Responsible Artificial Intelligence Research Articles

AI-Enabled Governance in Cryptocurrency Communities

This paper explores how the combination of artificial intelligence (AI) can enhance governance in cryptocurrency communities and Decentralized Autonomous Organizations (DAOs). Using insights from blockchain, machine studying, and social computing, we examine moral concerns and dangers While addressing them, we discuss the potential of AI to improve efficiency, transparency and inclusion in phrases of governance shape. Through case studies, we demonstrate sensible packages of AI, consisting of social media sentiment analysis, algorithmic trading, and decentralized forecasting markets. We explore the impact of AI on governance token systems, selection- making processes and community-pushed governance models. Challenges along with algorithmic bias, records privacy, and the need for human oversight are discussed in conjunction with suggested studies suggestions and great practices for implementing responsible AI. This paper explores how the integration of synthetic intelligence (AI) can enhance governance in cryptocurrency communities and decentralized c Decentralized Autonomous Organizations (DAOs). Using insights from blockchain, gadget learning, and social computing, we examine moral worries and dangers While addressing them, we talk the potential of AI to enhance performance, transparency and inclusion in terms of governance structure. Through case research, we display realistic programs of AI, which include social media sentiment evaluation, algorithmic trading, and decentralized forecasting markets. We discover the effect of AI on governance token systems, decision-making methods and network-pushed governance models. Challenges including algorithmic bias, records privateness, and the need for human oversight are mentioned in conjunction with suggested research tips and exceptional practices for the responsible use of AI By clarifying the ability of AI in cryptocurrency governance, we help bridge the space among AI and decentralized selection-making.

Exploring the Role of Artificial Intelligence in Enhancing Equity and Inclusion in Education

The purpose of this study was to assess the impact of Artificial Intelligence (AI) on education. Premised on a narrative and framework for assessing AI identified from a preliminary analysis, the scope of the study was limited to the application and effects of AI in administration, instruction, and learning. Artificial Intelligence (AI) has emerged as a transformative force in education, promising to revolutionize traditional teaching and learning methods. One critical aspect of this transformation is AI's potential to enhance equity and inclusion in educational settings. This paper explores the current state, challenges, and opportunities regarding AI's role in promoting equity and inclusion in education. The historical evolution of AI in education is examined, tracing its roots from early intelligent tutoring systems to contemporary adaptive learning platforms and virtual tutoring systems. Advances in machine learning, natural language processing, and data analytics have expanded AI's capabilities, enabling personalized learning experiences tailored to individual student needs. However, the widespread implementation of AI in education faces several challenges, including concerns about data privacy, algorithmic bias, and the digital divide. It is crucial to address these challenges through responsible and ethical AI deployment, ensuring that AI interventions prioritize equity, inclusivity, and transparency. Further research is needed to explore the effectiveness of AI interventions in different educational contexts and to develop strategies for mitigating potential risks and maximizing benefits. By leveraging AI technologies thoughtfully and ethically, educators and policymakers can work towards building a more equitable and inclusive education system that empowers all learners to reach their full potential.

Challenges and Prospects of Artificial Intelligence in Nigerian Journalism Practice: A Narrative Review

The integration of artificial intelligence (AI) into Nigerian journalism practices presents both challenges and prospects for the industry. This paper explores the dynamic interplay between AI technologies and journalism in Nigeria, addressing key conceptual clarifications, theoretical frameworks, challenges, and prospects associated with AI utilization in the field. Drawing upon existing literature, the study examines the multifaceted nature of AI, ranging from its conceptual underpinnings to its practical applications in journalism. It utilizes the Technology-Organization-Environment (TOE) framework to analyze the factors influencing AI adoption within Nigerian newsrooms, considering technological, organizational, and environmental contexts. Identifying challenges such as infrastructural limitations, financial constraints, cultural resistance, and ethical considerations, the paper elucidates the complexities inherent in AI integration in Nigerian journalism. These challenges encompass issues of data quality, transparency, bias, and accountability, underscoring the need for responsible AI implementation and robust ethical frameworks. Additionally, the paper discusses the prospects offered by AI in enhancing journalistic efficiency, facilitating data-driven reporting, personalizing news delivery, and combating misinformation. By leveraging AI for fact-checking, multilingual reporting, predictive analytics, and automated content generation, Nigerian journalists can innovate and adapt to the evolving media landscape. Moreover, AI presents opportunities for improving audience engagement, storytelling, collaboration, and addressing bias and ethics concerns. Embracing AI in journalism also creates educational pathways for aspiring journalists, fostering skill development and innovation in the industry.

Beyond CheatBots: Examining Tensions in Teachers’ and Students’ Perceptions of Cheating and Learning with ChatGPT

As artificial intelligence (AI) is increasingly integrated into educational technologies, teachers and students must acquire new forms of AI literacy, including an understanding of responsible use of AI. In this study, we explored tensions in teachers’ and students’ opinions about what constitutes learning and cheating with AI. Using qualitative methods, we asked Pre-K through postsecondary writing teachers (n = 16) and a linguistically diverse group of students (n = 12) to consider examples of how students might use ChatGPT, rank them in order of how much they thought each student learned and cheated, and explain their rankings. Our study yielded three findings. First, teachers and students used similar criteria to determine their rankings. Second, teachers and students arrived at similar conclusions about learning with ChatGPT but different conclusions about cheating. Finally, disagreements centered on four main tensions between (1) using ChatGPT as a shortcut versus as a scaffold; (2) using ChatGPT to generate ideas versus language; (3) getting support from ChatGPT versus analogous support from other sources; and (4) learning from ChatGPT versus learning without. These findings underscore the importance of student voice in co-constructing norms around responsible AI use.

A new framework for ethical artificial intelligence: keeping HRD in the loop

ABSTRACT As a result of the rapid development of technologies, artificial intelligence (AI) is changing human experiences and workplaces in ways that we are not prepared for. Recognized as a double-edged tool, AI has brought both positive and negative outcomes to organisations and employees. With its increasing popularity in the workplace and our daily practice, how to use AI intelligently and responsibly has become a top concern raised by both academics and practitioners. In this article, we discuss the desired and unintended consequences of AI as documented in current literature, examine the ethical concerns, and identify current solutions. We propose ‘keeping HRD in the loop’ as a means to addressing ethical challenges associated with AI and offer a new conceptual framework as a tool for reference. Integrating general AI principles and ethical guidelines developed by the Academy of HRD, we map out an ethical boundary consisting of nine human-centred principles and suggest a sample of six HRD interventions that can facilitate responsible AI practices and productive human-machine interfaces. By bringing HRD perspectives into the domain of AI practice, we hope to bring ethical considerations to the forefront of AI decision-making and stimulate more interest in interdisciplinary research and academic-industry collaboration.

The use of artificial intelligence in marketing strategies: Automation, personalization and forecasting

The integration of Artificial Intelligence (AI) in marketing strategies is pivotal in the era of digital transformation, especially in automation, personalization, and forecasting. This research investigates the evolutionary role of AI in transitioning from traditional marketing frameworks to data-driven methodologies, thereby enhancing marketing efficiency and customer engagement. The increasing reliance on AI for strategic decision-making in marketing underscores the significance of this study. Employing a systematic literature review and thematic analysis, this research synthesizes data from an array of studies to thoroughly understand the impact of AI on marketing. The findings reveal that AI significantly streamlines marketing operations, fosters highly personalized marketing strategies, and enhances the accuracy of forecasting market trends and consumer behavior. However, this study also sheds light on the ethical and privacy concerns associated with the use of AI in marketing. Results point towards a significant transformation in marketing practices propelled by AI, marked by improvements in operational efficiency and customer interaction. Nevertheless, the study advocates the importance of addressing ethical considerations and privacy issues, emphasizing responsible AI deployment. The study offers a comprehensive perspective on the integration of AI in marketing and suggests insights into prospective trends. It recommends a balanced approach to leveraging AI’s capabilities while upholding ethical standards. The research’s practical implications aim to guide marketers and researchers towards responsible and effective AI adoption in marketing strategies, paving the way for a future where technology enhances marketing endevaours without compromising ethical integrity.

Artificial Intelligence in the Classroom: Revolutionizing English Language Teaching

This qualitative study investigates the integration of Artificial Intelligence (AI) in English Language Teaching (ELT) within university settings, with a specific focus on the viewpoints and experiences of university-level English teachers in Nepal. The research was conducted in Lumbini Province, Nepal, where 14 university-level English teachers were purposively selected from seven constituent campuses. Through unstructured smartphone interviews, participants shared insights on AI integration in ELT. The findings reveal a diverse range of expectations and concerns among university-level English teachers regarding AI’s role in language instruction. While participants expressed optimism about AI’s potential to revolutionize language learning through personalized experiences and immediate feedback, they also voiced apprehensions. These concerns encompassed job displacement, potential erosion of human interaction, and ethical implications related to AI usage. To address these challenges, participants employed various strategies. They navigated ethical considerations by raising awareness, engaging in reflection, and advocating for ethical guidelines. The study emphasizes the importance of a balanced approach to AI integration-one that harnesses its promises while addressing potential pitfalls. Responsible and inclusive AI usage in language education necessitates thoughtful consideration of both benefits and challenges.

Systematic technical analysis: Enhancing AI deployment in procurement for optimal transparency and accountability

In today's rapidly evolving business landscape, the integration of Artificial Intelligence (AI) in procurement processes holds significant promise for improving transparency and accountability. This systematic technical analysis explores the implications of AI deployment in procurement and its potential to enhance transparency and accountability within organizations. The study adopts a mixed-methods approach, combining quantitative surveys and qualitative interviews to gather comprehensive data on the use of AI in procurement, legal and ethical challenges faced by organizations, and the effectiveness of current legal and ethical frameworks. Quantitative surveys are distributed to a diverse sample of organizations to assess the extent of AI use in procurement, perceived impacts on legal and ethical frameworks, and overall satisfaction with AI deployment. Qualitative interviews with key stakeholders, including procurement managers and legal advisors, provide deeper insights into the nuances of AI deployment and its implications for transparency and accountability. The analysis of quantitative data reveals the prevalence of AI use in procurement processes and its perceived impact on legal and ethical frameworks. Organizations report improvements in contract management, risk reduction, and compliance with regulations due to AI deployment. However, concerns remain regarding the legal implications of AI decision-making and the need for robust ethical frameworks to ensure accountability. Qualitative interviews shed light on the practical challenges and opportunities associated with AI deployment in procurement. Stakeholders highlight the importance of transparency, fairness, and human oversight in AI-driven processes. They emphasize the need for clear ethical guidelines and oversight mechanisms to address potential biases and ensure accountability. Overall, this systematic technical analysis provides valuable insights into the implications of AI deployment in procurement for transparency and accountability. The findings underscore the importance of integrating AI-related training and education into procurement processes and developing robust legal and ethical frameworks to mitigate risks and ensure responsible AI deployment.

Ethical Implication of Artificial Intelligence (AI) Adoption in Financial Decision Making

The integration of artificial intelligence (AI) into the financial sector has raised ethical concerns that need to be addressed. This paper analyzes the ethical implications of using AI in financial decision-making and emphasizes the importance of an ethical framework to ensure its fair and trustworthy deployment. The study explores various ethical considerations, including the need to address algorithmic bias, promote transparency and explainability in AI systems, and adhere to regulations that protect equity, accountability, and public trust. By synthesizing research and empirical evidence, the paper highlights the complex relationship between AI innovation and ethical integrity in finance. To tackle this issue, the paper proposes a comprehensive and actionable ethical framework that advocates for clear guidelines, governance structures, regular audits, and collaboration among stakeholders. This framework aims to maximize the potential of AI while minimizing negative impacts and unintended consequences. The study serves as a valuable resource for policymakers, industry professionals, researchers, and other stakeholders, facilitating informed discussions, evidence-based decision-making, and the development of best practices for responsible AI integration in the financial sector. The ultimate goal is to ensure fairness, transparency, and accountability while reaping the benefits of AI for both the financial sector and society.

Assessing the Knowledge and Perception of Artificial Intelligence for Teaching and Research among Lecturers in the Faculties of Arts in Nigeria

This study assesses the knowledge of artificial intelligence (AI) for teaching and research among lecturers in the faculties of arts in Nigeria. Despite the growing recognition of AI's potential to enhance educational practices, there are significant gaps in educators' AI literacy. The research adopts a quantitative approach, surveying lecturers across Nigerian universities to gauge their awareness, engagement, and perceptions of AI integration. Results reveal a moderate level of AI awareness among respondents, with a notable interest in further training tailored to arts disciplines. Challenges such as technical barriers and limited resources hinder seamless AI integration, highlighting the need for targeted interventions and support mechanisms. Recommendations include enhanced training programs, infrastructure improvement, and ethical guidelines to facilitate responsible AI utilization in arts education. Addressing these challenges and fostering AI literacy among educators can create an enabling environment for leveraging AI to enhance teaching and research outcomes in Nigerian arts faculties.

AI-driven Solutions for Cloud Compliance Challenges

The integration of artificial intelligence (AI) in cloud compliance management has emerged as a transformative approach to address complex regulatory challenges in contemporary IT environments. This research paper explores the role of AI-driven solutions in enhancing cloud compliance, focusing on key applications, benefits, challenges, and future trends. The paper begins by examining the automation of compliance reporting and documentation through AI technologies, highlighting significant improvements in accuracy, efficiency, and cost-effectiveness. Real-world case studies from leading organizations such as J.P. Morgan Chase & Co., Mayo Clinic, and Microsoft Corporation illustrate the practical implementation and impact of AI in various sectors, including finance, healthcare, and technology. Ethical and legal implications associated with AI in cloud compliance are discussed, emphasizing the importance of transparency, fairness, and regulatory adherence. Emerging trends such as Explainable AI (XAI), AI governance, and continuous compliance monitoring are identified as critical factors shaping the future of AI-driven cloud compliance. The paper concludes by addressing anticipated challenges in data privacy, algorithmic bias, and regulatory complexity, underscoring the need for collaborative efforts among stakeholders to foster responsible AI deployment in compliance operations.

Exploring the Limits of Artificial Intelligence for Referencing Scientific Articles.

To evaluate the reliability of three artificial intelligence (AI) chatbots (ChatGPT, Google Bard, and Chatsonic) in generating accurate references from existing obstetric literature. Between mid-March and late April 2023, ChatGPT, Google Bard, and Chatsonic were prompted to provide references for specific obstetrical randomized controlled trials (RCTs) published in 2020. RCTs were considered for inclusion if they were mentioned in a previous article that primarily evaluated RCTs published by the top medical and obstetrics and gynecology journals with the highest impact factors in 2020 as well as RCTs published in a new journal focused on publishing obstetric RCTs. The selection of the three AI models was based on their popularity, performance in natural language processing, and public availability. Data collection involved prompting the AI chatbots to provide references according to a standardized protocol. The primary evaluation metric was the accuracy of each AI model in correctly citing references, including authors, publication title, journal name, and digital object identifier (DOI). Statistical analysis was performed using a permutation test to compare the performance of the AI models. Among the 44 RCTs analyzed, Google Bard demonstrated the highest accuracy, correctly citing 13.6% of the requested RCTs, whereas ChatGPT and Chatsonic exhibited lower accuracy rates of 2.4 and 0%, respectively. Google Bard often substantially outperformed Chatsonic and ChatGPT in correctly citing the studied reference components. The majority of references from all AI models studied were noted to provide DOIs for unrelated studies or DOIs that do not exist. To ensure the reliability of scientific information being disseminated, authors must exercise caution when utilizing AI for scientific writing and literature search. However, despite their limitations, collaborative partnerships between AI systems and researchers have the potential to drive synergistic advancements, leading to improved patient care and outcomes. · AI chatbots often cite scientific articles incorrectly.. · AI chatbots can create false references.. · Responsible AI use in research is vital..

‘We have opened a can of worms’: using collaborative ethnography to advance responsible artificial intelligence innovation

ABSTRACT With the recent rapid developments in artificial intelligence (AI), social scientists and computational scientists have approached overlapping questions about ethics, responsibility, and fairness. Joined-up efforts between these disciplines have nonetheless been scarce due to, among other factors, unfavourable institutional arrangements, unclear publication avenues, and sometimes incompatible normative, epistemological and methodological commitments. In this paper, we offer collaborative ethnography as one concrete methodology to address some of these challenges. We report on an interdisciplinary collaboration between science and technology studies scholars and data scientists developing an AI system to detect online misinformation. The study combined description, interpretation, and (self-)critique throughout the design and development of the AI system. We draw three methodological lessons to move from critique to action for interdisciplinary teams pursuing responsible AI innovation: (1) Collective self-critique as a tool to resist techno-centrism and relativism, (2) Moving from strategic vagueness to co-production, and (3) Using co-authorship as a method.

Utilizing AI for Social Good: Tackling Global Issues and Fostering Inclusive Solutions

This research delves into the intricate influence of Artificial Intelligence (AI) on community development across vital sectors such as healthcare, education, environmental sustainability, and community empowerment. Its core aim is to comprehensively analyze how individuals in underserved communities perceive and experience the use of AI technologies. To achieve this, a mixed-methods approach is adopted, combining quantitative surveys for statistical insights with qualitative narratives for nuanced perspectives. Engaging 120 participants from diverse backgrounds and age groups, the research methodology incorporates Likert scales and regression analysis for data interpretation. The study reveals a prevalent positive outlook on AI's impact across various domains, particularly highlighting its significant effects on healthcare, education, and environmental sustainability. Integration of qualitative narratives enriches the findings, offering depth and context to statistical analyses. Its novelty lies in the comprehensive examination of AI's influence on community development, seamlessly blending quantitative and qualitative dimensions. By providing nuanced insights into AI's multifaceted role in community contexts, the research significantly contributes to the field. Ultimately, the study underscores the importance of responsible AI deployment, aligned with community values, to navigate the evolving technological landscape and foster sustainable community development.

Ai-Powered Customer Experience: Personalization, Engagement, and Intelligent Decision-Making in Crm

There has been a recent increase in interest regarding the remarkable potential of artificial intelligence (AI) to profoundly transform online advertising. The purpose of this research is to critically assess how AI can enhance customer experience (CX) in various business applications. We aim to identify important concepts, evaluate the impact of AI-powered CX initiatives, and offer suggestions for future research. By conducting a thorough analysis of academic publications, industry reports, and case studies, this study extracts theoretical frameworks, empirical findings, and practical insights. The results highlight the significant changes that occur with the integration of AI into Customer Relationship Management (CRM). AI enables personalized interactions, strengthens customer engagement through interactive agents, provides data-driven insights, and empowers informed decision-making throughout the customer journey. Four key themes emerge from research findings: personalized service, improved engagement, data-driven strategy, and intelligent decision-making. However, challenges such as data privacy concerns, ethical considerations, and potential negative experiences with poorly implemented AI persist. This article makes a valuable contribution to the AI in CRM discourse by summarizing the current state, exploring key themes, and suggesting future research opportunities. It is strongly advocated for responsible AI implementation, emphasizing ethical considerations and providing guidance to organizations as they navigate the opportunities and challenges presented by AI.

Plato’s Shadows in the Digital Cave: Controlling Cultural Bias in Generative AI

Generative Artificial Intelligence (AI) systems, like ChatGPT, have the potential to perpetuate and amplify cultural biases embedded in their training data, which are predominantly produced by dominant cultural groups. This paper explores the philosophical and technical challenges of detecting and mitigating cultural bias in generative AI, drawing on Plato’s Allegory of the Cave to frame the issue as a problem of limited and distorted representation. We propose a multifaceted approach combining technical interventions, such as data diversification and culturally aware model constraints, with a deeper engagement with the cultural and philosophical dimensions of the problem. Drawing on theories of extended cognition and situated knowledge, we argue that mitigating AI biases requires a reflexive interrogation of the cultural contexts of AI development and a commitment to empowering marginalized voices and perspectives. We claim that controlling cultural bias in generative AI is inseparable from the larger project of promoting equity, diversity, and inclusion in AI development and governance. By bridging philosophical reflection with technical innovation, this paper contributes to the growing discourse on responsible and inclusive AI, offering a roadmap for detecting and mitigating cultural biases while grappling with the profound cultural implications of these powerful technologies.

Navigating the Future: Exploring the Strategic Integration of Artificial Intelligence in Contemporary Management Practices

In today’s rapidly evolving business landscape, artificial intelligence (AI) has emerged as a transformative force, reshaping traditional management practices across industries. This research paper delves into the strategic integration of AI in contemporary management, aiming to provide insights into the challenges, opportunities, and implications faced by organizations navigating this transformative journey. Through a comprehensive analysis of case studies, industry trends, and expert opinions, this study explores the ways in which AI is influencing decision-making, efficiency, innovation, and sustainability within organizations. Furthermore, it examines the ethical considerations and change management strategies required to ensure responsible and effective AI adoption. The findings of this research offer a roadmap for organizations seeking to harness the potential of AI while addressing the complexities of its integration into management practices.

Transforming Education: The Evolving Role of Artificial Intelligence in The Students Academic Performance

As technology continues to advance, its integration into various aspects of education has become inevitable.  This article delves into the transformative impact of Artificial Intelligence (AI) on students' academic performance.  AI's role in education has shifted from a mere supplementary tool to a fundamental component reshaping teaching and learning paradigms.  This paper explores how AI-powered educational technologies, such as adaptive learning platforms, intelligent tutoring systems, and automated assessment tools, are revolutionizing traditional educational practices.  It examines the benefits AI brings to students, educators, and educational institutions, including personalized learning experiences, enhanced student engagement, and efficient assessment mechanisms.  Furthermore, the article discusses the potential challenges and ethical considerations associated with AI integration in education, such as data privacy concerns, algorithmic biases, and the digital divide.  By analyzing recent research findings and real-world implementations, this paper provides insights into the evolving landscape of education empowered by AI and underscores the importance of responsible AI adoption to optimize students' academic outcomes in the digital era.

Enabling Responsible Artificial Intelligence Research and Development Through the Democratization of Advanced Cyberinfrastructure

Enabling Responsible Artificial Intelligence Research and Development Through the Democratization of Advanced Cyberinfrastructure

The Transformative Impact of AI in Finance and Banking

The transformative impact of artificial intelligence (AI) in finance and banking is pro7 found, revolutionizing the way financial institutions operate, interact with customers, and make 8 decisions. This article explores the technological landscape that has paved the way for AI adoption, including falling data storage costs, data availability, advancements in machine learning, cost reduction, regulatory compliance, competitive advantage, risk management, customer experience, fraud detection, increased connectivity, and rapid advances in AI technologies. It discusses how AI is enhancing customer support, improving security through fraud detection algorithms, and enhancing credit scoring accuracy through machine learning. The value creation potential of AI in banking includes unlocking up to $1 trillion of incremental value annually through personalized services, cost reduction via automation, and uncovering new opportunities. Additionally, it provides examples of AI applications in banking, including personalization, automation, and insight extraction, showcasing how AI is transforming the industry. Despite these advancements, the article acknowledges challenges such as a lack of clear strategy, legacy systems, and fragmented data assets and proposes solutions like promoting a growth mindset and responsible AI deployment. It also addresses current issues in the banking sector, such as cyberattacks, voice cloning, and fraud, emphasizing the importance of AI in addressing these challenges. Overall, the article highlights the transformative potential of AI in finance and banking, urging banks to embrace an AI-first mindset for sustained growth and innovation.