Re: [madPL] Elena Glassman talk to madPL group

["LORIS D'ANTONI" <ldantoni@xxxxxxxx>]

We will also stream the talk on zoom here
https://uwmadison.zoom.us/j/91525760309?pwd=d2dUdnRjTGw2aHZyUy9wU0NOMGNIQT09

 

 

From: LORIS D'ANTONI <ldantoni@xxxxxxxx>
Date: Tuesday, April 12, 2022 at 4:48 PM
To: pl-seminar@xxxxxxxxxxx <pl-seminar@xxxxxxxxxxx>
Cc: YEA-SEUL KIM <yeaseul.kim@xxxxxxxxxxx>, Yuhang Zhao <yuhang.zhao@xxxxxxxxxxx>, Bilge Mutlu <bilge@xxxxxxxxxxx>, JERRY ZHU <jerryzhu@xxxxxxxxxxx>
Subject: Elena Glassman talk to madPL group

Hi everyone,

 

Elena Glassman is in town for a conference and will visit our department to give a talk at the intersection of HCI, PL, and AI.

Please share the info below with your group and anyone interested in attending.

If you’d like to meet Elena (in person), we still have a few spots here https://docs.google.com/spreadsheets/d/1MoCSAYn3nyjbTL2WV1JR6HFFF3xXzyBV0D8fHdxojWU/edit?usp=sharing

 

Cheers,

-Loris

 

When: 4/21/22, 10 am

Where: CS3310

Who: Elena Glassman

 

“Human-AI (Mis)Communication: challenges and tools for successfully communicating what we want to computers”

 

Abstract: While we don’t always use words, communicating what we want to a computer, especially an artificially intelligent one, is a conversation—with ourselves as well as with it, a recurring loop with optional steps depending on the complexity of the situation and our request. I will present some key, perhaps previously under-appreciated steps and describe conditions where it is critical to support them, illustrated with examples from recent publications of (1) novel interfaces for interactive program synthesis and (2) interactive visualizations of large piles of complex data. Time permitting, I will describe relevant theories from the learning sciences, i.e., Variation Theory and Analogical Learning Theory, that have design implications for future interface and interactive system design—to hopefully maximize the bidirectional speed and accuracy of human-AI communication.

 

Bio

Elena L. Glassman is the Stanley A. Marks and William H. Marks Assistant Professor at Harvard Radcliffe Institute and an assistant professor of computer science at the Harvard John A. Paulson School of Engineering and Applied Sciences. She specializes in human-computer interaction and leads a research group that aims to augment human intelligence with computation. 

 

Glassman earned a PhD and MEng in electrical engineering and computer science and a BS in electrical science and engineering from the Massachusetts Institute of Technology. She has received fellowships from the Berkeley Institute for Data Science, the National Defense Science and Engineering Graduate Fellowship Program, and the National Science Foundation Graduate Research Fellowship Program. She was also awarded the Intel Foundation Young Scientist Scholarship, the MIT Amar Bose Teaching Fellowship, and an MIT Morris Joseph Levin Award, among others.