WhatA platform where users consciously contribute photos, video, and sensor data for AI training in exchange for transparent, fair-market compensation.
SignalCommenters point out that companies like Meta steal training data by burying consent in terms of service because they refuse to pay fair value — and that most users would either refuse or demand payment if the exchange were made honest.
Why NowRegulatory crackdowns on non-consensual data harvesting (EU AI Act, FTC actions) are making the 'bury it in TOS' approach legally risky, creating demand for a legitimate, compliant data supply chain.
MarketAI companies desperate for high-quality, legally clean training data (~$10B+ data labeling/collection market); key gap is that no major marketplace offers verified-consent real-world visual data at scale.
MoatNetwork effects — more contributors means richer, more diverse datasets, which attracts more AI buyers, which increases payouts, which attracts more contributors.
Meta’s AI smart glasses and data privacy concernsView discussion ↗ · Article ↗ · 1,448 pts · March 2, 2026
Carrier-Independent RCS Messaging Without Big TechC5/10An open-source or independent RCS client and server that implements the full RCS Universal Profile without routing through Google's Jibe platform.
One-Click Privacy OS Installation Service For PhonesC5/10A service — online and in retail kiosks — that installs GrapheneOS on customer-supplied or purchased phones with guided setup, app migration, and banking app verification.
Privacy-First Wearable Camera With On-Device AIP6/10Smart glasses with all AI processing done on-device, no cloud uploads, no account required, with hardware-enforced recording indicators that cannot be disabled.
Wearable Detection and Alerting for Private SpacesC6/10A detection system (hardware sensor + app) for businesses, homes, and private venues that identifies nearby smart glasses and always-on recording devices and alerts owners or triggers policies.