top of page

RESOURCE LIST

Resource list.jpeg
Resource List: News

ESSENTIAL READING

CORRIN, KENNEDY
& DE BARBA

Corrin, L., Kennedy, G. & de Barba, P. (2017, February 27) Asking the right questions of big data in education, Pursuit [blog], The University of Melbourne, https://pursuit.unimelb.edu.au/articles/asking-the-right-questions-of-big-data-in-education

SHIVHARE

Shivhare, N. (2018, March 8), AI in schools — here’s what we need to consider, The Conversationhttps://theconversation.com/ai-in-schools-heres-what-we-need-to-consider-109450

WATTERS

Watters A. (2017, December 23) Education technology and the new behaviourism, Hack Education [blog], http://hackeducation.com/2017/12/23/top-ed-tech-trends-social-emotional-learning

WILLIAMSON

Williamson, B. (2018, March 17) 10 definitions of datafication in education, code acts in education  [blog], https://codeactsineducation.wordpress.com/2018/03/17/10-definitions-datafication/

Resource List: List

PODCASTS

PRACTICAL AI

Benson, C. & Whitenack, D. (Hosts). (2018-) Practical AI [Audio podcast]. Retrieved from: https://changelog.com/practicalai

MIND & MACHINE

Bradley, A. (Host). (2017-) MIND & MACHINE: Future Tech + Futurist Ideas + Futurism [Audio podcast]. Retrieved from: https://www.mindandmachine.io/

MACHINE ETHICS

Byford, B. (Host). (2016-) The Machine Ethics Podcast: Interrogating Technology, Artificial Intelligence and Autonomy [Audio podcast]. Retrieved from: https://www.machine-ethics.net/

THIS WEEK IN MACHINE LEARNING

Charrington, S. (Host). (2016-) The TWIML AI Podcast [Audio podcast]. Retrieved from: https://twimlai.com/

ARTIFICIAL INTELLIGENCE

Fridman, L. (Host). (2018-) Artificial Intelligence: AI Podcast [Audio podcast]. Retrieved from: https://lexfridman.com/ai/

LEARNING MACHINES 101

Golden, R. M. (Host). (2014-2018) Learning Machines 101: A Gentle Introduction to Artificial Intelligence and Machine Learning [Audio podcast]. Retrieved from: https://www.learningmachines101.com/

TALKING MACHINES

Lawrence, N. & Gorman, K. (Hosts). (2015-) Talking Machines: Human Conversations About Machine Learning [Audio podcast]. Retrieved from: https://www.thetalkingmachines.com/

LINEAR DIGRESSIONS

Malone, K. (Host). (2016-) Linear Digressions [Audio podcast]. Retrieved from: http://lineardigressions.com/

BRAIN-INSPIRED

Middlebrooks, P. (Host). (2018-) Brain-Inspired [Audio podcast]. Retrieved from: https://braininspired.co/podcast/

DATA SKEPTIC

Polich, K. (Host). (2014-) Data Skeptic [Audio podcast]. Retrieved from:

https://dataskeptic.com/podcast

Resource List: List

MULTIMEDIA

CUKIER

Cukier, K. (2013, April 10) The Birth of Datafication, Big Think, via Youtube, https://www.youtube.com/watch?v=FUj9Ug5kGH 

CUKIER

Cukier, K. (2014, April 23) Big Data at School, The Economist, via Youtube, https://www.youtube.com/watch?v=4G4RUgenV3U 

CUKIER

Cukier, K. (2014, September 23) Big Data is Better Data, TED, via Youtube, https://www.youtube.com/watch?v=8pHzROP1D-w

CRAWFORD

Crawford, K. (2013, February 28) Algorithmic Illusions: Hidden Biases of Big Data, O'Reilly, via Youtube, https://www.youtube.com/watch?v=irP5RCdpilc

CRAWFORD

Crawford, K. (2013, November 8) Big Data Gets Personal, MIT Technology Review, via Youtube, https://www.youtube.com/watch?v=JltwkXiBBTU&t=6s

GREENFIELD

Greenfield, A. (2017, July 7) What are the real dangers of Artificial Intelligence? Verso Books, via Youtube, https://www.youtube.com/watch?v=nzoXsUtWFpY

HAGGIS-BURRIDGE

Haggis-Burridge, M. (2018, May 10) Stop Assuming Data, Algorithms and AI Are Objective, TEDx Talks, via Youtube, https://www.youtube.com/watch?v=Hft8xiycH2Y 

NOBLE

Noble, S. U. (2014, April 18) How Biased Are Our Algorithms? TEDx Talks, via Youtube, https://www.youtube.com/watch?v=UXuJ8yQf6dI

ZHOU

Zhou, W. (2016, June 16) Should Technology Replace Teachers? TEDx Talks, via Youtube, 

https://www.youtube.com/watch?v=LIR60cgfOFU

Resource List: List

FURTHER READING

BEER

Beer, D. (2019) The Data Gaze: Capitalism, Power and Perception. Thousand Oaks, CA: Sage.

BENJAMIN

Benjamin, R. (2019) Race After Technology: Abolitionist Tools for the New Jim Code. Hoboken, NJ: Wiley. 

BOYD &
CRAWFORD

boyd, d. & Crawford, C. (2012) Critical questions for big data, Information, Communication & Society, 15:5, 662-679. https://doi.org/10.1080/1369118X.2012.678878 

BROUSSARD

Broussard, M. (2018) Artificial Unintelligence: How Computers Misunderstand the World. Cambridge, MA: The MIT Press. 

BUCHER

Bucher, T. (2018) If... Then: Algorithmic Power and Politics. Oxford: Oxford University Press.

CHENEY-LIPPOLD

Cheney-Lippold, J. (2011) A new algorithmic identity: Soft biopolitics and the modulation of control, Theory, Culture & Society, 28:6, 164-181. https://doi.org/10.1177/0263276411424420

EUBANKS

Eubanks, V. (2018) Automating Inequality: How High-Tech Tools Profile, Police, and Punish the Poor. New York, NY: St Martin's Press.

EYNON

Eynon, R. (2013) The rise of big data: What does it mean for education, technology, and media research? Learning, Media and Technology, 38:3, 237-240. https://doi.org/10.1080/17439884.2013.771783

GITELMAN

Gitelman, L. (ed.) (2013) “Raw Data” is an Oxymoron. Cambridge, MA: The MIT Press.

GREENFIELD

Greenfield, A. (2018) Radical Technologies: The Design of Everyday Life. London: Verso Books. 

KITCHIN

Kitchin, R. (2014). Big Data, new epistemologies and paradigm shifts. Big Data & Society, 1:1, 1-12. 

https://doi.org/10.1177/2053951714528481

KITCHIN

Kitchin, R. (2014) The Data Revolution: Big Data, Open Data, Data Infrastructures and their Consequences. London: Sage.

KNOX, WILLIAMSON & BAYNE

Knox, J. Williamson, B. & Bayne, S. (2019) Machine behaviourism: Future visions of ‘learnification’ and ‘datafication’ across humans and digital technologies, Learning, Media and Technology

https://doi.org/10.1080/17439884.2019.1623251

MACKENZIE

Mackenzie, A. (2015) The production of prediction: What does machine learning want? European Journal of Cultural Studies, 18:4-5, 429-445. https://doi.org/10.1177/1367549415577384

NOBLE

Noble, S. (2018) Algorithms of Oppression: How Search Engines Reinforce Racism. New York, NY: NYU Press.

PASQUALE

Pasquale, F. (2015) The Black Box Society: The Secret Algorithms that Control Money and Information. Cambridge, MA: Harvard University Press.

SELWYN

Selwyn, N. (2015) Data entry: Towards the critical study of digital data and education, Learning, Media and Technology, 40:1, 64-82. https://doi.org/10.1080/17439884.2014.921628

WILLIAMSON

Williamson, B. (2017a) Big Data in Education: The Digital Future of Learning, Policy and Practice. Thousand Oaks, CA: Sage.

WILLIAMSON

Williamson, B. (2017b) Computing brains: Learning algorithms and neurocomputation in the smart city, Information, Communication & Society, 20:1, 81-99. https://doi.org/10.1080/1369118X.2016.1181194

WILLIAMSON

Williamson, B. (2019) Brain data: Scanning, scraping and sculpting the plastic learning brain through neurotechnology, Postdigital Science and Education, 1: 65-86. https://doi.org/10.1007/s42438-018-0008-5

WILLIAMSON
& PIATTOEVA

Williamson, B. & Piattoeva, N. (2019) Objectivity as standardization in data-scientific education policy, technology and governance, Learning, Media and Technology, 44:1, 64-76. 

https://doi.org/10.1080/17439884.2018.1556215

ZUBOFF

Zuboff, S. (2019) The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. New York, NY: Public Affairs.

Resource List: List
bottom of page