They see your photos

Perceived Privacy Risks from Photos

• Many note that big platforms already combine photo data with messaging, likes, ad clicks, etc., to build rich profiles, even of non‑users appearing in others’ uploads.
• Photos expose EXIF (camera, time, GPS) plus visual signals: faces, clothing, homes, social circles, travel frequency, apparent wealth, health, and habits.
• Commenters worry that this feeds “surveillance capitalism”: pricing, eligibility for jobs, rentals, insurance, legal risk, and targeted manipulation, not just ads.
• Some extend concern to physical photo labs and employers, assuming most commercial entities hoard and monetize any data they get.

Capabilities and Limits of AI Image Analysis

• Many testers report surprisingly detailed descriptions: specific locations, camera models, inferred socioeconomic status, context of events, even from old or technical photos.
• Others see blatant hallucinations (invented objects, misread scenes, wrong time of day) and bias (e.g., different “status” guesses by race, or economic status of animals).
• The tool appears prompted to speculate about subtle details and economic class, often producing verbose but shallow “filler” analysis.
• Some browsers’ anti‑fingerprinting features cause uploads to be replaced by canvas noise, leading to “no people present” descriptions.

Trust, Big Tech, and Data Use

• There is debate over whether Google/OpenAI can be trusted with sensitive family photos; some prefer Google’s compliance reputation, others see both as indiscriminate data vacuums.
• Official assurances like “we don’t use your photos for advertising” are widely viewed as weasel‑worded and non‑binding, given past reversals and legal loopholes.
• A minority think the concern is overblown or obvious (“of course computers can look at images”), while others see this demo as a concrete wake‑up call.

Photo Storage: Cloud, E2EE, and Self‑Hosting

• Encrypted services with on‑device AI (e.g., Ente) and self‑hosted tools (Immich, Syncthing + face_recognition, etc.) are discussed as ways to get search and face grouping without exposing data to big clouds.
• Trade‑offs: encryption vs recovery convenience, speed of indexing, platform lock‑in (e.g., iCloud’s Apple focus), and cost.

Mitigation and Workarounds

• Practical tips: strip or scrub EXIF (exiftool, jhead, exifstrip, ImageMagick), avoid Live Photos, consider noise/cropping to weaken forensic links (with disagreement on effectiveness).
• Some conclude the only robust “opt‑out” from profile enrichment is not uploading to large platforms at all.

Reaction to the Site’s Framing

• Several see the project as effective education; others dismiss it as FUD and marketing for a photo service with arbitration‑heavy terms.
• Underneath the disagreement, many agree that large‑scale, automated understanding of photos is here and has broad implications.