I am an applied scientist at Amazon Web Services
working on issues around Responsible AI. In July 2022 I completed a PhD
in Statistics at Carnegie Mellon University under the supervision of
Alexandra Chouldechova and Zachary Lipton.
During the PhD, I interned at Microsoft Research
working with Besmira Nushi, Kori Inkpen, and Eric Horvitz, and I spent
seven months working as a research fellow at the Partnership on AI with
Alice Xiang. Before joining CMU for my graduate studies, I was a student
at the Collegio Carlo Alberto and at the University of Torino, where I
was advised by Matteo Ruggiero. I received my ungraduate degree from the
University of Padova, with an Erasmus exchange at the École
Normale Supérieure de Cachan.
I am broadly interested in the application of statistical machine learning
methods to the
social sciences.
My current research is driven by the following two questions:
• How does sampling bias affect the data on which risk assessment instruments are trained and
and what are its consequences?
• How do experts integrate the recommendations made by risk assessment instruments into their
decision-making processes?
You can contact me at riccardofogliato [at] gmail [dot] com.
When I'm not injured, I run and log some miles (kms) on
Strava.
-
A Case for Humans-in-the-Loop: Decisions in the Presence of Misestimated Algorithmic Scores
Riccardo Fogliato*, Maria De-Arteaga*, and Alexandra Chouldechova (* co-first)
SSRN
-
maars
: an R
implementation of Models As Approximations
Riccardo Fogliato*, Shamindra Shrotriya*, and Arun Kumar Kuchibhotla (* co-first)
GitHub arXiv
talk @ useR!2021
Publications
- Homophily and Incentive Effects in Use of Algorithms
Riccardo Fogliato, Sina Fazelpour, Shantanu Gupta, Zachary Lipton, David Danks
CogSci 2022 arXiv
- Who Goes First? Influences of Human-AI Workflow on Decision Making in Clinical Imaging
Riccardo Fogliato, Shreya Chappidi, Michael Fitzke, Mark
Parkinson, Diane Wilson, Paul Fisher, Matthew Lungren, Eric
Horvitz, Kori Inkpen, Besmira Nushi
FAccT 2022 pdf arXiv
platform
- Racial Disparities in the Enforcement of Marijuana Violations in the US
Bradley Butcher, Chris Robinson, Miri Zilka, Riccardo Fogliato, Carolyn Ashurst, Adrian Weller
AIES 2022 arXiv code
- On the Validity of Arrest as a Proxy for Offense: Race and
the Likelihood of Arrest for Violent Crimes
Riccardo Fogliato, Alice Xiang, Zachary Lipton, Daniel Nagin, Alexandra Chouldechova
AIES 2021 (oral) arXiv ACM code
- The Impact of Algorithmic Risk Assessments on Human Predictions and its Analysis via Crowdsourcing
Studies
Riccardo Fogliato, Alexandra Chouldechova, Zachary Lipton
CSCW 2021 arXiv ACM data+code
- Uncertainty as a Form of Transparency: Measuring, Communicating, and Using Uncertainty
U.
Bhatt, Y. Zhang, J. AntorĂ¡n, Q.V. Liao, P. Sattigeri, R. Fogliato, G.G. Melançon, R. Krishnan, J.
Stanley,
O.
Tickoo, L. Nachman, R. Chunara, A. Weller, A. Xiang
AIES 2021 arXiv ACM
- Lessons from the Deployment of an Algorithmic Tool in Child Welfare
Riccardo
Fogliato*,
Maria De-Arteaga*, Alexandra Chouldechova (* co-first)
Fair & Responsible AI Workshop, CHI 2020
workshop
- A Case for Humans-in-the-Loop: Decisions in the Presence of Erroneous Algorithmic Scores
Maria De-Arteaga*, Riccardo Fogliato*, Alexandra Chouldechova (* co-first)
CHI 2020 arXiv ACM Medium
post
- Fairness Evaluation in the Presence of Biased Noisy Labels
Riccardo Fogliato, Max
G'Sell,
Alexandra Chouldechova
AISTATS 2020 arXiv PMLR
- TRAP: A Predictive Framework for Trail Running Assessment of Performance
Riccardo
Fogliato,
Natalia L. Oliveira, Ronald Yurko
Journal of Quantitative Analysis in Sports arXiv JQAS Talk @ MIT SSAC
† Best poster award at NESSIS 2019 and at CMSAC 2019 (1 of 4) poster
- Trajectories of Prescription Opioids Filled Over Time
J. Elmer, R. Fogliato, N.
Setia,
W.
Mui, M. Lynch, E. Hulsey, D. Nagin
PLOS one, 2019
PLOS
- Why PATTERN Should Not Be Used: The Perils of Using Algorithmic Risk Assessment Tools During
COVID-19
Riccardo Fogliato, Alice Xiang, Alexandra Chouldechova
Issue brief of the Partnership on AI
issue
brief