Artificial intelligence and UK national security: Policy considerations

RUSI was commissioned by GCHQ to conduct an independent research study into the use of artificial intelligence (AI) for national security purposes. The aim of this project is to establish an independent evidence base to inform future policy development regarding national security uses of AI. The findings are based on in-depth consultation with stakeholders from across the UK national security community, law enforcement agencies, private sector companies, academic and legal experts, and civil society representatives. This was complemented by a targeted review of existing literature on the topic of AI and national security. The research has found that AI offers numerous opportunities for the UK national security community to improve efficiency and effectiveness of existing processes. AI methods can rapidly derive insights from large, disparate datasets and identify connections that would otherwise go unnoticed by human operators. However, in the context of national security and the powers given to UK intelligence agencies, use of AI could give rise to additional privacy and human rights considerations which would need to be assessed within the existing legal and regulatory framework. For this reason, enhanced policy and guidance is needed to ensure the privacy and human rights implications of national security uses of AI are reviewed on an ongoing basis as new analysis methods are applied to data

First Steps Towards an Ethics of Robots and Artificial Intelligence

This article offers an overview of the main first-order ethical questions raised by robots and Artificial Intelligence (RAIs) under five broad rubrics: functionality, inherent significance, rights and responsibilities, side-effects, and threats. The first letter of each rubric taken together conveniently generates the acronym FIRST. Special attention is given to the rubrics of functionality and inherent significance given the centrality of the former and the tendency to neglect the latter in virtue of its somewhat nebulous and contested character. In addition to exploring some illustrative issues arising under each rubric, the article also emphasizes a number of more general themes. These include: the multiplicity of interacting levels on which ethical questions about RAIs arise, the need to recognise that RAIs potentially implicate the full gamut of human values (rather than exclusively or primarily some readily identifiable sub-set of ethical or legal principles), and the need for practically salient ethical reflection on RAIs to be informed by a realistic appreciation of their existing and foreseeable capacities

Double elevation: Autonomous weapons and the search for an irreducible law of war

What should be the role of law in response to the spread of artificial intelligence in war? Fuelled by both public and private investment, military technology is accelerating towards increasingly autonomous weapons, as well as the merging of humans and machines. Contrary to much of the contemporary debate, this is not a paradigm change; it is the intensification of a central feature in the relationship between technology and war: Double elevation, above one's enemy and above oneself. Elevation above one's enemy aspires to spatial, moral, and civilizational distance. Elevation above oneself reflects a belief in rational improvement that sees humanity as the cause of inhumanity and de-humanization as our best chance for humanization. The distance of double elevation is served by the mechanization of judgement. To the extent that judgement is seen as reducible to algorithm, law becomes the handmaiden of mechanization. In response, neither a focus on questions of compatibility nor a call for a 'ban on killer robots' help in articulating a meaningful role for law. Instead, I argue that we should turn to a long-standing philosophical critique of artificial intelligence, which highlights not the threat of omniscience, but that of impoverished intelligence. Therefore, if there is to be a meaningful role for law in resisting double elevation, it should be law encompassing subjectivity, emotion and imagination, law irreducible to algorithm, a law of war that appreciates situated judgement in the wielding of violence for the collective

Beneficial Artificial Intelligence Coordination by means of a Value Sensitive Design Approach

This paper argues that the Value Sensitive Design (VSD) methodology provides a principled approach to embedding common values in to AI systems both early and throughout the design process. To do so, it draws on an important case study: the evidence and final report of the UK Select Committee on Artificial Intelligence. This empirical investigation shows that the different and often disparate stakeholder groups that are implicated in AI design and use share some common values that can be used to further strengthen design coordination efforts. VSD is shown to be both able to distill these common values as well as provide a framework for stakeholder coordination

Artificial intelligence: opportunities and implications for the future of decision making

Artificial intelligence has arrived. In the online world it is already a part of everyday life, sitting invisibly behind a wide range of search engines and online commerce sites. It offers huge potential to enable more efficient and effective business and government but the use of artificial intelligence brings with it important questions about governance, accountability and ethics. Realising the full potential of artificial intelligence and avoiding possible adverse consequences requires societies to find satisfactory answers to these questions. This report sets out some possible approaches, and describes some of the ways government is already engaging with these issues

Automated verification of refinement laws

Demonic refinement algebras are variants of Kleene algebras. Introduced by von Wright as a light-weight variant of the refinement calculus, their intended semantics are positively disjunctive predicate transformers, and their calculus is entirely within first-order equational logic. So, for the first time, off-the-shelf automated theorem proving (ATP) becomes available for refinement proofs. We used ATP to verify a toolkit of basic refinement laws. Based on this toolkit, we then verified two classical complex refinement laws for action systems by ATP: a data refinement law and Back's atomicity refinement law. We also present a refinement law for infinite loops that has been discovered through automated analysis. Our proof experiments not only demonstrate that refinement can effectively be automated, they also compare eleven different ATP systems and suggest that program verification with variants of Kleene algebras yields interesting theorem proving benchmarks. Finally, we apply hypothesis learning techniques that seem indispensable for automating more complex proofs

A brave new world of Ambient Intelligence in the casinos of Macau: reality or fiction?

The article scrutinizes the brave new world of ambient intelligence in the casinos of the Macau, Special Administrative Region of People´s Republic of China, chiefly in regards to the (candent) issue of privacy of the casino patrons. Moreover, this scientific article provides an overview about the secondary use of big data of the casino patrons for law enforcement purposes