Devansh Saxena
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View article: ADMAPS Lifecycle Checklist (v1)
ADMAPS Lifecycle Checklist (v1) Open
This record contains two complementary artifacts derived from the ADMAPS framework for high-stakes public-sector algorithmic decision-making: (1) A one-page operational lifecycle checklist for audits, design reviews, procurement, and post-…
View article: ADMAPS Lifecycle Checklist (v1)
ADMAPS Lifecycle Checklist (v1) Open
This record contains two complementary artifacts derived from the ADMAPS framework for high-stakes public-sector algorithmic decision-making: (1) A one-page operational lifecycle checklist for audits, design reviews, procurement, and post-…
View article: Measurement as Bricolage: Examining How Data Scientists Construct Target Variables for Predictive Modeling Tasks
Measurement as Bricolage: Examining How Data Scientists Construct Target Variables for Predictive Modeling Tasks Open
Data scientists often formulate predictive modeling tasks involving fuzzy, hard-to-define concepts, such as the ''authenticity'' of student writing or the ''healthcare need'' of a patient. Yet the process by which data scientists translate…
View article: Making the Right Thing: Bridging HCI and Responsible AI in Early-Stage AI Concept Selection
Making the Right Thing: Bridging HCI and Responsible AI in Early-Stage AI Concept Selection Open
AI projects often fail due to financial, technical, ethical, or user acceptance challenges -- failures frequently rooted in early-stage decisions. While HCI and Responsible AI (RAI) research emphasize this, practical approaches for identif…
View article: The Datafication of Care in Public Homelessness Services
The Datafication of Care in Public Homelessness Services Open
Homelessness systems in North America adopt coordinated data-driven approaches to efficiently match support services to clients based on their assessed needs and available resources. AI tools are increasingly being implemented to allocate …
View article: Emerging Practices in Participatory AI Design in Public Sector Innovation
Emerging Practices in Participatory AI Design in Public Sector Innovation Open
Local and federal agencies are rapidly adopting AI systems to augment or automate critical decisions, efficiently use resources, and improve public service delivery. AI systems are being used to support tasks associated with urban planning…
View article: AI Mismatches: Identifying Potential Algorithmic Harms Before AI Development
AI Mismatches: Identifying Potential Algorithmic Harms Before AI Development Open
AI systems are often introduced with high expectations, yet many fail to deliver, resulting in unintended harm and missed opportunities for benefit. We frequently observe significant "AI Mismatches", where the system's actual performance f…
View article: Are We Asking the Right Questions?: Designing for Community Stakeholders’ Interactions with AI in Policing
Are We Asking the Right Questions?: Designing for Community Stakeholders’ Interactions with AI in Policing Open
Research into recidivism risk prediction in the criminal legal system has garnered significant attention from HCI, critical algorithm studies, and the emerging field of human-AI decision-making. This study focuses on algorithmic crime mapp…
View article: Beyond Predictive Algorithms in Child Welfare
Beyond Predictive Algorithms in Child Welfare Open
Caseworkers in the child welfare (CW) sector use predictive decision-making algorithms built on risk assessment (RA) data to guide and support CW decisions. Researchers have highlighted that RAs can contain biased signals which flatten CW …
View article: Algorithmic Harms in Child Welfare: Uncertainties in Practice, Organization, and Street-level Decision-making
Algorithmic Harms in Child Welfare: Uncertainties in Practice, Organization, and Street-level Decision-making Open
Algorithms in public services such as child welfare, criminal justice, and education are increasingly being used to make high-stakes decisions about human lives. Drawing upon findings from a two-year ethnography conducted at a child welfar…
View article: Algorithmic Harms in Child Welfare: Uncertainties in Practice, Organization, and Street-level Decision-Making
Algorithmic Harms in Child Welfare: Uncertainties in Practice, Organization, and Street-level Decision-Making Open
Algorithms in public services such as child welfare, criminal justice, and education are increasingly being used to make high-stakes decisions about human lives. Drawing upon findings from a two-year ethnography conducted at a child welfar…
View article: 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 Open
Risk assessment algorithms are being adopted by public sector agencies to make high-stakes decisions about human lives. Algorithms model "risk" based on individual client characteristics to identify clients most in need. However, this unde…
View article: 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 Open
Risk assessment algorithms are being adopted by public sector agencies to make high-stakes decisions about human lives. Algorithms model "risk" based on individual client characteristics to identify clients most in need. However, this unde…
View article: Designing Human-Centered Algorithms for the Public Sector A Case Study of the U.S. Child-Welfare System
Designing Human-Centered Algorithms for the Public Sector A Case Study of the U.S. Child-Welfare System Open
The U.S. Child Welfare System (CWS) is increasingly seeking to emulate\nbusiness models of the private sector centered in efficiency, cost reduction,\nand innovation through the adoption of algorithms. These data-driven systems\npurportedl…
View article: How to Train a (Bad) Algorithmic Caseworker: A Quantitative Deconstruction of Risk Assessments in Child Welfare
How to Train a (Bad) Algorithmic Caseworker: A Quantitative Deconstruction of Risk Assessments in Child Welfare Open
Child welfare (CW) agencies use risk assessment tools as a means to achieve evidence-based, consistent, and unbiased decision-making. These risk assessments act as data collection mechanisms and have been further developed into algorithmic…
View article: How to Train a (Bad) Algorithmic Caseworker: A Quantitative Deconstruction of Risk Assessments in Child-Welfare
How to Train a (Bad) Algorithmic Caseworker: A Quantitative Deconstruction of Risk Assessments in Child-Welfare Open
Child welfare (CW) agencies use risk assessment tools as a means to achieve evidence-based, consistent, and unbiased decision-making. These risk assessments act as data collection mechanisms and have further evolved into algorithmic system…
View article: A Framework of High-Stakes Algorithmic Decision-Making for the Public Sector Developed through a Case Study of Child-Welfare
A Framework of High-Stakes Algorithmic Decision-Making for the Public Sector Developed through a Case Study of Child-Welfare Open
Algorithms have permeated throughout civil government and society, where they are being used to make high-stakes decisions about human lives. In this paper, we first develop a cohesive framework of algorithmic decision-making adapted for t…
View article: A Framework of High-Stakes Algorithmic Decision-Making for the Public\n Sector Developed through a Case Study of Child-Welfare
A Framework of High-Stakes Algorithmic Decision-Making for the Public\n Sector Developed through a Case Study of Child-Welfare Open
Algorithms have permeated throughout civil government and society, where they\nare being used to make high-stakes decisions about human lives. In this paper,\nwe first develop a cohesive framework of algorithmic decision-making adapted\nfo…
View article: Empowered Participatory Design in Algorithm Design for the U.S.Child-Welfare System
Empowered Participatory Design in Algorithm Design for the U.S.Child-Welfare System Open
The Child-Welfare System (CWS) in the United States has come under escalating public and media scrutiny because of the potential damage done to children who are inappropriately removed from the care of their parents [4].CWS has increasingl…
View article: A Human-Centered Review of Algorithms used within the U.S. Child Welfare System
A Human-Centered Review of Algorithms used within the U.S. Child Welfare System Open
The U.S. Child Welfare System (CWS) is charged with improving outcomes for foster youth; yet, they are overburdened and underfunded. To overcome this limitation, several states have turned towards algorithmic decision-making systems to red…
View article: A Human-Centered Review of the Algorithms used within the U.S. Child\n Welfare System
A Human-Centered Review of the Algorithms used within the U.S. Child\n Welfare System Open
The U.S. Child Welfare System (CWS) is charged with improving outcomes for\nfoster youth; yet, they are overburdened and underfunded. To overcome this\nlimitation, several states have turned towards algorithmic decision-making\nsystems to …
View article: Confronting Autism in Urban Bangladesh: Unpacking Infrastructural and Cultural Challenges
Confronting Autism in Urban Bangladesh: Unpacking Infrastructural and Cultural Challenges Open
Autism Spectrum Disorder (ASD) is a critical problem worldwide; however, low and middle-income countries (LMICs) often suffer more from it due to the lack of contextual research and effective care infrastructure. Moreover, ASD in LMICs off…