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Moodle Usability Assessment Methodology using the Universal Design for Learning perspective arXiv.cs.CY Pub Date : 2024-03-15 Rosana Montes, Liliana Herrera, Emilio Crisol
The application of the Universal Design for Learning framework favors the creation of virtual educational environments for all. It requires developing accessible content, having a usable platform, and the use of flexible didactics and evaluations that promote constant student motivation. The present study aims to design a methodology to evaluate the usability of the Moodle platform based on the principles
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Safety Cases: Justifying the Safety of Advanced AI Systems arXiv.cs.CY Pub Date : 2024-03-15 Joshua Clymer, Nick Gabrieli, David Krueger, Thomas Larsen
As AI systems become more advanced, companies and regulators will make difficult decisions about whether it is safe to train and deploy them. To prepare for these decisions, we investigate how developers could make a 'safety case,' which is a structured rationale that AI systems are unlikely to cause a catastrophe. We propose a framework for organizing a safety case and discuss four categories of arguments
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AI-enhanced Collective Intelligence: The State of the Art and Prospects arXiv.cs.CY Pub Date : 2024-03-15 Hao Cui, Taha Yasseri
The current societal challenges exceed the capacity of human individual or collective effort alone. As AI evolves, its role within human collectives is poised to vary from an assistive tool to a participatory member. Humans and AI possess complementary capabilities that, when synergized, can achieve a level of collective intelligence that surpasses the collective capabilities of either humans or AI
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Understanding Stress: A Web Interface for Mental Arithmetic Tasks in a Trier Social Stress Test arXiv.cs.CY Pub Date : 2024-03-15 Manjeet Yadav, Nilesh Kumar Sahu
Stress is a dynamic process that reflects the responses of the brain. Traditional methods for measuring stress are often time-consuming and susceptible to recall bias. To address this, we investigated changes in heart rate (HR) during the Trier Social Stress Test (TSST). Our study incorporated varying levels of complexity in mental arithmetic problems. Participants' HR increased during the Mental Arithmetic
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Emotion-Aware Multimodal Fusion for Meme Emotion Detection arXiv.cs.CY Pub Date : 2024-03-15 Shivam Sharma, Ramaneswaran S, Md. Shad Akhtar, Tanmoy Chakraborty
The ever-evolving social media discourse has witnessed an overwhelming use of memes to express opinions or dissent. Besides being misused for spreading malcontent, they are mined by corporations and political parties to glean the public's opinion. Therefore, memes predominantly offer affect-enriched insights towards ascertaining the societal psyche. However, the current approaches are yet to model
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Designing Sousveillance Tools for Gig Workers arXiv.cs.CY Pub Date : 2024-03-15 Kimberly Do, Maya De Los Santos, Michael Muller, Saiph Savage
As independently-contracted employees, gig workers disproportionately suffer the consequences of workplace surveillance, which include increased pressures to work, breaches of privacy, and decreased digital autonomy. Despite the negative impacts of workplace surveillance, gig workers lack the tools, strategies, and workplace social support to protect themselves against these harms. Meanwhile, some
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Comparing Rationality Between Large Language Models and Humans: Insights and Open Questions arXiv.cs.CY Pub Date : 2024-03-14 Dana Alsagheer, Rabimba Karanjai, Nour Diallo, Weidong Shi, Yang Lu, Suha Beydoun, Qiaoning Zhang
This paper delves into the dynamic landscape of artificial intelligence, specifically focusing on the burgeoning prominence of large language models (LLMs). We underscore the pivotal role of Reinforcement Learning from Human Feedback (RLHF) in augmenting LLMs' rationality and decision-making prowess. By meticulously examining the intricate relationship between human interaction and LLM behavior, we
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Predicting Generalization of AI Colonoscopy Models to Unseen Data arXiv.cs.CY Pub Date : 2024-03-14 Joel Shor, Carson McNeil, Yotam Intrator, Joseph R Ledsam, Hiro-o Yamano, Daisuke Tsurumaru, Hiroki Kayama, Atsushi Hamabe, Koji Ando, Mitsuhiko Ota, Haruei Ogino, Hiroshi Nakase, Kaho Kobayashi, Masaaki Miyo, Eiji Oki, Ichiro Takemasa, Ehud Rivlin, Roman Goldenberg
Background and aims Generalizability of AI colonoscopy algorithms is important for wider adoption in clinical practice. However, current techniques for evaluating performance on unseen data require expensive and time-intensive labels. Methods We use a "Masked Siamese Network" (MSN) to identify novel phenomena in unseen data and predict polyp detector performance. MSN is trained to predict masked out
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Unlocking the Potential of Open Government Data: Exploring the Strategic, Technical, and Application Perspectives of High-Value Datasets Opening in Taiwan arXiv.cs.CY Pub Date : 2024-03-14 Hsien-Lee Tseng, Anastasija Nikiforova
Today, data has an unprecedented value as it forms the basis for data-driven decision-making, including serving as an input for AI models, where the latter is highly dependent on the availability of the data. However, availability of data in an open data format creates a little added value, where the value of these data, i.e., their relevance to the real needs of the end user, is key. This is where
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Older adults' safety and security online: A post-pandemic exploration of attitudes and behaviors arXiv.cs.CY Pub Date : 2024-03-14 Edgar Pacheco
Older adults' growing use of the internet and related technologies, further accelerated by the COVID-19 pandemic, has prompted not only a critical examination of their behaviors and attitudes about online threats but also a greater understanding of the roles of specific characteristics within this population group. Based on survey data and using descriptive and inferential statistics, this empirical
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MetroGNN: Metro Network Expansion with Reinforcement Learning arXiv.cs.CY Pub Date : 2024-03-14 Hongyuan Su, Yu Zheng, Jingtao Ding, Depeng Jin, Yong Li
Selecting urban regions for metro network expansion to meet maximal transportation demands is crucial for urban development, while computationally challenging to solve. The expansion process relies not only on complicated features like urban demographics and origin-destination (OD) flow but is also constrained by the existing metro network and urban geography. In this paper, we introduce a reinforcement
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Trust AI Regulation? Discerning users are vital to build trust and effective AI regulation arXiv.cs.CY Pub Date : 2024-03-14 Zainab Alalawi, Paolo Bova, Theodor Cimpeanu, Alessandro Di Stefano, Manh Hong Duong, Elias Fernandez Domingos, The Anh Han, Marcus Krellner, Bianca Ogbo, Simon T. Powers, Filippo Zimmaro
There is general agreement that some form of regulation is necessary both for AI creators to be incentivised to develop trustworthy systems, and for users to actually trust those systems. But there is much debate about what form these regulations should take and how they should be implemented. Most work in this area has been qualitative, and has not been able to make formal predictions. Here, we propose
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Gun Culture in Fringe Social Media arXiv.cs.CY Pub Date : 2024-03-14 Fatemeh Tahmasbi, Aakarsha Chug, Barry Bradlyn, Jeremy Blackburn
The increasing frequency of mass shootings in the United States has, unfortunately, become a norm. While the issue of gun control in the US involves complex legal concerns, there are also societal issues at play. One such social issue is so-called "gun culture," i.e., a general set of beliefs and actions related to gun ownership. However relatively little is known about gun culture, and even less is
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An Extensive Comparison of Static Application Security Testing Tools arXiv.cs.CY Pub Date : 2024-03-14 Matteo Esposito, Valentina Falaschi, Davide Falessi
Context: Static Application Security Testing Tools (SASTTs) identify software vulnerabilities to support the security and reliability of software applications. Interestingly, several studies have suggested that alternative solutions may be more effective than SASTTs due to their tendency to generate false alarms, commonly referred to as low Precision. Aim: We aim to comprehensively evaluate SASTTs
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Caveat Lector: Large Language Models in Legal Practice arXiv.cs.CY Pub Date : 2024-03-14 Eliza Mik
The current fascination with large language models, or LLMs, derives from the fact that many users lack the expertise to evaluate the quality of the generated text. LLMs may therefore appear more capable than they actually are. The dangerous combination of fluency and superficial plausibility leads to the temptation to trust the generated text and creates the risk of overreliance. Who would not trust
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Usable XAI: 10 Strategies Towards Exploiting Explainability in the LLM Era arXiv.cs.CY Pub Date : 2024-03-13 Xuansheng Wu, Haiyan Zhao, Yaochen Zhu, Yucheng Shi, Fan Yang, Tianming Liu, Xiaoming Zhai, Wenlin Yao, Jundong Li, Mengnan Du, Ninghao Liu
Explainable AI (XAI) refers to techniques that provide human-understandable insights into the workings of AI models. Recently, the focus of XAI is being extended towards Large Language Models (LLMs) which are often criticized for their lack of transparency. This extension calls for a significant transformation in XAI methodologies because of two reasons. First, many existing XAI methods cannot be directly
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Language-based game theory in the age of artificial intelligence arXiv.cs.CY Pub Date : 2024-03-13 Valerio Capraro, Roberto Di Paolo, Matjaz Perc, Veronica Pizziol
Understanding human behaviour in decision problems and strategic interactions has wide-ranging applications in economics, psychology, and artificial intelligence. Game theory offers a robust foundation for this understanding, based on the idea that individuals aim to maximize a utility function. However, the exact factors influencing strategy choices remain elusive. While traditional models try to
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Towards a Privacy and Security-Aware Framework for Ethical AI: Guiding the Development and Assessment of AI Systems arXiv.cs.CY Pub Date : 2024-03-13 Daria Korobenko, Anastasija Nikiforova, Rajesh Sharma
As artificial intelligence continues its unprecedented global expansion, accompanied by a proliferation of benefits, an increasing apprehension about the privacy and security implications of AI-enabled systems emerges. The pivotal question of effectively controlling AI development at both jurisdictional and organizational levels has become a prominent theme in contemporary discourse. While the European
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Governing Through the Cloud: The Intermediary Role of Compute Providers in AI Regulation arXiv.cs.CY Pub Date : 2024-03-13 Lennart Heim, Tim Fist, Janet Egan, Sihao Huang, Stephen Zekany, Robert Trager, Michael A Osborne, Noa Zilberman
As jurisdictions around the world take their first steps toward regulating the most powerful AI systems, such as the EU AI Act and the US Executive Order 14110, there is a growing need for effective enforcement mechanisms that can verify compliance and respond to violations. We argue that compute providers should have legal obligations and ethical responsibilities associated with AI development and
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Interactive environments for training children's curiosity through the practice of metacognitive skills: a pilot study arXiv.cs.CY Pub Date : 2024-03-13 Rania Abdelghani, Edith Law, Chloé Desvaux, Pierre-Yves Oudeyer, Hélène Sauzéon
Curiosity-driven learning has shown significant positive effects on students' learning experiences and outcomes. But despite this importance, reports show that children lack this skill, especially in formal educational settings. To address this challenge, we propose an 8-session workshop that aims to enhance children's curiosity through training a set of specific metacognitive skills we hypothesize
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Preserving Automotive Heritage: A Blockchain-Based Solution for Secure Documentation of Classic Cars Restoration arXiv.cs.CY Pub Date : 2024-03-12 José Murta, Vasco Amaral, Fernando Brito e Abreu
Classic automobiles are an important part of the automotive industry and represent the historical and technological achievements of certain eras. However, to be considered masterpieces, they must be maintained in pristine condition or restored according to strict guidelines applied by expert services. Therefore, all data about restoration processes and other relevant information about these vehicles
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Exploring the Impact of ChatGPT on Student Interactions in Computer-Supported Collaborative Learning arXiv.cs.CY Pub Date : 2024-03-11 Han Kyul Kim, Shriniwas Nayak, Aleyeh Roknaldin, Xiaoci Zhang, Marlon Twyman, Stephen Lu
The growing popularity of generative AI, particularly ChatGPT, has sparked both enthusiasm and caution among practitioners and researchers in education. To effectively harness the full potential of ChatGPT in educational contexts, it is crucial to analyze its impact and suitability for different educational purposes. This paper takes an initial step in exploring the applicability of ChatGPT in a computer-supported
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Retail Central Bank Digital Currency: Motivations, Opportunities, and Mistakes arXiv.cs.CY Pub Date : 2024-03-11 Geoffrey Goodell, Hazem Danny Al-Nakib, Tomaso Aste
Nations around the world are conducting research into the design of central bank digital currency (CBDC), a new, digital form of money that would be issued by central banks alongside cash and central bank reserves. Retail CBDC would be used by individuals and businesses as form of money suitable for routine commerce. An important motivating factor in the development of retail CBDC is the decline of
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MoralBERT: Detecting Moral Values in Social Discourse arXiv.cs.CY Pub Date : 2024-03-12 Vjosa Preniqi, Iacopo Ghinassi, Kyriaki Kalimeri, Charalampos Saitis
Morality plays a fundamental role in how we perceive information while greatly influencing our decisions and judgements. Controversial topics, including vaccination, abortion, racism, and sexuality, often elicit opinions and attitudes that are not solely based on evidence but rather reflect moral worldviews. Recent advances in natural language processing have demonstrated that moral values can be gauged
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On the Preservation of Africa's Cultural Heritage in the Age of Artificial Intelligence arXiv.cs.CY Pub Date : 2024-03-11 Mohamed El Louadi
In this paper we delve into the historical evolution of data as a fundamental element in communication and knowledge transmission. The paper traces the stages of knowledge dissemination from oral traditions to the digital era, highlighting the significance of languages and cultural diversity in this progression. It also explores the impact of digital technologies on memory, communication, and cultural
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Authorship and the Politics and Ethics of LLM Watermarks arXiv.cs.CY Pub Date : 2024-03-11 Tim Räz
Recently, watermarking schemes for large language models (LLMs) have been proposed to distinguish text generated by machines and by humans. The present paper explores philosophical, political, and ethical ramifications of implementing and using watermarking schemes. A definition of authorship that includes both machines (LLMs) and humans is proposed to serve as a backdrop. It is argued that private
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Exploiting the Margin: How Capitalism Fuels AI at the Expense of Minoritized Groups arXiv.cs.CY Pub Date : 2024-03-10 Nelson Colón Vargas
This article investigates the complex nexus of capitalism, racial oppression, and artificial intelligence (AI), revealing how these elements coalesce to deepen social inequities. By tracing the historical exploitation of marginalized communities through capitalist practices, the study demonstrates how AI technologies not only reflect but also amplify societal biases, particularly in exacerbating racial
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Simulating Family Conversations using LLMs: Demonstration of Parenting Styles arXiv.cs.CY Pub Date : 2024-03-10 Frank Tian-fang YeDepartment of Applied Social Sciences, The Hong Kong Polytechnic University, Hong Kong SAR, Xiaozi GaoDepartment of Early Childhood Education, The Education University of Hong Kong, Hong Kong SAR
This study presents a framework for conducting psychological and linguistic research through simulated conversations using large language models (LLMs). The proposed methodology offers significant advantages, particularly for simulating human interactions involving potential unethical language or behaviors that would be impermissible in traditional experiments with human participants. As a demonstration
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Sistemas de información de salud en contextos extremos: Uso de teléfonos móviles para combatir el sida en Uganda arXiv.cs.CY Pub Date : 2024-03-10 Livingstone NjubaKalangala Infrastructure Services LtdUniversity of Manchester, Juan E. Gómez-MorantesPontificia Universidad Javeriana, Andrea HerreraUniversidad de los Andes, Sonia CamachoUniversidad de los Andes
The HIV/AIDS pandemic is a global issue that has unequally affected several countries. Due to the complexity of this condition and the human drama it represents to those most affected by it, several fields have contributed to solving or at least alleviating this situation, and the information systems (IS) field has not been absent from these efforts. With the importance of antiretroviral therapy (ART)
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And Then the Hammer Broke: Reflections on Machine Ethics from Feminist Philosophy of Science arXiv.cs.CY Pub Date : 2024-03-09 Andre Ye
Vision is an important metaphor in ethical and political questions of knowledge. The feminist philosopher Donna Haraway points out the ``perverse'' nature of an intrusive, alienating, all-seeing vision (to which we might cry out ``stop looking at me!''), but also encourages us to embrace the embodied nature of sight and its promises for genuinely situated knowledge. Current technologies of machine
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Defaults: a double-edged sword in governing common resources arXiv.cs.CY Pub Date : 2024-03-11 Eladio Montero-Porras, Rémi Suchon, Tom Lenaerts, Elias Fernández Domingos
Extracting from shared resources requires making choices to balance personal profit and sustainability. We present the results of a behavioural experiment wherein we manipulate the default extraction from a finite resource. Participants were exposed to two treatments -- pro-social or self-serving extraction defaults -- and a control without defaults. We examined the persistence of these nudges by removing
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Restoring Ancient Ideograph: A Multimodal Multitask Neural Network Approach arXiv.cs.CY Pub Date : 2024-03-11 Siyu Duan, Jun Wang, Qi Su
Cultural heritage serves as the enduring record of human thought and history. Despite significant efforts dedicated to the preservation of cultural relics, many ancient artefacts have been ravaged irreversibly by natural deterioration and human actions. Deep learning technology has emerged as a valuable tool for restoring various kinds of cultural heritages, including ancient text restoration. Previous
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Academically intelligent LLMs are not necessarily socially intelligent arXiv.cs.CY Pub Date : 2024-03-11 Ruoxi Xu, Hongyu Lin, Xianpei Han, Le Sun, Yingfei Sun
The academic intelligence of large language models (LLMs) has made remarkable progress in recent times, but their social intelligence performance remains unclear. Inspired by established human social intelligence frameworks, particularly Daniel Goleman's social intelligence theory, we have developed a standardized social intelligence test based on real-world social scenarios to comprehensively assess
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Understanding Hybrid Spaces: Designing a Spacetime Model to Represent Dynamic Topologies of Hybrid Spaces arXiv.cs.CY Pub Date : 2024-03-08 Wolfgang Höhl
This paper develops a spatiotemporal model for the visualization of dynamic topologies of hybrid spaces. The visualization of spatiotemporal data is a well-known problem, for example in digital twins in urban planning. There is also a lack of a basic ontology for understanding hybrid spaces. The developed spatiotemporal model has three levels: a level of places and media types, a level of perception
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Interoperability of the Metaverse: A Digital Ecosystem Perspective Review arXiv.cs.CY Pub Date : 2024-03-08 Liang Yang, Shi-Ting Ni, Yuyang Wang, Ao Yu, Jyh-An Lee, Pan Hui
The Metaverse is at the vanguard of the impending digital revolution, with the potential to significantly transform industries and lifestyles. However, in 2023, skepticism surfaced within industrial and academic spheres, raising concerns that excitement may outpace actual technological progress. Interoperability, recognized as a major barrier to the Metaverse's full potential, is central to this debate
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Tell me the truth: A system to measure the trustworthiness of Large Language Models arXiv.cs.CY Pub Date : 2024-03-08 Carlo Lipizzi
Large Language Models (LLM) have taken the front seat in most of the news since November 2023, when ChatGPT was introduced. After more than one year, one of the major reasons companies are resistant to adopting them is the limited confidence they have in the trustworthiness of those systems. In a study by (Baymard, 2023), ChatGPT-4 showed an 80.1% false-positive error rate in identifying usability
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Disciplining deliberation: a sociotechnical perspective on machine learning trade-offs arXiv.cs.CY Pub Date : 2024-03-07 Sina Fazelpour
This paper focuses on two highly publicized formal trade-offs in the field of responsible artificial intelligence (AI) -- between predictive accuracy and fairness and between predictive accuracy and interpretability. These formal trade-offs are often taken by researchers, practitioners, and policy-makers to directly imply corresponding tensions between underlying values. Thus interpreted, the trade-offs
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Don't Blame the Data, Blame the Model: Understanding Noise and Bias When Learning from Subjective Annotations arXiv.cs.CY Pub Date : 2024-03-06 Abhishek Anand, Negar Mokhberian, Prathyusha Naresh Kumar, Anweasha Saha, Zihao He, Ashwin Rao, Fred Morstatter, Kristina Lerman
Researchers have raised awareness about the harms of aggregating labels especially in subjective tasks that naturally contain disagreements among human annotators. In this work we show that models that are only provided aggregated labels show low confidence on high-disagreement data instances. While previous studies consider such instances as mislabeled, we argue that the reason the high-disagreement
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Demographic Dynamics and Artificial Intelligence: Challenges and Opportunities in Europe and Africa for 2050 arXiv.cs.CY Pub Date : 2024-03-06 Mohamed El Louadi
This paper explores the complex relationship between demographics and artificial intelligence (AI) advances in Europe and Africa, projecting into the year 2050. The advancement of AI technologies has occurred at diverse rates, with Africa lagging behind Europe. Moreover, the imminent economic consequences of demographic shifts require a more careful examination of immigration patterns, with Africa
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Digitality as a "longue durèe" historical phenomenon arXiv.cs.CY Pub Date : 2024-03-06 Salvatore Spina
The digital age introduced the Digital Ecological Niche (DEN), revolutionizing human interactions. The advent of Digital History (DHy) has marked a methodological shift in historical studies, tracing its roots to Babbage and Lovelace's 19th-century work on "coding" as a foundational communication process, fostering a new interaction paradigm between humans and machines, termed "person2persons2machines
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An Online Approach to Solving Public Transit Stationing and Dispatch Problem arXiv.cs.CY Pub Date : 2024-03-05 Jose Paolo Talusan, Chaeeun Han, Ayan Mukhopadhyay, Aron Laszka, Dan Freudberg, Abhishek Dubey
Public bus transit systems provide critical transportation services for large sections of modern communities. On-time performance and maintaining the reliable quality of service is therefore very important. Unfortunately, disruptions caused by overcrowding, vehicular failures, and road accidents often lead to service performance degradation. Though transit agencies keep a limited number of vehicles
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Impoverished Language Technology: The Lack of (Social) Class in NLP arXiv.cs.CY Pub Date : 2024-03-06 Amanda Cercas Curry, Zeerak Talat, Dirk Hovy
Since Labov's (1964) foundational work on the social stratification of language, linguistics has dedicated concerted efforts towards understanding the relationships between socio-demographic factors and language production and perception. Despite the large body of evidence identifying significant relationships between socio-demographic factors and language production, relatively few of these factors
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Quantifying Media Influence on Covid-19 Mask-Wearing Beliefs arXiv.cs.CY Pub Date : 2024-03-06 Nicholas Rabb, Nitya Nadgir, Jan P. de Ruiter, Lenore Cowen
How political beliefs change in accordance with media exposure is a complicated matter. Some studies have been able to demonstrate that groups with different media diets in the aggregate (e.g., U.S. media consumers ingesting partisan news) arrive at different beliefs about policy issues, but proving this from data at a granular level -- at the level of attitudes expressed in news stories -- remains
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Emotional Manipulation Through Prompt Engineering Amplifies Disinformation Generation in AI Large Language Models arXiv.cs.CY Pub Date : 2024-03-06 Rasita Vinay, Giovanni Spitale, Nikola Biller-Andorno, Federico Germani
This study investigates the generation of synthetic disinformation by OpenAI's Large Language Models (LLMs) through prompt engineering and explores their responsiveness to emotional prompting. Leveraging various LLM iterations using davinci-002, davinci-003, gpt-3.5-turbo and gpt-4, we designed experiments to assess their success in producing disinformation. Our findings, based on a corpus of 19,800
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Global Geolocated Realtime Data of Interfleet Urban Transit Bus Idling arXiv.cs.CY Pub Date : 2024-03-06 Nicholas Kunz, H. Oliver Gao
Urban transit bus idling is a contributor to ecological stress, economic inefficiency, and medically hazardous health outcomes due to emissions. The global accumulation of this frequent pattern of undesirable driving behavior is enormous. In order to measure its scale, we propose GRD-TRT- BUF-4I (Ground Truth Buffer for Idling) an extensible, realtime detection system that records the geolocation and
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An AI-enabled Agent-Based Model and Its Application in Measles Outbreak Simulation for New Zealand arXiv.cs.CY Pub Date : 2024-03-06 Sijin Zhang, Alvaro Orsi, Richard Dean, Lei Chen, Rachel Qiu, Jiawei Zhao
Agent Based Models (ABMs) have emerged as a powerful tool for investigating complex social interactions, particularly in the context of public health and infectious disease investigation. In an effort to enhance the conventional ABM, enabling automated model calibration and reducing the computational resources needed for scaling up the model, we have developed a tensorized and differentiable agent-based
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Leveraging Federated Learning for Automatic Detection of Clopidogrel Treatment Failures arXiv.cs.CY Pub Date : 2024-03-05 Samuel Kim, Min Sang Kim
The effectiveness of clopidogrel, a widely used antiplatelet medication, varies significantly among individuals, necessitating the development of precise predictive models to optimize patient care. In this study, we leverage federated learning strategies to address clopidogrel treatment failure detection. Our research harnesses the collaborative power of multiple healthcare institutions, allowing them
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The Case for Globalizing Fairness: A Mixed Methods Study on Colonialism, AI, and Health in Africa arXiv.cs.CY Pub Date : 2024-03-05 Mercy Asiedu, Awa Dieng, Alexander Haykel, Negar Rostamzadeh, Stephen Pfohl, Chirag Nagpal, Maria Nagawa, Abigail Oppong, Sanmi Koyejo, Katherine Heller
With growing application of machine learning (ML) technologies in healthcare, there have been calls for developing techniques to understand and mitigate biases these systems may exhibit. Fair-ness considerations in the development of ML-based solutions for health have particular implications for Africa, which already faces inequitable power imbalances between the Global North and South.This paper seeks
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An Ensemble Framework for Explainable Geospatial Machine Learning Models arXiv.cs.CY Pub Date : 2024-03-05 Lingbo Liu
Analyzing spatial varying effect is pivotal in geographic analysis. Yet, accurately capturing and interpreting this variability is challenging due to the complexity and non-linearity of geospatial data. Herein, we introduce an integrated framework that merges local spatial weighting scheme, Explainable Artificial Intelligence (XAI), and cutting-edge machine learning technologies to bridge the gap between
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When Industry meets Trustworthy AI: A Systematic Review of AI for Industry 5.0 arXiv.cs.CY Pub Date : 2024-03-05 Eduardo Vyhmeister, Gabriel G. Castane
Industry is at the forefront of adopting new technologies, and the process followed by the adoption has a significant impact on the economy and society. In this work, we focus on analysing the current paradigm in which industry evolves, making it more sustainable and Trustworthy. In Industry 5.0, Artificial Intelligence (AI), among other technology enablers, is used to build services from a sustainable
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Improving the quality of individual-level online information tracking: challenges of existing approaches and introduction of a new content- and long-tail sensitive academic solution arXiv.cs.CY Pub Date : 2024-03-05 Silke Adam, Mykola Makhortykh, Michaela Maier, Viktor Aigenseer, Aleksandra Urman, Teresa Gil Lopez, Clara Christner, Ernesto de León, Roberto Ulloa
This article evaluates the quality of data collection in individual-level desktop information tracking used in the social sciences and shows that the existing approaches face sampling issues, validity issues due to the lack of content-level data and their disregard of the variety of devices and long-tail consumption patterns as well as transparency and privacy issues. To overcome some of these problems
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An Empirical Analysis on the Use and Reporting of National Security Letters arXiv.cs.CY Pub Date : 2024-03-05 Alex Bellon, Miro Haller, Andrey Labunets, Enze Liu, Stefan Savage
National Security Letters (NSLs) are similar to administrative subpoenas and can be issued directly by elements of the executive branch without requiring prior approval from a court or grand jury. Importantly, NSLs authorize the imposition of nondisclosure orders (aka "gag orders") on the receiving party. Controversy about potential abuses of this authority has driven a range of legal and policy discussions
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Design2Code: How Far Are We From Automating Front-End Engineering? arXiv.cs.CY Pub Date : 2024-03-05 Chenglei Si, Yanzhe Zhang, Zhengyuan Yang, Ruibo Liu, Diyi Yang
Generative AI has made rapid advancements in recent years, achieving unprecedented capabilities in multimodal understanding and code generation. This can enable a new paradigm of front-end development, in which multimodal LLMs might directly convert visual designs into code implementations. In this work, we formalize this as a Design2Code task and conduct comprehensive benchmarking. Specifically, we
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Metamorpheus: Interactive, Affective, and Creative Dream Narration Through Metaphorical Visual Storytelling arXiv.cs.CY Pub Date : 2024-03-01 Qian Wan, Xin Feng, Yining Bei, Zhiqi Gao, Zhicong Lu
Human emotions are essentially molded by lived experiences, from which we construct personalised meaning. The engagement in such meaning-making process has been practiced as an intervention in various psychotherapies to promote wellness. Nevertheless, to support recollecting and recounting lived experiences in everyday life remains under explored in HCI. It also remains unknown how technologies such
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Position Paper: Towards Implicit Prompt For Text-To-Image Models arXiv.cs.CY Pub Date : 2024-03-04 Yue Yang, Yuqi lin, Hong Liu, Wenqi Shao, Runjian Chen, Hailong Shang, Yu Wang, Yu Qiao, Kaipeng Zhang, Ping Luo
Recent text-to-image (T2I) models have had great success, and many benchmarks have been proposed to evaluate their performance and safety. However, they only consider explicit prompts while neglecting implicit prompts (hint at a target without explicitly mentioning it). These prompts may get rid of safety constraints and pose potential threats to the applications of these models. This position paper
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AI Language Models Could Both Help and Harm Equity in Marine Policymaking: The Case Study of the BBNJ Question-Answering Bot arXiv.cs.CY Pub Date : 2024-03-04 Matt Ziegler, Sarah Lothian, Brian O'Neill, Richard Anderson, Yoshitaka Ota
AI Large Language Models (LLMs) like ChatGPT are set to reshape some aspects of policymaking processes. Policy practitioners are already using ChatGPT for help with a variety of tasks: from drafting statements, submissions, and presentations, to conducting background research. We are cautiously hopeful that LLMs could be used to promote a marginally more balanced footing among decision makers in policy
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Recommendations for Government Development and Use of Advanced Automated Systems to Make Decisions about Individuals arXiv.cs.CY Pub Date : 2024-03-04 Susan Landau, James X. Dempsey, Ece Kamar, Steven M. Bellovin
Contestability -- the ability to effectively challenge a decision -- is critical to the implementation of fairness. In the context of governmental decision making about individuals, contestability is often constitutionally required as an element of due process; specific procedures may be required by state or federal law relevant to a particular program. In addition, contestability can be a valuable
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Deeply Embedded Wages: Navigating Digital Payments in Data Work arXiv.cs.CY Pub Date : 2024-03-03 Julian Posada
Many of the world's workers rely on digital platforms for their income. In Venezuela, a nation grappling with extreme inflation and where most of the workforce is self-employed, data production platforms for machine learning have emerged as a viable opportunity for many to earn a flexible income in US dollars. Platform workers are deeply interconnected within a vast network of firms and entities that
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Autonomous Intelligent Systems: From Illusion of Control to Inescapable Delusion arXiv.cs.CY Pub Date : 2024-03-02 Stéphane Grumbach, Giorgio Resta, Riccardo Torlone
Autonomous systems, including generative AI, have been adopted faster than previous digital innovations. Their impact on society might as well be more profound, with a radical restructuring of the economy of knowledge and dramatic consequences for social and institutional balances. Different attitudes to control these systems have emerged rooted in the classical pillars of legal systems, proprietary
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Inevitable-Metaverse: A Novel Twitter Dataset for Public Sentiments on Metaverse arXiv.cs.CY Pub Date : 2024-03-02 Kadhim Hayawi, Sakib Shahriar, Mohamed Adel Serhani, Eiman Alothali
Metaverse has emerged as a novel technology with the objective to merge the physical world into the virtual world. This technology has seen a lot of interest and investment in recent times from prominent organizations including Facebook which has changed its company name to Meta with the goal of being the leader in developing this technology. Although people in general are excited about the prospects