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A Systematic Literature Review on AI Safety: Identifying Trends, Challenges, and Future Directions
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A Systematic Literature Review on AI Safety: Identifying Trends, Challenges, and Future Directions (2024)A Systematic Literature Review on AI Safe…Updating guidance for reporting systematic reviews: development of the PRISMA 2020 statement (2021)Updating guidance for reporti…PRISMA 2020 explanation and elaboration: updated guidance and exemplars for reporting systematic reviews (2021)PRISMA 2020 explanation and e…Linking Human And Machine Behavior: A New Approach to Evaluate Training Data Quality for Beneficial Machine Learning (2021)Linking Human And Machine Beh…Human-Centered Artificial Intelligence: Three Fresh Ideas (2020)Human-Centered Artificial Int…Human-Centered Artificial Intelligence: Reliable, Safe & Trustworthy (2020)Human-Centered Artificial Int…Multiparty Dynamics and Failure Modes for Machine Learning and Artificial Intelligence (2019)Multiparty Dynamics and Failu…How to carry out a literature search for a systematic review: a practical guide (2018)How to carry out a literature…Optimal database combinations for literature searches in systematic reviews: a prospective exploratory study (2017)Optimal database combinations…Counterfactual Fairness (2017)Counterfactual FairnessAgnostic Learning with Unknown Utilities (2016)Agnostic Learning with Unknow…Fairness through awareness (2012)Fairness through awarenessFairness-aware Learning through Regularization Approach (2011)Fairness-aware Learning throu…Discrimination-aware data mining (2008)Three naive Bayes approaches for discrimination-free classification (2010)A Reductions Approach to Fair Classification (2018)Fairness in Recommendation Ranking through Pairwise Comparisons (2019)A snapshot of the frontiers of fairness in machine learning (2020)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 Survey on Bias and Fairness in Machine Learning (2021)The second machine age: work, progress, and prosperity in a time of brilliant technologies (2015)The future of employment: How susceptible are jobs to computerisation? 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References

  • 2021PRISMA 2020 explanation and elaboration: updated guidance and exemplars for reporting systematic reviews11,660 cited
  • 2012Fairness through awareness3,501 cited
  • 2021Updating guidance for reporting systematic reviews: development of the PRISMA 2020 statement3,479 cited
  • 2017Optimal database combinations for literature searches in systematic reviews: a prospective exploratory study2,104 cited
  • 2020Human-Centered Artificial Intelligence: Reliable, Safe & Trustworthy1,724 cited
  • 2016Agnostic Learning with Unknown Utilities1,314 cited
  • 2017Counterfactual Fairness995 cited
  • 2020Human-Centered Artificial Intelligence: Three Fresh Ideas427 cited
  • 2011Fairness-aware Learning through Regularization Approach375 cited
  • 2018How to carry out a literature search for a systematic review: a practical guide155 cited
  • 2019Multiparty Dynamics and Failure Modes for Machine Learning and Artificial Intelligence49 cited
  • 2021Linking Human And Machine Behavior: A New Approach to Evaluate Training Data Quality for Beneficial Machine Learning47 cited

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