Flickr: CSAM Classifier Case Study

Flickr's small Trust & Safety team used AI to make a big impact.

Millions of photos are uploaded to Flickr every day, and with those photos comes a responsibility to keep the platform safe. With a small team, they needed a tool that could help them quickly detect new and previously unknown CSAM.

IN THIS CASE STUDY:

How Flickr leveraged Safer’s CSAM Classifier's machine learning classification model to accelerate their detection of new or previously unknown CSAM
How Safer’s AI/ML helped Flickr’s small Trust & Safety team make a big impact
How Safer x Flickr are working together to improve cross-platform intelligence

Flickr Uses Safer’s Image Classifier to Expand Their Detection of Child Sexual Abuse Material (CSAM)

Flickr's small Trust & Safety team used AI to make a big impact.

Get the full case study to see how many classifier hits Flickr had in 2022 alone.

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THE WORLD’S MOST INNOVATIVE COMPANIES PROTECT THEIR PLATFORMS USING SAFER

Protect your platform and your users from abuse content at scale.

Hash Matching

CSAM Image and Video Classifiers

Review Tool

Reporting API

With Safer’s CSAM Classifier, we’re finding content that we would not have known existed. What you don’t know is what’s going to hurt you in this line of work.

We don’t have a million bodies to throw at this problem, so having the right tooling is really important for us. The Classifier enables us to be proactive. We’re not just keeping our platform safe, we’re protecting it and making it a safe, equitable platform.

—JACE POMALES, TRUST AND SAFETY MANAGER, FLICKR