AI/Machine Learning/regulation of technology (and related topics): general readings and resources
Since these subjects often overlap, see also the sources available in the ‘Privacy/Data Protection’ list.
Springer’s handbooks temporarily made freely accessible during Corona times:
- Handbook on Robotics;
- Introduction to AI;
- Introduction to Machine Learning;
- Introduction to Data Science.
Additional specific sources:
- Good Data, by A. Daly e.a., Amsterdam: Institute of Network Cultures 2019;
- Data Feminism, by C. D’Ignazio & L.F. Klein, Cambridge: MIT 2020,
See also the reading group;
- The Datafied Society, by M.T. Schäfer & K. van Es, Amsterdam: AUP 2017.
Comprehensive reports curated by research institutes and civil society:
- Algorithm Watch’s reports;
- AI Now Institute;
- Data Society;
- Harvard’s Berkman Klein Center for Internet & Society;
- Ada Lovelace Institute.
Some open access technology/regulation/interdisciplinary journals and sources:
- Stanford’s Plato Dictionary (see voice ‘Ethics of AI and Robotics’);
- [New journal] Technology & Regulation;
- [New journal] Human-Machine communication;
- Big Data & Society;
- Ethics and Information Technology (access should be possible via university credentials).
- ACM FAccT 2020 conference (fairness, accountability, and transparency).