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Bias and Fairness Issues in Artificial Intelligence-driven Cybersecurity
10 references·0 citing·37 second hop
Bias and Fairness Issues in Artificial Intelligence-driven Cybersecurity (2024)Bias and Fairness Issues in Artificial In…Fairness and Bias in Artificial Intelligence: A Brief Survey of Sources, Impacts, and Mitigation Strategies (2023)Fairness and Bias in Artifici…A Review of Bias and Fairness in Artificial Intelligence. (2023)A Review of Bias and Fairness…The Role of Data and Artificial Intelligence in Driving Diversity, Equity, and Inclusion (2022)The Role of Data and Artifici…Algorithmic reparation (2021)Algorithmic reparationAI-Driven Cybersecurity: An Overview, Security Intelligence Modeling and Research Directions (2021)AI-Driven Cybersecurity: An O…Model Cards for Model Reporting (2019)Model Cards for Model Reporti…Epistemic Therapy for Bias in Automated Decision-Making (2019)Epistemic Therapy for Bias in…Fair Prediction with Disparate Impact: A Study of Bias in Recidivism Prediction Instruments (2017)Fair Prediction with Disparat…Big Data's Disparate Impact (2014)Big Data's Disparate ImpactPredictive Policing and Reasonable Suspicion (2012)Predictive Policing and Reaso…Fairness through awareness (2012)Equality of Opportunity in Supervised Learning (2016)Inherent Trade-Offs in the Fair Determination of Risk Scores (2016)Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD): The TRIPOD Statement (2015)Demarginalizing the Intersection of Race and Sex: A Black Feminist Critique of Antidiscrimination Doctrine, Feminist Theory, and Antiracist Politics [1989] (2018)Gender Shades: Intersectional Accuracy Disparities in Commercial Gender Classification (2018)Closing the AI accountability gap (2020)On the Opportunities and Risks of Foundation Models (2021)Man is to Computer Programmer as Woman is to Homemaker? Debiasing Word Embeddings (2016)Gaydar: Facebook friendships expose sexual orientation (2009)Three naive Bayes approaches for discrimination-free classification (2010)Private traits and attributes are predictable from digital records of human behavior (2013)How the machine ‘thinks’: Understanding opacity in machine learning algorithms (2016)The ethics of algorithms: Mapping the debate (2016)A theory of justice original edition (1971)Mapping the Margins: Intersectionality, Identity Politics, and Violence against Women of Color (1991)The Complexity of Intersectionality (2005)Ethics for the majority world: AI and the question of violence at scale (2022)The uselessness of AI ethics (2022)Considering Biased Data as Informative Artifacts in AI-Assisted Health Care (2023)Certifying and Removing Disparate Impact (2015)A Survey on Bias and Fairness in Machine Learning (2021)Ethics of AI in Education: Towards a Community-Wide Framework (2021)AI and ethical accounting: Navigating challenges and opportunities (2024)Bias and Fairness Addressing Discrimination in AI Systems (2024)Digital Revolution, Artificial Intelligence, and Ethical Challenges (2024)Demarginalizing the Intersection of Race and Sex: A Black Feminist Critique of Antidiscrimination Doctrine, Feminist Theory, and Antiracist Politics (2018)Dissecting racial bias in an algorithm used to manage the health of populations (2019)Should ChatGPT be biased? Challenges and risks of bias in large language models (2023)AI ‐driven adaptive learning for sustainable educational transformation (2024)Leveraging generative AI for urban digital twins: a scoping review on the autonomous generation of urban data, scenarios, designs, and 3D city models for smart city advancement (2024)Artificial intelligence, bureaucratic form, and discretion in public service (2020)Predict and Surveil (2020)Data Science and Analytics: An Overview from Data-Driven Smart Computing, Decision-Making and Applications Perspective (2021)Securing distributed systems: A survey on access control techniques for cloud, blockchain, IoT and SDN (2023)AI-Driven Supply Chain Transformation in Industry 5.0: Enhancing Resilience and Sustainability (2024)Artificial Intelligence: The Present and Future of Human Resources Recruitment and Selection Processes (2023)
this work references cited by second hop

References

  • 2014Big Data's Disparate Impact3,281 cited
  • 2019Model Cards for Model Reporting3,049 cited
  • 2017Fair Prediction with Disparate Impact: A Study of Bias in Recidivism Prediction Instruments2,270 cited
  • 2023Fairness and Bias in Artificial Intelligence: A Brief Survey of Sources, Impacts, and Mitigation Strategies1,148 cited
  • 2021AI-Driven Cybersecurity: An Overview, Security Intelligence Modeling and Research Directions549 cited
  • 2021Algorithmic reparation143 cited
  • 2012Predictive Policing and Reasonable Suspicion134 cited
  • 2023A Review of Bias and Fairness in Artificial Intelligence.63 cited
  • 2022The Role of Data and Artificial Intelligence in Driving Diversity, Equity, and Inclusion18 cited
  • 2019Epistemic Therapy for Bias in Automated Decision-Making16 cited

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