Fact-Checkers Demand Transparent AI: Study Shows Need for Explainable Automated Fact-Checking Systems

#machinelearning #ai #programming #datascience

This is a Plain English Papers summary of a research paper called Fact-Checkers Demand Transparent AI: Study Shows Need for Explainable Automated Fact-Checking Systems. If you like these kinds of analysis, you should join AImodels.fyi or follow us on Twitter.

Overview

Research examines fact-checkers' requirements for explainable AI fact-checking systems
Study conducted through interviews with 20 professional fact-checkers
Identified key needs: transparency, source verification, and step-by-step reasoning
Fact-checkers want AI systems that show their work, not just conclusions
Found significant gaps between current AI capabilities and fact-checker needs

Plain English Explanation

Professional fact-checkers need AI systems that can explain themselves clearly. Just like a student showing their work on a math problem, fact-checkers want AI to demonstrate how it reached its conclusions.

The researchers talked to 20 fact-checkers about what they need from A...

Click here to read the full summary of this paper

Hands-on debugging session: instrument, monitor, and fix

Join Lazar for a hands-on session where you’ll build it, break it, debug it, and fix it. You’ll set up Sentry, track errors, use Session Replay and Tracing, and leverage some good ol’ AI to find and fix issues fast.

RSVP here →