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Lessons from Archives: Strategies for Collecting Sociocultural Data in Machine Learning
13 references·16 citing·47 second hop
Lessons from Archives: Strategies for Collecting Sociocultural Data in Machine Learning (2019)Lessons from Archives: Strategies for Col…The global landscape of AI ethics guidelines (2019)The global landscape of AI et…Model Cards for Model Reporting (2019)Model Cards for Model Reporti…Fairness and Abstraction in Sociotechnical Systems (2019)Fairness and Abstraction in S…An algorithm for removing sensitive information: Application to race-independent recidivism prediction (2019)An algorithm for removing sen…A Framework for Understanding Unintended Consequences of Machine Learning (2019)A Framework for Understanding…Word embeddings quantify 100 years of gender and ethnic stereotypes (2018)Word embeddings quantify 100 …Gender Recognition or Gender Reductionism? (2018)Gender Recognition or Gender …Documenting Regional Latino Arts and Culture: Case Studies for a Collaborative, Community-Oriented Approach (2013)Documenting Regional Latino A…Community Histories, Community Archives: Some Opportunities and Challenges1 (2007)Community Histories, Communit…ARCHIVAL PERILS: AN HISTORIAN’S PLAINT (2006)ARCHIVAL PERILS: AN HISTORIAN…Without consent: The ethics of disclosing personal information in public archives (1993)Without consent: The ethics o…Selecting and Appraising Archives and Manuscripts (1993)Selecting and Appraising Arch…A Modern archives reader: Basic readings on archival theory and practice (1984)A Modern archives reader: Bas…Generative Ai in EU Law: Liability, Privacy, Intellectual Property, and Cybersecurity (2024)Generative Ai in EU Law: Liab…Responsible AI in Africa (2023)Responsible AI in AfricaTowards Intersectionality in Machine Learning: Including More Identities, Handling Underrepresentation, and Performing Evaluation (2022)Towards Intersectionality in …Toward accountable human-centered AI: rationale and promising directions (2022)Toward accountable human-cent…The Worst of Both Worlds: A Comparative Analysis of Errors in Learning from Data in Psychology and Machine Learning (2022)The Worst of Both Worlds: A C…Value Cards (2021)Value CardsUnderstanding and Evaluating Racial Biases in Image Captioning (2021)Understanding and Evaluating …Softcite dataset: A dataset of software mentions in biomedical and economic research publications (2021)Softcite dataset: A dataset o…Retiring Adult: New Datasets for Fair Machine Learning (2021)Retiring Adult: New Datasets …Linking Human And Machine Behavior: A New Approach to Evaluate Training Data Quality for Beneficial Machine Learning (2021)Linking Human And Machine Beh…Ethical Data Curation for AI: An Approach based on Feminist Epistemology and Critical Theories of Race (2021)Ethical Data Curation for AI:…Data and its (dis)contents: A survey of dataset development and use in machine learning research (2021)Data and its (dis)contents: A…Computer Vision and Conflicting Values: Describing People with Automated Alt Text (2021)Computer Vision and Conflicti…REVISE: A Tool for Measuring and Mitigating Bias in Visual Datasets (2020)REVISE: A Tool for Measuring …Bringing the People Back In: Contesting Benchmark Machine Learning Datasets (2020)Bringing the People Back In: …Fair Generative Modeling via Weak Supervision (2019)Fair Generative Modeling via …Fairness through awareness (2012)Big Data's Disparate Impact (2014)Equality of Opportunity in Supervised Learning (2016)Achieving Fairness through Adversarial Learning: an Application to Recidivism Prediction (2018)Predictive Policing and the Politics of Patterns (2018)Algorithmic Political Bias in Artificial Intelligence Systems (2022)Semantics. 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References

  • 2019The global landscape of AI ethics guidelines6,172 cited
  • 2019Model Cards for Model Reporting2,653 cited
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  • 2018Word embeddings quantify 100 years of gender and ethnic stereotypes1,064 cited
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Cited by

  • 2021Retiring Adult: New Datasets for Fair Machine Learning93 cited
  • 2022Towards Intersectionality in Machine Learning: Including More Identities, Handling Underrepresentation, and Performing Evaluation

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  • 2021Value Cards71 cited
  • 2021Data and its (dis)contents: A survey of dataset development and use in machine learning research58 cited
  • 2024Generative Ai in EU Law: Liability, Privacy, Intellectual Property, and Cybersecurity57 cited
  • 2019Fair Generative Modeling via Weak Supervision52 cited
  • 2020Bringing the People Back In: Contesting Benchmark Machine Learning Datasets51 cited
  • 2021Ethical Data Curation for AI: An Approach based on Feminist Epistemology and Critical Theories of Race50 cited
  • 2021Linking Human And Machine Behavior: A New Approach to Evaluate Training Data Quality for Beneficial Machine Learning47 cited
  • 2022Toward accountable human-centered AI: rationale and promising directions46 cited
  • 2021Softcite dataset: A dataset of software mentions in biomedical and economic research publications39 cited
  • 2021Computer Vision and Conflicting Values: Describing People with Automated Alt Text38 cited
  • 2022The Worst of Both Worlds: A Comparative Analysis of Errors in Learning from Data in Psychology and Machine Learning35 cited