LinkedIn is very proud of the semantic mapping and other capabilities that underpin the feed you’re seeing now.
It’s technically impressive, yet functionally specious.
The algorithm is vain - in all three definitions of the word. Here’s some data from the past week to back this up.
Post 1 describing how the LinkedIn feed is on the path to becoming as ignorable as our email spam folder: 7,000 impressions.
Post 2 offering commentary on Canada’s AI Strategy survey and important questions that remain unasked: 480 impressions.
Post 3 calling LinkedIn users who post AI slop the Zombies of the Dead Internet. 17,000 impressions.
Post 4 announcing TYPECHA, an AI-slop-fighting text editor that provides proof of work for your writing and editing process: 170 impressions.
Post 5 synthesizing a decade of experience in medical imaging and how solutions fell short of accounting for the myriad of cognitive and workflow factors that would affect the adoption of AI by radiologists. Most importantly, it offered the insight that every domain is full of such AI blind spots. 160 impressions.
Vain as in ingeniously contrived - yes.
Vain as in marked by ineffectiveness - yes.
Vain as lacking in real value - yes.
I think the lack of attention to human factor engineering principles is real issue in the current design and implementation of AI systems - both at the consumer and enterprise levels. I would love it if a post on the topic got tens of thousands of view. It could save someone millions of dollars.