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The Safety of Autonomy: A Systematic Approach Computer (IF 2.2) Pub Date : 2024-04-03 John A. McDermid, Radu Calinescu, Ibrahim Habli, Richard Hawkins, Yan Jia, John Molloy, Matt Osborne, Colin Paterson, Zoe Porter, Philippa Ryan Conmy
Autonomy does not subvert existing safety processes, but they must be supplemented with methods that address autonomy’s challenges, especially where perception and decision-making tasks are implemented with machine learning. We present an approach to address the safety of autonomous systems, building on and complementing established safety engineering methods.
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The CORRECT First Course in Computing for Serious Students Computer (IF 2.2) Pub Date : 2024-04-02 Yale N. Patt
This article proposes a bottom-up approach to the first course in computing, in contrast to the conventional top-down approach of teaching programming in a high-level language first, describing details of the course and its benefits.
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Semiconductor Memory Technologies: State-of-the-Art and Future Trends Computer (IF 2.2) Pub Date : 2024-04-02 Shimeng Yu, Tae-Hyeon Kim
This article surveys the recent development of semiconductor memory technologies spanning from the mainstream static random-access memory, dynamic random-access memory, and flash memory toward emerging candidates such as resistive, ferroelectric, and magnetic memories. Pathways for future technological innovations are presented.
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23 Security Risks in Black-Box Large Language Model Foundation Models Computer (IF 2.2) Pub Date : 2024-04-02 Gary McGraw, Richie Bonett, Harold Figueroa, Katie McMahon
We applied our previous generic machine learning risk analysis to the more specific case of large language models (LLMs), identifying an architectural black box with 23 associated risks—a reasonable starting point for the regulation of LLMs.
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Thoughts on Dependability Computer (IF 2.2) Pub Date : 2024-04-02 Jeffrey Voas
Dependability suffers from various misunderstandings as to what the term means. Here, we discuss a few of these difficulties.
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Open Digital Safety Computer (IF 2.2) Pub Date : 2024-04-02 Sean McGregor
This work makes the argument for elevating “safety data” as a class of obliged-to-share open data among intelligent system vendors so developers of digital systems can produce safer systems without independently producing repeated harms.
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Machine Learning for Enhancing Public Safety in Modern Cities Computer (IF 2.2) Pub Date : 2024-04-02 Eugenio Cesario
Machine learning offers effective techniques to analyze crime data with spatial and temporal information, providing accurate predictions of criminal activities, with the aim to develop more effective strategies for crime prevention and improve public safety.
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Economics of Artificial Intelligence Governance Computer (IF 2.2) Pub Date : 2024-04-02 Nir Kshetri
Artificial intelligence (AI)-related institutions are a key factor influencing the economic benefits of this innovations and how such benefits are distributed. This article examines the current stage of AI governance institutions and barriers hindering the widespread adoption of such institutions.
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Exploring Threats, Defenses, and Privacy-Preserving Techniques in Federated Learning: A Survey Computer (IF 2.2) Pub Date : 2024-04-02 Ren-Yi Huang, Dumindu Samaraweera, J. Morris Chang
This article presents a comprehensive survey of both attack and defense mechanisms within the federated learning (FL) landscape. Furthermore, it explores the challenges involved and outlines future directions for the development of a robust and efficient FL solution.
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Industry Trends 2024: Innovation Needs Competence Computer (IF 2.2) Pub Date : 2024-04-02 Christof Ebert
What are the major industry challenges? A global industry survey gives answers. Competitiveness is increasingly jeopardized by lack of competences. The effects of working in office versus remote work get tangible. The article provides insights and resolutions.
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Distributed Quantum Computing via Integrating Quantum and Classical Computing Computer (IF 2.2) Pub Date : 2024-04-02 Wei Tang, Margaret Martonosi
As quantum computing confronts scalability challenges, distributed hybrid QPU–CPU techniques emerge as a crucial solution. These techniques distribute quantum algorithms across quantum and classical computing resources to surpass the computational reach of either one alone.
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Software Dependability Measurement at the Age of 36 Computer (IF 2.2) Pub Date : 2024-04-02 Robert V. Binder
Thirty-six years after the first edition of IEEE standard 982.1, Measures of the Software Aspects of Dependability, the third edition focuses on the measurement of in-service software dependability. This article explains how this new point of view evolved and shaped the third edition’s guidance for software dependability measurement.
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50 & 25 Years Ago Computer (IF 2.2) Pub Date : 2024-04-02 Erich Neuhold
Summary form only: Summaries of articles presented in this issue of the publication.
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Dependable Computing Computer (IF 2.2) Pub Date : 2024-04-02 Joanna F. DeFranco, Phil Laplante, Rick Kuhn, Steven Li
With the increased complexity of software systems, dependable, reliable, and trustworthy computing is of paramount importance. Of these qualities, dependability is of particular interest in mission critical systems, where failure can lead to loss of human life. The technology used to build such systems must meet the expectations of its stakeholders’ and regulatory requirements.
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From P Versus NP to Probabilistic and Zero Knowledge Proof Systems Computer (IF 2.2) Pub Date : 2024-04-02 Doron Drusinsky
I present an overview of the field of zero knowledge proof systems, which has evolved considerably over the last four decades, with applications ranging from secure authentication, secure communications, crypto-currency, and online privacy.
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Performance Comparison of Software Reliability Estimation Algorithms Computer (IF 2.2) Pub Date : 2024-04-02 Hiromu Yano, Tadashi Dohi, Hiroyuki Okamura
Specific optimization algorithms have been developed for the purpose of automated software reliability assessment tools. In this article, we propose the Monte Carlo expectation-maximization algorithm as another optimization algorithm, and carry out the performance comparison of the software reliability estimation algorithms through comprehensive numerical experiments.
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Computer Highlights Society Magazines Computer (IF 2.2) Pub Date : 2024-04-02
Summaries of articles presented from various Compute Society publications.
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Reliability and Availability Analysis in Practice: Toward Multilevel Models for Complex Systems Computer (IF 2.2) Pub Date : 2024-04-02 Kishor Trivedi, Andrea Bobbio
This article discusses model-driven methods with analytic-numeric solutions. In addition to traditional non-state-space and state-space methods, multilevel methods are explored using real case studies. Challenges met while developing and solving dependability models of real systems are listed, and some solutions are outlined.
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Internet of Things-Flavored Chips Computer (IF 2.2) Pub Date : 2024-04-02 Joanna F. DeFranco, Jeffrey Voas
Systems that use Internet of Things (IoT), Artificial Intelligence of Things, and 5G use IoT semiconductors chips to meet the requirements of those systems. This article will highlight the features and applications of IoT chips.
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Dependability Improvement Depends on Dependable Measurement Computer (IF 2.2) Pub Date : 2024-04-02 Les Hatton
If computing is ever to be considered dependable by all its stakeholders, both computer scientists and computer users, we must address the most fundamental aspect of process improvement, that of measurement. As currently practiced, it is wholly and demonstrably inadequate.
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High-Integrity Runtime Verification Computer (IF 2.2) Pub Date : 2024-04-02 Alwyn E. Goodloe, Klaus Havelund
We introduce the concept of runtime verification that can be a critical element of an assurance case by guaranteeing that specifications hold at runtime. We show how runtime verification can be a trustworthy approach to assuring that critical systems are safe and dependable.
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AI and Big Data in Contemporary Marketing Computer (IF 2.2) Pub Date : 2024-04-02 Sugandha Agarwal, Norita Ahmad, Dima Jamali
This article explores the integration of artificial intelligence (AI) and big data in marketing, emphasizing transformative impacts, benefits (for example, real-time personalization), challenges (for example, biases and data privacy), and the evolving dynamics of human–AI cooperation.
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The Distribution Is the Performance Computer (IF 2.2) Pub Date : 2024-04-02 Eitan Frachtenberg, Viyom Mittal, Pedro Bruel, Michalis Faloutsos, Dejan Milojicic
In this column, we suggest how to sharpen our understanding of computer performance evaluation in light of variability and heterogeneity.
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Human-Centered Trustworthy Framework: A Human–Computer Interaction Perspective Computer (IF 2.2) Pub Date : 2024-03-08 Sonia Sousa, David Lamas, José Cravino, Paulo Martins
The proposed framework (Human-Centered Trustworthy Framework) provides a novel human–computer interaction approach to incorporate positive and meaningful trustful user experiences in the system design process. It helps to illustrate potential users' trust concerns in artificial intelligence and guides nonexperts to avoid designing vulnerable interactions that lead to breaches of trust.
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Making Large Language Models More Reliable and Beneficial: Taking ChatGPT as a Case Study Computer (IF 2.2) Pub Date : 2024-03-08 Abdul Majeed, Seong Oun Hwang
This article suggests practical ways to make large language models more reliable and beneficial by taking ChatGPT as a case study. Specifically, we describe ChatGPT’s workflow and promised services and highlight the perils requiring the immediate attention of ChatGPT stakeholders.
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Computer Highlights Society Magazines Computer (IF 2.2) Pub Date : 2024-03-06
Summary form only: Summaries of articles presented in this issue of the publication.
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Safety and Artificial Intelligence in Cyberphysical Systems Computer (IF 2.2) Pub Date : 2024-03-06 Dimitrios Serpanos, Marilyn Wolf
Safe artificial intelligence/machine learning (AI/ML)-enabled systems require design methodologies that accommodate for failures in AI/ML decisions. Certification of AI/ML systems and components will increase trust and accelerate adoption, deployment, and use in critical domains.
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Security Advantages and Challenges of 3D Heterogeneous Integration Computer (IF 2.2) Pub Date : 2024-03-06 Yuntao Liu, Daniel Xing, Isaac McDaniel, Olsan Ozbay, Abir Akib, Mumtahina Islam Sukanya, Sanjay Rekhi, Ankur Srivastava
Three-dimensional heterogeneous integration offers compelling opportunities to enhance the security and trust in the current semiconductor chain while new attack surfaces may emerge.
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Also in this Issue Computer (IF 2.2) Pub Date : 2024-03-06 Jeffrey Voas
Summary form only: Summaries of articles presented in this issue of the publication.
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Eight Sustainable Practices for Digital Activity Development: Drivers and Barriers in International Higher Education Collaboration Computer (IF 2.2) Pub Date : 2024-03-06 Alice Barana, Marina Marchisio Conte
Short-term technology-enhanced activities of international collaboration conducted in virtual, hybrid, or blended modalities can attract a greater number of students. We selected eight sustainable practices that higher education institutions could adopt to develop digital mobility activities.
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Trustworthy AI-Based Personalized Insulin Recommender for Elderly People Who Have Type-2 Diabetes Computer (IF 2.2) Pub Date : 2024-03-06 Padmapritha T, Korkut Bekiroglu, Subathra Seshadhri, Seshadhri Srinivasan
We propose TRAINER, a TRustworthy Artificial Intelligence-based iNsulin recommendER for elderly individuals with type 2 diabetes, ensuring reliability and trust in insulin dosage recommendations. TRAINER exemplifies this trustworthiness and addresses such concerns by offering reliable insulin recommendations supported by clinical evidence.
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An AI Harms and Governance Framework for Trustworthy AI Computer (IF 2.2) Pub Date : 2024-03-06 Jeremy B. Peckham
Many guidelines have been written and some frameworks proposed for the development of trustworthy artificial intelligence (AI), but a common concern is the lack of precision in definitions, which can make application difficult. This article proposes a novel governance and harms framework to provide more precision in the assessment and deployment of AI to meet trustworthiness objectives.
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Trustworthy AI—Part III Computer (IF 2.2) Pub Date : 2024-03-06 Riccardo Mariani, Francesca Rossi, Rita Cucchiara, Marco Pavone, Barnaby Simkin, Ansgar Koene, Jochen Papenbrock
The final part of our Trustworthy AI special issue features four articles on AI security, reliability, trust, and AI trustworthiness as a whole.
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Assured Autonomy, Artificial Intelligence, and Machine Learning: A Roundtable Discussion Computer (IF 2.2) Pub Date : 2024-03-06 Phil Laplante, Joanna F. DeFranco, Rick Kuhn
This report summarizes a roundtable panel discussion held at the Second Annual IEEE Workshop on Assured Autonomy, AI, and Machine Learning. Eight expert panelists discussed ways to ensure that artificial intelligence and machine learning systems are safe.
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