I was interviewed on the Monocle’s Globalist show this morning to discuss a new proposed watchdog set up to regulate the use of algorithms by technology giants like Google and Facebook.
Category: technology
AI4People—An Ethical Framework for a Good AI Society: Opportunities, Risks, Principles, and Recommendations
I am a co-author on a new paper which appears in Minds and Machines (open access).
This article reports the findings of AI4People, an Atomium—EISMD initiative designed to lay the foundations for a “Good AI Society”. We introduce the core opportunities and risks of AI for society; present a synthesis of five ethical principles that should undergird its development and adoption; and offer 20 concrete recommendations—to assess, to develop, to incentivise, and to support good AI—which in some cases may be undertaken directly by national or supranational policy makers, while in others may be led by other stakeholders. If adopted, these recommendations would serve as a firm foundation for the establishment of a Good AI Society.
Radio Appearance: Google withdraws from DoD contract
I appeared on the Monocle yesterday to discuss Google’s retreat from a Department of Defence contract following protests.
Ethics and innovation belong hand in hand
New blog post at The Turing:
Ethics and innovation belong hand in hand. By Helen Margetts, Cosmina Dorobantu, and Josh Cowls.
Prolegomena to a White Paper on an Ethical Framework for a Good AI Society
Myself and Luciano Floridi have released a new paper on SSRN:
Prolegomena to a White Paper on an Ethical Framework for a Good AI Society.
The paper discusses the opportunities and challenges of AI for society and reports the results of a meta analysis, which found that five principles – beneficence, non-maleficence, autonomy, justice, and explicability – undergird the emerging ethics of AI as expressed by leading multistakeholder organisations.
The ethics of AI: how to hold machines accountable
I am quoted in a new article in Raconteur, which also appeared in a supplement to the London Times:
The ethics of AI: how to hold machines accountable. By Nick Easen.
The Potential and Perils of Election Prediction Using Social Media Sources
The Potential and Perils of Election Prediction Using Social Media Sources (with Federico Nanni). Invited presentation to Connected Life 2016, Oxford Internet Institute, University of Oxford.
2016: year of the tactical takedown?
Cross-posted from MIT’s Center for Civic Media blog.
The present presidential election is a spectacle, in the truest sense of the word, like few before. Just as FDR’s weekly radio addresses and JFK’s success in the first televised presidential debate watermark the adoption and cooption of a particular communication medium for political ends, so the 2016 campaign may go down in history as marking a seismic shift in the landscape of political uses of media. The candidate leading the charge, this time round, is unquestionably Donald Trump, currently the frontrunner for the Republican nomination. Yet it’s a little more difficult to identify precisely which medium or platform Trump has coopted. The most readily available answer seems to be ‘all of the above’ – although in different ways.
Consider the Lawn Sign: elections as civic engagement
Cross-posted from the Center for Civic Media blog.
Last week I had the chance to watch one of the world’s great electoral-political spectacles – the New Hampshire primary – up close. It wasn’t by any means my first dalliance with American politics: I’ve had at least a loose involvement in the fascinating and frequently Freudian process by which Americans elect their leaders for several cycles now. But this time I saw the process through a slightly different lens.
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Causation, Correlation, and Big Data in Social Science Research
The emergence of big data offers not only a potential boon for social scientific inquiry, but also raises distinct epistemological issues for this new area of research. Drawing on interviews conducted with researchers at the forefront of big data research, we offer insight into questions of causal versus correlational research, the use of inductive methods, and the utility of theory in the big data age. While our interviewees acknowledge challenges posed by the emergence of big data approaches, they reassert the importance of fundamental tenets of social science research such as establishing causality and drawing on existing theory. They also discussed more pragmatic issues, such as collaboration between researchers from different fields, and the utility of mixed methods. We conclude by putting the themes emerging from our interviews into the broader context of the role of data in social scientific inquiry, and draw lessons about the future role of big data in research.
Josh Cowls 