Special Issue "On Defining Artificial Intelligence"—Commentaries and Author's Response

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Social Choice for Partial Preferences Using Imputation

Within the field of multiagent systems, the area of computational social choice considers the problems arising when decisions must be made collectively by a group of agents. Usually such systems collect a ranking of the alternatives from each member of the group in turn, and aggregate these individual rankings to arrive at a collective decision. However, when there are many alternatives to consider, individual agents may be unwilling, or unable, to rank all of them, leading to decisions that must be made on the basis of incomplete information. While earlier approaches attempt to work with the provided rankings by making assumptions about the nature of the missing information, this can lead to undesirable outcomes when the assumptions do not hold, and is ill-suited to certain problem domains. In this thesis, we propose a new approach that uses machine learning algorithms (both conventional and purpose-built) to generate plausible completions of each agent’s rankings on the basis of the partial rankings the agent provided (imputations), in a way that reflects the agents’ true preferences. We show that the combination of existing social choice functions with certain classes of imputation algorithms, which forms the core of our proposed solution, is equivalent to a form of social choice. Our system then undergoes an extensive empirical validation under 40 different test conditions, involving more than 50,000 group decision problems generated from real-world electoral data, and is found to outperform existing competitors significantly, leading to better group decisions overall. Detailed empirical findings are also used to characterize the behaviour of the system, and illustrate the circumstances in which it is most advantageous. A general testbed for comparing solutions using real-world and artificial data (Prefmine) is then described, in conjunction with results that justify its design decisions. We move on to propose a new machine learning algorithm intended specifically to learn and impute the preferences of agents, and validate its effectiveness. This Markov-Tree approach is demonstrated to be superior to imputation using conventional machine learning, and has a simple interpretation that characterizes the problems on which it will perform well. Later chapters contain an axiomatic validation of both of our new approaches, as well as techniques for mitigating their manipulability. The thesis concludes with a discussion of the applicability of its contributions, both for multiagent systems and for settings involving human elections. In all, we reveal an interesting connection between machine learning and computational social choice, and introduce a testbed which facilitates future research efforts on computational social choice for partial preferences, by allowing empirical comparisons between competing approaches to be conducted easily, accurately, and quickly. Perhaps most importantly, we offer an important and effective new direction for enabling group decision making when preferences are not completely specified, using imputation methods

The Democratization of Artificial Intelligence

After a long time of neglect, Artificial Intelligence is once again at the center of most of our political, economic, and socio-cultural debates. Recent advances in the field of Artifical Neural Networks have led to a renaissance of dystopian and utopian speculations on an AI-rendered future. Algorithmic technologies are deployed for identifying potential terrorists through vast surveillance networks, for producing sentencing guidelines and recidivism risk profiles in criminal justice systems, for demographic and psychographic targeting of bodies for advertising or propaganda, and more generally for automating the analysis of language, text, and images. Against this background, the aim of this book is to discuss the heterogenous conditions, implications, and effects of modern AI and Internet technologies in terms of their political dimension: What does it mean to critically investigate efforts of net politics in the age of machine learning algorithms

The Democratization of Artificial Intelligence: Net Politics in the Era of Learning Algorithms

After a long time of neglect, Artificial Intelligence is once again at the center of most of our political, economic, and socio-cultural debates. Recent advances in the field of Artifical Neural Networks have led to a renaissance of dystopian and utopian speculations on an AI-rendered future. Algorithmic technologies are deployed for identifying potential terrorists through vast surveillance networks, for producing sentencing guidelines and recidivism risk profiles in criminal justice systems, for demographic and psychographic targeting of bodies for advertising or propaganda, and more generally for automating the analysis of language, text, and images. Against this background, the aim of this book is to discuss the heterogenous conditions, implications, and effects of modern AI and Internet technologies in terms of their political dimension: What does it mean to critically investigate efforts of net politics in the age of machine learning algorithms

Proliferate! A techno-social history of the internet meme, from print to platforms

Internet memes are often understood as artefacts that have communicative utility within online discourses replete with legible aesthetic and affective attributes. Accordingly, valuable scholarly work has been done to understand how internet memes function as and within online social interactions. However, less attention has been paid to the ways in which the assemblage of technologies that comprise the internet mediate the social practices that produce internet memes. This thesis attends to this lesser-studied area by acknowledging that it is from the internet, as a particular but evolving assemblage of technologies, that the internet meme emerges. In so doing, I develop an analytic framework which recovers technics as co-constitutive of the social practices that bring forth internet memes. Thus, the techno-social of this thesis’ title references the supposition that internet memes are contingent on the irreducible relationship between the technics of the internet and the associated social practices they mediate. This claim is advanced by historicising the internet meme. In the first half of this thesis, I identify a selection of precursor “memes” that emerged from antecedent techno-social arrangements present in mid-to-late 20th century Anglo / U.S.-centric discourses. These accounts are mobilised to better clarify the specificity of the internet in mediating the techno-social practices that produce internet memes – a dynamic explored in the latter chapters of the thesis. A techno-social history of the meme therefore asserts that memes – internet or otherwise – have historically emerged and will continue to emerge across myriad techno-social milieu; with the historical framing functioning as an analytic device that draws into relief the ways in which the internet makes the internet meme distinct. Such an approach relies on a working definition of the meme, internet or otherwise. This is no simple task. As is recounted in this thesis’ introduction, the concept of “the meme” has been a contested one since the term’s emergence. Drawing on the work of Limor Shifman in particular, I assert that memes can only be differentiated from other forms of cultural production in the specific ways they proliferate – via social practices of reproduction and remix animated by the use of technical media. Notably, the recognition of proliferation as the meme’s defining feature undergirds this thesis’ analytical framing, since proliferation as a social practice, and the aesthetic and affective attributes of the memes that emerge, must be realised in ways contingent on technical affordances. The internet meme then, is recognisable as such since it proliferates, and is rendered distinct through being proliferated on the internet. Having provided terms of definition, Chapter One moves to historicise the proliferating meme. In this section, the manipulation of photographic imagery relating to the Kennedy Assassination – by professional media, governmental bodies, and private citizen researchers – is reconsidered as a form of meme. Articulated as such, this chapter goes on to detail the ways in which the aesthetics and utilities of the Kennedy Assassination “meme” were realised in ways contingent on the techno-social conditions from which it emerged. Chapter Two develops this perspective further in assessing the production of mid-to-late 20th century alt-media as a form of memetic social practice; afforded by the appropriation of reprographic technologies, which in turn supplied the artefactual output with distinct forms and functions, and cultural significances. Having made the case for mobilising a techno-social history of the meme in the preceding sections, Chapter Three moves this work “online”, and offers an account of how the early web of the ’90’s and ‘00’s brought forth its own meme forms, notably the spread of web-based urban legends. Chapter Four then turns to address examples of what might be widely understood as internet memes proper - the Image Macro and GIF formats – and accounts for the ways in which the social usage of the assemblage of digital media technologies that comprise the internet gave rise to and proliferated these meme forms. Finally, Chapter Five will reflexively consider what the framework established in the prior chapters reveals about the contemporaneous internet meme – a meme form that emerges from a platformised techno social milieu – a milieu I’ll argue is characterised by financialised media ubiquity. The framework developed in this thesis provides a lens not only for studying the distinct forms and functions of meme forms, with particular attention paid to the internet meme, but also accounts for the inevitable future evolution of memes as techno-social arrays continue to reconfigur

The Democratization of Artificial Intelligence

After a long time of neglect, Artificial Intelligence is once again at the center of most of our political, economic, and socio-cultural debates. Recent advances in the field of Artifical Neural Networks have led to a renaissance of dystopian and utopian speculations on an AI-rendered future. Algorithmic technologies are deployed for identifying potential terrorists through vast surveillance networks, for producing sentencing guidelines and recidivism risk profiles in criminal justice systems, for demographic and psychographic targeting of bodies for advertising or propaganda, and more generally for automating the analysis of language, text, and images. Against this background, the aim of this book is to discuss the heterogenous conditions, implications, and effects of modern AI and Internet technologies in terms of their political dimension: What does it mean to critically investigate efforts of net politics in the age of machine learning algorithms

Knowledge and Management Models for Sustainable Growth

In the last years sustainability has become a topic of global concern and a key issue in the strategic agenda of both business organizations and public authorities and organisations. Significant changes in business landscape, the emergence of new technology, including social media, the pressure of new social concerns, have called into question established conceptualizations of competitiveness, wealth creation and growth. New and unaddressed set of issues regarding how private and public organisations manage and invest their resources to create sustainable value have brought to light. In particular the increasing focus on environmental and social themes has suggested new dimensions to be taken into account in the value creation dynamics, both at organisations and communities level. For companies the need of integrating corporate social and environmental responsibility issues into strategy and daily business operations, pose profound challenges, which, in turn, involve numerous processes and complex decisions influenced by many stakeholders. Facing these challenges calls for the creation, use and exploitation of new knowledge as well as the development of proper management models, approaches and tools aimed to contribute to the development and realization of environmentally and socially sustainable business strategies and practices

Design revolutions: IASDR 2019 Conference Proceedings. Volume 4: Learning, Technology, Thinking

In September 2019 Manchester School of Art at Manchester Metropolitan University was honoured to host the bi-annual conference of the International Association of Societies of Design Research (IASDR) under the unifying theme of DESIGN REVOLUTIONS. This was the first time the conference had been held in the UK. Through key research themes across nine conference tracks – Change, Learning, Living, Making, People, Technology, Thinking, Value and Voices – the conference opened up compelling, meaningful and radical dialogue of the role of design in addressing societal and organisational challenges. This Volume 4 includes papers from Learning, Technology and Thinking tracks of the conference