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Rethinking "Risk" in Algorithmic Systems Through A Computational
  Narrative Analysis of Casenotes in Child-Welfare

Rethinking "Risk" in Algorithmic Systems Through A Computational Narrative Analysis of Casenotes in Child-Welfare

16 February 2023
Devansh Saxena
Erin Moon
Aryan Chaurasia
Yixin Guan
Shion Guha
ArXivPDFHTML

Papers citing "Rethinking "Risk" in Algorithmic Systems Through A Computational Narrative Analysis of Casenotes in Child-Welfare"

5 / 5 papers shown
Title
AI Mismatches: Identifying Potential Algorithmic Harms Before AI Development
AI Mismatches: Identifying Potential Algorithmic Harms Before AI Development
Devansh Saxena
Ji-Youn Jung
J. Forlizzi
Kenneth Holstein
J. Zimmerman
55
0
0
25 Feb 2025
The Situate AI Guidebook: Co-Designing a Toolkit to Support
  Multi-Stakeholder Early-stage Deliberations Around Public Sector AI Proposals
The Situate AI Guidebook: Co-Designing a Toolkit to Support Multi-Stakeholder Early-stage Deliberations Around Public Sector AI Proposals
Anna Kawakami
Amanda Coston
Haiyi Zhu
Hoda Heidari
Kenneth Holstein
31
23
0
29 Feb 2024
Machine Learning Uncertainty as a Design Material: A
  Post-Phenomenological Inquiry
Machine Learning Uncertainty as a Design Material: A Post-Phenomenological Inquiry
J. Benjamin
Arne Berger
Nick Merrill
James Pierce
25
91
0
11 Jan 2021
A Human-Centered Review of the Algorithms used within the U.S. Child
  Welfare System
A Human-Centered Review of the Algorithms used within the U.S. Child Welfare System
Devansh Saxena
Karla A. Badillo-Urquiola
Pamela J. Wisniewski
Shion Guha
46
104
0
07 Mar 2020
Dropout as a Bayesian Approximation: Representing Model Uncertainty in
  Deep Learning
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning
Y. Gal
Zoubin Ghahramani
UQCV
BDL
247
9,042
0
06 Jun 2015
1