"Our algorithm and AI systems do not use demographic information (such as age, race, or gender) as a signal to determine the visibility of content, profile or posts in the Feed Our product and engineering teams have tested a number of these posts and comparisons, and while different posts did get different levels of engagement, we found that their distribution was not influenced by gender, pronouns, or any other demographic information."
"A side-by-side snapshot of your own feed updates that are not perfectly representative, or equal in reach, doesn't automatically imply unfair treatment or bias. In addition, we are seeing the volume of content created daily on LinkedIn has grown rapidly over the past year, which means more competition for attention but also more opportunities for creators and viewers alike."
"...whether the Feed quality for one demographic is systematically worse than another, such as if females are seeing more irrelevant feed items compared to men."
Product and engineering teams tested numerous posts and comparisons and found varying engagement across posts but no evidence that distribution was influenced by gender, pronouns, or other demographic information. A side-by-side snapshot of feed updates that are not perfectly representative or equal in reach does not automatically indicate unfair treatment or bias. The daily volume of content has grown rapidly over the past year, increasing competition for attention while also creating more opportunities for creators and viewers. Teams continue to evaluate whether Feed quality is systematically worse for any demographic, such as women seeing more irrelevant items.
Read at Social Media Today
Unable to calculate read time
Collection
[
|
...
]