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Book ; Online: A Human-Centered Review of Algorithms in Decision-Making in Higher Education

McConvey, Kelly / Guha, Shion / Kuzminykh, Anastasia

2023

Abstract: The use of algorithms for decision-making in higher education is steadily growing, promising cost-savings to institutions and personalized service for students but also raising ethical challenges around surveillance, fairness, and interpretation of data. ...

Abstract	The use of algorithms for decision-making in higher education is steadily growing, promising cost-savings to institutions and personalized service for students but also raising ethical challenges around surveillance, fairness, and interpretation of data. To address the lack of systematic understanding of how these algorithms are currently designed, we reviewed an extensive corpus of papers proposing algorithms for decision-making in higher education. We categorized them based on input data, computational method, and target outcome, and then investigated the interrelations of these factors with the application of human-centered lenses: theoretical, participatory, or speculative design. We found that the models are trending towards deep learning, and increased use of student personal data and protected attributes, with the target scope expanding towards automated decisions. However, despite the associated decrease in interpretability and explainability, current development predominantly fails to incorporate human-centered lenses. We discuss the challenges with these trends and advocate for a human-centered approach.
Keywords	Computer Science - Human-Computer Interaction ; Computer Science - Artificial Intelligence ; Computer Science - Computers and Society
Subject code	006
Publishing date	2023-02-11
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Book ; Online: How to Train a (Bad) Algorithmic Caseworker

Saxena, Devansh / Repaci, Charlie / Sage, Melanie / Guha, Shion

A Quantitative Deconstruction of Risk Assessments in Child-Welfare

2022

Abstract: 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 systems in recent ... ...

Abstract	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 systems in recent years. Moreover, several of these algorithms have reinforced biased theoretical constructs and predictors because of the easy availability of structured assessment data. In this study, we critically examine the Washington Assessment of Risk Model (WARM), a prominent risk assessment tool that has been adopted by over 30 states in the United States and has been repurposed into more complex algorithms. We compared WARM against the narrative coding of casenotes written by caseworkers who used WARM. We found significant discrepancies between the casenotes and WARM data where WARM scores did not not mirror caseworkers' notes about family risk. We provide the SIGCHI community with some initial findings from the quantitative de-construction of a child-welfare algorithm.
Keywords	Computer Science - Human-Computer Interaction
Publishing date	2022-03-10
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Book ; Online: The Principles of Data-Centric AI (DCAI)

Jarrahi, Mohammad Hossein / Memariani, Ali / Guha, Shion

2022

Abstract: Data is a crucial infrastructure to how artificial intelligence (AI) systems learn. However, these systems to date have been largely model-centric, putting a premium on the model at the expense of the data quality. Data quality issues beset the ... ...

Abstract	Data is a crucial infrastructure to how artificial intelligence (AI) systems learn. However, these systems to date have been largely model-centric, putting a premium on the model at the expense of the data quality. Data quality issues beset the performance of AI systems, particularly in downstream deployments and in real-world applications. Data-centric AI (DCAI) as an emerging concept brings data, its quality and its dynamism to the forefront in considerations of AI systems through an iterative and systematic approach. As one of the first overviews, this article brings together data-centric perspectives and concepts to outline the foundations of DCAI. It specifically formulates six guiding principles for researchers and practitioners and gives direction for future advancement of DCAI. Comment: Forthcoming: The Communications of the ACM
Keywords	Computer Science - Machine Learning ; Computer Science - Artificial Intelligence ; Computer Science - Human-Computer Interaction ; E.0 ; I.2
Subject code	006
Publishing date	2022-11-26
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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

Saxena, Devansh / Moon, Erina Seh-Young / Chaurasia, Aryan / Guan, Yixin / Guha, Shion

2023

Abstract: 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 understanding of ... ...

Abstract	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 understanding of risk is primarily based on easily quantifiable risk factors that present an incomplete and biased perspective of clients. We conducted a computational narrative analysis of child-welfare casenotes and draw attention to deeper systemic risk factors that are hard to quantify but directly impact families and street-level decision-making. We found that beyond individual risk factors, the system itself poses a significant amount of risk where parents are over-surveilled by caseworkers and lack agency in decision-making processes. We also problematize the notion of risk as a static construct by highlighting the temporality and mediating effects of different risk, protective, systemic, and procedural factors. Finally, we draw caution against using casenotes in NLP-based systems by unpacking their limitations and biases embedded within them.
Keywords	Computer Science - Human-Computer Interaction
Publishing date	2023-02-16
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Book ; Online: Unpacking Invisible Work Practices, Constraints, and Latent Power Relationships in Child Welfare through Casenote Analysis

Saxena, Devansh / Moon, Erina Seh-Young / Shehata, Dahlia / Guha, Shion

2022

Abstract: Caseworkers are trained to write detailed narratives about families in Child-Welfare (CW) which informs collaborative high-stakes decision-making. Unlike other administrative data, these narratives offer a more credible source of information with respect ...

Abstract	Caseworkers are trained to write detailed narratives about families in Child-Welfare (CW) which informs collaborative high-stakes decision-making. Unlike other administrative data, these narratives offer a more credible source of information with respect to workers' interactions with families as well as underscore the role of systemic factors in decision-making. SIGCHI researchers have emphasized the need to understand human discretion at the street-level to be able to design human-centered algorithms for the public sector. In this study, we conducted computational text analysis of casenotes at a child-welfare agency in the midwestern United States and highlight patterns of invisible street-level discretionary work and latent power structures that have direct implications for algorithm design. Casenotes offer a unique lens for policymakers and CW leadership towards understanding the experiences of on-the-ground caseworkers. As a result of this study, we highlight how street-level discretionary work needs to be supported by sociotechnical systems developed through worker-centered design. This study offers the first computational inspection of casenotes and introduces them to the SIGCHI community as a critical data source for studying complex sociotechnical systems.
Keywords	Computer Science - Human-Computer Interaction ; Computer Science - Computers and Society
Subject code	360
Publishing date	2022-03-10
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Book ; Online: A Framework of High-Stakes Algorithmic Decision-Making for the Public Sector Developed through a Case Study of Child-Welfare

Saxena, Devansh / Badillo-Urquiola, Karla / Wisniewski, Pamela / Guha, Shion

2021

Abstract: 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 the public ... ...

Abstract	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 the public sector (ADMAPS) that reflects the complex socio-technical interactions between \textit{human discretion}, \textit{bureaucratic processes}, and \textit{algorithmic decision-making} by synthesizing disparate bodies of work in the fields of Human-Computer Interaction (HCI), Science and Technology Studies (STS), and Public Administration (PA). We then applied the ADMAPS framework to conduct a qualitative analysis of an in-depth, eight-month ethnographic case study of the algorithms in daily use within a child-welfare agency that serves approximately 900 families and 1300 children in the mid-western United States. Overall, we found there is a need to focus on strength-based algorithmic outcomes centered in social ecological frameworks. In addition, algorithmic systems need to support existing bureaucratic processes and augment human discretion, rather than replace it. Finally, collective buy-in in algorithmic systems requires trust in the target outcomes at both the practitioner and bureaucratic levels. As a result of our study, we propose guidelines for the design of high-stakes algorithmic decision-making tools in the child-welfare system, and more generally, in the public sector. We empirically validate the theoretically derived ADMAPS framework to demonstrate how it can be useful for systematically making pragmatic decisions about the design of algorithms for the public sector.
Keywords	Computer Science - Human-Computer Interaction ; Computer Science - Computers and Society
Subject code	006
Publishing date	2021-07-07
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Real-world clinical outcomes and treatment patterns in patients with MDD treated with vortioxetine: a retrospective study.

McDaniel, Brandon T / Cornet, Victor / Carroll, Jeanne / Chrones, Lambros / Chudzik, Joseph / Cochran, Jeanette / Guha, Shion / Lawrence, Debra F / McCue, Maggie / Sarkey, Sara / Lorenz, Betty / Fawver, Jay

BMC psychiatry

2023 Volume 23, Issue 1, Page(s) 938

Abstract: Background: This study included evaluation of the effectiveness of vortioxetine, a treatment for adults with major depressive disorder (MDD), using patient-reported outcome measures (PROMs) in a real-world setting.: Methods: This retrospective chart ... ...

Abstract	Background: This study included evaluation of the effectiveness of vortioxetine, a treatment for adults with major depressive disorder (MDD), using patient-reported outcome measures (PROMs) in a real-world setting. Methods: This retrospective chart review analyzed the care experiences of adult patients with a diagnosis of MDD from Parkview Physicians Group - Mind-Body Medicine, Midwestern United States. Patients with a prescription for vortioxetine, an initial baseline visit, and ≥ 2 follow-up visits within 16 weeks from September 2014 to December 2018 were included. The primary outcome measure was effectiveness of vortioxetine on depression severity as assessed by change in Patient Health Questionnaire-9 (PHQ-9) scores ~ 12 weeks after initiation of vortioxetine. Secondary outcomes included changes in depression-related symptoms (i.e., sexual dysfunction, sleep disturbance, cognitive function, work/social function), clinical characteristics, response, remission, and medication persistence. Clinical narrative notes were also analyzed to examine sleep disturbance, sexual dysfunction, appetite, absenteeism, and presenteeism. All outcomes were examined at index (start of vortioxetine) and at ~ 12 weeks, and mean differences were analyzed using pairwise t tests. Results: A total of 1242 patients with MDD met inclusion criteria, and 63.9% of these patients had ≥ 3 psychiatric diagnoses and 65.9% were taking ≥ 3 medications. PHQ-9 mean scores decreased significantly from baseline to week 12 (14.15 ± 5.8 to 9.62 ± 6.03, respectively; p < 0.001). At week 12, the response and remission rates in all patients were 31.0% and 23.1%, respectively, and 67% continued vortioxetine treatment. Overall, results also showed significant improvements by week 12 in anxiety (p < 0.001), sexual dysfunction (p < 0.01), sleep disturbance (p < 0.01), cognitive function (p < 0.001), work/social functioning (p = 0.021), and appetite (p < 0.001). A significant decrease in presenteeism was observed at week 12 (p < 0.001); however, no significant change was observed in absenteeism (p = 0.466). Conclusions: Using PROMs, our study results suggest that adults with MDD prescribed vortioxetine showed improvement in depressive symptoms in the context of a real-world clinical practice setting. These patients had multiple comorbid psychiatric and physical diagnoses and multiple previous antidepressant treatments had failed.
MeSH term(s)	Adult ; Humans ; Vortioxetine/therapeutic use ; Depressive Disorder, Major/psychology ; Retrospective Studies ; Antidepressive Agents/therapeutic use ; Sexual Dysfunction, Physiological ; Treatment Outcome ; Double-Blind Method
Chemical Substances	Vortioxetine (3O2K1S3WQV) ; Antidepressive Agents
Language	English
Publishing date	2023-12-13
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2050438-X
ISSN	1471-244X ; 1471-244X
ISSN (online)	1471-244X
ISSN	1471-244X
DOI	10.1186/s12888-023-05439-8
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Noninvasive Hemoglobin Level Prediction in a Mobile Phone Environment: State of the Art Review and Recommendations.

Hasan, Md Kamrul / Aziz, Md Hasanul / Zarif, Md Ishrak Islam / Hasan, Mahmudul / Hashem, Mma / Guha, Shion / Love, Richard R / Ahamed, Sheikh

JMIR mHealth and uHealth

2021 Volume 9, Issue 4, Page(s) e16806

Abstract: Background: There is worldwide demand for an affordable hemoglobin measurement solution, which is a particularly urgent need in developing countries. The smartphone, which is the most penetrated device in both rich and resource-constrained areas, would ... ...

Abstract	Background: There is worldwide demand for an affordable hemoglobin measurement solution, which is a particularly urgent need in developing countries. The smartphone, which is the most penetrated device in both rich and resource-constrained areas, would be a suitable choice to build this solution. Consideration of a smartphone-based hemoglobin measurement tool is compelling because of the possibilities for an affordable, portable, and reliable point-of-care tool by leveraging the camera capacity, computing power, and lighting sources of the smartphone. However, several smartphone-based hemoglobin measurement techniques have encountered significant challenges with respect to data collection methods, sensor selection, signal analysis processes, and machine-learning algorithms. Therefore, a comprehensive analysis of invasive, minimally invasive, and noninvasive methods is required to recommend a hemoglobin measurement process using a smartphone device. Objective: In this study, we analyzed existing invasive, minimally invasive, and noninvasive approaches for blood hemoglobin level measurement with the goal of recommending data collection techniques, signal extraction processes, feature calculation strategies, theoretical foundation, and machine-learning algorithms for developing a noninvasive hemoglobin level estimation point-of-care tool using a smartphone. Methods: We explored research papers related to invasive, minimally invasive, and noninvasive hemoglobin level measurement processes. We investigated the challenges and opportunities of each technique. We compared the variation in data collection sites, biosignal processing techniques, theoretical foundations, photoplethysmogram (PPG) signal and features extraction process, machine-learning algorithms, and prediction models to calculate hemoglobin levels. This analysis was then used to recommend realistic approaches to build a smartphone-based point-of-care tool for hemoglobin measurement in a noninvasive manner. Results: The fingertip area is one of the best data collection sites from the body, followed by the lower eye conjunctival area. Near-infrared (NIR) light-emitting diode (LED) light with wavelengths of 850 nm, 940 nm, and 1070 nm were identified as potential light sources to receive a hemoglobin response from living tissue. PPG signals from fingertip videos, captured under various light sources, can provide critical physiological clues. The features of PPG signals captured under 1070 nm and 850 nm NIR LED are considered to be the best signal combinations following a dual-wavelength theoretical foundation. For error metrics presentation, we recommend the mean absolute percentage error, mean squared error, correlation coefficient, and Bland-Altman plot. Conclusions: We addressed the challenges of developing an affordable, portable, and reliable point-of-care tool for hemoglobin measurement using a smartphone. Leveraging the smartphone's camera capacity, computing power, and lighting sources, we define specific recommendations for practical point-of-care solution development. We further provide recommendations to resolve several long-standing research questions, including how to capture a signal using a smartphone camera, select the best body site for signal collection, and overcome noise issues in the smartphone-captured signal. We also describe the process of extracting a signal's features after capturing the signal based on fundamental theory. The list of machine-learning algorithms provided will be useful for processing PPG features. These recommendations should be valuable for future investigators seeking to build a reliable and affordable hemoglobin prediction model using a smartphone.
MeSH term(s)	Algorithms ; Hemoglobins ; Humans ; Machine Learning ; Smartphone
Chemical Substances	Hemoglobins
Language	English
Publishing date	2021-04-08
Publishing country	Canada
Document type	Journal Article
ZDB-ID	2719220-9
ISSN	2291-5222 ; 2291-5222
ISSN (online)	2291-5222
ISSN	2291-5222
DOI	10.2196/16806
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Book ; Online: A Human-Centered Review of the Algorithms used within the U.S. Child Welfare System

Saxena, Devansh / Badillo-Urquiola, Karla / Wisniewski, Pamela J. / Guha, Shion

2020

Abstract: 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 reduce costs and ... ...

Abstract	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 reduce costs and determine better processes for improving CWS outcomes. Using a human-centered algorithmic design approach, we synthesize 50 peer-reviewed publications on computational systems used in CWS to assess how they were being developed, common characteristics of predictors used, as well as the target outcomes. We found that most of the literature has focused on risk assessment models but does not consider theoretical approaches (e.g., child-foster parent matching) nor the perspectives of caseworkers (e.g., case notes). Therefore, future algorithms should strive to be context-aware and theoretically robust by incorporating salient factors identified by past research. We provide the HCI community with research avenues for developing human-centered algorithms that redirect attention towards more equitable outcomes for CWS.
Keywords	Computer Science - Computers and Society ; Computer Science - Artificial Intelligence ; Computer Science - Human-Computer Interaction
Publishing date	2020-03-07
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Book ; Online: Methods for Generating Typologies of Non/use

Saxena, Devansh / Skeba, Patrick / Guha, Shion / Baumer, Eric P. S.

2020

Abstract: Prior studies of technology non-use demonstrate the need for approaches that go beyond a simple binary distinction between users and non-users. This paper proposes a set of two different methods by which researchers can identify types of non/use$^{1}$ ... ...

Abstract	Prior studies of technology non-use demonstrate the need for approaches that go beyond a simple binary distinction between users and non-users. This paper proposes a set of two different methods by which researchers can identify types of non/use$^{1}$ relevant to the particular sociotechnical settings they are studying. These methods are demonstrated by applying them to survey data about Facebook non/use. The results demonstrate that the different methods proposed here identify fairly comparable types of non/use. They also illustrate how the two methods make different trade offs between the granularity of the resulting typology and the total sample size. The paper also demonstrates how the different typologies resulting from these methods can be used in predictive modeling, allowing for the two methods to corroborate or disconfirm results from one another. The discussion considers implications and applications of these methods, both for research on technology non/use and for studying social computing more broadly.
Keywords	Computer Science - Human-Computer Interaction ; Computer Science - Computers and Society
Subject code	303 ; 310
Publishing date	2020-04-09
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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