Person
1 episodes · 8 quoted claims
Kate Niederhoffer and Jeff Hancock's research defines AI workslop as low-effort, low-quality AI-generated work that appears to fulfill a workplace task but lacks the substance to do so.
“low effort, low quality AI generated work that appears to fulfill a workplace task, but doesn't really have the substance necessary to do that.”
Kate Niederhoffer says the research found managers reported spending more time and effort dealing with workslop than others did.
“we found that managers are actually reporting spending more time and effort dealing with it.”
Kate Niederhoffer says receiving workslop led people to judge the sender as less competent and less trustworthy and to be less willing to work with them.
“it actually makes you judge the producer of the content to be less competent, less trustworthy, like you don't wanna work with them anymore.”
Kate Niederhoffer says whether AI use is mandated in an organization was the single biggest predictor of workslop in the researchers' findings.
“understand is AI mandated in the organization? That's like the single biggest predictor of work slop”
Kate Niederhoffer says the most common self-reported reason for creating workslop was that everything felt urgent and important.
“the self-reported reason for creating work slop is because everything feels urgent and important.”
Kate Niederhoffer and Jeff Hancock proposed a new organizational role called an AI collaboration architect, who is fluent in both people and technology.
“Jeff and I had suggested, you know, a new role as something like an AI collaboration architect.”
Kate Niederhoffer describes a 'pilot mindset' as one marked by high agency and high optimism about AI.
“It's people who have high agency and high optimism about AI. It's their mindset toward using the tools.”
Kate Niederhoffer says some organizations pick fewer than ten priority areas, such as seven, in which to embed AI into workflows and then measure specific outcomes.
“I see some organizations identifying less than 10, for example, 7 priority areas where they can really embed AI into the workflows to solve particular challenges.”