Artificial Intelligence Usage Research Articles

The Impact of Artificial Intelligence on Organisational Behavior: A Risky Tale between Myth and Reality for Sustaining Workforce

Purpose: This research paper examines quantitatively the impact of Artificial Intelligence (AI) as an independent variable on three organisational behavior components as dependent variables: job satisfaction, personality, and attitudes.
 Design/methodology: The sample of our study includes alumni graduates of the past two years reflecting on post-covid19 era as young workforce from Cairo, Egypt. It is important to note that there is no sufficient data regarding the impact of AI on OB testing this bracket of young population workforce, and highlighting specific components in the study of OB.
 Findings: This research finding revealed that AI can explain 46.5 % of Organizational Behavior which refers to the importance of AI usage among organizations and how this might change the current organizational environments. 
 Research Limitations: This research is limited by the fact that the sample encompassed a specific bracket of the young workforce age ranging from 20-35 years old even though they come from different backgrounds.
 Practical Implications: AI tools can enhance employees job satisfaction as well as it can help mitigate cognitive biases and groupthink, developing a decision-making culture that is more objective and data driven.
 Originality: Therefore, the utility of this research on the academic level highlights the fact of identifying major concerns and formulations of essential conclusions to get a deeper understanding of the relationship between the different variables stated. On the practical level, it sheds light for several organisations on the danger of technology replacement of employees due to the invasive impact of AI usage.
 Keywords: Artificial Intelligence, Personality, Attitudes, Job Satisfaction, Organisational Behavior

Governance of artificial intelligence and data in Australasian higher education: A snapshot of policy and practice

Governance of Artificial Intelligence (AI) is becoming increasingly urgent in higher education institutions for its impact on the quality and equity of education. Earlier in 2023, AI usage conversations across the sector appeared to predominantly focus on the other AI, Academic Integrity. Just like the technology has advanced in the past eight months since the first ACODE (Australasian Council of Open Digital Education) whitepaper on this topic this year, so too has the practice of using AI. In October 2023, ACODE conducted a survey to get an understanding of AI policy and practice in member institutions. The results show there is a mixed view whether guidelines and policies are in place with respect to the governance of AI and data which suggests the sector needs to continue these conversations for some time to come. Furthermore, ethical application of AI is emerging through experimental activities and pilots of proof of concepts, suggesting that case studies and recommendations for practice could be developed in 2024 to further assure quality and equity in education.

Academic publisher guidelines on AI usage: A ChatGPT supported thematic analysis.

As Artificial Intelligence (AI) technologies such as Generative AI (GenAI) have become more common in academic settings, it is necessary to examine how these tools interact with issues of authorship, academic integrity, and research methodologies. The current landscape lacks cohesive policies and guidelines for regulating AI's role in academic research which has prompted discussions among publishers, authors, and institutions. This study employs inductive thematic analysis to explore publisher policies regarding AI-assisted authorship and academic work. Our methods involved a two-fold analysis using both AI-assisted and traditional unassisted techniques to examine the available policies from leading academic publishers and other publishing or academic entities. The framework was designed to offer multiple perspectives, harnessing the strengths of AI for pattern recognition while leveraging human expertise for nuanced interpretation. The results of these two analyses are combined to form the final themes. Our findings indicate six overall themes, three of which were independently identified in both the AI-assisted and unassisted, manual analysis using common software tools. A broad consensus appears among publishers that human authorship remains paramount and that the use of GenAI tools is permissible but must be disclosed. However, GenAI tools are increasingly acknowledged for their supportive roles, including text generation and data analysis. The study also discusses the inherent limitations and biases of AI-assisted analysis, necessitating rigorous scrutiny by authors, reviewers, and editors. There is a growing recognition of AI's role as a valuable auxiliary tool in academic research, but one that comes with caveats pertaining to integrity, accountability, and interpretive limitations. This study used a novel analysis supported by GenAI tools to identify themes emerging in the policy landscape, underscoring the need for an informed, flexible approach to policy formulation that can adapt to the rapidly evolving landscape of AI technologies.

What Do the Regulators Mean? A Taxonomy of Regulatory Principles for the Use of AI in Financial Services

The intended automation in the financial industry creates a proper area for artificial intelligence usage. However, complex and high regulatory standards and rapid technological developments pose significant challenges in developing and deploying AI-based services in the finance industry. The regulatory principles defined by financial authorities in Europe need to be structured in a fine-granular way to promote understanding and ensure customer safety and the quality of AI-based services in the financial industry. This will lead to a better understanding of regulators’ priorities and guide how AI-based services are built. This paper provides a classification pattern with a taxonomy that clarifies the existing European regulatory principles for researchers, regulatory authorities, and financial services companies. Our study can pave the way for developing compliant AI-based services by bringing out the thematic focus of regulatory principles.

Towards an AI policy framework in scholarly publishing

The rapid adoption of artificial intelligence (AI) tools in academic research raises pressing ethical concerns. I examine major publishing policies in science and medicine, uncovering inconsistencies and limitations in guiding AI usage. To encourage responsible AI integration while upholding transparency, I propose an enabling framework with author and reviewer policy templates.

Enhancement of Customer Complaints: Digitalization of Synchronous Model for Problem-Solving of Manufacturing Complaints

In today’s manufacturing environment, companies are facing new challenges brought by advances in technology which are reflected in the output of their processes or products delivered to the customers. At the same time, customer expectations have changed over time, and the modern customer needs a fast solution when the product received does not meet its requirements. Having this background in mind, how can a traditional problem-solving model tackle a modern issue? This question has been the starting point for developing the Synchronous Model for structured problem solving and further propose its digitalization and AI (artificial intelligence) usage for ensuring operational excellence, enhancing customer satisfaction, and maintaining competitiveness in this rapidly evolving market landscape. The model was created from a comparative analysis between seven most known and used structured problem-solving models within manufacturing companies where all the advantages and disadvantages were collected. Within this paper, a digitalized platform is proposed, and its features are validated through a case study on a manufacturing company, struggling with answer time for customer complaints, where a decreasing trend was observed after using the Synchronous model for addressing complaints, proving its efficiency.

Students’ Intention to Learn and Academic Performance in the Blended Learning Environment: The Role of Artificial Intelligence Chatbots

In the era of universal digitalization, new technologies and services are being created, among which we can highlight the development of chatbot technologies that can be effectively used in the educational process and that will be of interest to representatives of the younger generations. The current study aims to reveal the influence of artificial intelligence chatbot integration on students’ intention to learn and their academic performance in the blended learning environment. The research framework includes 7 key indicators: Satisfaction (SAT), Perceived Usefulness (PU), Attitude (ATD), Subjective Norms (SN), and Perceived Behavioral Control (PBC), Continuance Intention to Learn (CIL) and academic performance (AP), which are evaluated in traditional blended learning setting (N=104) and blended learning based on artificial intelligence chatbot (N=107). For comparison we used the average scores, standard deviations (σ) of students on 23 items and student’s t-test for independent samples. We also calculated Pearson correlation coefficient for all analyzed. The results of the current study confirmed the positive influence of artificial intelligence usage during the blended learning as it increases students’ attitude, satisfaction and perceived usefulness which directly and highly affects the intention to continue learning and academic performance.

From Bias to Brilliance: The Impact of Artificial Intelligence Usage on Recruitment Biases in China

From Bias to Brilliance: The Impact of Artificial Intelligence Usage on Recruitment Biases in China

Relationships between (Un)known consequences of Artificial Intelligence usage in an organizational or societal context

This study investigates the relationships between (un)known consequences of artificial intelligence (AI) and usage in an organizational or societal context. The study adopts a qualitative approach and toes an interpretive constructivist perspective. Used the resources of AI to construct the data corpus on which content analysis was performed. Additionally, to triangulate we also drawn on interview of six specialists with varied knowledge as consultants, strategists, developers and users, and also data from Digital Week held by PwC. Results show that the consequences of AI are complex and multifaceted thus requiring thorough planning, constitution of GenAI teams among users from business focal points to pose adequate and diverse questions and build consistent algorithms in line with policies to mitigate risks of negative impacts. Results also show that consequences of AI are highly context-dependent and can vary based on the specific application and dataset. The conceptions that have implications on the unknow known consequences of AI are Automation, Improved efficiency, Enhanced decision making, Personalization, Cost reduction, Healthcare advancements, Autonomous decisions, Natural Language Processing (NLP), Predictive Maintenance, Environmental monitoring, Fraud detection and Education & Training. Others are Scientific Research, Customer Services, Accessibility, Agricultural baseline, Security and Entertainment. Overall, to harness the values, addressing the challenges is inevitable to avoid pitfalls by turning GenAI more inclusive through continuous experimentation and maximizing the benefits of AI. AI have left a lasting imprint on our society and will continue to do so as AI technologies advance and become more integrated into various aspects of our lives. This study contributes to the debate on AI and serves as a limelight to the academia, professionals, and policy makers.

Perception of Generative Artificial Intelligence in Higher Education Research

Integrating Generative Artificial Intelligence (AI) into higher education research holds great promise, but understanding researchers' perceptions and addressing associated challenges is crucial for success. This study investigates how researchers perceive the potential benefits of Generative AI, its ease of use, and the challenges affecting its adoption in higher education research. It aims to uncover diverse perspectives and insights for effective integration. Using a qualitative case study approach, data was collected from 33 researchers in social sciences at one institution through online surveys and interviews. Thematic analysis, guided by the Technology Acceptance Model (TAM), identified recurring themes. The findings reveal significant engagement with AI adoption, with most participants integrating Generative AI into their research. However, readiness to adopt varied, reflecting different levels of enthusiasm and preparedness. Participants' perceptions ranged from recognizing Generative AI's convenience to expressing concerns about potential negative impacts such as becoming overly reliant, aligning with TAM constructs. Additionally, participants stressed the importance of responsible and ethical Generative AI usage through training and awareness initiatives. These findings lay the foundation for strategies promoting Generative AI adoption and responsible integration in higher education research. Implications for institutions aiming to integrate Generative AI effectively emphasize the need to understand researchers' perspectives and address their concerns.

UNMASKING DECEPTION IN THE AGE OF ARTIFICIAL INTELLIGENCE: A COMPREHENSIVE ANALYSIS OF INDIAN CELEBRITY’S DEEPFAKES NEWS

The rapid advancement of Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL) has ushered in a new era of digital disruption, particularly in the domain of disinformation and content manipulation. Among the various applications emerging from this progress, the phenomenon of deepfakes has emerged as a formidable challenge. Deepfakes represent synthetic media productions, intricately crafted through AI algorithms, with the ability to seamlessly replace a person's likeness in videos or images. The consequences of deepfakes are profound, encompassing the propagation of misinformation, reputation damage, and erosion of trust in digital content. The rising cases of deepfake news underscore a significant threat in the field of artificial intelligence. To mitigate this issue a comprehensive strategy requires to development of awareness, education, technological advancements, and strong legal frameworks to safeguard identities and curtail the misuse of deepfakes. This involves key steps like the development of detection technologies, the establishment of clear legal guidelines, heightened public awareness, empowerment of individuals, and promotion of responsible AI use.This paper conducts an in-depth analysis of three case studies involving prominent Indian celebrities—Rashmika Mandhana, Kajol Devgan, and Katrina Kaif—affected by deepfake news. The prime objective of the research is to understand the key factors that determine the authenticity of these deepfake contents to combat the spread of misinformation by promoting responsible AI usage and fostering a culture of digital literacy. Through concerted efforts encompassing technological innovation, legal reform, public awareness, and individual empowerment, the researcher tries to counter the threat posed by Deepfakes and uphold the integrity of digital discourse in the age of AI.

Ethical Dilemmas in Using AI for Academic Writing and an Example Framework for Peer Review in Nephrology Academia: A Narrative Review.

The emergence of artificial intelligence (AI) has greatly propelled progress across various sectors including the field of nephrology academia. However, this advancement has also given rise to ethical challenges, notably in scholarly writing. AI's capacity to automate labor-intensive tasks like literature reviews and data analysis has created opportunities for unethical practices, with scholars incorporating AI-generated text into their manuscripts, potentially undermining academic integrity. This situation gives rise to a range of ethical dilemmas that not only question the authenticity of contemporary academic endeavors but also challenge the credibility of the peer-review process and the integrity of editorial oversight. Instances of this misconduct are highlighted, spanning from lesser-known journals to reputable ones, and even infiltrating graduate theses and grant applications. This subtle AI intrusion hints at a systemic vulnerability within the academic publishing domain, exacerbated by the publish-or-perish mentality. The solutions aimed at mitigating the unethical employment of AI in academia include the adoption of sophisticated AI-driven plagiarism detection systems, a robust augmentation of the peer-review process with an "AI scrutiny" phase, comprehensive training for academics on ethical AI usage, and the promotion of a culture of transparency that acknowledges AI's role in research. This review underscores the pressing need for collaborative efforts among academic nephrology institutions to foster an environment of ethical AI application, thus preserving the esteemed academic integrity in the face of rapid technological advancements. It also makes a plea for rigorous research to assess the extent of AI's involvement in the academic literature, evaluate the effectiveness of AI-enhanced plagiarism detection tools, and understand the long-term consequences of AI utilization on academic integrity. An example framework has been proposed to outline a comprehensive approach to integrating AI into Nephrology academic writing and peer review. Using proactive initiatives and rigorous evaluations, a harmonious environment that harnesses AI's capabilities while upholding stringent academic standards can be envisioned.

EMPLOYEE UNDERSTANDING OF ARTIFICIAL INTELLIGENCE: A PRELIMINARY STUDY IN INDONESIA FINANCIAL SECTOR INDUSTRY

The emergence of artificial intelligence (AI) in the financial services industry is driven by increased demand for financial regulation, the need for profitability, and competition between companies. Despite the heightened importance of this new technology, there has been a gap in knowledge regarding the use of AI in financial services. This study aims to provide preliminary research to explore the level of understanding of middle level managers in the context of artificial intelligence usage in marketing activities. The sample is 11 managers from banking, fintech and other financial sectors. The findings provide guidance for organizations in terms of usage and knowledge of AI in the sector.

AI and Chat GPT in Language Teaching: Enhancing EFL Classroom Support and Transforming Assessment Techniques

The integration of artificial intelligence (AI) and Chat GPT technology in English as a Foreign Language (EFL) instruction has ushered in transformative changes in language learning and assessment. This essay explores the multifaceted impact of AI and Chat GPT on EFL education, emphasizing their role in personalized language learning, real-time language practice, and examination techniques. AI facilitates personalized language learning by tailoring lessons to individual students' needs, promoting deeper language understanding. Real-time language practice is enhanced through dynamic interactions with AI-powered chatbots, which provide immediate feedback, boosting proficiency and confidence. In examination techniques, AI automates grading and feedback, improving efficiency and consistency, while also enhancing test security. The integration of AI and Chat GPT raises ethical considerations regarding privacy, equity, and responsible AI usage. Successful case studies, including Duolingo's language learning platform, Chat GPT in EFL classrooms, and ExamSoft's examination software, highlight the practical benefits of AI integration. The future of EFL education lies in a collaborative relationship between human teachers and AI, addressing challenges and limitations while prioritizing ethical considerations, equitable access, and meaningful human interaction. The potential for a more effective and engaging EFL learning experience is achievable with a commitment to these principles.

Should We Wait for Major Frauds to Unveil to Plan an AI Use License?

Should We Wait for Major Frauds to Unveil to Plan an AI Use License?

Algorithm aversion, emotions, and investor reaction: Does disclosing the use of AI influence investment decisions?

Businesses are increasingly using artificial intelligence (AI) in accounting systems to reduce uncertainty and improve accuracy. However, algorithm aversion (Dietvorst et al., 2015) indicates that individuals often avoid information provided by automated systems as compared to that provided by humans. This paper is an exploratory step towards documenting an emotional response to AI. We experimentally investigate how disclosing the use of AI rather than human staff for estimating the fair value of an asset influences investment decisions through lower levels of emotional response, particularly in pleasantness and attentiveness. Consistent with algorithm aversion, we find that disclosing the use of AI to estimate the asset’s fair value reduces the effect of information valence on nonprofessional investor responses. Specifically, when a company’s AI usage is disclosed, investors make smaller additional investments when fair value information is positive and smaller investment withdrawals when fair value information is negative, as compared to when human staff usage is disclosed. Importantly, we also find that emotions mediate the effect of information source (AI versus human staff) and moderate the effect of information valence on investment decisions.

Converging perspectives: Assessing AI readiness and utilization in Philippine higher education

In rapidly evolving landscape of technology, the integration of artificial intelligence (AI) has become prevalent, reshaping various facets of students’ lives. This study delved into the uncharted territory of AI awareness, utilization, and perceptions among college students. The study used a convergent parallel mixed-methods design, integrating quantitative survey data with qualitative responses in order to get insights on the impact of AI in education and society. The survey found that college students familiarity on AI depends on age, academic year, and field of study. This emphasizes the need for targeted AI education to overcome knowledge inequalities, particularly among younger cohorts and in fields with little AI expertise. AI usage is usually modest for academic and personal purposes, while insights includes its uses in academic research, job administration, and language translation. The varied application of AI requires institutions to adapt their procedures, and societal impacts which are largely seen positively. This optimism is tempered by concerns about job loss, data privacy breach, technological overuse, and human decision-making. Thus, comprehensive AI education programs are needed to address and traverse these varied opinions. The results emphasized the necessity for institutions and policymakers to be proactive when artificial intelligence is transforming many companies and social systems. Students must learn AI literacy, combining knowledge and practical application, to navigate the AI-driven environment's complexity and opportunities. The endeavor requires teaching technical skills and a deep grasp of AI's social and ethical implications. Institutions can prepare students for a future where artificial intelligence is becoming more important by understanding these effects and tailoring teaching.

Artificial Intelligence Usage in Higher Education: Academicians' Perspective

Artificial Intelligence Usage in Higher Education: Academicians' Perspective

Prospek Pembelajaran Bahasa Arab di Era Generative Artificial Intelligence

This research explores the role of Artificial Intelligence (AI), specifically Generative AI, in Arabic language learning and the importance of AI literacy for educators, students, and parents. Employing a qualitative method through a literature review, the study examines the extent of AI utilization in foreign language education, the prospects of Generative AI in Arabic language instruction, as well as the impacts and necessity of AI literacy. The findings indicate that Generative AI, such as ChatGPT, holds significant potential in enhancing Arabic language instruction. This AI can create tailored learning experiences, deliver interactive learning materials, and facilitate communication with native speakers. However, AI usage poses challenges, including issues of bias in generated outcomes. Hence, AI literacy is crucial for understanding the limitations and ethical use of this technology. The research underscores the need for the development of AI optimized for Arabic language education, while emphasizing the importance of ethical understanding and AI literacy for all stakeholders involved in education.

The rise of artificial intelligence as the future of Korean culture diplomacy

The COVID-19 pandemic ushered in a new era of technology, pushing everything online and necessitating human adaptation to computers. Industry 4.0 proved invaluable during this pandemic, with Artificial Intelligence (AI) emerging as a key player, particularly in the beloved South Korean music industry, which enjoys international acclaim. The pandemic played a significant role in the increased use of AI within the K-POP industry, with the emergence of the Aespa Girl Group being a pivotal moment in shaping a futuristic concept. This research aims to investigate the recent surge in AI usage as a futuristic K-Pop concept through a qualitative literature study method. This paper contends that AI has the potential to profoundly impact Korean cultural diplomacy, serving as a game-changing element in the realm of digital diplomacy. While AI has traditionally been applied in high-context scenarios, such as search engines or high-tech automotive control systems, its application in cultural contexts could propel South Korea's cultural diplomacy to unprecedented heights, rendering the concept difficult for other nations to replicate.