Jan 23 at 12pm (NSH 3305) -- Ashique KhudaBukhsh (RIT) -- Down the Toxicity Rabbit Hole: A Novel Framework to Bias Audit LLMs -- AI Seminar sponsored by SambaNova Systems

[Victor Akinwande]

Reminder: this is happening today!

On Tue, Jan 16, 2024 at 10:44 AM Victor Akinwande <vakinwan at andrew.cmu.edu>
wrote:

> Dear all,
>
> We look forward to seeing you *next Tuesday (01/23) from 12:00-1:00 PM
> (ET) *for the first talk of this semester's CMU AI Seminar, sponsored by
> SambaNova Systems (https://sambanova.ai). The seminar will be held in *NSH
> 3305 *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 (01/23), Ashique KhudaBukhsh (RIT) will be giving a talk
> titled "Down the Toxicity Rabbit Hole: A Novel Framework to Bias Audit
> LLMs".
>
>
> ///////////////////
> *Talk Abstract:* How safe is generative AI for disadvantaged groups? This
> paper conducts a bias audit of large language models (LLMs) through a
> novel toxicity rabbit hole framework introduced here. Starting with a
> stereotype, the framework instructs the LLM to generate more toxic content
> than the stereotype. Every subsequent iteration it continues instructing
> the LLM to generate more toxic content than the previous iteration until
> the safety guardrails (if any) throw a safety violation or it meets some
> other halting criteria (e.g., identical generation or rabbit hole depth
> threshold). Our experiments reveal highly disturbing content, including but
> not limited to antisemitic, misogynistic, racist, Islamophobic, and
> homophobic generated content, perhaps shedding light on the underbelly of
> LLM training data, prompting deeper questions about AI equity and alignment.
>
> *Speaker Bio: *Ashique KhudaBukhsh is an assistant professor at the
> Golisano College of Computing and Information Sciences, Rochester Institute
> of Technology (RIT). His current research lies at the intersection of NLP
> and AI for Social Impact as applied to: (i) globally important events
> arising in linguistically diverse regions requiring methods to tackle
> practical challenges involving multilingual, noisy, social media texts;
> (ii) polarization in the context of the current US political crisis; and
> (iii) auditing AI systems and platforms for unintended harms. In addition
> to having his research been accepted at top artificial intelligence
> conferences and journals, his work has also received widespread
> international media attention that includes coverage from The New York
> Times, BBC, Wired, Times of India, The Indian Express, The Daily Mail,
> VentureBeat, and Digital Trends.
> ///////////////////
>
>
> *In person: NSH 3305*
> *Zoom Link:*
> https://cmu.zoom.us/j/99510233317?pwd=ZGx4aExNZ1FNaGY4SHI3Qlh0YjNWUT09
>
>
> - Victor Akinwande
>
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