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The AI life cycle: a holistic approach to creating ethical AI for health decisions
4 references·1 citing·22 second hop
The AI life cycle: a holistic approach to creating ethical AI for health decisions (2022)The AI life cycle: a holistic approach to…Peeking into a black box, the fairness and generalizability of a MIMIC-III benchmarking model (2022)Peeking into a black box, the…Jury Learning: Integrating Dissenting Voices into Machine Learning Models (2022)Jury Learning: Integrating Di…An empirical characterization of fair machine learning for clinical risk prediction (2020)An empirical characterization…Dissecting racial bias in an algorithm used to manage the health of populations (2019)Dissecting racial bias in an …Picture a data scientist: a call to action for increasing diversity, equity, and inclusion in the age of AI (2022)Picture a data scientist: a c…Big Data's Disparate Impact (2014)Fair Prediction with Disparate Impact: A Study of Bias in Recidivism Prediction Instruments (2017)Semantics derived automatically from language corpora contain human-like biases (2017)Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence (2020)Addressing bias in big data and AI for health care: A call for open science (2021)Algorithmic Bias in Education (2021)Demarginalizing the Intersection of Race and Sex: A Black Feminist Critique of Antidiscrimination Doctrine, Feminist Theory, and Antiracist Politics (1998)Demarginalizing the Intersection of Race and Sex: A Black Feminist Critique of Antidiscrimination Doctrine, Feminist Theory, and Antiracist Politics [1989] (2018)Mitigating Racial And Ethnic Bias And Advancing Health Equity In Clinical Algorithms: A Scoping Review (2023)Towards Risk‐Free Trustworthy Artificial Intelligence: Significance and Requirements (2023)A toolbox for surfacing health equity harms and biases in large language models (2024)Implicit bias in healthcare professionals: a systematic review (2017)Data Feminism (2020)Auditing and Generating Synthetic Data with Controllable Trust Trade-offs (2024)The Impact of Race, Ethnicity, and Sex on Fairness in Artificial Intelligence for Glaucoma Prediction Models (2024)Fairness through awareness (2012)A Survey on Bias and Fairness in Machine Learning (2021)Understanding Practices, Challenges, and Opportunities for User-Engaged Algorithm Auditing in Industry Practice (2023)Collective Constitutional AI: Aligning a Language Model with Public Input (2024)Farsight: Fostering Responsible AI Awareness During AI Application Prototyping (2024)AI can be sexist and racist — it’s time to make it fair (2018)The gender gap in science: How long until women are equally represented? (2018)
this work references cited by second hop

References

  • 2019Dissecting racial bias in an algorithm used to manage the health of populations7,086 cited
  • 2020An empirical characterization of fair machine learning for clinical risk prediction165 cited
  • 2022Jury Learning: Integrating Dissenting Voices into Machine Learning Models136 cited
  • 2022Peeking into a black box, the fairness and generalizability of a MIMIC-III benchmarking model73 cited

Cited by

  • 2022Picture a data scientist: a call to action for increasing diversity, equity, and inclusion in the age of AI40 cited

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