Ask HN: Do you verify AI-generated content before publishing?
1 comments
I am in Camp A. I verify AI-generated content closely. I am usually using AI to improve content that I have provided. Because I am knowledgeable about the information and topic, I can quickly recognize when AI is wrong or stupid.
I find a lot of errors and would never recommend Camp B as a smart way to use AI. It may seem efficient, but knowledgeably readers or listeners will lose trust in you.
I find a lot of errors and would never recommend Camp B as a smart way to use AI. It may seem efficient, but knowledgeably readers or listeners will lose trust in you.
When you use AI to turn podcasts/interviews/webinars into social posts, do you verify accuracy before publishing?
Context: Tools like Castmagic and Descript are 85-95% accurate. That 5-15% error rate means AI sometimes: - Misquotes speakers - Paraphrases in ways that change meaning - Attributes quotes to wrong person (multi-speaker issue)
I've found two camps:
Camp A: "I carefully verify everything" - Re-read transcripts or scrub audio - Takes 20-30 minutes per post - Zero tolerance for publishing errors
Camp B: "I trust AI and publish" - "Good enough" for social media - Errors are rare enough to accept - Speed > perfection
My questions: 1. Which camp are you in? 2. If Camp A: what's your verification workflow? 3. Has anyone been burned by publishing inaccurate AI content? 4. Would "click any quote to hear exact audio timestamp" be valuable?
Building a tool that links every generated claim to source evidence. Trying to validate if this solves a real problem or if I'm overthinking content accuracy.
Appreciate any insights from the HN community.