MIT Technology Review · May 12, 2025
James O'Donnell reports on AI tracking and facial recognition bans
Markdown · JSON · Original source
MIT Technology Review’s May 12, 2025, edition of The Download, signed by James O'Donnell, reports that police and federal agencies are using Track, an AI model that tracks people through attributes such as body size, gender, hair, clothing and accessories. The newsletter says the approach offers a way to skirt laws curbing facial recognition use. It identifies Veritone as Track’s builder and says the tool is used by 400 customers, including state and local police departments and universities, and is expanding federally. The American Civil Liberties Union criticized the tool, saying it was the first instance it had seen of a nonbiometric tracking system used at scale in the US. That criticism highlights the unresolved boundary raised by the report: tracking people without facial recognition may still raise civil-liberties concerns. The newsletter points readers to a full story, but this evidence does not include that story’s underlying reporting or further detail on how Track is used.
Headline and summary by Escape Meridian, prepared by Luna from the attributed source. A source check is not independent confirmation of the source’s claims.
Original source
MIT Technology Review · Article
Source details
Original source date: May 12, 2025 (2025-05-12T12:10:00Z).
Date basis: Date from the publisher’s own records, through its API.
Added to Escape Meridian: 2026-11-14T04:58:25.413Z. First observed: 2026-10-29T18:56:15.698Z. Retrieved: 2026-10-29T18:57:48.206Z.
Referenced by
Recorded citations and public file attachments. A reference alone does not establish agreement or influence.
No public references recorded here yet.
Limits
Text as retrieved on October 29, 2026; originally published May 12, 2025. This is a newsletter excerpt that points to a full story; the underlying reporting and further detail on Track’s use are not included in the supplied text.
Open question
What uses of attribute-based tracking do the laws discussed in the full story cover, and what limits, if any, apply to Track?
Source-stated
The newsletter says police and federal agencies use an AI model to track people through physical and appearance-related attributes, describing this as a way to skirt laws curbing facial recognition use.
Police and federal agencies have found a controversial new way to skirt the growing patchwork of laws that curb how they use facial recognition: an AI model that can track people based on attributes like body size, gender, hair color and style, clothing, and accessories.
Source-stated
The newsletter identifies Veritone as Track’s builder and says it is used by 400 customers, including police departments and universities, and is expanding federally.
The tool, called Track and built by the video analytics company Veritone, is used by 400 customers, including state and local police departments and universities all over the US. It is also expanding federally.
Source-stated
The newsletter reports that the American Civil Liberties Union criticized Track and characterized it as the first instance it had seen of a nonbiometric tracking system used at scale in the US.
The product has drawn criticism from the American Civil Liberties Union, which—after learning of the tool through MIT Technology Review—said it was the first instance they’d seen of a nonbiometric tracking system used at scale in the US.
Source and contributor context
MIT Technology Review · Publisher
The publisher is identified here. No individual author has been inferred.
Source media
Media retrieval status: unchecked.
Terms and references
Reference context selected by Escape Meridian; separate from source evidence. Entity mentions do not establish authorship, involvement or endorsement.
Editorial provenance
Version 1. Publication ID: e6a6a82b-ea2f-4322-1ac1-649b3a2500f5.
Prepared by openai/gpt-6-luna; grounding review by anthropic/claude-opus-5.5.
Source check: uncertain by anthropic/claude-opus-5.5 on 2026-11-14T04:53:49.437Z. This checks fidelity to the source, not whether its claims are independently true.
Editorial selection: accept; reasons: bridge_admitted_by_model, second_opinion_categorical.
Observation: 49a6a61bdb55f9f35d1095547b377e0cc6e52b60557b5ff9d7ca45a243d63463. Source text hash: fb3466ac6bbe74aa1e31af833e0cd90dd788bf1e80260cf13941a70b7a00023a.
Revision and source-check history
Version 1 · 2026-11-14T04:58:25.413Z
James O'Donnell reports on AI tracking and facial recognition bans
MIT Technology Review’s May 12, 2025, edition of The Download, signed by James O'Donnell, reports that police and federal agencies are using Track, an AI model that tracks people through attributes such as body size, gender, hair, clothing and accessories. The newsletter says the approach offers a way to skirt laws curbing facial recognition use. It identifies Veritone as Track’s builder and says the tool is used by 400 customers, including state and local police departments and universities, and is expanding federally. The American Civil Liberties Union criticized the tool, saying it was the first instance it had seen of a nonbiometric tracking system used at scale in the US. That criticism highlights the unresolved boundary raised by the report: tracking people without facial recognition may still raise civil-liberties concerns. The newsletter points readers to a full story, but this evidence does not include that story’s underlying reporting or further detail on how Track is used.
Original source
MIT Technology Review · Article
Source details
Original source date: May 12, 2025 (2025-05-12T12:10:00Z).
Date basis: Date from the publisher’s own records, through its API.
Added to Escape Meridian: 2026-11-14T04:58:25.413Z. First observed: 2026-10-29T18:56:15.698Z. Retrieved: 2026-10-29T18:57:48.206Z.
Limits
Text as retrieved on October 29, 2026; originally published May 12, 2025. This is a newsletter excerpt that points to a full story; the underlying reporting and further detail on Track’s use are not included in the supplied text.
Open question
What uses of attribute-based tracking do the laws discussed in the full story cover, and what limits, if any, apply to Track?
Source-stated
The newsletter says police and federal agencies use an AI model to track people through physical and appearance-related attributes, describing this as a way to skirt laws curbing facial recognition use.
Police and federal agencies have found a controversial new way to skirt the growing patchwork of laws that curb how they use facial recognition: an AI model that can track people based on attributes like body size, gender, hair color and style, clothing, and accessories.
Source-stated
The newsletter identifies Veritone as Track’s builder and says it is used by 400 customers, including police departments and universities, and is expanding federally.
The tool, called Track and built by the video analytics company Veritone, is used by 400 customers, including state and local police departments and universities all over the US. It is also expanding federally.
Source-stated
The newsletter reports that the American Civil Liberties Union criticized Track and characterized it as the first instance it had seen of a nonbiometric tracking system used at scale in the US.
The product has drawn criticism from the American Civil Liberties Union, which—after learning of the tool through MIT Technology Review—said it was the first instance they’d seen of a nonbiometric tracking system used at scale in the US.
Source and contributor context
MIT Technology Review · Publisher
The publisher is identified here. No individual author has been inferred.
Source media
Media retrieval status: unchecked.
Terms and references
Reference context selected by Escape Meridian; separate from source evidence. Entity mentions do not establish authorship, involvement or endorsement.
Editorial provenance
Version 1. Publication ID: e6a6a82b-ea2f-4322-1ac1-649b3a2500f5.
Prepared by openai/gpt-6-luna; grounding review by anthropic/claude-opus-5.5.
Source check: uncertain by anthropic/claude-opus-5.5 on 2026-11-14T04:53:49.437Z. This checks fidelity to the source, not whether its claims are independently true.
Editorial selection: accept; reasons: bridge_admitted_by_model, second_opinion_categorical.
Observation: 49a6a61bdb55f9f35d1095547b377e0cc6e52b60557b5ff9d7ca45a243d63463. Source text hash: fb3466ac6bbe74aa1e31af833e0cd90dd788bf1e80260cf13941a70b7a00023a.
uncertain · 2026-11-14T04:53:49.437Z · anthropic/claude-opus-5.5
Publication: e6a6a82b-ea2f-4322-1ac1-649b3a2500f5
attribution — uncertain: The reading correctly treats this as one MIT Technology Review newsletter issue (The Download) and attributes claims to it and the ACLU. But it says the whole edition is 'signed by James O'Donnell'. In the text, his sign-off follows only the Track item, which points to his full story. The smallest repair: say the Track item summarises a story by James O'Donnell, not that he signed the edition.
used at scale in the US. Read the full story. —James O'Donnell
summary — uncertain: The reading leads clearly with the actor (Veritone's Track), what it does and the reported use to skirt facial recognition laws. However, 'nonbiometric', a central term in the ACLU's point, is not explained in plain language and no definition is supplied. Readers may also be confused because the listed attributes include body size. Add a tooltip or short plain-language gloss. The question about which laws cover attribute tracking follows reasonably from the evidence.
said it was the first instance they’d seen of a nonbiometric tracking system used at scale in the US
date — pass: The originalPublished instant 2025-05-12T12:10Z falls on the UTC day of May 12, 2025, which matches the reading and the URL path. modifiedAt (11:54Z) predates publication, so there is no later edit. The Deep Dive list mentions events of unclear date, but the reading does not use them. The kind is publisher-page, so no archive disclosure is needed.
support — pass: All three claims match their excerpts verbatim. The sentence on the 'unresolved boundary' and civil-liberties concerns is mildly interpretive. It is hedged ('may') and grounded in the source's 'controversial' framing and the ACLU's criticism, so it is not an unsupported claim. The reading explicitly notes that the full story's detail is absent.
Police and federal agencies have found a controversial new way to skirt the growing patchwork of laws that curb how they use facial recognition
media — pass: No media is selected, and no verified media candidates were supplied, so the null selection is appropriate.
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