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This book constitutes the thoroughly refereed proceedings of the 1st International Conference on AI for People: Towards Sustainable AI, CAIP'21, held Virtually, on November 20-24, 2021. This event, organized by the non-profit association 'AI for People', aims to provide a platform for people to present, learn and discuss the use of Artificial Intelligence for the societal good, addressing its benefits as well as its risks. In this year's edition, we focus on Sustainable AI as a movement to foster change towards greater ecological integrity and social justice in the entire life cycle of AI systems. The 11 full papers and 1 short paper presented were carefully reviewed and selected from 27 submissions. The presentations covered multiple research fields like Computer Science, Artificial Intelligence, Social Science, and Philosophy brought the discussion on how to shape Artificial Intelligence technology around human and societal needs. In order to foster this idea, this conference hoped to narrow the gap between civil society and technical experts.
The two volume set LNCS 13052 and 13053 constitutes the refereed proceedings of the 19th International Conference on Computer Analysis of Images and Patterns, CAIP 2021, held virtually, in September 2021. The 87 papers presented were carefully reviewed and selected from 129 submissions. The papers are organized in the following topical sections across the 2 volumes: 3D vision, biomedical image and pattern analysis; machine learning; feature extractions; object recognition; face and gesture, guess the age contest, biometrics, cryptography and security; and segmentation and image restoration.
This book fills a large gap in our understanding of how to prepare teachers for the challenging but increasingly popular task of integrating content and language instruction. It brings together findings on content-based teacher education from Africa, Asia, Australia, Europe and North America in order to inform researchers and teacher educators and enable them to play a critical role in the continued success of such programs. It offers a solid grounding in theories and applications of content-based approaches with empirical studies investigating teacher identity, materials design, use of cognitive discourse functions and best practices for teacher education. Responding to the growing popularity of content-based programs and the shortage of qualified teachers for these contexts, this book promotes teacher-researcher collaboration and provides support for trainee teachers, in-service teachers and course leaders.
This book constitutes the proceedings of the 24th International Conference on Web Information Systems Engineering, WISE 2023, held in Melbourne, Victoria, Australia, in October 2023. The 33 full and 40 short papers were carefully reviewed and selected from 137 submissions. They were organized in topical sections as follows: text and sentiment analysis; question answering and information retrieval; social media and news analysis; security and privacy; web technologies; graph embeddings and link predictions; predictive analysis and machine learning; recommendation systems; natural language processing (NLP) and databases; data analysis and optimization; anomaly and threat detection; streaming data; miscellaneous; explainability and scalability in AI.
As generative AI rapidly advances with the field of artificial intelligence, its presence poses significant ethical, security, and data management challenges. While this technology encourages innovation across various industries, ethical concerns regarding the potential misuse of AI-generated content for misinformation or manipulation may arise. The risks of AI-generated deepfakes and cyberattacks demand more research into effective security tactics. The supervision of datasets required to train generative AI models raises questions about privacy, consent, and responsible data management. As generative AI evolves, further research into the complex issues regarding its potential is required to safeguard ethical values and security of people’s data. Generative AI and Implications for Ethics, Security, and Data Management explores the implications of generative AI across various industries who may use the tool for improved organizational development. The security and data management benefits of generative AI are outlined, while examining the topic within the lens of ethical and social impacts. This book covers topics such as cybersecurity, digital technology, and cloud storage, and is a useful resource for computer engineers, IT professionals, technicians, sociologists, healthcare workers, researchers, scientists, and academicians.
The two-volume set LNCS 13373 and 13374 constitutes the papers of several workshops which were held in conjunction with the 21st International Conference on Image Analysis and Processing, ICIAP 2022, held in Lecce, Italy, in May 2022. The 96 revised full papers presented in the proceedings set were carefully reviewed and selected from 157 submissions. ICIAP 2022 presents the following Sixteen workshops: Volume I: GoodBrother workshop on visual intelligence for active and assisted livingParts can worth like the Whole - PART 2022Workshop on Fine Art Pattern Extraction and Recognition - FAPERWorkshop on Intelligent Systems in Human and Artificial Perception - ISHAPE 2022Artificial Intelligence and Radiomics in Computer-Aided Diagnosis - AIRCADDeep-Learning and High Performance Computing to Boost Biomedical Applications - DeepHealth Volume II: Human Behaviour Analysis for Smart City Environment Safety - HBAxSCESBinary is the new Black (and White): Recent Advances on Binary Image ProcessingArtificial Intelligence for preterm infants’ healthCare - AI-careTowards a Complete Analysis of People: From Face and Body to Clothes - T-CAPArtificial Intelligence for Digital Humanities - AI4DHMedical Transformers - MEDXFLearning in Precision Livestock Farming - LPLFWorkshop on Small-Drone Surveillance, Detection and Counteraction Techniques - WOSDETCMedical Imaging Analysis For Covid-19 - MIACOVID 2022Novel Benchmarks and Approaches for Real-World Continual Learning - CL4REAL
This anthology contributes to creating awareness on how digital ageism operates in relation to the widely spread symbolic representations of old and young age around digital technologies, the (lack of) representation of diverse older individuals in the design, development, and marketing of digital technologies and in the actual algorithms and datasets that constitute them. It also shows how individuals and institutions deal with digital ageism in everyday life. In the past decades, digital technologies permeated most aspects of everyday life. With a focus on how age is represented and experienced in relation to digital technologies leading to digital ageism, digitalisation’s reinforcement of spirals of exclusion and loss of autonomy of some collectives is explored, when it could be natural for a great part of society and represent a sort of improvement. The book addresses social science students and scholars interested in everyday digital technologies, society and the power struggles about it, providing insights from different parts of the globe. By using different methods and touching upon different aspects of digital ageism and how it plays out in contemporary connected data societies, this volume will raise awareness, challenge power, initiate discussions and spur further research into this field. The Open Access version of this book, available at www.taylorfrancis.com, has been made available under a Creative Commons Attribution 4.0 license.
Identifying and stopping the dissemination of fabricated news, hate speech, or deceptive information camouflaged as legitimate news poses a significant technological hurdle. This book presents emergent methodologies and technological approaches of natural language processing through machine learning for counteracting the spread of fake news and hate speech on social media platforms. • Covers various approaches, algorithms, and methodologies for fake news and hate speech detection. • Explains the automatic detection and prevention of fake news and hate speech through paralinguistic clues on social media using artificial intelligence. • Discusses the application of machine learning models to learn linguistic characteristics of hate speech over social media platforms. • Emphasizes the role of multilingual and multimodal processing to detect fake news. • Includes research on different optimization techniques, case studies on the identification, prevention, and social impact of fake news, and GitHub repository links to aid understanding. The text is for professionals and scholars of various disciplines interested in fake news and hate speech detection.