-05-15 | 0.48 |
| 2026-05-28 | 0.34 |
| 2026-06-01 | 0.81 |
| 2026-06-05 | 1.00 |
| 2026-07-02 | −0.05 |
| 2026-07-03 | 0.97 |
| 2026-08-10 | −0.04 |
| What was said | Momentum |
|---|---|
| threadfork is an AI notetaker that runs locally on Apple Silicon with strong privacy protection where meeting data is not sent or saved anywhere. | −100% |
| Granola AI Notetaker has a one-click account takeover vulnerability. | −100% |
| AI note-taking tools have been highly beneficial for managing ADHD symptoms and providing visibility into incomplete tasks. | −100% |
| The AI note taker generates helpful action items and meeting highlights with timestamps that are useful after meetings. | −100% |
| AI note-takers can produce dangerously inaccurate summaries that misrepresent what was said in meetings. | −100% |
| AI note-takers limit the ability to take detailed notes during meetings due to competing cognitive demands. | −100% |
| AI note takers are added to calls and capture personal information without obtaining consent first. | −100% |
| Doctors spend more time typing notes than interacting with patients, reducing listening and empathy in healthcare. | −100% |
| AI note takers frequently miss critical information, focus on wrong topics, and sometimes record the opposite of what was actually decided. | −100% |
| AI note takers provide limited value for people who attended the meeting but are useful for those who did not attend. | −100% |
| Users want AI note takers to help make their written communication sound more professional and courteous. | −100% |
| Employees ignore security policies and send AI note-takers to sensitive meetings without authorization, exposing confidential data. | −100% |
| AI note-takers produce excessive bullet points with frequent errors, requiring users to still manually write impressions after meetings. | −100% |
| Software subscription costs are increasing to justify AI features that users do not want or use. | −100% |
| AI note-takers hallucinate and misreport details including non-existent items and inflated numbers, creating liability issues. | −100% |
| AI note-takers struggle with accuracy when participants have heavy accents or international English speakers are present. | −100% |
| AI note-takers cannot be reliably checked for accuracy without human review or cross-checking, which defeats their purpose. | −100% |
| AI note-takers can be activated without participant knowledge and changed meeting dynamics by forcing people to perform for the recorder. | −100% |
| AI note-takers require healthcare providers to spend more time talking to the computer than to patients to ensure accurate transcription. | −100% |
| Users need local AI models for meeting transcription to maintain privacy while taking notes on conference calls. | −100% |