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Best Practices for Transparency in Machine Generated Personalization
13 references·2 citing·49 second hop
Best Practices for Transparency in Machine Generated Personalization (2020)Best Practices for Transparency in Machin…The Problem of Online Manipulation (2019)The Problem of Online Manipul…Online Manipulation: Hidden Influences in a Digital World (2018)Online Manipulation: Hidden I…Gender Shades: Intersectional Accuracy Disparities in Commercial Gender Classification (2018)Gender Shades: Intersectional…Explaining the privacy paradox: A systematic review of literature investigating privacy attitude and behavior (2018)Explaining the privacy parado…AI4People—An Ethical Framework for a Good AI Society: Opportunities, Risks, Principles, and Recommendations (2018)AI4People—An Ethical Framewor…Fair, Transparent, and Accountable Algorithmic Decision-making Processes (2017)Fair, Transparent, and Accoun…Appraising Black-Boxed Technology: the Positive Prospects (2017)Appraising Black-Boxed Techno…Why a Right to Explanation of Automated Decision-Making Does Not Exist in the General Data Protection Regulation (2016)Why a Right to Explanation of…The ethics of algorithms: Mapping the debate (2016)The ethics of algorithms: Map…Seeing without knowing: Limitations of the transparency ideal and its application to algorithmic accountability (2016)Seeing without knowing: Limit…How the machine ‘thinks’: Understanding opacity in machine learning algorithms (2016)How the machine ‘thinks’: Und…The entanglement of trust and knowledge on the Web (2010)The entanglement of trust and…The ethics of information transparency (2009)The ethics of information tra…Preparing for an Era of Deepfakes and AI-Generated Ads: A Framework for Understanding Responses to Manipulated Advertising (2021)Preparing for an Era of Deepf…Ethics of AI in Education: Towards a Community-Wide Framework (2021)Ethics of AI in Education: To…International Encyclopedia of the Social Sciences. 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References

  • 2018AI4People—An Ethical Framework for a Good AI Society: Opportunities, Risks, Principles, and Recommendations5,876 cited
  • 2016The ethics of algorithms: Mapping the debate4,103 cited
  • 2016How the machine ‘thinks’: Understanding opacity in machine learning algorithms3,601 cited
  • 2018Gender Shades: Intersectional Accuracy Disparities in Commercial Gender Classification3,544 cited
  • 2016Seeing without knowing: Limitations of the transparency ideal and its application to algorithmic accountability2,008 cited
  • 2017Fair, Transparent, and Accountable Algorithmic Decision-making Processes749 cited
  • 2018Explaining the privacy paradox: A systematic review of literature investigating privacy attitude and behavior511 cited
  • 2009The ethics of information transparency431 cited
  • 2016Why a Right to Explanation of Automated Decision-Making Does Not Exist in the General Data Protection Regulation361 cited
  • 2018Online Manipulation: Hidden Influences in a Digital World340 cited
  • 2010The entanglement of trust and knowledge on the Web67 cited
  • 2019The Problem of Online Manipulation50 cited
  • 2017Appraising Black-Boxed Technology: the Positive Prospects41 cited

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  • 2021Ethics of AI in Education: Towards a Community-Wide Framework

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1,951 cited
  • 2021Preparing for an Era of Deepfakes and AI-Generated Ads: A Framework for Understanding Responses to Manipulated Advertising399 cited