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is-it.ai
Vote on AI vs human. Reputation, not detection.
Vote first, see the crowd's call. Not an AI detector — a reputation-weighted community for judging suspect images, text, and video. Debate the evidence, build streaks, climb the leaderboard. Free.
An arXiv paper from April 2026 — "Humans Cannot Detect AI-Generated Media But Communities May — For Now" (2605.24287) — studied r/RealOrAI, the 189K-member subreddit built around this exact question. 7,342 posts, 288,277 comments.
The headline finding: aggregated community judgments beat isolated guessing (~72% on verified challenge posts). But the nuance matters — as suspicion grows, people increasingly over-flag real content as AI. The internet's failure mode is shifting from "I got fooled" to "everything weird gets called fake."
Human guesses are noisy. AI detectors are brittle. We're building toward reputation-weighted communities that surface evidence and provenance as a practical authenticity layer for the internet — starting with the vote-and-debate loop that's live today.
is-it.ai is the standalone version of what that paper measured on Reddit — not "Reddit guesses, but prettier":
WHAT'S LIVE NOW • Vote first — crowd consensus + verified labels hidden until you commit (off the network response too) • Persistent reputation — accuracy across hundreds of votes weighs more than a drive-by comment • Gated debate — comments unlock after your vote, so they're arguments not anchoring signals • Daily challenge + streaks + leaderboard (yes, it's fun — engagement is how we get signal at scale) • 11 categories, multi-modal: images, text, video (voice clones next)
WHAT WE'RE BUILDING TOWARD • Calibration metrics — false-AI rate, not just accuracy (the paper's biggest warning) • Structured evidence on comments — anatomy, artifacts, audio, provenance • Provenance attachments — source links, reverse image, creator verification • API for platforms and newsrooms
This is NOT another closed-box AI detector. Detectors give you a score you can't argue with. We're the social, debatable, reputation-weighted layer — the crowd is a signal, strongest when paired with evidence, reputation, and verified labels when we have them.
What I'd love from PH: cast 5–10 votes on the homepage demo or feed, then tell me which categories feel under-served and where the UX breaks. Calibration feedback > feature requests.
is-it.ai was submitted on Product Hunt and earned 8 upvotes and 2 comments, placing #68 on the daily leaderboard. Vote first, see the crowd's call. Not an AI detector — a reputation-weighted community for judging suspect images, text, and video. Debate the evidence, build streaks, climb the leaderboard. Free.
On the analytics side, is-it.ai competes within Artificial Intelligence, Side Project and Community — topics that collectively have 481.6k followers on Product Hunt. The dashboard above tracks how is-it.ai performed against the three products that launched closest to it on the same day.
Who hunted is-it.ai?
is-it.ai was hunted by is-it.ai. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
For a complete overview of is-it.ai including community comment highlights and product details, visit the product overview.
is-it.ai
Hey Product Hunt 👋
An arXiv paper from April 2026 — "Humans Cannot Detect AI-Generated Media But Communities May — For Now" (2605.24287) — studied r/RealOrAI, the 189K-member subreddit built around this exact question. 7,342 posts, 288,277 comments.
The headline finding: aggregated community judgments beat isolated guessing (~72% on verified challenge posts). But the nuance matters — as suspicion grows, people increasingly over-flag real content as AI. The internet's failure mode is shifting from "I got fooled" to "everything weird gets called fake."
Human guesses are noisy. AI detectors are brittle. We're building toward reputation-weighted communities that surface evidence and provenance as a practical authenticity layer for the internet — starting with the vote-and-debate loop that's live today.
is-it.ai is the standalone version of what that paper measured on Reddit — not "Reddit guesses, but prettier":
WHAT'S LIVE NOW
• Vote first — crowd consensus + verified labels hidden until you commit (off the network response too)
• Persistent reputation — accuracy across hundreds of votes weighs more than a drive-by comment
• Gated debate — comments unlock after your vote, so they're arguments not anchoring signals
• Daily challenge + streaks + leaderboard (yes, it's fun — engagement is how we get signal at scale)
• 11 categories, multi-modal: images, text, video (voice clones next)
WHAT WE'RE BUILDING TOWARD
• Calibration metrics — false-AI rate, not just accuracy (the paper's biggest warning)
• Structured evidence on comments — anatomy, artifacts, audio, provenance
• Provenance attachments — source links, reverse image, creator verification
• API for platforms and newsrooms
This is NOT another closed-box AI detector. Detectors give you a score you can't argue with. We're the social, debatable, reputation-weighted layer — the crowd is a signal, strongest when paired with evidence, reputation, and verified labels when we have them.
What I'd love from PH: cast 5–10 votes on the homepage demo or feed, then tell me which categories feel under-served and where the UX breaks. Calibration feedback > feature requests.
Free at the core, forever. Paper: https://arxiv.org/abs/2605.24287