[CMU AI Seminar] October 25 at 12pm (NSH 3305 & Zoom) -- Charvi Rastogi (CMU) -- Two Studies on Peer Review: Finding implicit biases in conference peer review -- AI Seminar sponsored by SambaNova Systems

[Asher Trockman]

Dear all,

We look forward to seeing you *tomorrow, **this Tuesday (10/25)* from
*1**2:00-1:00
PM (U.S. Eastern time)* for the next 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/>.

Tomorrow (10/25), *Charvi Rastogi* (CMU MLD) will be giving a talk titled
*"**Two Studies on Peer Review: Finding implicit biases in conference peer
review**".*

*Title*: Two Studies on Peer Review: Finding implicit biases in conference
peer review

*Talk Abstract*: Modern peer review systems are a huge part of academia,
and play a consequential role in participants' career trajectories. In this
talk, we will discuss two studies (involving several thousand papers and
reviewers) that scrutinize certain aspects of the peer-review process in
two conferences: ICML and EC. In this work, we focus on sources of implicit
bias in the decision-making process. In the first study, we investigate the
positive and negative effects of posting preprints online for multiple
stakeholders. ArXiv is an increasingly popular choice for posting
preprints, however it stands to dilute anonymity in double-blind peer
review. This can negatively impact the review process for authors
affiliated to lower ranked institutions. We conduct a study to help
quantify the associated risks and benefits of posting preprints online for
authors from different institutions. In the second study, we investigate
whether cited reviewers are implicitly biased in favor of acceptance of the
paper. For this, we intervene in the paper-reviewer assignment procedure
and carefully analyze the outcomes of the review process (observational
data) to test for the presence of citation bias. Our work has  policy
implications for conference peer-review design and authors' engagement with
it.

*In person: *NSH 3305
*Zoom Link*:
https://cmu.zoom.us/j/99510233317?pwd=ZGx4aExNZ1FNaGY4SHI3Qlh0YjNWUT09

Thanks,
Asher Trockman
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