A new short paper by Luciano Floridi and I has been published, open access, in the inaugural issue of the Harvard Data Science Review.
Artificial Intelligence (AI) is already having a major impact on society. As a result, many organizations have launched a wide range of initiatives to establish ethical principles for the adoption of socially beneficial AI. Unfortunately, the sheer volume of proposed principles threatens to overwhelm and confuse. How might this problem of ‘principle proliferation’ be solved? In this paper, we report the results of a fine-grained analysis of several of the highest-profile sets of ethical principles for AI. We assess whether these principles converge upon a set of agreed-upon principles, or diverge, with significant disagreement over what constitutes ‘ethical AI.’ Our analysis finds a high degree of overlap among the sets of principles we analyze. We then identify an overarching framework consisting of five core principlesfor ethical AI. Four of them are core principles commonly used in bioethics: beneficence, non-maleficence, autonomy, and justice.On the basis of our comparative analysis, we argue that a new principle is needed in addition: explicability, understood as incorporating both the epistemological sense of intelligibility (as an answer to the question ‘how does it work?’) and in the ethical sense of accountability (as an answer to the question: ‘who is responsible for the way it works?’). In the ensuing discussion, we note the limitations and assess the implications of this ethical framework for future efforts to create laws, rules, technical standards, and best practices for ethical AI in a wide range of contexts.
I presented this paper, co-authored with Katie Arthur, at MIT’s Media in Transition conference in May 2019.
That social media both “giveth and taketh away” is not a new idea, but it is one that came to the fore in the tumultuous 2016. As the events of that year showed, while technological advances have afforded new space for radical media strategies—helping advance goals such as climate justice—so too have they created opportunities for political candidates from outside the mainstream to leverage populist resentment in the successful pursuit of political power. In this paper, we will explore how the use of civic media has evolved in the two years since our CMS Masters theses were submitted. While Donald Trump has, as President, consolidated his hold on mainstream media attention via his Twitter account, other voices have also emerged from the very different tradition of civic organising to share space on the “platform” of Twitter. Among the most prominent of these new voices is Alexandria Ocasio-Cortez, whose political experience as an organizer for the Bernie Sanders campaign and as a supporter of marginalised communities such as the residents of Standing Rock, helped propel her to the U.S. House of Representatives, as the youngest woman ever elected to Congress. In the paper we will explore Ocasio-Cortez’s rise, with a focus on her visibility on social media. As we will show, the rapid rise of “AOC” holds lessons for the prospects of both the “Green New Deal” policy she has trumpeted, and for whichever Democratic candidate is nominated to challenge Donald Trump in 2020.
I appeared on Monocle 24 earlier to discuss the hacking and release of EU diplomatic cables.
Listen at the Monocle.
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.
Listen at the Monocle.
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.
I appeared on the Monocle yesterday to discuss Google’s retreat from a Department of Defence contract following protests.
Listen at the Monocle.
New blog post at The Turing:
Ethics and innovation belong hand in hand. By Helen Margetts, Cosmina Dorobantu, and Josh Cowls.
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.
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 (with Federico Nanni). Invited presentation to Connected Life 2016, Oxford Internet Institute, University of Oxford.