A Unified Framework of Five Principles for AI in Society

A new short paper by Luciano Floridi and I has been published, open access, in the inaugural issue of the Harvard Data Science Review. 2000px-Black_pencil.svg

Abstract:

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.

Deciding how to decide: Six key questions for reducing AI’s democratic deficit

Artificial intelligence (AI) has a “democratic deficit” — and maybe that shouldn’t be a surprise. As Jonnie Penn and others have argued, AI, in conception and application, has long been bound up with the logic and operations of big business. Today, we find AI put to use in an increasing array of socially significant settings, from sifting through CVs to swerving through traffic, many of which continue to serve these corporate interests. (We also find “AI” the brand put to use in the absence of AI the technlogy: a recent study suggests that 40% of start-ups who claim to use AI do not in fact do so.) Nor are governments of all stripes lacking interest in the potential power of AI to patrol and cajole the movements and mindsets of citizens.

Read more at Medium.

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).2000px-Black_pencil.svgThis 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.