1.- The Toronto Declaration: Protecting the right to equality and non-discrimination in machine learning systems
F: The-Toronto-Declaration_ENG_08-2018.pdf
2.- An Extensive Study on Data Anonymization Algorithms Based on K-Anonymity
F: An Extensive Study on Data Anonymization Algorithms Based on K-Anonymity.pdf
3.- A Theory of Creepy: Technology, Privacy and Shifting Social Norms
W: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2326830
4.- Artificial intelligence the global landscape of ethics guidelines
W: https://arxiv.org/ftp/arxiv/papers/1906/1906.11668.pdf
5.- A Value-Sensitive Design Approach to Augmented Reality
F: https://faculty.washington.edu/pkahn/articles/New_Directions.pdf
6.- Computing ethics values in design
W: https://escholarship.org/uc/item/1nd0p7hh
7.- Ethical issues in empirical studies of software engineering
W: https://ieeexplore.ieee.org/document/1158289
8.- Ethics in Information Technology and Software Use
W: https://www.jstor.org/stable/25075213
9.- Hedonic and ergonomic quality aspects determine a software's appeal
W: https://dl.acm.org/doi/10.1145/332040.332432
10.- The ethics of algorithms: Mapping the debate
W: https://journals.sagepub.com/doi/full/10.1177/2053951716679679
11.- Algorithmic Equity Toolkit – ACLU Washington
W: https://www.aclu-wa.org/AEKit
12.- Principled Artificial Intelligence: Mapping Consensus in Ethical and Rights - based Approaches to Principles for AI
W: https://dash.harvard.edu/bitstream/handle/1/42160420/HLS%20White%20Paper%20Final_v3.pdf?sequence=1&isAllowed=y
1.- Modelling the social dynamics of moral enhancement: social strategies sold over-the-counter and the stability of society*
W: https://ora.ox.ac.uk/objects/uuid:afeef153-75ff-4ccd-8298-e7b48f0b5893/download_file?file_format=pdf&safe_filename=Fabiano_and_Sandberg_2017.pdf&type_of_work=Journal+article
2.- Image Representations Learned With Unsupervised Pre-Training Contain Human-like Biases
W: https://arxiv.org/abs/2010.15052
3.- Socially Fair k-Means Clustering
W: https://arxiv.org/abs/2006.10085
4.- The relationship between trust in AI and trustworthy machine learning technologies
W: https://arxiv.org/abs/1912.00782
5.- The Social Cost of Strategic Classification
W:https://arxiv.org/abs/1808.08460
6.- Towards Fair Deep Anomaly Detection
W: https://arxiv.org/abs/2012.14961
7.- Biases in Generative Art -- A Causal Look from the Lens of Art History
W: https://arxiv.org/abs/2010.13266
8.- Can You Fake It Until You Make It?: Impacts of Di�erentially Private Synthetic Data on Downstream Classification Fairness FAccT ’21
W:https://openreview.net/forum?id=Ov9804iqM6r
9.- Designing an Online Infrastructure for Collecting AI Data From People With Disabilities
F: https://hci.stanford.edu/publications/2021/park_inclusiveAI/FAccT21_Inclusive_AI_Dataset.pdf
10.- Evaluating Fairness of Machine Learning Models Under Uncertain and Incomplete Information
W: https://arxiv.org/abs/2102.08410
11.- Towards Fairer Datasets: Filtering and Balancing the Distribution of the People Subtree in the ImageNet Hierarchy
W: https://arxiv.org/abs/1912.07726
12.- A Moral Framework for Understanding Fair ML through Economic Models of Equality of Opportunity
W: https://las.inf.ethz.ch/files/fat-main.pdf
1.- The Anatomy of Bias How Neural Circuits Weigh the Options
W: https://mitpress.mit.edu/books/anatomy-bias
2.- Bias in Computer Systems
F: https://nissenbaum.tech.cornell.edu/papers/Bias%20in%20Computer%20Systems.pdf
3.- Bias in algorithmic filtering and personalization
W: https://link.springer.com/article/10.1007/s10676-013-9321-6
4.- Algorithmic Bias
W: https://articlegateway.com/index.php/JLAE/article/view/170
1.- “Digital Transformation and Ethics” by Kirchschläger
W: https://sbeonline.org/2021/08/kirchschlager/
2.- Responsible AI in Consumer Enterprise
W: https://static1.squarespace.com/static/5d387c126be524000116bbdb/t/5d77e37092c6df3a5151c866/1568138185862/Ethics-of-artificial-intelligence.pdf
3.- Everyday Ethics for Artificial Intelligence - IBM
W: https://www.ibm.com/watson/assets/duo/pdf/everydayethics.pdf
1.- HIGH-LEVEL EXPERT GROUP ON ARTIFICIAL INTELLIGENCE
F: https://www.aepd.es/sites/default/files/2019-12/ai-definition.pdf
2.- Understanding artificial intelligence ethics and safety: A guide for the responsible design and implementation of AI systems in the public sector
W: https://zenodo.org/record/3240529#.YfBGj2AyFTb
1.- Computing and Moral Responsibility - Stanford
W:https://plato.stanford.edu/entries/computing-responsibility/
2.- Moral Reasoning - Stanford
W: https://plato.stanford.edu/entries/reasoning-moral/
3.- Virtue Ethics - Stanford
W: https://plato.stanford.edu/entries/ethics-virtue/
1.- Unnatural Selection: The Challenges of Engineering Tomorrow's People (The Earthscan Science in Society Series) W: https://www.amazon.co.uk/d/cka/Unnatural-Selection-Challenges-Engineering-Tomorrows-Earthscan-Science/1844076229
2.- Whole Brain Emulation A Roadmap W: http://www.fhi.ox.ac.uk/reports/2008-3.pdf
1.- AI Ethics - By Mark Coeckelbergh
W: https://mitpress.mit.edu/books/ai-ethics
2.- Embodying Values in Technology: Theory and Practice - Cambridge
W: https://www.cambridge.org/core/books/abs/information-technology-and-moral-philosophy/embodying-values-in-technology-theory-and-practice/14500603971A7DCF628026A240189CE0
3.- Human values, ethics and design
W: https://depts.washington.edu/hints/publications/Human_Values_Ethics_Design.pdf
4.- Value Sensitive Design Shaping Technology with Moral Imagination
W: https://mitpress.mit.edu/books/value-sensitive-design