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Author(s)URLTitle
Author(s) website (if applicable)
Category/KeywordsOther Notes
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Marcus and Davishttp://rebooting.ai/Book: Rebooting AI Book websiteAnalysis/History
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Gary Marcushttps://arxiv.org/pdf/2002.06177.pdfThe Next Decade in AI' paper - ARXIVAnalysis/Forecast/Proposal
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Varioushttps://arxiv.org/abs/2011.03395Underspecification Presents Challenges for Credibility in Modern Machine LearningUnderspecification
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Heaven, Williamhttps://bit.ly/2KiaHPpAI is wrestling with a replication crisisReplication Crisis
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Brevini, Pasqualehttps://journals.sagepub.com/page/bds/collections/revisitingtheblackboxsocietyRevisiting The Black Box Society by Rethinking the Political Economy of Big DataGPT-3
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Chiriatti, Floridihttps://www.readcube.com/articles/10.1007/s11023-020-09548-1GPT-3: Its Nature, Scope, Limits, and ConsequencesGPT-3
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Birhane, Guesthttps://arxiv.org/abs/2009.14258Towards decolonising computational sciencesAnalysis/Bias
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Chenhttps://bit.ly/3pMxN0SHow Silicon Valley’s successes are fueled by an underclass of ‘ghost workers’ - The VergeLabor Impact
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Noblehttps://nyupress.org/9781479837243/Book - 'Algorithms of Oppression'https://safiyaunoble.com/Analysis
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Heaven, Williamhttps://www.technologyreview.com/2020/11/18/1012234/training-machine-learning-broken-real-world-heath-nlp-computer-vision/The way we train AI is fundamentally flawedAI Training
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Varioushttps://youtu.be/cNKwH6wBpnIFake it Till You Make it: AI and HypeHype
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Varioushttps://mitpress.mit.edu/books/your-computer-fireBook: Your Computer is on FireAnalysis/History
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Bauer, Dorotheahttps://dorotheabaur.medium.com/four-reasons-why-hyping-ai-is-an-ethical-problem-8db47b17bf43Four reasons why hyping AI is an ethical problemHype
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Monett, Dagmar - othershttp://ceur-ws.org/Vol-2735/paper37.pdfIntelligence Catalog-guided Tracking of the Evolution of (machine) Intelligence: Preliminary resultsAnalysis/History
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Heaven, Douglashttps://www.nature.com/articles/d41586-020-00507-5Why faces don’t always tell the truth about feelingsFacial Recognition
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Perez, Caroloshttps://medium.com/intuitionmachine/the-many-doctrines-of-agi-research-af6d37feca47Map of AGI DoctrinesAnalysis/Industry
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Various (NVidia, Rice Univ)https://papers.nips.cc/paper/2020/file/bf15e9bbff22c7719020f9df4badc20a-Paper.pdfBONGARD-LOGO: A New Benchmark for Human-Level Concept Learning and ReasoningBenchmarks
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Marcushttps://www.zdnet.com/article/the-next-decade-in-ai-gary-marcus-four-steps-towards-robust-artificial-intelligence/What's next for AI: Gary Marcus talks about the journey toward robust artificial intelligenceRobust AI
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Raji, Deborahhttps://www.technologyreview.com/2020/12/10/1013617/racism-data-science-artificial-intelligence-ai-opinion/How our data encodes systematic racismRacism
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Mohamed Abdalla, Moustafa Abdallahttps://arxiv.org/abs/2009.13676The Grey Hoodie Project: Big Tobacco, Big Tech, and the threat on academic integrityAcademia
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Khari Johnsonhttps://venturebeat.com/2020/12/10/timnit-gebru-googles-dehumanizing-memo-paints-me-as-an-angry-black-woman/Timnit Gebru: Google’s ‘dehumanizing’ memo paints me as an angry Black womanTimnit Gebru
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Smith, Garyhttps://mindmatters.ai/2020/12/ai-still-just-curve-fitting-not-finding-a-theory-of-everything/AI: STILL JUST CURVE FITTING, NOT FINDING A THEORY OF EVERYTHINGCurve Fitting
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Hanna, Parkhttps://drive.google.com/file/d/1SNIobaYjgWvTjZGpMkhJCGvnA1oWKNms/viewAgainst Scale: Provocations and Resistances to Scale ThinkingScale
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Earl, Charleshttps://drive.google.com/file/d/1nRYUu_NgqncRpLVeBAcd1P9Iili0zd7g/viewTowards an Abolitionist’s AI: the role of HBCUsAI and HBCUs
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Paullada, Amandalynnehttps://drive.google.com/file/d/1wO5UOxTThrcCiU-gEJm_KBShxL_YXEXx/viewHow Does Machine Translation Shift Power?Power Analysis
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Butterman, Leehttps://drive.google.com/file/d/17YCcwaPtbRtKAYYved13NEYlXcTPJH4w/viewGPT-3 output as human rights violation collaboration, and resistance via GeDi class-conditional generative discriminationGPT-3
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Reddyhoff, Dennishttps://drive.google.com/file/d/1m9FRfoClzqflT2HjlNoOTsJw7OxcsMOc/viewDependency, Data and Decolonisation: A Framework for Decolonial Thinking in Collaborative AI ResearchDecolonization
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Hampton, Leilahttps://drive.google.com/file/d/1dJUBwtxQz-s81s_yLM20UvO_NyDnquiw/viewBlack Feminist Musings on Algorithmic Oppression (Or Rather a Blunt Rant from a Tired Black Feminist)Feminism
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Laufer, Benjamin Dhttps://drive.google.com/file/d/1z1tJoQ2SDN1VkzYn2uWI5gh98vrCW2f9/viewAbandoning Criminal Risk and Recidivism: On Dangerous Goals in ML Scoring-Decision SystemsRecidivism Algorithms
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Markup (magazine) staff
https://themarkup.org/2020-in-review/2020/12/15/algorithms-bias-racism-surveillance
Algorithms Behaving Badly: 2020 EditionAI Industy Impact Review
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PIEKNIEWSKI, FILIPhttps://blog.piekniewski.info/2020/12/30/ai-update-late-2020-dumpster-fire/AI Update, Late 2020 - Dumpster FireAI Industy Impact Review
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Henrik Skaug Sætrahttps://www.mdpi.com/2071-1050/13/4/1738AI in Context and the Sustainable Development Goals: Factoring in the Unsustainability of the Sociotechnical SystemSustainability
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Hawkins, Andrewhttps://www.theverge.com/2021/3/8/22315361/waymo-autonomous-vehicle-simulation-car-crash-deathsWaymo simulated real-world crashes to prove its self-driving cars can prevent deathsSelf-driving
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Bender, McMillan-Major, Gebru, Shmitchellhttp://faculty.washington.edu/ebender/papers/Stochastic_Parrots.pdfOn the Dangers of Stochastic Parrots: Can Language Models Be Too Big?Language Models
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Ho, Karen
https://www.technologyreview.com/2021/03/11/1020600/facebook-responsible-ai-misinformation/
How Facebook got addicted to spreading misinformationFacebook
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Henrik Skaug Sætrahttps://www.researchgate.net/publication/347749359_Confounding_Complexity_of_Machine_Action_A_Hobbesian_Account_of_Machine_ResponsibilityConfounding Complexity of Machine Action: A Hobbesian Account of Machine ResponsibilityAccountability
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Abeba Birhanehttps://bit.ly/3tZohJDAlgorithmic injustice: a relational ethics approachEthics
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ReportLinkerhttps://www.globenewswire.com/news-release/2021/03/19/2195963/0/en/The-Artificial-Intelligence-in-military-market-is-estimated-at-USD-6-3-billion-in-2020-and-is-projected-to-reach-USD-11-6-billion-by-2025-at-a-CAGR-of-13-1.htmlSummary of report: The Artificial Intelligence in military market is estimated at USD 6.3 billion in 2020 and is projected to reach USD 11.6 billion by 2025, at a CAGR of 13.1%Military
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Benanav, Aaronhttps://www.versobooks.com/books/3717-automation-and-the-future-of-workAutomation and the Future of Work
https://www.aaronbenanav.com/
Automationhttps://soundcloud.com/rhodescenter/the-robots-may-be-coming-but-probably-not-for-your-job
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Mitchell, Melaniehttps://arxiv.org/pdf/2104.12871.pdfWhy AI is Harder than We ThinkAI limits
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Tom Carduso and Bill Curryhttps://www.theglobeandmail.com/canada/article-national-defence-skirted-federal-rules-in-using-artificial/National Defence skirted federal rules in using artificial intelligenceMilitary
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Marcushttps://arxiv.org/pdf/1801.05667.pdfInnateness, AlphaZero, and Artificial IntelligenceInnateness
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Alkhatib, Alihttps://youtu.be/ClGIosevT0Y
To Live in Their Utopia: Why Algorithmic Systems Create Absurd Outcomes (video)
Impacts
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EU Commissionhttps://acmpstor.blob.core.windows.net/acmpblob1/Proposal-for-a-Regulation-a-European-approach-for-AI.pdfProposal for a Regulation - a European approach for AIEU Regulation
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Alkhatib, Alihttps://ali-alkhatib.com/papers/chi/utopia/utopia.pdf
To Live in Their Utopia: Why Algorithmic Systems Create Absurd Outcomes (Paper)
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Abeba Birhane, Jelle van Dijkhttps://arxiv.org/abs/2001.05046v1Robot Rights? Let's Talk about Human Welfare InsteadRobot rights
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Various authorshttps://www.nscai.gov/wp-content/uploads/2021/03/Full-Report-Digital-1.pdfNational Security Commission on Artificial IntelligenceGovernment commission review
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Angela Lashbrookhttps://www.theatlantic.com/health/archive/2018/08/machine-learning-dermatology-skin-color/567619/AI-Driven Dermatology Could Leave Dark-Skinned Patients BehindFacial Recognition
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Robert Epstein
https://aeon.co/essays/your-brain-does-not-process-information-and-it-is-not-a-computer
Your brain does not process information and it is not a computerCognitive science
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J. Khadijah Abdurahman
https://upfromthecracks.medium.com/on-the-moral-collapse-of-ai-ethics-791cbc7df872
On the Moral Collapse of AI EthicsAI Ethics
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Weintraub, PamYour brain does not process information and it is not a computer | Aeon EssaysYour brain does not process information and it is not a computerCognitive science
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Abeba Birhanehttps://acmpstor.blob.core.windows.net/acmpblob1/artl_a_00336.pdfThe Impossibility of Automating AmbiguityAmbiguity
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Barissi, VeronicaThe Human Error of Artificial Intelligence | Agenda DigitaleThe Human Error of Artificial IntelligenceReductionism
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Cummings, M.L.
http://hal.pratt.duke.edu/sites/hal.pratt.duke.edu/files/u36/reality%20check%20final_compressed.pdf
Rethinking the maturity of artificial intelligence in safety-critical settingsSelf driving
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Ross, Casey
https://www.statnews.com/2021/06/02/machine-learning-ai-methodology-research-flaws/
Machine learning is booming in medicine. It’s also facing a credibility crisisMedicine
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Simonite, Tomhttps://www.wired.com/story/google-timnit-gebru-ai-what-really-happened/What Really Happened When Google Ousted Timnit GebruTimnit Gebru
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Turkewitz, Neil
https://medium.com/@nturkewitz_56674/copyright-and-artificial-intelligence-an-exceptional-tale-60bdd77a8f13
Copyright and Artificial Intelligence: An Exceptional TaleCopyright
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Smith, Garyhttps://mindmatters.ai/2021/06/the-great-american-novel-will-not-be-written-by-a-computer/THE GREAT AMERICAN NOVEL WILL NOT BE WRITTEN BY A COMPUTERWriting
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Chieko Tsuneoka
https://www.wsj.com/articles/japans-in-home-robot-experiment-short-circuits-11624977476
Japan’s In-Home Robot Experiment Short CircuitsIn home healthcare robot
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Wong, Andrew
https://jamanetwork.com/journals/jamainternalmedicine/article-abstract/2781307
External Validation of a Widely Implemented Proprietary Sepsis Prediction Model in Hospitalized PatientsMedicine
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Various authors (MIT Symposium notes)
https://docs.google.com/document/d/1s_AgoeL2y_4iuedGuQNH6Fl1744twhe8Kj2qSfTqyHg/mobilebasic
Promises and Perils of AIAnalysis
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Stilgoe, Jackhttps://link.springer.com/article/10.1007/s10676-021-09602-1How can we know a self-driving car is safe?Self driving
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Chris Tennant, Jack Stilgoehttps://journals.sagepub.com/doi/full/10.1177/03063127211038752The attachments of ‘autonomous’ vehiclesSelf driving
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Varioushttps://arxiv.org/abs/2107.03451Anticipating Safety Issues in E2E Conversational AI: Framework and ToolingConversational AI
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Amandalynne Paulladahttps://thegradient.pub/machine-translation-shifts-power/Machine Translation Shifts PowerTranslation
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Millar, Isabelhttps://www.palgrave.com/gp/book/9783030679804Book: The Psychoanalysis of Artificial IntelligencePsychoanalysis
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Sapignoli, Mariahttps://www.cambridge.org/core/journals/american-journal-of-international-law/article/anthropology-and-the-aiturn-in-global-governance/63AE483BC9BF7EB047555B807978E414#Anthropology and the AI-Turn in Global GovernanceGovernance
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Henrik Skaug Sætra, Eduard Fosch-Villarongahttps://www.nomos-elibrary.de/10.5771/2747-5174-2021-1-60/research-in-ai-has-implications-for-society-how-do-we-respond-volume-1-2021-issue-1Morals & Machines Morality
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Federico Cabitza Andrea Campagner Carla Simonehttps://www.sciencedirect.com/science/article/abs/pii/S1071581921001142The need to move away from agential-AI: Empirical investigations, useful concepts and open issuesAgents
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Princeton Center for Information Technologyhttps://reproducible.cs.princeton.edu/Irreproducibility in Machine LearningIrreproducibility
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Various (submitted by Pedro Tsividis)https://arxiv.org/abs/2107.12544v1Human-Level Reinforcement Learning through Theory-Based Modeling, Exploration, and PlanningReinforcement learning
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Jessie Danielshttps://www.publicbooks.org/the-manifest-destiny-of-computing/THE MANIFEST DESTINY OF COMPUTINGAnalysis
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Edward Jones-Imhotephttps://www.tandfonline.com/doi/full/10.1080/07341512.2020.1757972The ghost factories: histories of automata and artificial lifeLabor
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Philip Ball
https://www.chemistryworld.com/opinion/behind-the-screens-of-alphafold/4012867.article
Behind the screens of AlphaFoldAlphafold
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Ben Dicksonhttps://bdtechtalks.com/2021/07/12/linguistics-for-the-age-of-ai/Why neural networks aren’t fit for natural language understandingNeural Networks
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Jeremy Howardhttps://www.fast.ai/2021/07/19/copilot/Is GitHub Copilot a blessing, or a curse?Github Copilot
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Daron Acemogluhttps://acmpstor.blob.core.windows.net/acmpblob1/HARMS-OF-AI-NBER.pdfNBER WORKING PAPER SERIES: HARMS OF AIAI harms
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Lauren Kaori Gurleyhttps://www.vice.com/en/article/88npjv/amazons-ai-cameras-are-punishing-drivers-for-mistakes-they-didnt-makeAmazon’s AI Cameras Are Punishing Drivers for Mistakes They Didn’t MakeLabor
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Milad Moradi, Kathrin Blagec, Florian Haberl, Matthias Samwaldhttps://arxiv.org/abs/2109.02555GPT-3 Models are Poor Few-Shot Learners in the Biomedical DomainGPT-3, Medicine
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Griff Ferris, Bruno Min, Misha Nayak-Oliver
https://www.fairtrials.org/sites/default/files/publication_pdf/Automating_Injustice.pdf
AUTOMATING INJUSTICE: THE USE OF ARTIFICIAL INTELLIGENCE & AUTOMATED DECISION-MAKING SYSTEMS IN CRIMINAL JUSTICE IN EUROPECriminal Justice
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Henrik Skaug Sætrahttps://link.springer.com/article/10.1007/s43681-021-00092-xRobotomorphyPsychoanalysis
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Emily Denton, Alex Hanna, Razvan Amironesei, Andrew Smart, Hilary Nicolehttps://journals.sagepub.com/doi/full/10.1177/20539517211035955On the genealogy of machine learning datasets: A critical history of ImageNetImageNet
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Jay Alammarhttps://jalammar.github.io/illustrated-transformer/The Illustrated Transformerhttps://jalammar.github.io/Translation
Good intro to Transformers and lanaguage modeling
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Allyson Ettingerhttps://arxiv.org/pdf/1907.13528.pdfWhat BERT is not: Lessons from a new suite of psycholinguistic diagnostics for language modelsLanguage model
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Alan Chan, Chinasa T. Okolo, Zachary Terner, Angelina Wang
https://arxiv.org/pdf/2102.01265.pdfThe Limits of Global Inclusion in AI DevelopmentInclusion
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Yarden Katzhttps://www.theatlantic.com/technology/archive/2012/11/noam-chomsky-on-where-artificial-intelligence-went-wrong/261637/Noam Chomsky on Where Artificial Intelligence Went WrongChomsky
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Cory Doctorowhttps://pluralistic.net/2021/08/05/comprehensive-sex-ed/#dronedAmazon Drone Delivery Effort CrashesAmazon Drones
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Amanda Levendowskihttps://papers.ssrn.com/sol3/papers.cfm?abstract_id=3924647Resisting Face Surveillance with Copyright LawFacial Recognition
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Dwayne Monroehttps://monroelab.net/attack-mannequins-ai-as-propagandaAttack Mannequins: AI as Propagandahttps://monroelab.net/Hype/Propaganda
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Tom Nicholashttps://www.youtube.com/watch?v=CM0aohBfUTcVeritasium: A Story of YouTube PropagandaHype/PropagandaYouTube Essayist Tom Nicholas analyzes propaganda re: Waymo 'self-driving' cars
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Iason Gabrielhttps://arxiv.org/abs/2110.14419#Towards a Theory of Justice for Artificial IntelligenceAI, Society, Justice
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Tom Simonitehttps://www.wired.com/story/group-pushed-ai-us-security-boosted-tech/This Group Pushed More AI in US Security—and Boosted Big TechAI, Government Policy, Lobbying
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Helen Ngo, João G.M. Araújo, Jeffrey Hui, Nicholas Frosst
https://arxiv.org/abs/2110.12609No News is Good News: A Critique of the One Billion Word BenchmarkLanguage model, benchmarking
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Abeba Birhane, Vinay Uday Prabhu, Emmanuel Kahembwe
https://arxiv.org/abs/2110.01963Multimodal datasets: misogyny, pornography, and malignant stereotypesLanguage model, stereotypes, misogyny
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Carnegie Council Interview with Gary Marcushttps://www.carnegiecouncil.org/studio/multimedia/20211103-honest-scientific-discourse-ai-deep-learning-gary-marcusTime for an Honest Scientific Discourse on AI & Deep Learning, with Gary MarcusMachine Learning, Deep Learning, Industry Analysis, anti-hype
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Zeerak Talat, Hagen Blix, Josef Valvoda, Maya Indira Ganesh, Ryan Cotterell, Adina Williamshttps://rycolab.io/publication/talatal-local-21/A Word on Machine Ethics: A Response to Jiang et al. (2021)Ethics
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Ingrid Burringtonhttps://www.theatlantic.com/technology/archive/2016/01/amazon-web-services-data-center/423147/Why Amazon's Data Centers Are Hidden in Spy CountryCloud Computing, Politics
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Patrick Clarkhttps://www.bloomberg.com/news/articles/2021-11-02/zillow-shuts-down-home-flipping-business-after-racking-up-lossesZillow Shuts Home-Flipping Business After Racking Up LossesAlgorithms, economy, housing market
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Zachary C. Lipton & Jacob Steinhardthttps://acmpstor.blob.core.windows.net/acmpblob1/Troubling%20Trends%20in%20Machine%20Learning%20Scholarship.pdfTroubling Trends in Machine Learning ScholarshipMachine Learning, Scholarship