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Uncovering Bias in Personal Informatics
16 references·0 citing·45 second hopsampled
Uncovering Bias in Personal Informatics (2023)Uncovering Bias in Personal InformaticsA Review on Fairness in Machine Learning (2022)A Review on Fairness in Machi…The (Im)possibility of fairness (2021)The (Im)possibility of fairne…Addressing Fairness, Bias, and Appropriate Use of Artificial Intelligence and Machine Learning in Global Health (2021)Addressing Fairness, Bias, an…A Survey on Bias and Fairness in Machine Learning (2021)A Survey on Bias and Fairness…Towards Fairness in Visual Recognition: Effective Strategies for Bias Mitigation (2020)Towards Fairness in Visual Re…Fairness and Abstraction in Sociotechnical Systems (2019)Fairness and Abstraction in S…Addressing Bias in Artificial Intelligence in Health Care (2019)Addressing Bias in Artificial…Fairness definitions explained (2018)Fairness definitions explainedBias on the web (2018)Bias on the webMan is to Computer Programmer as Woman is to Homemaker? Debiasing Word Embeddings (2016)Man is to Computer Programmer…Racial/Ethnic Differences in Sleep Disturbances: The Multi-Ethnic Study of Atherosclerosis (MESA) (2015)Racial/Ethnic Differences in …StudentLife (2014)StudentLifeFairness through awareness (2012)Fairness through awarenessDiscrimination-aware data mining (2008)Discrimination-aware data min…Uniform Guidelines on Employee Selection Procedures (2007)Uniform Guidelines on Employe…Physicians’ Perceptions of Patients’ Social and Behavioral Characteristics and Race Disparities in Treatment Recommendations for Men With Coronary Artery Disease (2005)Physicians’ Perceptions of Pa…Reliability and Factor Analysis of the Epworth Sleepiness Scale (1992)Mortality Associated With Sleep Duration and Insomnia (2002)Practice Parameters for the Use of Actigraphy in the Assessment of Sleep and Sleep Disorders: An Update for 2007 (2007)The epidemiology of sleep and obesity (2017)Are sleep patterns influenced by race/ethnicity – a marker of relative advantage or disadvantage? Evidence to date (2019)Sleep Irregularity and Risk of Cardiovascular Events (2020)The Economics of Discrimination. (1972)Racial Profiling, Insurance Style: Insurance Redlining and the Uneven Development of Metropolitan Areas (2003)Black Job Applicants and the Hiring Officer's Race (2004)Concrete Problems in AI Safety (2016)Justice as Fairness: A Restatement (2002)Incorporating Fairness into Game Theory and Economics (2011)How the machine ‘thinks’: Understanding opacity in machine learning algorithms (2016)Princeton University Press (2017)Semantics derived automatically from language corpora contain human-like biases (2017)A Global Measure of Perceived Stress (1983)Development and validation of brief measures of positive and negative affect: The PANAS scales. (1988)The PHQ-9 (2001)Mobile Phone Sensor Correlates of Depressive Symptom Severity in Daily-Life Behavior: An Exploratory Study (2015)Personal Sensing: Understanding Mental Health Using Ubiquitous Sensors and Machine Learning (2017)Mental Health and Behavior of College Students During the Early Phases of the COVID-19 Pandemic: Longitudinal Smartphone and Ecological Momentary Assessment Study (2020)Measuring individual differences in implicit cognition: The implicit association test. (1998)Big Data's Disparate Impact (2014)The global landscape of AI ethics guidelines (2019)On the Opportunities and Risks of Foundation Models (2021)Equality of Opportunity in Supervised Learning (2016)Fair Prediction with Disparate Impact: A Study of Bias in Recidivism Prediction Instruments (2017)Model Cards for Model Reporting (2019)Algorithmic Bias in Education (2021)Some Elements of a Sociology of Translation: Domestication of the Scallops and the Fishermen of St Brieuc Bay (1984)Science in Action (1987)Science in Action: How to Follow Scientists and Engineers through Society (1988)The Ethics of AI Ethics: An Evaluation of Guidelines (2020)The Statistical Theory of Racism and Sexism. (1972)Gender Shades: Intersectional Accuracy Disparities in Commercial Gender Classification (2018)Connecting the dots in trustworthy Artificial Intelligence: From AI principles, ethics, and key requirements to responsible AI systems and regulation (2023)Fairness and Bias in Artificial Intelligence: A Brief Survey of Sources, Impacts, and Mitigation Strategies (2023)Complacency and Bias in Human Use of Automation: An Attentional Integration (2010)PROBAST: A Tool to Assess the Risk of Bias and Applicability of Prediction Model Studies (2018)Can AI Help Reduce Disparities in General Medical and Mental Health Care? (2019)Addressing bias in big data and AI for health care: A call for open science (2021)Updated Guidance on the Reporting of Race and Ethnicity in Medical and Science Journals (2021)Bias and Unfairness in Machine Learning Models: A Systematic Review on Datasets, Tools, Fairness Metrics, and Identification and Mitigation Methods (2023)Fairness in recommender systems: research landscape and future directions (2023)Mental-LLM (2024)
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References

  • 2021A Survey on Bias and Fairness in Machine Learning6,499 cited
  • 2012Fairness through awareness3,545 cited
  • 2016Man is to Computer Programmer as Woman is to Homemaker? Debiasing Word Embeddings1,853 cited
  • 2019Fairness and Abstraction in Sociotechnical Systems1,850 cited
  • 2014StudentLife1,170 cited
  • 2018Fairness definitions explained1,133 cited
  • 2015Racial/Ethnic Differences in Sleep Disturbances: The Multi-Ethnic Study of Atherosclerosis (MESA)918 cited
  • 2019Addressing Bias in Artificial Intelligence in Health Care778 cited
  • 2008Discrimination-aware data mining688 cited
  • 2022A Review on Fairness in Machine Learning620 cited
  • 2018Bias on the web439 cited
  • 2007Uniform Guidelines on Employee Selection Procedures403 cited
  • 2021Addressing Fairness, Bias, and Appropriate Use of Artificial Intelligence and Machine Learning in Global Health304 cited
  • 2020Towards Fairness in Visual Recognition: Effective Strategies for Bias Mitigation285 cited
  • 2021The (Im)possibility of fairness262 cited
  • 2005Physicians’ Perceptions of Patients’ Social and Behavioral Characteristics and Race Disparities in Treatment Recommendations for Men With Coronary Artery Disease

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