Particle’s way to reduce errors in AI news reporting
Particle is a (new) news app that relies on AI summarization. I’ve been testing it from the beginning and it is the most reliable AI implementation for news, and the most eye candy.
This is a fascinating and well written article by Particle, on how they work on AI summaries errors.
Reality checks: These checks require that all of the claims in the summary remain faithful to the source material, even with respect to nuances, as described earlier. At every step, the AI is required to “show its work” and explain why it has made its assessments, with evidence and reasoning. Below is an example of Particle’s Reality Check in action.
Step 1: Particle generates a headline for a given story.
Generated Headline: Los Angeles Wildfires Highlight Tensions Over Fire Department Budget Cuts
Step 2: Particle takes the generated headline and runs a Reality Check against the sources used to generate it.
Reality Check evaluation: Fail
Reasoning: The evidence provided from the articles supports the claims made in the summary regarding tensions over budget cuts and their impact on the fire department’s ability to respond to wildfires. Crowley’s criticism of the budget cuts and the acknowledgment of limited training and response capabilities due to reduced funding are directly referenced. However, the articles also highlight that despite these cuts, the overall budget for the fire department increased, which complicates the narrative of a purely negative impact from the budget reductions. Therefore, while the headline captures the essenceof the situation, it may oversimplify the complexities involved.
I love the conclusion:
Companies using AI can do a lot more to reduce hallucinations, and they should
