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Supplementary conference reading material

Machine learning and artificial intelligence: how do we make sure technology serves the open society?


Conference Description



Please note that this is not a recommended reading list produced by the Ditchley Foundation.

Conference participants are invited to recommend pre-conference reading materials relevant to the topic of this conference, and we are happy to post links to the items here for your reference. 


Kenneth Cukier: The economic implications of artificial intelligence. Chatham House, forthcoming, January 2018

Tim Urban: The AI Revolution: the road to superintelligence. WaitButWhy.com, 22 January, 2015

Ansgar Koene: Facebook's algorithms give it more editorial responsibility - not less. The Conversation, 14 September, 2016

Kathy Pretz: Keeping Bias from Creeping Into Code.  The Institute, 12 September 2017

Ansgar Koene: Machine gaydar: AI is reinforcing stereotypes that liberal societies are trying to get rid of. The Conversation, 13 September, 2017

Vyacheslav W. Polonski: How artificial intelligence conquered democracy. The Independent, 15 August 2017

IEEE Global Initiative for Ethical Considerations in Artificial Intelligence and Autonomous Systems: Ethically Aligned Design: A vision for prioritizing human wellbeing with Artificial Intelligence and Autonomous Systems. December 2016

Manoj Saxena: Six reasons for the failure of first generation Enterprise AI. LinkedIn, 21 August, 2017

Jacques Bughin, Brian McCarthy, Michael Chui: A Survey of 3,000 Executives Reveals How Businesses Succeed with AI. Harvard Business Review, 28 August, 2017

Julia Bossmann: Top 9 ethical issues in artificial intelligence. 21 October, 2016

Centre for Public Impact: Destination Unknown: Exploring the impact of Artificial Intelligence on Government. September 2017




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