534 research outputs found

    Multidisciplinary perspectives on Artificial Intelligence and the law

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    This open access book presents an interdisciplinary, multi-authored, edited collection of chapters on Artificial Intelligence (‘AI’) and the Law. AI technology has come to play a central role in the modern data economy. Through a combination of increased computing power, the growing availability of data and the advancement of algorithms, AI has now become an umbrella term for some of the most transformational technological breakthroughs of this age. The importance of AI stems from both the opportunities that it offers and the challenges that it entails. While AI applications hold the promise of economic growth and efficiency gains, they also create significant risks and uncertainty. The potential and perils of AI have thus come to dominate modern discussions of technology and ethics – and although AI was initially allowed to largely develop without guidelines or rules, few would deny that the law is set to play a fundamental role in shaping the future of AI. As the debate over AI is far from over, the need for rigorous analysis has never been greater. This book thus brings together contributors from different fields and backgrounds to explore how the law might provide answers to some of the most pressing questions raised by AI. An outcome of the Católica Research Centre for the Future of Law and its interdisciplinary working group on Law and Artificial Intelligence, it includes contributions by leading scholars in the fields of technology, ethics and the law.info:eu-repo/semantics/publishedVersio

    ACiS: smart switches with application-level acceleration

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    Network performance has contributed fundamentally to the growth of supercomputing over the past decades. In parallel, High Performance Computing (HPC) peak performance has depended, first, on ever faster/denser CPUs, and then, just on increasing density alone. As operating frequency, and now feature size, have levelled off, two new approaches are becoming central to achieving higher net performance: configurability and integration. Configurability enables hardware to map to the application, as well as vice versa. Integration enables system components that have generally been single function-e.g., a network to transport data—to have additional functionality, e.g., also to operate on that data. More generally, integration enables compute-everywhere: not just in CPU and accelerator, but also in network and, more specifically, the communication switches. In this thesis, we propose four novel methods of enhancing HPC performance through Advanced Computing in the Switch (ACiS). More specifically, we propose various flexible and application-aware accelerators that can be embedded into or attached to existing communication switches to improve the performance and scalability of HPC and Machine Learning (ML) applications. We follow a modular design discipline through introducing composable plugins to successively add ACiS capabilities. In the first work, we propose an inline accelerator to communication switches for user-definable collective operations. MPI collective operations can often be performance killers in HPC applications; we seek to solve this bottleneck by offloading them to reconfigurable hardware within the switch itself. We also introduce a novel mechanism that enables the hardware to support MPI communicators of arbitrary shape and that is scalable to very large systems. In the second work, we propose a look-aside accelerator for communication switches that is capable of processing packets at line-rate. Functions requiring loops and states are addressed in this method. The proposed in-switch accelerator is based on a RISC-V compatible Coarse Grained Reconfigurable Arrays (CGRAs). To facilitate usability, we have developed a framework to compile user-provided C/C++ codes to appropriate back-end instructions for configuring the accelerator. In the third work, we extend ACiS to support fused collectives and the combining of collectives with map operations. We observe that there is an opportunity of fusing communication (collectives) with computation. Since the computation can vary for different applications, ACiS support should be programmable in this method. In the fourth work, we propose that switches with ACiS support can control and manage the execution of applications, i.e., that the switch be an active device with decision-making capabilities. Switches have a central view of the network; they can collect telemetry information and monitor application behavior and then use this information for control, decision-making, and coordination of nodes. We evaluate the feasibility of ACiS through extensive RTL-based simulation as well as deployment in an open-access cloud infrastructure. Using this simulation framework, when considering a Graph Convolutional Network (GCN) application as a case study, a speedup of on average 3.4x across five real-world datasets is achieved on 24 nodes compared to a CPU cluster without ACiS capabilities

    LIPIcs, Volume 261, ICALP 2023, Complete Volume

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    LIPIcs, Volume 261, ICALP 2023, Complete Volum

    Flip: Data-Centric Edge CGRA Accelerator

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    Coarse-Grained Reconfigurable Arrays (CGRA) are promising edge accelerators due to the outstanding balance in flexibility, performance, and energy efficiency. Classic CGRAs statically map compute operations onto the processing elements (PE) and route the data dependencies among the operations through the Network-on-Chip. However, CGRAs are designed for fine-grained static instruction-level parallelism and struggle to accelerate applications with dynamic and irregular data-level parallelism, such as graph processing. To address this limitation, we present Flip, a novel accelerator that enhances traditional CGRA architectures to boost the performance of graph applications. Flip retains the classic CGRA execution model while introducing a special data-centric mode for efficient graph processing. Specifically, it exploits the natural data parallelism of graph algorithms by mapping graph vertices onto processing elements (PEs) rather than the operations, and supporting dynamic routing of temporary data according to the runtime evolution of the graph frontier. Experimental results demonstrate that Flip achieves up to 36×\times speedup with merely 19% more area compared to classic CGRAs. Compared to state-of-the-art large-scale graph processors, Flip has similar energy efficiency and 2.2×\times better area efficiency at a much-reduced power/area budget

    Internet Mediated NGO Activity: How Environmental NGOs use Weibo in China

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    This thesis uses an interdisciplinary approach that draws on both the political science and media and communication fields to analyse how Chinese environmental NGOs use the microblogging site, Sina Weibo, in their online activism. The study of NGOs and how they use the internet in China is widespread. However, in many cases, the way that NGOs in China work, both online and offline, has been analysed through the lens of traditional civil society and internet studies literature, which has mostly focused on the ability of NGOs, and the internet, to give rise to significant political change, and even democratisation.Through a mixture of thematic, network, and organisational analysis, this thesis investigates the communicative functions, themes, and use of interactive features in posts on Weibo, including the use of hashtags, retweets and @mentions. At the organisational level, the ways that NGOs engage with different actors, both online and offline, including fellow NGOs, government departments, their followers, and potential donors are interrogated using four case studies. These analyses found that although the political space afforded to environmental NGOs in China is severely constrained, and the operations of the NGOs could not be seen as overtly activist or confrontational in the traditional sense, the NGOs do in fact retain a certain amount of autonomy and are able to carve out some political space for themselves. The findings of this thesis therefore challenge the notion that NGOs in China are co-opted organisations without autonomy from the state and suggests that there is scope for digital activism by NGOs in an authoritarian context, even though the online and offline political space they inhabit may be tightly regulated and controlled

    Manipulating, Lying, and Engineering the Future

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    Decision-making should reflect personal autonomy. Yet, it is not entirely an autonomous process. Influencing individuals’ decision-making is not new. It is and always has been the engine that drives markets, politics, and debates. However, in the digital marketplace of ideas the nature of influence is different in scale, scope, and depth. The asymmetry of information shapes a new model of surveillance capitalism. This model promises profits gained by behavioral information collected from consumers and personal targeting. The Internet of Things, Big Data and Artificial Intelligence open a new dimension for manipulation. In the age of Metaverse that would be mediated through virtual spaces and augmented reality manipulation is expected to get stronger. Such manipulation could be performed by either commercial corporations or governments, though this Article primarily focuses on the former, rather than the latter. Surveillance capitalism must depend on technology but also on marketing, as commercial entities push their goods and agendas unto their consumers. This new economic order presents benefits in the form of improved services, but it also has negative consequences: it treats individuals as instruments; it may infringe on individuals’ autonomy and future development; and it manipulates consumers to make commercial choices that could potentially harm their own welfare. Moreover, it may also hinder individuals’ free speech and erode some of the privileges enshrined in a democracy. What can be done to limit the negative consequences of hyper-manipulation in digital markets? Should the law impose limitations on digital influence? If so, how and when? This Article aims to answer these questions in the following manner: First, this Article demonstrates how companies influence decisions by collecting, analyzing, and manipulating information. Understanding the tools of the new economic order is the first step in developing legal policy that mitigates harm. Second, this Article analyzes the concept of manipulation. It explains how digital manipulation differs from traditional commercial influences in scope, scale, and depth. Since there are many forms of manipulation, an outright ban on manipulation is not possible, nor is it encouraged since it could undermine the very basis of free markets and even free speech. As a result, this Article proposes a limiting principle on entities identified in literature as “powerful commercial speakers,” focusing on regulating lies and misrepresentations of these entities. This Article outlines disclosure obligations of contextual elements of advertisements and imposes a duty of avoiding false information. In addition to administrative enforcement of commercial lies and misrepresentations, this Article advocates for a new remedy of compensation for autonomy infringement when a powerful speaker lies or disobeys mandated disclosure on products. Third, this Article proposes a complementary solution for long-term effects of manipulation. This solution does not focus on the manipulation itself, but rather offers limitations on data retention for commercial purposes. Such limitations can mitigate the depth of manipulation and may prevent commercial entities from shackling individuals to their past decisions. Fourth, this Article addresses possible objections to the proposed solutions, by demonstrating that they are not in conflict with the First Amendment, but rather promote freedom of expression

    Sustainable Value Co-Creation in Welfare Service Ecosystems : Transforming temporary collaboration projects into permanent resource integration

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    The aim of this paper is to discuss the unexploited forces of user-orientation and shared responsibility to promote sustainable value co-creation during service innovation projects in welfare service ecosystems. The framework is based on the theoretical field of public service logic (PSL) and our thesis is that service innovation seriously requires a user-oriented approach, and that such an approach enables resource integration based on the service-user’s needs and lifeworld. In our findings, we identify prerequisites and opportunities of collaborative service innovation projects in order to transform these projects into sustainable resource integration once they have ended

    Machine Learning Algorithms for Robotic Navigation and Perception and Embedded Implementation Techniques

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    L'abstract è presente nell'allegato / the abstract is in the attachmen

    Flexible Hardware-based Security-aware Mechanisms and Architectures

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    For decades, software security has been the primary focus in securing our computing platforms. Hardware was always assumed trusted, and inherently served as the foundation, and thus the root of trust, of our systems. This has been further leveraged in developing hardware-based dedicated security extensions and architectures to protect software from attacks exploiting software vulnerabilities such as memory corruption. However, the recent outbreak of microarchitectural attacks has shaken these long-established trust assumptions in hardware entirely, thereby threatening the security of all of our computing platforms and bringing hardware and microarchitectural security under scrutiny. These attacks have undeniably revealed the grave consequences of hardware/microarchitecture security flaws to the entire platform security, and how they can even subvert the security guarantees promised by dedicated security architectures. Furthermore, they shed light on the sophisticated challenges particular to hardware/microarchitectural security; it is more critical (and more challenging) to extensively analyze the hardware for security flaws prior to production, since hardware, unlike software, cannot be patched/updated once fabricated. Hardware cannot reliably serve as the root of trust anymore, unless we develop and adopt new design paradigms where security is proactively addressed and scrutinized across the full stack of our computing platforms, at all hardware design and implementation layers. Furthermore, novel flexible security-aware design mechanisms are required to be incorporated in processor microarchitecture and hardware-assisted security architectures, that can practically address the inherent conflict between performance and security by allowing that the trade-off is configured to adapt to the desired requirements. In this thesis, we investigate the prospects and implications at the intersection of hardware and security that emerge across the full stack of our computing platforms and System-on-Chips (SoCs). On one front, we investigate how we can leverage hardware and its advantages, in contrast to software, to build more efficient and effective security extensions that serve security architectures, e.g., by providing execution attestation and enforcement, to protect the software from attacks exploiting software vulnerabilities. We further propose that they are microarchitecturally configured at runtime to provide different types of security services, thus adapting flexibly to different deployment requirements. On another front, we investigate how we can protect these hardware-assisted security architectures and extensions themselves from microarchitectural and software attacks that exploit design flaws that originate in the hardware, e.g., insecure resource sharing in SoCs. More particularly, we focus in this thesis on cache-based side-channel attacks, where we propose sophisticated cache designs, that fundamentally mitigate these attacks, while still preserving performance by enabling that the performance security trade-off is configured by design. We also investigate how these can be incorporated into flexible and customizable security architectures, thus complementing them to further support a wide spectrum of emerging applications with different performance/security requirements. Lastly, we inspect our computing platforms further beneath the design layer, by scrutinizing how the actual implementation of these mechanisms is yet another potential attack surface. We explore how the security of hardware designs and implementations is currently analyzed prior to fabrication, while shedding light on how state-of-the-art hardware security analysis techniques are fundamentally limited, and the potential for improved and scalable approaches

    LIPIcs, Volume 274, ESA 2023, Complete Volume

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    LIPIcs, Volume 274, ESA 2023, Complete Volum
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