These tools and metrics are designed to help AI actors develop and use trustworthy AI systems and applications that respect human rights and are fair, transparent, explainable, robust, secure and safe.
References on Machine Learning Ethics
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References about Machine Learning and Data Science discrimination, bias, ethics.
Discussion
Discussion
- AI Ethics on Reddit
- (HN) Attacking discrimination with smarter machine learning
- (HN) Cathy O’Neil on Weapons of Math Destruction
- (HN) on Neural Net Trained on Mugshots Predicts Criminals
- (HN) Justice.exe: Bias in Algorithmic sentencing
Podcast
Videos
- Ethics of Artificial Intelligence conference NYU 2016
- A Story of Discrimination and Unfairness – Aylin Caliskan 33c3 2016
- AI Now 2017 Symposium
- The Trouble with Bias – NIPS 2017 Keynote
- Eyeo 2018 – Meredith Whittaker – DATA GENESIS: AI’S PRIMORDIAL SOUP
- “Privacy: the Last Stand for Fair Algorithms” by Katharine Jarmul
Papers
- Bias in Computer Systems
- Equality of Opportunity in Supervised Learning
- Using sensitive personal data may be necessary for avoiding discrimination in data-driven decision models
- The Ethics of Artificial Intelligence
- Automated Inference on Criminality using Face Images
- Semantics derived automatically from language corpora contain human-like biases
- European Union regulations on algorithmic decision-making and a “right to explanation”
- Men Also Like Shopping: Reducing Gender Bias Amplification using Corpus-level Constraints
- Man is to Computer Programmer as Woman is to Homemaker? Debiasing Word Embeddings
- Deep neural networks are more accurate than humans at detecting sexual orientation from facial images.
- Delayed Impact of Fair Machine Learning
- Bias detectives: the researchers striving to make algorithms fair
- No Classification without Representation: Assessing Geodiversity Issues in Open Data Sets for the Developing World
Books
- Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy
- Interpretable Machine Learning A Guide for Making Black Box Models Explainable.
- Fairness and machine learning book
Articles
- Algorithms: AI’s creepy control must be open to inspection
- AI watchdog needed to regulate automated decision-making, say experts
- Scholars Delve Deeper Into The Ethics Of Artificial Intelligence
- ProPublica series on Machine Bias
- Artificial Intelligence’s White Guy Problem
- Neural Net Trained on Mugshots Predicts Criminals
- Attacking discrimination with smarter machine learning
- The Ethical Data Scientis
- Machine Bias
- Machine Bias – How We Analyzed the COMPAS Recidivism Algorithm
- ProPublica Responds to Company’s Critique of Machine Bias Story
- Are Machines Biased, or Are We Biased Against Machines?
- Artificial Intelligence’s White Guy Problem
- Buyer Beware: A hard look at police ‘threat scores.’
- Computer and Information Ethics
- Social Networking and Ethics
- Internet Research Ethics
- Search Engines and Ethics
- How a Machine Learns Prejudice
- Courts Are Using AI to Sentence Criminals. That Must Stop Now
- Sent to Prison by a Software Program’s Secret Algorithms
- Even artificial intelligence can acquire biases against race and gender
- Inspecting Algorithms for Bias
- If you’re not a white male, artificial intelligence’s use in healthcare could be dangerous
- Biased Algorithms Are Everywhere, and No One Seems to Care
- Turns Out Algorithms Are Racist
- Machines Taught by Photos Learn a Sexist View of Women
- How Tech Giants Are Devising Real Ethics for Artificial Intelligence
- New AI can guess whether you’re gay or straight from a photograph
- Something is wrong on the internet, on youtube automated videos by James Bridle
- Trump’s “extreme-vetting” software will discriminate against immigrants “under a veneer of objectivity,” say experts
- ACLU calls out Amazon, Washington Co. sheriff’s office for facial recognition tech
- This startup’s racial-profiling algorithm shows AI can be dangerous way before any robot apocalypse
- Facial recognition software is not ready for use by law enforcement
- Prescription: AI – Quartz series
- Amazon scraps secret AI recruiting tool that showed bias against women
- A skeptic’s guide to thinking about AI – on AI Now 2018
Others
- Machine ethics: The robot’s dilemma
- Morals and the machine
- Robotics: Ethics of artificial intelligence
- Do no harm, don’t discriminate: official guidance issued on robot ethics
- “RoboCop” assignment Columbia University NYPD’s “Stop, Question and Frisk” records
- Professor Satyen Kale Responds to ‘RoboCop’ Machine Learning Assignment
- White House document: Preparing for the Future of Artificial Intelligence
- Justice.exe – Educative Game
- mathwashing
- ConceptNet Numberbatch 17.04: better, less-stereotyped word vectors
- Research on Algorithmic Fairness, haverford
- NORMAN World’s first psychopath AI
- AI can be sexist and racist — it’s time to make it fair
Reports
- ARTIFICIAL INTELLIGENCE AND LIFE IN 2030 – 2016 Report
- AI Now Report 2018.pdf
- AI Now 2019 Discriminating Systems: Gender, Race, and Power in AI
Conferences, Workshops, Symposiums
- Workshop on Fairness, Accountability, and Transparency in Machine Learning
- AI Now
- Ethics of Artificial Intelligence
- Black in AI
- Algorithms and Explanations
- Machine Learning and the Law
- Ethics in Mathematics – Cambridge University
- AI Now 2018 Symposium – video
- AI Now 2019 Symposium – video
Classes
- Fairness in Machine Learning
- INFO 4270: ETHICS AND POLICY IN DATA SCIENCE
- CS109: Ethical Foundations of Computer Science
- An Introduction to Data Ethics
- Machine Learning Fairness by Google
Lists
- A critical reading list for engineers, designers, and policy makers
- Awesome-Machine-Learning-Interpretability
- Fast AI Ethics Resources
People and Organizations
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