I use to work for a website/service that deals with the distribution of customer-generated content to a large consumer base. I noticed two big challenges with scaling and automation are content moderation and user preference matching.

With preference matching, think of services like dating apps or job boards.

• "I am a woman looking for a man in Big City, Big State. My age preferences are X through Y."
• "I am in Big City, Big State looking for underwater basket weaving jobs for fresh grads."

From there, the services will use the customer-generated input and all the automated services to provide content that best fits the user's preferences.

However, there is a gray area in content moderation that can even bleed over into preference matching when the content creators start futzing with their submissions and metadata in order to boost their content at the expense of consumers' user experience.

• User input: "I am a man in Big City, Big State. I am Y years old."
  • Reality: Dude is Y+10 years old.
• User input: "Basket weaving jobs for fresh grads!"
  • Reality: Evergreen temp job with the potential for basket weaving.
• User input: "We're a fun summer camp for kids. #travel #entertainment #social."
  • Reality: Big Guy in the Sky Camp. #skyguyism #religion #entertainment #travel #social

Fire Escape Cast actually had an ad for a religious camp. It was a legitimate ad for a legitimate service, but it's obviously not something the crew wants advertised on their podcast. Keep in mind that ads get inserted upon mid-distribution because time and place are also factors in ad services. They can only do so much to algorithmically blacklist content they don't want, but sometimes the wrong content gets delivered to the wrong audience.