i was about to offer to start being the mechanical turk for chatgpt
ETHICS
-
Responsible AI in the Intelligence Age: Ethical Considerations
By
–
Thank you so much my @ThuliumCo team for sharing my article and amplifying this important conversation! The Intelligence Age brings immense potential, but it also calls for thoughtful reflection on how we harness AI responsibly. I'm grateful to be part of a team that values both
-
AI Face Clones: The Emerging Identity Crisis in Fintech
By
–
The Rise Of AI Face Clones Could Trigger A Fintech Identity Crisis
#payments #fintech #paymentsolutions @briansolis @Xbond49 @VitalikButerin @DataScienceCtrl @Benioff @johnnosta @IrmaRaste @Tiffani_Bova -
Publishing research in Statistics over CS for community engagement
By
–
Thank you! We probably could have published it faster in a CS conference. But I really think it's of significant interest to the Statistics community, and believe there should be more engagement between the CS and Stats privacy communities, so we put our money where our mouth is.
-
Apple Intelligence Updates: New Features and Privacy Approach
By
–
The full blog post has more info about all the Apple Intelligence updates including this info about other upcoming features and how it's handling privacy with AI.
-
Efforts to avoid doom ultimately unsuccessful
By
–
We spent a lot of effort trying to make it not-doom before being pulled back in that direction.
-
AI Models Confidently Make Mistakes Despite External Context
By
–
AI systems often gather external info as context when answering a particular query. Even w/this relevant info, models can make mistakes w/seemingly high doses of confidence.
-
ContextCite: Tracing AI Sources and Detecting Hallucinations
By
–
If the AI generates an inaccurate fact, users can trace the error back to its original source & understand the model’s reasoning. If the AI hallucinates an answer, ContextCite can indicate that the information didn’t come from any real source at all.
— MIT CSAIL (@MIT_CSAIL) 11 décembre 2024
The tool could be valuable… pic.twitter.com/D8ViuL2cjXIf the AI generates an inaccurate fact, users can trace the error back to its original source & understand the model’s reasoning. If the AI hallucinates an answer, ContextCite can indicate that the information didn’t come from any real source at all. The tool could be valuable
-
MIT ContextCite tool improves chatbot answer reliability verification
By
–
How can we really know if a chatbot is giving a reliable answer? MIT CSAIL’s "ContextCite" tool can ID the parts of external context used to generate any particular statement from a language model, improving trust by helping users easily verify the statement: