Cybercriminals Are Complaining About AI Slop Flooding Their Forums
It's not just you. Hackers and other cybercriminals are complaining about “AI shit” flooding platforms where they discuss cyberattacks and other illegal activity.
Government Technology AI·
A school district in New Hampshire updated its AI policy to stipulate which platforms are allowed and when students and staff must disclose their use, though some staff members raised questions about enforceability.
Read full articleIt's not just you. Hackers and other cybercriminals are complaining about “AI shit” flooding platforms where they discuss cyberattacks and other illegal activity.
The Emily Hart case shows the gap between what platforms say about AI transparency and what users actually see in their feeds.
For teachers, advocating for your classroom and students isn’t just about the big, visible moments, but the quiet ones: the follow-up email, the extra conversation, the willingness to try again after hearing “no.”
Vibe coding and spec-driven development (SDD) are two emerging approaches where devops teams use AI to develop all of an application’s code. There are discussions about which approach to use for different use cases, and there are many platforms to consider with varying capabilities and experiences. Some experts question whether AI delivers reliable, maintainable applications, while others suggest that, at some point, AI can lead the end-to-end software development process. But one certainty IT organizations face is that there’s more demand for applications, integrations, and analytics than there is supply of agile teams and devops engineers. Compound this imbalance with business priorities to address application security vulnerabilities, modernize applications for the cloud, and address technical debt. It results in tough choices on what work to prioritize and where to drive efficiencies in the software development life cycle. Even before AI code generators emerged, IT leaders sought
Vibe coding and spec-driven development (SDD) are two emerging approaches where devops teams use AI to develop all of an application’s code. There are discussions about which approach to use for different use cases, and there are many platforms to consider with varying capabilities and experiences. Some experts question whether AI delivers reliable, maintainable applications, while others suggest that, at some point, AI can lead the end-to-end software development process. But one certainty IT organizations face is that there’s more demand for applications, integrations, and analytics than there is supply of agile teams and devops engineers. Compound this imbalance with business priorities to address application security vulnerabilities, modernize applications for the cloud, and address technical debt. It results in tough choices on what work to prioritize and where to drive efficiencies in the software development life cycle. Even before AI code generators emerged, IT leaders sought
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High school and college teachers are watching students write, in the classroom, in order to protect against the incursion of artificial intelligence.
"As knowledge becomes democratized, the ability to think critically is going to become more and more important"