[Theory] TODAY: 2/8 Talks at TTIC: Lydia T. Liu, Cornell University
Mary Marre
mmarre at ttic.edu
Wed Feb 8 10:16:28 CST 2023
*When:* Wednesday, February 8th at *11:30** a**m CT *
*Where: *Talk will be given *live, in-person* at
TTIC, 6045 S. Kenwood Avenue
5th Floor, Room 530
*Virtually:* *via* Panopto (*livestream
<https://uchicago.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=5bf55682-3277-427c-b608-af9c017082e4>*
)
*Who: * Lydia T. Liu, Cornell University
------------------------------
*Title: *Towards Responsible Machine Learning in Societal Systems
*Abstract:* Machine learning systems are deployed in consequential domains
such as education, employment, and credit, where decisions have profound
effects on socioeconomic opportunity and life outcomes. High stakes
decision settings present new statistical, algorithmic, and ethical
challenges. In this talk, we examine the distributive impact of machine
learning algorithms in societal contexts, and investigate the algorithmic
and sociotechnical interventions that bring machine learning systems into
alignment with societal values---equity and long-term welfare. First, we
study the dynamic interactions between machine learning algorithms and
populations, for the purpose of mitigating disparate impact in applications
such as algorithmic lending and hiring. Next, we consider data-driven
decision systems in competitive environments such as markets, and devise
learning algorithms to ensure efficiency and allocative fairness. We end by
outlining future directions for responsible machine learning in societal
systems that bridge the gap between the optimization of predictive models
and the evaluation of downstream decisions and impact.
*Bio: *Lydia T. Liu is a postdoctoral researcher in Computer Science at
Cornell University, working with Jon Kleinberg, Karen Levy, and Solon
Barocas. Her research examines the theoretical foundations of machine
learning and algorithmic decision-making, with a focus on societal impact
and human welfare. She obtained her PhD in Electrical Engineering and
Computer Sciences from UC Berkeley, advised by Moritz Hardt and Michael
Jordan, and has received a Microsoft Ada Lovelace Fellowship, an Open
Philanthropy AI Fellowship, an NUS Development Grant, and a Best Paper
Award at the International Conference on Machine Learning.
*Host: Avrim Blum <avrim at ttic.edu>*
Mary C. Marre
Faculty Administrative Support
*Toyota Technological Institute*
*6045 S. Kenwood Avenue, Rm 517*
*Chicago, IL 60637*
*773-834-1757*
*mmarre at ttic.edu <mmarre at ttic.edu>*
On Tue, Feb 7, 2023 at 3:28 PM Mary Marre <mmarre at ttic.edu> wrote:
> *When:* Wednesday, February 8th at *11:30** a**m CT *
>
>
> *Where: *Talk will be given *live, in-person* at
>
> TTIC, 6045 S. Kenwood Avenue
>
> 5th Floor, Room 530
>
>
> *Virtually:* *via* Panopto (*livestream
> <https://uchicago.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=5bf55682-3277-427c-b608-af9c017082e4>*
> )
>
>
> *Who: * Lydia T. Liu, Cornell University
>
>
> ------------------------------
>
> *Title: *Towards Responsible Machine Learning in Societal Systems
>
> *Abstract:* Machine learning systems are deployed in consequential
> domains such as education, employment, and credit, where decisions have
> profound effects on socioeconomic opportunity and life outcomes. High
> stakes decision settings present new statistical, algorithmic, and ethical
> challenges. In this talk, we examine the distributive impact of machine
> learning algorithms in societal contexts, and investigate the algorithmic
> and sociotechnical interventions that bring machine learning systems into
> alignment with societal values---equity and long-term welfare. First, we
> study the dynamic interactions between machine learning algorithms and
> populations, for the purpose of mitigating disparate impact in applications
> such as algorithmic lending and hiring. Next, we consider data-driven
> decision systems in competitive environments such as markets, and devise
> learning algorithms to ensure efficiency and allocative fairness. We end by
> outlining future directions for responsible machine learning in societal
> systems that bridge the gap between the optimization of predictive models
> and the evaluation of downstream decisions and impact.
>
>
> *Bio: *Lydia T. Liu is a postdoctoral researcher in Computer Science at
> Cornell University, working with Jon Kleinberg, Karen Levy, and Solon
> Barocas. Her research examines the theoretical foundations of machine
> learning and algorithmic decision-making, with a focus on societal impact
> and human welfare. She obtained her PhD in Electrical Engineering and
> Computer Sciences from UC Berkeley, advised by Moritz Hardt and Michael
> Jordan, and has received a Microsoft Ada Lovelace Fellowship, an Open
> Philanthropy AI Fellowship, an NUS Development Grant, and a Best Paper
> Award at the International Conference on Machine Learning.
>
>
> *Host: Avrim Blum <avrim at ttic.edu>*
>
>
>
>
>
> Mary C. Marre
> Faculty Administrative Support
> *Toyota Technological Institute*
> *6045 S. Kenwood Avenue, Rm 517*
> *Chicago, IL 60637*
> *773-834-1757*
> *mmarre at ttic.edu <mmarre at ttic.edu>*
>
>
> On Wed, Feb 1, 2023 at 4:27 PM Mary Marre <mmarre at ttic.edu> wrote:
>
>> *When:* Wednesday, February 8th at *11:30** a**m CT *
>>
>>
>> *Where: *Talk will be given *live, in-person* at
>>
>> TTIC, 6045 S. Kenwood Avenue
>>
>> 5th Floor, Room 530
>>
>>
>> *Virtually:* *via* Panopto (*livestream
>> <https://uchicago.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=5bf55682-3277-427c-b608-af9c017082e4>*
>> )
>>
>>
>> *Who: * Lydia T. Liu, Cornell University
>>
>>
>> ------------------------------
>>
>> *Title: *Towards Responsible Machine Learning in Societal Systems
>>
>> *Abstract:* Machine learning systems are deployed in consequential
>> domains such as education, employment, and credit, where decisions have
>> profound effects on socioeconomic opportunity and life outcomes. High
>> stakes decision settings present new statistical, algorithmic, and ethical
>> challenges. In this talk, we examine the distributive impact of machine
>> learning algorithms in societal contexts, and investigate the algorithmic
>> and sociotechnical interventions that bring machine learning systems into
>> alignment with societal values---equity and long-term welfare. First, we
>> study the dynamic interactions between machine learning algorithms and
>> populations, for the purpose of mitigating disparate impact in applications
>> such as algorithmic lending and hiring. Next, we consider data-driven
>> decision systems in competitive environments such as markets, and devise
>> learning algorithms to ensure efficiency and allocative fairness. We end by
>> outlining future directions for responsible machine learning in societal
>> systems that bridge the gap between the optimization of predictive models
>> and the evaluation of downstream decisions and impact.
>>
>>
>> *Bio: *Lydia T. Liu is a postdoctoral researcher in Computer Science at
>> Cornell University, working with Jon Kleinberg, Karen Levy, and Solon
>> Barocas. Her research examines the theoretical foundations of machine
>> learning and algorithmic decision-making, with a focus on societal impact
>> and human welfare. She obtained her PhD in Electrical Engineering and
>> Computer Sciences from UC Berkeley, advised by Moritz Hardt and Michael
>> Jordan, and has received a Microsoft Ada Lovelace Fellowship, an Open
>> Philanthropy AI Fellowship, an NUS Development Grant, and a Best Paper
>> Award at the International Conference on Machine Learning.
>>
>>
>> *Host: Avrim Blum <avrim at ttic.edu>*
>>
>>
>>
>>
>>
>>
>> Mary C. Marre
>> Faculty Administrative Support
>> *Toyota Technological Institute*
>> *6045 S. Kenwood Avenue, Rm 517*
>> *Chicago, IL 60637*
>> *773-834-1757*
>> *mmarre at ttic.edu <mmarre at ttic.edu>*
>>
>
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