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fuck_ai·Fuck AIbymorrowind

Gen-Z, I've noticed people using the same messaging for AI as climate change.

The messaging for climate change, often wrapped as a joke or not said directly to Gen Z is "this is your problem, [the consequences will come in your adulthood]" or "this is for your generation to solve".

B.S of course, By the time Gen-Z gets any power it'll be too late.

With AI I'm frequently seeing people, often fairly smart, good people saying things like "oh yeah AI is totally going to destroy X industry. I mean I'll be retired, so I'll be fine, but you'll have to figure something out".

My father says this frequently. My CTO at work who's been heavily pushing AI was asked "aren't you afraid it'll make you dumber?" responded "of course! But I'm retiring soon anyway, who cares". A lot of AI "leaders" often imply the same thing.

Often dressed up as a joke. I laugh along. It's never been funny and continues to get less funny.

Usually from older people, millennials are still young enough that ill effects will hit them before retirement (assuming you chaps manage to retire at all).

View original on lemmy.ml
fuck_ai·Fuck AIbymorrowind

[paper] Evidence of a social evaluation penalty for using AI

cross-posted from: https://lemmy.ml/post/30013197

Significance

As AI tools become increasingly prevalent in workplaces, understanding the social dynamics of AI adoption is crucial. Through four experiments with over 4,400 participants, we reveal a social penalty for AI use: Individuals who use AI tools face negative judgments about their competence and motivation from others. These judgments manifest as both anticipated and actual social penalties, creating a paradox where productivity-enhancing AI tools can simultaneously improve performance and damage one’s professional reputation. Our findings identify a potential barrier to AI adoption and highlight how social perceptions may reduce the acceptance of helpful technologies in the workplace.

Abstract

Despite the rapid proliferation of AI tools, we know little about how people who use them are perceived by others. Drawing on theories of attribution and impression management, we propose that people believe they will be evaluated negatively by others for using AI tools and that this belief is justified. We examine these predictions in four preregistered experiments (N = 4,439) and find that people who use AI at work anticipate and receive negative evaluations regarding their competence and motivation. Further, we find evidence that these social evaluations affect assessments of job candidates. Our findings reveal a dilemma for people considering adopting AI tools: Although AI can enhance productivity, its use carries social costs.

https://www.pnas.org/doi/full/10.1073/pnas.2426766122Open linkView original on lemmy.ml
technology·Technologybymorrowind

[paper] Evidence of a social evaluation penalty for using AI

cross-posted from: https://lemmy.ml/post/30013147

Significance

As AI tools become increasingly prevalent in workplaces, understanding the social dynamics of AI adoption is crucial. Through four experiments with over 4,400 participants, we reveal a social penalty for AI use: Individuals who use AI tools face negative judgments about their competence and motivation from others. These judgments manifest as both anticipated and actual social penalties, creating a paradox where productivity-enhancing AI tools can simultaneously improve performance and damage one’s professional reputation. Our findings identify a potential barrier to AI adoption and highlight how social perceptions may reduce the acceptance of helpful technologies in the workplace.

Abstract

Despite the rapid proliferation of AI tools, we know little about how people who use them are perceived by others. Drawing on theories of attribution and impression management, we propose that people believe they will be evaluated negatively by others for using AI tools and that this belief is justified. We examine these predictions in four preregistered experiments (N = 4,439) and find that people who use AI at work anticipate and receive negative evaluations regarding their competence and motivation. Further, we find evidence that these social evaluations affect assessments of job candidates. Our findings reveal a dilemma for people considering adopting AI tools: Although AI can enhance productivity, its use carries social costs.

https://www.pnas.org/doi/full/10.1073/pnas.2426766122Open linkView original on lemmy.ml
technology·Technologybymorrowind

[paper] Evidence of a social evaluation penalty for using AI

Significance

As AI tools become increasingly prevalent in workplaces, understanding the social dynamics of AI adoption is crucial. Through four experiments with over 4,400 participants, we reveal a social penalty for AI use: Individuals who use AI tools face negative judgments about their competence and motivation from others. These judgments manifest as both anticipated and actual social penalties, creating a paradox where productivity-enhancing AI tools can simultaneously improve performance and damage one’s professional reputation. Our findings identify a potential barrier to AI adoption and highlight how social perceptions may reduce the acceptance of helpful technologies in the workplace.

Abstract

Despite the rapid proliferation of AI tools, we know little about how people who use them are perceived by others. Drawing on theories of attribution and impression management, we propose that people believe they will be evaluated negatively by others for using AI tools and that this belief is justified. We examine these predictions in four preregistered experiments (N = 4,439) and find that people who use AI at work anticipate and receive negative evaluations regarding their competence and motivation. Further, we find evidence that these social evaluations affect assessments of job candidates. Our findings reveal a dilemma for people considering adopting AI tools: Although AI can enhance productivity, its use carries social costs.

https://www.pnas.org/doi/full/10.1073/pnas.2426766122Open linkView original on lemmy.ml