Oct 29 at 12pm (GHC 6115) -- Virginia Smith (CMU) -- A Reality Check for Vibes-Based ML Safety

[Victor Akinwande]

Virginia's talk is happening in less than an hour.

See you there.

On Wed, Oct 23, 2024 at 12:28 PM Victor Akinwande <vakinwan at andrew.cmu.edu>
wrote:

> Dear all,
>
> We look forward to seeing you next *Tuesday (10/29) from 12:00-1:00 PM
> (ET)* for the next talk of this semester's CMU AI Seminar, sponsored by SambaNova
> Systems <https://sambanova.ai>. The seminar will be held in *GHC 6115*
> with pizza provided and will be streamed on Zoom.
>
> To learn more about the seminar series or to see the future schedule,
> please visit the seminar website (http://www.cs.cmu.edu/~aiseminar/).
>
> Next Tuesday (10/29), Virginia Smith (CMU) will be giving a talk titled "A
> Reality Check for Vibes-Based ML Safety".
>
> *Abstract:* Machine learning applications are increasingly reliant on
> black-box pretrained models. To ensure safe use of these models, techniques
> such as unlearning, guardrails, and watermarking have been proposed to curb
> model behavior and audit usage. Unfortunately, while these post-hoc
> approaches give positive safety ‘vibes’ when evaluated in isolation, our
> work shows that existing techniques are quite brittle when deployed as part
> of larger systems. In a series of recent works, we show that: (a) small
> amounts of auxiliary data can be used to 'jog' the memory of unlearned
> models; (b) current unlearning benchmarks obscure deficiencies in both
> finetuning and guardrail-based approaches; and (c) simple, scalable attacks
> erode existing LLM watermarking systems and reveal fundamental trade-offs
> in watermark design. Taken together, these results highlight major
> deficiencies in the practical use of post-hoc ML safety methods. We end by
> discussing promising alternatives to ML safety, which instead aim to ensure
> safety by design during the development of ML systems.
>
> *Bio: *Virginia Smith is the Leonardo Associate Professor of Machine
> Learning at Carnegie Mellon University. Her current work addresses
> challenges related to safety and efficiency in large-scale machine learning
> systems.
>
>
> *In person: GHC 6115Zoom Link:
>  https://cmu.zoom.us/j/99510233317?pwd=ZGx4aExNZ1FNaGY4SHI3Qlh0YjNWUT09
> <https://cmu.zoom.us/j/99510233317?pwd=ZGx4aExNZ1FNaGY4SHI3Qlh0YjNWUT09>*
>
>
> - Victor
>
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mailman.srv.cs.cmu.edu/pipermail/ai-seminar-announce/attachments/20241029/ad99c063/attachment.html>