Spring 2017 Course Reading List (Designing A.I.)
This is a public-facing version of the reading list for the course Designing A.I. This may be updated over the course of the semester and will be supplemented by other readings posted to the course’s private Slack team.
Pre-Class [Week 0]
“The next wave of AI is rooted in human culture and history” (alternates to a tech-focused approach, and getting new perspectives in the future of AI)
https://www.engadget.com/2016/08/16/the-next-wave-of-ai-is-rooted-in-human-culture-and-history/
Technology (technical)
“Machine Learning: The New AI” (The MIT Press Essential Knowledge series), Ethem Alpaydin, 2016 https://www.amazon.com/dp/0262529513 or https://mitpress.mit.edu/books/machine-learning-1
“A Course in Machine Learning” Hal Daumé III
http://ciml.info
“Machine Learning: The Art and Science of Algorithms that Make Sense of Data”, Peter Flach
https://www.amazon.com/Machine-Learning-Science-Algorithms-Sense/dp/1107422221
Technology (Overview and general trends) [Week 1]
High-level overviews and discussions on the re-emergence of A.I. and machine learning…
“Barack Obama, Neural Nets, Self-Driving Cars, and the Future of the World” (Wired magazine)
https://www.wired.com/2016/10/president-obama-mit-joi-ito-interview
“AI Takes Off” (Special report section from Technology Review)
https://www.technologyreview.com/business-report/ai-takes-off/
“The Return of the Machinery Question” (special report section from The Economist)
http://www.economist.com/news/special-report/21700761-after-many-false-starts-artificial-intelligence-has-taken-will-it-cause-mass
“What’s Next in Computing?” (history and upcoming trends)
https://medium.com/software-is-eating-the-world/what-s-next-in-computing-e54b870b80cc
“The AI Revolution: The Road to Superintelligence” (related to “what’s next” — a big shift about to happen — may be too focused on AGI)
http://waitbutwhy.com/2015/01/artificial-intelligence-revolution-1.html
“CreativeAI: On the Democratisation & Escalation of Creativity — Chapter 01” (ways AI can enhance creativity)
https://medium.com/@ArtificialExperience/creativeai-9d4b2346faf3
Technology (Learning the tech) [Week 1]
Getting more detailed on how the technology works…
“Machine Learning for Designers” (very good overview. See also the section: “Common Analogies for Machine Learning”)
http://www.oreilly.com/design/free/files/machine-learning-for-designers.pdf
“Blaise Agüera y Arcas: How computers are learning to be creative” (explaining machine learning, relates to biology) (video)
http://www.ted.com/talks/blaise_aguera_y_arcas_how_computers_are_learning_to_be_creative#t-275453
“Artificial Intelligence and You: Demystifying the Technology Landscape”
https://thinkgrowth.org/artificial-intelligence-and-you-demystifying-the-technology-landscape-21d4d34fbb10
“Facebook’s Fascinating New Videos Demystify A.I.’s Scary Reputation” (sequence of videos)
https://www.inverse.com/article/24561-facebook-yann-lecun-ai
“Machine Learning is Fun” (Introducing different types of learning)
https://medium.com/@ageitgey/machine-learning-is-fun-80ea3ec3c471
“An Honest Guide to Machine Learning: Part One” (This is the beginning of a series of posts that steps through a range of ML themes)
https://medium.com/axiomzenteam/an-honest-guide-to-machine-learning-2f6d7a6df60e
“Inside Deep Dreams: How Google Made Its Computers Go Crazy” (can this tech allow us to understand what’s happening inside neural networks?)
https://backchannel.com/inside-deep-dreams-how-google-made-its-computers-go-crazy-83b9d24e66df
“Inceptionism: Going Deeper into Neural Networks” (Google research blog)
https://research.googleblog.com/2015/06/inceptionism-going-deeper-into-neural.html
A Return to Machine Learning (An artist experiments with some ML techniques)
https://medium.com/@kcimc/a-return-to-machine-learning-2de3728558eb
Specific Technologies & Platforms [Weeks 2,3,4]
A (rather incomplete) list of specific tools that are being used. This is an area where new discoveries can be shared via Slack.
“The Google Brain team — Looking Back on 2016” (good summary of all the work Google has been doing)
https://research.googleblog.com/2017/01/the-google-brain-team-looking-back-on.html
Facebook AI Research (access point to much of Facebook’s AI work)
https://research.fb.com/category/facebook-ai-research-fair/
https://aws.amazon.com/rekognition/ (image recognition/analysis)
https://www.tensorflow.org
https://universe.openai.com
“The Non-Technical Guide to Machine Learning & Artificial Intelligence” (has an extensive list of companies doing ML)
https://machinelearnings.co/a-humans-guide-to-machine-learning-e179f43b67a0
Lists of New Applications of AI (startups)
https://angel.co/artificial-intelligence
https://www.crunchbase.com/category/artificial-intelligence/c4d8caf35fe7359bf9f22d708378e4ee
https://www.producthunt.com/topics/artificial-intelligence
Lists of Known Applications of AI (Goals, Approaches, Use cases, examples of artificial intelligence algorithms applied to real-world problems)
https://en.wikipedia.org/wiki/Applications_of_artificial_intelligence
https://en.wikipedia.org/wiki/Category:Artificial_intelligence_applications
http://beebom.com/examples-of-artificial-intelligence/
Deep Learning papers (mostly technical)
https://github.com/terryum/awesome-deep-learning-papers
Bias, Diversity, Ethics, Privacy [Week 3 (was 2)]
“How Machines Learn to Be Racist” (very simple overview)
https://www.propublica.org/article/breaking-the-black-box-how-machines-learn-to-be-racist
“Memo to the DOJ: Facial Recognition’s Threat to Privacy is Worse Than Anyone Thought” (single topic — but good to sense the scope of what’s possible)
https://www.eff.org/deeplinks/2016/10/memo-doj-facial-recognitions-threat-privacy-worse-anyone-thought
“Inside Google’s Internet Justice League and its AI-Powered War on Trolls” (working to prevent racism / support civil discourse)
https://www.wired.com/2016/09/inside-googles-internet-justice-league-ai-powered-war-trolls/
http://www.nytimes.com/interactive/2016/09/20/insider/approve-or-reject-moderation-quiz.html
https://jigsaw.google.com
“What World Are We Building?” (data and society — tendency to mirror and magnify the issues that affect everyday life. The good, bad, and ugly)
https://points.datasociety.net/what-world-are-we-building-9978495dd9ad
“Artificial intelligence is hard to see” (on the need to measure AI’s societal impacts)
https://medium.com/@katecrawford/artificial-intelligence-is-hard-to-see-a71e74f386db
Ethics of A.I. (conference, with link to video talks)
https://wp.nyu.edu/consciousness/ethics-of-artificial-intelligence/
“IEEE puts out a first draft guide for how tech can achieve ethical AI design”
https://techcrunch.com/2016/12/13/ieee-puts-out-a-first-draft-guide-for-how-tech-can-achieve-ethical-ai-design
https://theglassroomnyc.org/resources/
https://shift.newco.co/where-should-machines-go-to-learn-c2461f7e45fc
https://beta.nyc (data sources)
Engaging Alternate / Underserved Communities [Week 3]
“The Women Changing The Face Of AI” (Fast Company on Women in Machine Learning)
https://www.fastcompany.com/3062932/mind-and-machine/ai-is-a-male-dominated-field-but-an-important-group-of-women-is-changing-th
“Civic Data Initiatives”
https://medium.com/graph-commons/civic-data-initiatives-c4a0f40d9a23
Bridging & Alternative A.I. [Week 2]
How do non-tech people talk about A.I.?
“Meet the artists who have embraced artificial intelligence” (There’s an opportunity to use art to break apart what’s going on inside A.I.)
http://fusion.net/story/346636/artists-neural-nets-deep-learning-machine-learning/
“What Do People — Not Techies, Not Companies — Think About Artificial Intelligence?”
https://hbr.org/2016/10/what-do-people-not-techies-not-companies-think-about-artificial-intelligence
“Movie written by algorithm turns out to be hilarious and intense”
http://arstechnica.com/the-multiverse/2016/06/an-ai-wrote-this-movie-and-its-strangely-moving/
Alt A.I. conference at the Center for Poetic Computation. (Interesting ways different artists talk about and use A.I.)
http://alt-ai.net/#watch
https://medium.com/artists-and-machine-intelligence/alt-ai-4f6e706c7aab
The Future of A.I. [Optional Readings]
How might A.I. evolve. And how does design and use influence the future of technology…
“The next wave of AI is rooted in human culture and history” (alternates to a tech-focused approach, and getting new perspectives in the future of AI)
https://www.engadget.com/2016/08/16/the-next-wave-of-ai-is-rooted-in-human-culture-and-history/
“What AI products can we expect by 2020?”
https://www.quora.com/What-AI-products-can-we-expect-by-2020
“The dynamic forces shaping AI” (It’s time to debate scenarios that will shift the balance of data, compute resources, algorithms, and talent.)
https://www.oreilly.com/ideas/the-four-dynamic-forces-shaping-ai
“Is Artificial Intelligence Permanently Inscrutable?” (are they impossible to understand?)
http://nautil.us/issue/40/learning/is-artificial-intelligence-permanently-inscrutable
“AI ON” (Open community drawing attention to important yet under-appreciated research problems)
http://ai-on.org
“How Music Works”, 2013, David Byrne — Chapter 3: Technology Shapes Music
Design Methods & Prototyping
“Experience Design in the Machine Learning Era”
https://www.bbvadata.com/experience-design-in-the-machine-learning-era/
“Rethink IxD” (It’s time to rethink Interaction Design.)
https://medium.com/@philvanallen/rethink-ixd-e489b843bfb6
“Design as Participation” Kevin Slavin, (A consideration of design as a form of participation in complex adaptive systems)
http://jods.mitpress.mit.edu/pub/design-as-participation
“Design and Science” Joi Ito (Can design advance science, and can science advance design?)
http://jods.mitpress.mit.edu/pub/designandscience
“Design Kit” (current human centered design methods)
http://www.designkit.org/methods
“Object of Intrigue: Disneyland’s Flirty, Talking Trash Can” (Simulating AI with a talking trash can)
http://www.atlasobscura.com/articles/object-of-intrigue-disneyland-s-flirty-talking-trash-can
Graph Commons [Week 1]
Network mapping and analysis intro materials. We will use this tool for the first couple weeks of class.
Part I: Creative and Critical Use of Complex Networks
https://medium.com/graph-commons/creative-and-critical-use-of-complex-networks-412fe9eddecb
Part II: Mapping Networks
https://medium.com/graph-commons/mapping-networks-1dea70b2f550
Part III: Analyzing Data Networks
https://medium.com/graph-commons/analyzing-data-networks-f4480a28fb4b
Slack channel for questions and discussions.
https://graphcommons.com/slack
Regularly updated resources
Jack Clark’s Import AI mailing list (with archives on the site)
https://jack-clark.net/import-ai/
NYC Media Lab mailing list
http://nycmedialab.org/newsletters (data mailing list includes AI)
Creative AI
http://www.creativeai.net
