In this paper, we examine the fundamental transformation of Property & Casualty (P&C) insurance through the introduction of Artificial Intelligence. This examination marks the shift from the traditional actuar...In this paper, we examine the fundamental transformation of Property & Casualty (P&C) insurance through the introduction of Artificial Intelligence. This examination marks the shift from the traditional actuarial methods to a dynamically data-driven approach. Some key innovations include the buzz around Large Language Models (LLMs) for customer interaction, Internet of Things (IoT) enabled risk-monitoring in real time and Machine Learning allowing for automated claims processing. The research highlights the early adopters like AXA, Lemonade and Allianz who are actively leveraging AI to reduce claims processing times by 80% while reducing manual labour and increasing customer satisfaction. The most critical of this transformation is the emergence of roles that act like hybrid strategists. Such professionals combine traditional insurance expertise with acumen in technology. In our paper, we discuss the requirement of how AI demands more than just simple adoption. It needs a comprehensive restructuring of organizational culture, better data infrastructure and better ethical frameworks. Development in Explainable AI (XAI) is also noteworthy for maintaining transparency, handling complex risks and addressing regulatory requirements while alignment with customer trust concerns.展开更多
The rapid integration of artificial intelligence(AI)into software development,driven by large language models(LLMs),is reshaping the role of programmers from traditional coders into strategic collaborators within Indu...The rapid integration of artificial intelligence(AI)into software development,driven by large language models(LLMs),is reshaping the role of programmers from traditional coders into strategic collaborators within Industry 4.0 ecosystems.This qualitative study employs a hermeneutic phenomenological approach to explore the lived experiences of Information Technology(IT)professionals as they navigate a dynamic technological landscape marked by intelligent automation,shifting professional identities,and emerging ethical concerns.Findings indicate that developers are actively adapting to AI-augmented environments by engaging in continuous upskilling,prompt engineering,interdisciplinary collaboration,and heightened ethical awareness.However,participants also voiced growing concerns about the reliability and security of AI-generated code,noting that these tools can introduce hidden vulnerabilities and reduce critical engagement due to automation bias.Many described instances of flawed logic,insecure patterns,or syntactically correct but contextually inappropriate suggestions,underscoring the need for rigorous human oversight.Additionally,the study reveals anxieties around job displacement and the gradual erosion of fundamental coding skills,particularly in environments where AI tools dominate routine development tasks.These findings highlight an urgent need for educational reforms,industry standards,and organizational policies that prioritize both technical robustness and the preservation of human expertise.As AI becomes increasingly embedded in software engineering workflows,this research offers timely insights into how developers and organizations can responsibly integrate intelligent systems to promote accountability,resilience,and innovation across the software development lifecycle.展开更多
This comprehensive study investigates the multifaceted impact of AI-powered personalization on strategic communications, delving deeply into its opportunities, challenges, and future directions. Employing a rigorous m...This comprehensive study investigates the multifaceted impact of AI-powered personalization on strategic communications, delving deeply into its opportunities, challenges, and future directions. Employing a rigorous mixed-methods approach, we conduct an in-depth analysis of the effects of AI-driven personalization on audience engagement, brand perception, and conversion rates across various industries and communication channels. Our findings reveal that while AI-powered personalization significantly enhances communication effectiveness and offers unprecedented opportunities for audience connection, it also raises critical ethical considerations and implementation challenges. The study contributes substantially to the growing body of literature on AI in communications, offering both theoretical insights and practical guidelines for professionals navigating this rapidly evolving landscape. Furthermore, we propose a novel framework for ethical AI implementation in strategic communications and outline a robust agenda for future research in this dynamic field.展开更多
Ethics and governance are vital to the healthy and sustainable development of artificial intelligence(AI).With the long-term goal of keeping AI beneficial to human society,governments,research organizations,and compan...Ethics and governance are vital to the healthy and sustainable development of artificial intelligence(AI).With the long-term goal of keeping AI beneficial to human society,governments,research organizations,and companies in China have published ethical guidelines and principles for AI,and have launched projects to develop AI governance technologies.This paper presents a survey of these efforts and highlights the preliminary outcomes in China.It also describes the major research challenges in AI governance research and discusses future research directions.展开更多
Although AI and quantum computing (QC) are fast emerging as key enablers of the future Internet, experts believe they pose an existential threat to humanity. Responding to the frenzied release of ChatGPT/GPT-4, thousa...Although AI and quantum computing (QC) are fast emerging as key enablers of the future Internet, experts believe they pose an existential threat to humanity. Responding to the frenzied release of ChatGPT/GPT-4, thousands of alarmed tech leaders recently signed an open letter to pause AI research to prepare for the catastrophic threats to humanity from uncontrolled AGI (Artificial General Intelligence). Perceived as an “epistemological nightmare”, AGI is believed to be on the anvil with GPT-5. Two computing rules appear responsible for these risks. 1) Mandatory third-party permissions that allow computers to run applications at the expense of introducing vulnerabilities. 2) The Halting Problem of Turing-complete AI programming languages potentially renders AGI unstoppable. The double whammy of these inherent weaknesses remains invincible under the legacy systems. A recent cybersecurity breakthrough shows that banning all permissions reduces the computer attack surface to zero, delivering a new zero vulnerability computing (ZVC) paradigm. Deploying ZVC and blockchain, this paper formulates and supports a hypothesis: “Safe, secure, ethical, controllable AGI/QC is possible by conquering the two unassailable rules of computability.” Pursued by a European consortium, testing/proving the proposed hypothesis will have a groundbreaking impact on the future digital infrastructure when AGI/QC starts powering the 75 billion internet devices by 2025.展开更多
The rapid integration of artificial intelligence (AI) into critical sectors has revealed a complex landscape of cybersecurity challenges that are unique to these advanced technologies. AI systems, with their extensive...The rapid integration of artificial intelligence (AI) into critical sectors has revealed a complex landscape of cybersecurity challenges that are unique to these advanced technologies. AI systems, with their extensive data dependencies and algorithmic complexities, are susceptible to a broad spectrum of cyber threats that can undermine their functionality and compromise their integrity. This paper provides a detailed analysis of these threats, which include data poisoning, adversarial attacks, and systemic vulnerabilities that arise from the AI’s operational and infrastructural frameworks. This paper critically examines the effectiveness of existing defensive mechanisms, such as adversarial training and threat modeling, that aim to fortify AI systems against such vulnerabilities. In response to the limitations of current approaches, this paper explores a comprehensive framework for the design and implementation of robust AI systems. This framework emphasizes the development of dynamic, adaptive security measures that can evolve in response to new and emerging cyber threats, thereby enhancing the resilience of AI systems. Furthermore, the paper addresses the ethical dimensions of AI cybersecurity, highlighting the need for strategies that not only protect systems but also preserve user privacy and ensure fairness across all operations. In addition to current strategies and ethical concerns, this paper explores future directions in AI cybersecurity.展开更多
Artificial intelligence (AI) based technology, machine learning, and cognitive systems have played a very active role in society’s economic and technological transformation. For industrial value chains and internatio...Artificial intelligence (AI) based technology, machine learning, and cognitive systems have played a very active role in society’s economic and technological transformation. For industrial value chains and international businesses, it means that a structural change is necessary since these machines can learn and apply new information in making forecasts, processing, and interacting with people. Artificial intelligence (AI) is a science that uses powerful enough techniques, strategies, and mathematical modelling to tackle complex actual problems. Because of its inevitable progress further into the future, there have been considerable safety and ethical concerns. Creating an environment that is AI friendly for the people and vice versa might be a solution for humans and machines to discover a common set of values. In this context, the goal of this study is to investigate the emerging trends of AI (the benefits that it brings to the society), the moral challenges that come from ethical algorithms, learned or pre-set ideals, as well as address the ethical issues and malpractices of AI and AI security. This paper will address the consequences of AI in relation to investors and financial services. The article will examine the challenges and possible alternatives for resolving the potential unethical issues in finance and will propose the necessity of new AI governance mechanisms to protect the efficiency of the capital markets as well as the role of financial authority in the regulation and monitoring of the huge expansion of AI in finance.展开更多
A complete examination of Large Language Models’strengths,problems,and applications is needed due to their rising use across disciplines.Current studies frequently focus on single-use situations and lack a comprehens...A complete examination of Large Language Models’strengths,problems,and applications is needed due to their rising use across disciplines.Current studies frequently focus on single-use situations and lack a comprehensive understanding of LLM architectural performance,strengths,and weaknesses.This gap precludes finding the appropriate models for task-specific applications and limits awareness of emerging LLM optimization and deployment strategies.In this research,50 studies on 25+LLMs,including GPT-3,GPT-4,Claude 3.5,DeepKet,and hybrid multimodal frameworks like ContextDET and GeoRSCLIP,are thoroughly reviewed.We propose LLM application taxonomy by grouping techniques by task focus—healthcare,chemistry,sentiment analysis,agent-based simulations,and multimodal integration.Advanced methods like parameter-efficient tuning(LoRA),quantumenhanced embeddings(DeepKet),retrieval-augmented generation(RAG),and safety-focused models(GalaxyGPT)are evaluated for dataset requirements,computational efficiency,and performance measures.Frameworks for ethical issues,data limited hallucinations,and KDGI-enhanced fine-tuning like Woodpecker’s post-remedy corrections are highlighted.The investigation’s scope,mad,and methods are described,but the primary results are not.The work reveals that domain-specialized fine-tuned LLMs employing RAG and quantum-enhanced embeddings performbetter for context-heavy applications.In medical text normalization,ChatGPT-4 outperforms previous models,while two multimodal frameworks,GeoRSCLIP,increase remote sensing.Parameter-efficient tuning technologies like LoRA have minimal computing cost and similar performance,demonstrating the necessity for adaptive models in multiple domains.To discover the optimum domain-specific models,explain domain-specific fine-tuning,and present quantum andmultimodal LLMs to address scalability and cross-domain issues.The framework helps academics and practitioners identify,adapt,and innovate LLMs for different purposes.This work advances the field of efficient,interpretable,and ethical LLM application research.展开更多
Purpose: This study examines the transformative impact of artificial intelligence (AI) in healthcare, focusing on its applications in medical diagnosis, drug discovery, surgery, and disease management while addressing...Purpose: This study examines the transformative impact of artificial intelligence (AI) in healthcare, focusing on its applications in medical diagnosis, drug discovery, surgery, and disease management while addressing ethical, technological, and social concerns. Method: A comprehensive literature review synthesizes research on AI applications, including AI-assisted diagnosis, drug discovery, robot-assisted surgery, stroke management, and artificial neurons. Findings: AI has enabled significant breakthroughs in healthcare, enhancing outcomes in diagnostics, personalized treatments, and surgical procedures. Despite its promise, challenges such as privacy, safety, and equitable access remain critical concerns. Research Limitations: The study relies on existing literature and lacks empirical validation of AI models, with its scope limited by the rapid evolution of AI technologies. Social Implications: The integration of AI raises concerns about privacy, patient rights, and equitable access, particularly in underserved regions, potentially exacerbating healthcare disparities. Practical Implications: The study urges healthcare practitioners to adopt AI tools for improved diagnostics and treatments while advocating for regulatory frameworks to ensure ethical and safe AI integration. Originality: This study offers a comprehensive review of AI’s transformative role in healthcare, emphasizing ethical considerations and providing actionable insights for researchers and practitioners.展开更多
Artificial Intelligence (AI) technology is profoundly transforming personalized marketing practices. This study employs a mixed-methods approach to explore the application effects of AI in personalized marketing. The ...Artificial Intelligence (AI) technology is profoundly transforming personalized marketing practices. This study employs a mixed-methods approach to explore the application effects of AI in personalized marketing. The research first outlines the primary forms of AI-driven personalized marketing, including intelligent recommendation systems, dynamic pricing, and personalized content generation. Through analysis across multiple industries, the study summarizes best practices and common pitfalls of AI applications. Results indicate that AI can significantly enhance marketing relevance and timeliness but may also raise concerns about privacy and algorithmic discrimination. The study compares the effectiveness of AI-driven and traditional methods in various marketing scenarios. AI excels in handling large-scale, real-time personalization needs but may be less effective than human intervention in scenarios requiring deep emotional connections. Finally, the study discusses the prospects of ethical AI in personalized marketing, emphasizing the importance of transparency and explainability. This research provides theoretical and practical guidance for enterprises to effectively leverage AI technology to improve personalized marketing effectiveness.展开更多
The life coaching industry has experienced significant growth,yet traditional models face challenges related to accessibility,affordability,and quality inconsistency.The integration of Artificial Intelligence(AI)into ...The life coaching industry has experienced significant growth,yet traditional models face challenges related to accessibility,affordability,and quality inconsistency.The integration of Artificial Intelligence(AI)into life coaching presents a transformative opportunity to democratize personal development and mental well-being services.This study explores FASSLING,the first and only unified emotional and life coaching support bot available on the official ChatGPT store,designed to provide free,unlimited,24/7 multilingual emotional and coaching support.By addressing systemic barriers such as financial constraints,limited access to qualified coaches,and coaching biases,FASSLING introduces an innovative approach that enhances scalability,personalization,and inclusivity.FASSLING is designed to safeguard all aspects of life,assisting individuals in navigating career decisions,emotional well-being,relationships,personal growth,and self-mastery.The study examines AI’s ability to mitigate unconscious bias,improve client engagement,facilitate proactive coaching interventions and other related functions.While AI-driven coaching tools like FASSLING offer unprecedented accessibility and consistency,concerns regarding ethical AI use,data privacy,and emotional intelligence limitations remain.The research argues for a hybrid coaching model,where AI complements human coaches rather than replacing them,ensuring a balanced approach to holistic personal development.This paper contributes to the evolving discourse on AI in coaching by offering insights into its benefits,challenges,and future implications for the coaching industry.展开更多
This study explores the integration of predictive analytics in strategic corporate communications, with a specific focus on stakeholder engagement and crisis management. Our mixed-methods approach, which combines a co...This study explores the integration of predictive analytics in strategic corporate communications, with a specific focus on stakeholder engagement and crisis management. Our mixed-methods approach, which combines a comprehensive literature review with case studies of five multinational corporations, allows us to investigate the applications, challenges, and ethical implications of leveraging predictive models in communication strategies. While our findings reveal significant potential for enhancing personalized content delivery, real-time sentiment analysis, and proactive crisis management, we stress the need for careful consideration of challenges such as data privacy concerns and algorithmic bias. This emphasis on ethical implementation is crucial in navigating the complex landscape of predictive analytics in corporate communications. To address these issues, we propose a framework that prioritizes ethical considerations. Furthermore, we identify key areas for future research, thereby contributing to the evolving field of data-driven communication management.展开更多
This article introduces the special issue“Technology Ethics in Action:Critical and Interdisciplinary Perspectives”.In response to recent controversies about the harms of digital technology,discourses and practices o...This article introduces the special issue“Technology Ethics in Action:Critical and Interdisciplinary Perspectives”.In response to recent controversies about the harms of digital technology,discourses and practices of“tech ethics”have proliferated across the tech industry,academia,civil society,and government.Yet despite the seeming promise of ethics,tech ethics in practice suffers from several significant limitations:tech ethics is vague and toothless,has a myopic focus on individual engineers and technology design,and is subsumed into corporate logics and incentives.These limitations suggest that tech ethics enables corporate“ethics-washing”:embracing the language of ethics to defuse criticism and resist government regulation,without committing to ethical behavior.Given these dynamics,I describe tech ethics as a terrain of contestation where the central debate is not whether ethics is desirable,but what“ethics”entails and who gets to define it.Current approaches to tech ethics are poised to enable technologists and technology companies to label themselves as“ethical”without substantively altering their practices.Thus,those striving for structural improvements in digital technologies must be mindful of the gap between ethics as a mode of normative inquiry and ethics as a practical endeavor.In order to better evaluate the opportunities and limits of tech ethics,I propose a sociotechnical approach that analyzes tech ethics in light of who defines it and what impacts it generates in practice.展开更多
Across Asia,countries are putting in place plans to lead the way in the artificial intelligence (AI)-driven era.From China’s Made in China 2025 and Singapore’s Smart Nation plan to Japan’s focus on automating more ...Across Asia,countries are putting in place plans to lead the way in the artificial intelligence (AI)-driven era.From China’s Made in China 2025 and Singapore’s Smart Nation plan to Japan’s focus on automating more tasks in a bid offset an aging workforce, it is clear Asia is taking adequate policy steps.展开更多
The intersection of artificial intelligence(AI)and software engineering marks a transformative phase in the technology industry.This paper delves into AI-driven software engineering,exploring its methodologies,implica...The intersection of artificial intelligence(AI)and software engineering marks a transformative phase in the technology industry.This paper delves into AI-driven software engineering,exploring its methodologies,implications,challenges,and benefits.Drawing from data sources such as GitHub and Bitbucket and insights from industry experts,the study offers a comprehensive view of the current landscape.While the results indicate a promising uptrend in the integration of AI techniques in software development,challenges like model interpretability,ethical concerns,and integration complexities emerge as significant.Nevertheless,the transformative potential of AI within software engineering is profound,ushering in new paradigms of efficiency,innovation,and user experience.The study concludes by emphasizing the need for further research,better tooling,ethical guidelines,and education to fully harness the potential of AI-driven software engineering.展开更多
The recent ability of machines to generate text and images that are fluent,coherent,and culturally nuanced is already causing major upheavals in the translation sector.Machine translation tools have exploded in number...The recent ability of machines to generate text and images that are fluent,coherent,and culturally nuanced is already causing major upheavals in the translation sector.Machine translation tools have exploded in number,sophistication,and quality,and the profession of human translator needs to adapt to work within this new environment–and avoid being replaced by it.This paper examines the major changes that have taken place,and which could take place in the near future,and suggests ways of revising translator-training curricula to adapt to these challenges.This is essential at a time when the profession is undergoing profound changes and when all translators and future translators need to be prepared for new skills in the field of post-editing,machine-reading,machine-cultures and multidisciplinarity.After outlining the challenges that AI is causing to the profession and to the norms and values of the translation sector in its current state,the author suggests that translator training should adapt to the new reality of the profession and not to what it used to be.The profession is undergoing profound changes,and all translators and future translators need to find new skills and knowledge in order to continue to work with AI.The article concludes with recommendations on how to design AI-friendly translation programmes that can train students for the post-AI era.展开更多
The realm of education is witnessing a transformative integration with Artificial Intelligence(AI),poised to redefine the contours of pedagogical strategies.Central to this transformation is the emergence of personali...The realm of education is witnessing a transformative integration with Artificial Intelligence(AI),poised to redefine the contours of pedagogical strategies.Central to this transformation is the emergence of personalized learning experiences,where AI endeavors to tailor educational content and interactions to resonate with individual learners'unique needs,preferences,and pace.This paper delves into the multifaceted dimensions of AI-driven personalized learning,from its potential to enhance e-learning modules,the advent of AI-powered virtual tutors,to the ethical challenges it surfaces.As the tapestry of education becomes more intertwined with digital innovations,understanding AI's role in individualizing learning becomes paramount.展开更多
Artificial intelligence(AI)has significantly transformed higher education by enabling personalized learning through adaptive platforms,intelligent tutoring systems,and real-time feedback mechanisms.This study ex-amine...Artificial intelligence(AI)has significantly transformed higher education by enabling personalized learning through adaptive platforms,intelligent tutoring systems,and real-time feedback mechanisms.This study ex-amines the benefits and challenges of AI-driven personalized learning,emphasizing its potential to improve student engagement,retention,and academic outcomes.However,ethical concerns—such as data privacy,al-gorithmic bias,and access disparities—pose challenges that must be addressed for sustainable AI integration.By analyzing case studies from multiple universities and synthesizing existing literature,this research proposes a framework for ethical AI implementation that balances innovation with accountability and inclusivity.The findings contribute to ongoing discussions on AI’s role in education,providing practical insights for educators,administrators,and policymakers.展开更多
Cognitive computing has emerged as a transformative force in artificial intelligence(AI)education,bridging theoretical advancements with practical applications.This article explores the role of cognitive models in en-...Cognitive computing has emerged as a transformative force in artificial intelligence(AI)education,bridging theoretical advancements with practical applications.This article explores the role of cognitive models in en-hancing learning systems,from intelligent tutoring and personalized recommendations to virtual laboratories and special education support.It examines key technologies—such as knowledge graphs,natural language processing,and multimodal data analysis—that enable adaptive,human-like responsiveness.The study also ad-dresses technical challenges like interpretability and data privacy,alongside ethical concerns including equity and bias.Looking forward,it discusses how cognitive computing could reshape future learning modalities and aligns with trends like artificial general intelligence and interdisciplinary learning science.By tracing the path from theory to practice,this work underscores the potential of cognitive computing to create an inclusive,dy-namic educational landscape,while highlighting the need for ethical and technical rigor to ensure its responsible evolution.展开更多
Tech critics become technocrats when they overlook the daunting administrative density of a digital-first society.The author implores critics to reject structural dependencies on digital tools rather than naturalize t...Tech critics become technocrats when they overlook the daunting administrative density of a digital-first society.The author implores critics to reject structural dependencies on digital tools rather than naturalize their integration through critique and reform.At stake is the degree to which citizens must defer to unelected experts to navigate such density.Democracy dies in the darkness of sysadmin.The argument and a candidate solution proceed as follows.Since entropy is intrinsic to all physical systems,including digital systems,perfect automation is a fiction.Concealing this fiction,however,are five historical forces usually treated in isolation:ghost work,technical debt,intellectual debt,the labor of algorithmic critique,and various types of participatory labor.The author connects these topics to emphasize the systemic impositions of digital decision tools,which compound entangled genealogies of oppression and temporal attrition.In search of a harmonious balance between the use of“AI”tools and the non-digital decision systems they are meant to supplant,the author draws inspiration from an unexpected source:musical notation.Just as musical notes require silence to be operative,the author positions algorithmic silence-the deliberate exclusion of highly abstract digital decision systems from human decision-making environments-as a strategic corrective to the fiction of total automation.Facial recognition bans and the Right to Disconnect are recent examples of algorithmic silence as an active trend.展开更多
文摘In this paper, we examine the fundamental transformation of Property & Casualty (P&C) insurance through the introduction of Artificial Intelligence. This examination marks the shift from the traditional actuarial methods to a dynamically data-driven approach. Some key innovations include the buzz around Large Language Models (LLMs) for customer interaction, Internet of Things (IoT) enabled risk-monitoring in real time and Machine Learning allowing for automated claims processing. The research highlights the early adopters like AXA, Lemonade and Allianz who are actively leveraging AI to reduce claims processing times by 80% while reducing manual labour and increasing customer satisfaction. The most critical of this transformation is the emergence of roles that act like hybrid strategists. Such professionals combine traditional insurance expertise with acumen in technology. In our paper, we discuss the requirement of how AI demands more than just simple adoption. It needs a comprehensive restructuring of organizational culture, better data infrastructure and better ethical frameworks. Development in Explainable AI (XAI) is also noteworthy for maintaining transparency, handling complex risks and addressing regulatory requirements while alignment with customer trust concerns.
文摘The rapid integration of artificial intelligence(AI)into software development,driven by large language models(LLMs),is reshaping the role of programmers from traditional coders into strategic collaborators within Industry 4.0 ecosystems.This qualitative study employs a hermeneutic phenomenological approach to explore the lived experiences of Information Technology(IT)professionals as they navigate a dynamic technological landscape marked by intelligent automation,shifting professional identities,and emerging ethical concerns.Findings indicate that developers are actively adapting to AI-augmented environments by engaging in continuous upskilling,prompt engineering,interdisciplinary collaboration,and heightened ethical awareness.However,participants also voiced growing concerns about the reliability and security of AI-generated code,noting that these tools can introduce hidden vulnerabilities and reduce critical engagement due to automation bias.Many described instances of flawed logic,insecure patterns,or syntactically correct but contextually inappropriate suggestions,underscoring the need for rigorous human oversight.Additionally,the study reveals anxieties around job displacement and the gradual erosion of fundamental coding skills,particularly in environments where AI tools dominate routine development tasks.These findings highlight an urgent need for educational reforms,industry standards,and organizational policies that prioritize both technical robustness and the preservation of human expertise.As AI becomes increasingly embedded in software engineering workflows,this research offers timely insights into how developers and organizations can responsibly integrate intelligent systems to promote accountability,resilience,and innovation across the software development lifecycle.
文摘This comprehensive study investigates the multifaceted impact of AI-powered personalization on strategic communications, delving deeply into its opportunities, challenges, and future directions. Employing a rigorous mixed-methods approach, we conduct an in-depth analysis of the effects of AI-driven personalization on audience engagement, brand perception, and conversion rates across various industries and communication channels. Our findings reveal that while AI-powered personalization significantly enhances communication effectiveness and offers unprecedented opportunities for audience connection, it also raises critical ethical considerations and implementation challenges. The study contributes substantially to the growing body of literature on AI in communications, offering both theoretical insights and practical guidelines for professionals navigating this rapidly evolving landscape. Furthermore, we propose a novel framework for ethical AI implementation in strategic communications and outline a robust agenda for future research in this dynamic field.
文摘Ethics and governance are vital to the healthy and sustainable development of artificial intelligence(AI).With the long-term goal of keeping AI beneficial to human society,governments,research organizations,and companies in China have published ethical guidelines and principles for AI,and have launched projects to develop AI governance technologies.This paper presents a survey of these efforts and highlights the preliminary outcomes in China.It also describes the major research challenges in AI governance research and discusses future research directions.
文摘Although AI and quantum computing (QC) are fast emerging as key enablers of the future Internet, experts believe they pose an existential threat to humanity. Responding to the frenzied release of ChatGPT/GPT-4, thousands of alarmed tech leaders recently signed an open letter to pause AI research to prepare for the catastrophic threats to humanity from uncontrolled AGI (Artificial General Intelligence). Perceived as an “epistemological nightmare”, AGI is believed to be on the anvil with GPT-5. Two computing rules appear responsible for these risks. 1) Mandatory third-party permissions that allow computers to run applications at the expense of introducing vulnerabilities. 2) The Halting Problem of Turing-complete AI programming languages potentially renders AGI unstoppable. The double whammy of these inherent weaknesses remains invincible under the legacy systems. A recent cybersecurity breakthrough shows that banning all permissions reduces the computer attack surface to zero, delivering a new zero vulnerability computing (ZVC) paradigm. Deploying ZVC and blockchain, this paper formulates and supports a hypothesis: “Safe, secure, ethical, controllable AGI/QC is possible by conquering the two unassailable rules of computability.” Pursued by a European consortium, testing/proving the proposed hypothesis will have a groundbreaking impact on the future digital infrastructure when AGI/QC starts powering the 75 billion internet devices by 2025.
文摘The rapid integration of artificial intelligence (AI) into critical sectors has revealed a complex landscape of cybersecurity challenges that are unique to these advanced technologies. AI systems, with their extensive data dependencies and algorithmic complexities, are susceptible to a broad spectrum of cyber threats that can undermine their functionality and compromise their integrity. This paper provides a detailed analysis of these threats, which include data poisoning, adversarial attacks, and systemic vulnerabilities that arise from the AI’s operational and infrastructural frameworks. This paper critically examines the effectiveness of existing defensive mechanisms, such as adversarial training and threat modeling, that aim to fortify AI systems against such vulnerabilities. In response to the limitations of current approaches, this paper explores a comprehensive framework for the design and implementation of robust AI systems. This framework emphasizes the development of dynamic, adaptive security measures that can evolve in response to new and emerging cyber threats, thereby enhancing the resilience of AI systems. Furthermore, the paper addresses the ethical dimensions of AI cybersecurity, highlighting the need for strategies that not only protect systems but also preserve user privacy and ensure fairness across all operations. In addition to current strategies and ethical concerns, this paper explores future directions in AI cybersecurity.
文摘Artificial intelligence (AI) based technology, machine learning, and cognitive systems have played a very active role in society’s economic and technological transformation. For industrial value chains and international businesses, it means that a structural change is necessary since these machines can learn and apply new information in making forecasts, processing, and interacting with people. Artificial intelligence (AI) is a science that uses powerful enough techniques, strategies, and mathematical modelling to tackle complex actual problems. Because of its inevitable progress further into the future, there have been considerable safety and ethical concerns. Creating an environment that is AI friendly for the people and vice versa might be a solution for humans and machines to discover a common set of values. In this context, the goal of this study is to investigate the emerging trends of AI (the benefits that it brings to the society), the moral challenges that come from ethical algorithms, learned or pre-set ideals, as well as address the ethical issues and malpractices of AI and AI security. This paper will address the consequences of AI in relation to investors and financial services. The article will examine the challenges and possible alternatives for resolving the potential unethical issues in finance and will propose the necessity of new AI governance mechanisms to protect the efficiency of the capital markets as well as the role of financial authority in the regulation and monitoring of the huge expansion of AI in finance.
文摘A complete examination of Large Language Models’strengths,problems,and applications is needed due to their rising use across disciplines.Current studies frequently focus on single-use situations and lack a comprehensive understanding of LLM architectural performance,strengths,and weaknesses.This gap precludes finding the appropriate models for task-specific applications and limits awareness of emerging LLM optimization and deployment strategies.In this research,50 studies on 25+LLMs,including GPT-3,GPT-4,Claude 3.5,DeepKet,and hybrid multimodal frameworks like ContextDET and GeoRSCLIP,are thoroughly reviewed.We propose LLM application taxonomy by grouping techniques by task focus—healthcare,chemistry,sentiment analysis,agent-based simulations,and multimodal integration.Advanced methods like parameter-efficient tuning(LoRA),quantumenhanced embeddings(DeepKet),retrieval-augmented generation(RAG),and safety-focused models(GalaxyGPT)are evaluated for dataset requirements,computational efficiency,and performance measures.Frameworks for ethical issues,data limited hallucinations,and KDGI-enhanced fine-tuning like Woodpecker’s post-remedy corrections are highlighted.The investigation’s scope,mad,and methods are described,but the primary results are not.The work reveals that domain-specialized fine-tuned LLMs employing RAG and quantum-enhanced embeddings performbetter for context-heavy applications.In medical text normalization,ChatGPT-4 outperforms previous models,while two multimodal frameworks,GeoRSCLIP,increase remote sensing.Parameter-efficient tuning technologies like LoRA have minimal computing cost and similar performance,demonstrating the necessity for adaptive models in multiple domains.To discover the optimum domain-specific models,explain domain-specific fine-tuning,and present quantum andmultimodal LLMs to address scalability and cross-domain issues.The framework helps academics and practitioners identify,adapt,and innovate LLMs for different purposes.This work advances the field of efficient,interpretable,and ethical LLM application research.
文摘Purpose: This study examines the transformative impact of artificial intelligence (AI) in healthcare, focusing on its applications in medical diagnosis, drug discovery, surgery, and disease management while addressing ethical, technological, and social concerns. Method: A comprehensive literature review synthesizes research on AI applications, including AI-assisted diagnosis, drug discovery, robot-assisted surgery, stroke management, and artificial neurons. Findings: AI has enabled significant breakthroughs in healthcare, enhancing outcomes in diagnostics, personalized treatments, and surgical procedures. Despite its promise, challenges such as privacy, safety, and equitable access remain critical concerns. Research Limitations: The study relies on existing literature and lacks empirical validation of AI models, with its scope limited by the rapid evolution of AI technologies. Social Implications: The integration of AI raises concerns about privacy, patient rights, and equitable access, particularly in underserved regions, potentially exacerbating healthcare disparities. Practical Implications: The study urges healthcare practitioners to adopt AI tools for improved diagnostics and treatments while advocating for regulatory frameworks to ensure ethical and safe AI integration. Originality: This study offers a comprehensive review of AI’s transformative role in healthcare, emphasizing ethical considerations and providing actionable insights for researchers and practitioners.
文摘Artificial Intelligence (AI) technology is profoundly transforming personalized marketing practices. This study employs a mixed-methods approach to explore the application effects of AI in personalized marketing. The research first outlines the primary forms of AI-driven personalized marketing, including intelligent recommendation systems, dynamic pricing, and personalized content generation. Through analysis across multiple industries, the study summarizes best practices and common pitfalls of AI applications. Results indicate that AI can significantly enhance marketing relevance and timeliness but may also raise concerns about privacy and algorithmic discrimination. The study compares the effectiveness of AI-driven and traditional methods in various marketing scenarios. AI excels in handling large-scale, real-time personalization needs but may be less effective than human intervention in scenarios requiring deep emotional connections. Finally, the study discusses the prospects of ethical AI in personalized marketing, emphasizing the importance of transparency and explainability. This research provides theoretical and practical guidance for enterprises to effectively leverage AI technology to improve personalized marketing effectiveness.
文摘The life coaching industry has experienced significant growth,yet traditional models face challenges related to accessibility,affordability,and quality inconsistency.The integration of Artificial Intelligence(AI)into life coaching presents a transformative opportunity to democratize personal development and mental well-being services.This study explores FASSLING,the first and only unified emotional and life coaching support bot available on the official ChatGPT store,designed to provide free,unlimited,24/7 multilingual emotional and coaching support.By addressing systemic barriers such as financial constraints,limited access to qualified coaches,and coaching biases,FASSLING introduces an innovative approach that enhances scalability,personalization,and inclusivity.FASSLING is designed to safeguard all aspects of life,assisting individuals in navigating career decisions,emotional well-being,relationships,personal growth,and self-mastery.The study examines AI’s ability to mitigate unconscious bias,improve client engagement,facilitate proactive coaching interventions and other related functions.While AI-driven coaching tools like FASSLING offer unprecedented accessibility and consistency,concerns regarding ethical AI use,data privacy,and emotional intelligence limitations remain.The research argues for a hybrid coaching model,where AI complements human coaches rather than replacing them,ensuring a balanced approach to holistic personal development.This paper contributes to the evolving discourse on AI in coaching by offering insights into its benefits,challenges,and future implications for the coaching industry.
文摘This study explores the integration of predictive analytics in strategic corporate communications, with a specific focus on stakeholder engagement and crisis management. Our mixed-methods approach, which combines a comprehensive literature review with case studies of five multinational corporations, allows us to investigate the applications, challenges, and ethical implications of leveraging predictive models in communication strategies. While our findings reveal significant potential for enhancing personalized content delivery, real-time sentiment analysis, and proactive crisis management, we stress the need for careful consideration of challenges such as data privacy concerns and algorithmic bias. This emphasis on ethical implementation is crucial in navigating the complex landscape of predictive analytics in corporate communications. To address these issues, we propose a framework that prioritizes ethical considerations. Furthermore, we identify key areas for future research, thereby contributing to the evolving field of data-driven communication management.
文摘This article introduces the special issue“Technology Ethics in Action:Critical and Interdisciplinary Perspectives”.In response to recent controversies about the harms of digital technology,discourses and practices of“tech ethics”have proliferated across the tech industry,academia,civil society,and government.Yet despite the seeming promise of ethics,tech ethics in practice suffers from several significant limitations:tech ethics is vague and toothless,has a myopic focus on individual engineers and technology design,and is subsumed into corporate logics and incentives.These limitations suggest that tech ethics enables corporate“ethics-washing”:embracing the language of ethics to defuse criticism and resist government regulation,without committing to ethical behavior.Given these dynamics,I describe tech ethics as a terrain of contestation where the central debate is not whether ethics is desirable,but what“ethics”entails and who gets to define it.Current approaches to tech ethics are poised to enable technologists and technology companies to label themselves as“ethical”without substantively altering their practices.Thus,those striving for structural improvements in digital technologies must be mindful of the gap between ethics as a mode of normative inquiry and ethics as a practical endeavor.In order to better evaluate the opportunities and limits of tech ethics,I propose a sociotechnical approach that analyzes tech ethics in light of who defines it and what impacts it generates in practice.
文摘Across Asia,countries are putting in place plans to lead the way in the artificial intelligence (AI)-driven era.From China’s Made in China 2025 and Singapore’s Smart Nation plan to Japan’s focus on automating more tasks in a bid offset an aging workforce, it is clear Asia is taking adequate policy steps.
文摘The intersection of artificial intelligence(AI)and software engineering marks a transformative phase in the technology industry.This paper delves into AI-driven software engineering,exploring its methodologies,implications,challenges,and benefits.Drawing from data sources such as GitHub and Bitbucket and insights from industry experts,the study offers a comprehensive view of the current landscape.While the results indicate a promising uptrend in the integration of AI techniques in software development,challenges like model interpretability,ethical concerns,and integration complexities emerge as significant.Nevertheless,the transformative potential of AI within software engineering is profound,ushering in new paradigms of efficiency,innovation,and user experience.The study concludes by emphasizing the need for further research,better tooling,ethical guidelines,and education to fully harness the potential of AI-driven software engineering.
文摘The recent ability of machines to generate text and images that are fluent,coherent,and culturally nuanced is already causing major upheavals in the translation sector.Machine translation tools have exploded in number,sophistication,and quality,and the profession of human translator needs to adapt to work within this new environment–and avoid being replaced by it.This paper examines the major changes that have taken place,and which could take place in the near future,and suggests ways of revising translator-training curricula to adapt to these challenges.This is essential at a time when the profession is undergoing profound changes and when all translators and future translators need to be prepared for new skills in the field of post-editing,machine-reading,machine-cultures and multidisciplinarity.After outlining the challenges that AI is causing to the profession and to the norms and values of the translation sector in its current state,the author suggests that translator training should adapt to the new reality of the profession and not to what it used to be.The profession is undergoing profound changes,and all translators and future translators need to find new skills and knowledge in order to continue to work with AI.The article concludes with recommendations on how to design AI-friendly translation programmes that can train students for the post-AI era.
文摘The realm of education is witnessing a transformative integration with Artificial Intelligence(AI),poised to redefine the contours of pedagogical strategies.Central to this transformation is the emergence of personalized learning experiences,where AI endeavors to tailor educational content and interactions to resonate with individual learners'unique needs,preferences,and pace.This paper delves into the multifaceted dimensions of AI-driven personalized learning,from its potential to enhance e-learning modules,the advent of AI-powered virtual tutors,to the ethical challenges it surfaces.As the tapestry of education becomes more intertwined with digital innovations,understanding AI's role in individualizing learning becomes paramount.
文摘Artificial intelligence(AI)has significantly transformed higher education by enabling personalized learning through adaptive platforms,intelligent tutoring systems,and real-time feedback mechanisms.This study ex-amines the benefits and challenges of AI-driven personalized learning,emphasizing its potential to improve student engagement,retention,and academic outcomes.However,ethical concerns—such as data privacy,al-gorithmic bias,and access disparities—pose challenges that must be addressed for sustainable AI integration.By analyzing case studies from multiple universities and synthesizing existing literature,this research proposes a framework for ethical AI implementation that balances innovation with accountability and inclusivity.The findings contribute to ongoing discussions on AI’s role in education,providing practical insights for educators,administrators,and policymakers.
文摘Cognitive computing has emerged as a transformative force in artificial intelligence(AI)education,bridging theoretical advancements with practical applications.This article explores the role of cognitive models in en-hancing learning systems,from intelligent tutoring and personalized recommendations to virtual laboratories and special education support.It examines key technologies—such as knowledge graphs,natural language processing,and multimodal data analysis—that enable adaptive,human-like responsiveness.The study also ad-dresses technical challenges like interpretability and data privacy,alongside ethical concerns including equity and bias.Looking forward,it discusses how cognitive computing could reshape future learning modalities and aligns with trends like artificial general intelligence and interdisciplinary learning science.By tracing the path from theory to practice,this work underscores the potential of cognitive computing to create an inclusive,dy-namic educational landscape,while highlighting the need for ethical and technical rigor to ensure its responsible evolution.
文摘Tech critics become technocrats when they overlook the daunting administrative density of a digital-first society.The author implores critics to reject structural dependencies on digital tools rather than naturalize their integration through critique and reform.At stake is the degree to which citizens must defer to unelected experts to navigate such density.Democracy dies in the darkness of sysadmin.The argument and a candidate solution proceed as follows.Since entropy is intrinsic to all physical systems,including digital systems,perfect automation is a fiction.Concealing this fiction,however,are five historical forces usually treated in isolation:ghost work,technical debt,intellectual debt,the labor of algorithmic critique,and various types of participatory labor.The author connects these topics to emphasize the systemic impositions of digital decision tools,which compound entangled genealogies of oppression and temporal attrition.In search of a harmonious balance between the use of“AI”tools and the non-digital decision systems they are meant to supplant,the author draws inspiration from an unexpected source:musical notation.Just as musical notes require silence to be operative,the author positions algorithmic silence-the deliberate exclusion of highly abstract digital decision systems from human decision-making environments-as a strategic corrective to the fiction of total automation.Facial recognition bans and the Right to Disconnect are recent examples of algorithmic silence as an active trend.
