Beyond Algorithms: A Comprehensive Analysis of AI-Driven Personalization in Strategic Communications

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.

Tackling the Existential Threats from Quantum Computers and AI

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.

Navigating AI Cybersecurity: Evolving Landscape and Challenges

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.

Ethical Principles and Governance Technology Development of AI in China

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.

Artificial Intelligence Trends and Ethics: Issues and Alternatives for Investors

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.

Research on the Application Effects of Artificial Intelligence in Personalized Marketing

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.

Leveraging Predictive Analytics for Strategic Corporate Communications: Enhancing Stakeholder Engagement and Crisis Management

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.

The Contestation of Tech Ethics: A Sociotechnical Approach to Technology Ethics in Practice

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.

Artificial Intelligence in Healthcare: A Fusion of Technologies

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.

OPINION The Need for Ethical AI

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.

Algorithmic Silence:A Call to Decomputerize

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.