Implications Of Artificial Intelligence Research Articles

Evaluating the Role of AI in Grants Management: Integration and Adoption of Technology and Innovation

The integration of artificial intelligence (AI) into grant management has the potential to revolutionize how organizations handle the application process, budgeting, reporting, and stakeholder engagement. This qualitative study explores the experiences of grant managers, financial officers, and other stakeholders in adopting AI tools. Through interviews and thematic analysis, this research identifies the benefits, challenges, and implications of AI in the grant management process. The findings suggest that while AI can enhance efficiency and decision-making, successful integration requires careful planning, training, and change management.

6.Y.2. AI and health care: what are the capabilities and limitations?

Abstract With the rapid advancement of artificial intelligence (AI) technologies and their implementation in health care, there is a critical need to explore the different applications and implications of AI. This workshop seeks to look at different aspects of AI, both potential applications for AI technology in health, public opinions of use of AI in health care, and the reality of implementing AI in different contexts. Understanding health care approaches to AI from different countries is a unique opportunity for shared learning of innovations across various sectors of health care and patient engagement in order to most effectively engage this emerging field. AI, in whichever form it may be incorporated into health care, has the opportunity to impart meaningful, innovative change, but understanding this new technology comes with important questions. This session will dive into research on AI in various areas of health care by 1) looking at different ways AI is being harnessed in health care; 2) discussing lessons which can be learned and adapted from other countries; 3) discussing promising solutions and approaches to implementing AI in health care; 4) discussing the limitations or concerns of integrating AI in health care. The panel will be composed of 1 moderator and 2 panelists. Panelists are experts in their fields, established researchers and practitioners, and alumni of the Harkness Fellowship from Germany and the United Kingdom. A moderator will briefly frame the discussion for the audience and introduce the speakers and their presentations before leading an interactive, engaging question and answer portion. The coherence of this panel lays in its theme of leveraging AI to enhance healthcare delivery and understanding ways we can work across countries to foster ethical, equitable AI technologies that revolutionize healthcare practices with the ultimate goal of improving patient outcomes and health system efficiencies. Dr. Saira Ghafur from the U.K. will begin by presenting her research on evidence-based reasons for implementing AI in health care and Dr. Benedikt Simon from Germany will close out by discussing his work in AI in Germany and the challenges that have prevented robust integration. Each panelist will speak for roughly 8-10 minutes, with about 5 minutes reserved for moderator and audience questions. Key messages • Sharing cross-country experiences and research enables us to better understand how AI can impact health care. • In weighing both the benefits and challenges or limitations of implementing AI, we can best understand effective approaches to utilizing AI in health care.

A Comprehensive Study on Artificial Intelligence and Machine Learning

Artificial Intelligence (AI) and Machine Learning (ML) have emerged as transformative technologies reshaping industries and society. This paper explores the foundational concepts of AI and ML, emphasizing their definitions, methodologies, and applications. AI encompasses a broad spectrum of techniques aimed at mimicking human intelligence, while ML, a subset of AI, focuses on the development of algorithms that enable machines to learn from data. We examine the historical evolution of these fields, the current state of research, and key technologies such as neural networks, natural language processing, and computer vision. The implications of AI and ML are vast, impacting sectors including healthcare, finance, and transportation, and raising ethical considerations regarding privacy, bias, and employment. By analyzing case studies and recent advancements, this paper aims to highlight the potential and challenges of integrating AI and ML into everyday life, paving the way for future research and development in this dynamic domain

Shaping Tomorrow: The Impact of AI on Architectural History and Interior Design Education

Artificial Intelligence (AI) techniques have become popular in architecture and design, and several studies have focused on using these technological advancements to solve various architectural problems. AI is used in various architectural design applications, from intelligent material composition to layout solutions, and it is also vital in supporting the architecture and design education mechanism. A comprehensive understanding of literature is necessary to use these powerful tools in education adequately. This is due to the large volume of research being created and disseminated on this subject as well as the increasing application of AI techniques to address various education design-related questions. This article offers a comprehensive and critical assessment of the study of artificial intelligence applications in architecture and interior design education as a course application in the history of architecture and interior design. The study's conclusions indicate that AI's implications in architecture and design re-imagination are beneficial; however, it was concluded that AI- in its current phase- cannot replace human input and perspective. The students' feedback indicates that critical thinking skills cannot be replaced, and AI complements but doesn't replace their intellect.

Role-playing the future: a simulation-based exploration of AI in social work

As Artificial Intelligence (AI) continues to permeate various sectors, its integration into social work practice, particularly in identifying at-risk families, demands a nuanced understanding and ethical engagement from future social workers. This paper presents an account of a simulation-based learning exercise conducted with Masters in Social Work [MSW] students at an Irish university. Through role-playing as different stakeholders, students engaged with a fictional scenario that involved the deployment of an AI algorithm in Ireland for identifying at-risk families. The exercise illuminated diverse perspectives on the implications of AI in social work, highlighting key ethical dilemmas, regulatory challenges and the need for comprehensive education on AI technologies. The findings support the effectiveness of simulation-based learning as an effective way to prepare social work students for the ethical, practical, and policy complexities of integrating AI into their future practice.

The Impact of Artificial Intelligence (AI) on the Scope of Accountancy: Difficulties and Challenges in a Literature Review

The rapid advancement of Artificial Intelligence (AI) technologies has permeated various industries, ushering in transformative changes. One such sector experiencing significant shifts is accountancy. This paper presents a systematic literature review to discern the impact of AI on the domain of accountancy, aiming to unveil its repercussions, challenges, and difficulties. The review draws from a vast array of academic journals, white papers, industry reports, and conference proceedings. The results indicate that while AI streamlines tasks like data processing and forecasting, leading to enhanced efficiency and accuracy, it also brings about potential challenges. These challenges include the demand for new skill sets, fears of job displacement, ethical considerations, and the requirement for updated regulatory frameworks. However, a noteworthy observation during this review was the complexities and challenges in carrying out a systematic review itself, given the rapid technological advancements and diverse perspectives in the existing literature. Inconsistencies in terminologies, overlapping scopes, and the multifaceted nature of AI applications in accountancy further complicated the process. This paper offers a dual contribution: shedding light on the implications of AI in accountancy and providing insights into the intricacies faced while conducting a systematic literature review in a dynamic field.

Artificial Intelligence in Healthcare With an Emphasis on Public Health.

Artificial Intelligence (AI), since its inception, has revolutionized multiple sectors, including healthcare in the 20th century, and has applications in data interpretation, leading to advancements in diagnostics, therapeutics, and clinical decision-making.AI is referred to as the capability of a software program to accurately analyze extrinsic information and utilize it for accomplishing desired goals and objectives through appropriate flexibility. It makes use of complicated operative algorithms to excel in humanlearning potential with overwhelming abilities to interpret large sets of data. The scope and implications of AI are consistently amplifying and have contributed significantly in nearly all phases of human life, especially healthcare. The integration of AI-related advancements would surely ameliorate the delivery of healthcare by allowing its accessibility, affordability, and level of care provided. For instance, reading CT scans is feasible by both AI as well as a radiologist. The screening of Tuberculosis is possible through AI via Chest X-rays with comparability in performance as molecular testing and mammography scans can predict the onset of breast cancer prior to the appearance of the ocular signs. Therefore, AI has been realized as one of the core areas by researchers and the governmentfor public health benefit. For the same reason, it is imperative to adopt an ethically sound policy framework for guiding the further development of AI-based technologies and their application in public health. AI-based interpretations themselves cannot be fully trusted for their diagnostic decisions and judgements, and hence, it is vital to assess their accountability through all phases of development and deployment in the field of health. This article emphasizes the advancements in AI-based technologies, their assistance in public healthcare delivery systems, and their merits and demerits. It also explores the various ethical directives that need to be adhered to while utilizing it for public health welfare.

Influence of AI on Shopping Experience of Generation Z Customers

Artificial intelligence (AI) refers to the simulation or approximation of human intelligence in machines. AI is being used today across different industries from finance to healthcare. It is also reinventing the retail landscape. Computer vision is enabling frictionless checkout and enhancing loss prevention for brick-and-mortar stores. Retailers that harness AI to connect with customers and operate more efficiently will be better positioned to thrive in today’s AI powered world. The study is conducted with the sample size of 61 respondents by conducting survey through questionnaire in Palakkad district. This paper attempts to get an insight into the influence of AI technologies in the shopping experience of customers especially on generation Z. It is high time that customers become aware of different implications of AI and how it is contributing to their shopping life. This paper further talks about the trust issues of customers when it comes to AI and personal data sharing and how it can be improved by taking necessary measures by retailers like educating the consumers in a proper way about AI. Customers also agree that AI has made a positive impact on their shopping experience especially in customer support after purchase.

Exploring teachers' artificial intelligence awareness

The impact of artificial intelligence (AI) technological advancements is reshaping various aspects of our daily lives, including education. Integrating AI in education offers advantages such as personalized learning and operational efficiency. However, educators need to be aware of AI's implications in education. Teachers must enhance their awareness and knowledge levels to adapt to the educational environment where AI technologies are becoming increasingly prevalent. Therefore, this research aims to assess teachers' AI awareness levels and investigate whether AI awareness varies based on age, graduation status, and years of experience. This study used data collected from 147 educators using the Teachers' Artificial Intelligence Awareness Scale. The results indicated that teachers' AI awareness was at a moderate level. Additionally, the study examined teachers' AI awareness across different variables. Independent sample t-tests and one-way ANOVA analyses determined teachers' AI awareness variation based on age. The research findings suggest that younger educators and those with higher academic qualifications have more excellent practical knowledge of AI. The study's limitations included a relatively small sample size and the assumption of accurate participant responses. Despite these limitations, understanding teachers' AI awareness levels is a foundation for developing educational programs related to AI. By understanding teachers' perceptions and knowledge of AI, tailored interventions and training initiatives can enhance educators' proficiency in effectively utilizing AI technologies within educational settings.

THE IMPACT OF AI ON LIBRARY INFORMATION SERVICE QUALITY

This research explores the transformative impact of Artificial Intelligence (AI) in library services. It investigates AI's potential to enhance efficiency, personalize service delivery, and improve library collection management. The study employs qualitative methods, including in-depth interviews and document analysis, with a focus on academic and public libraries that have integrated AI. The findings reveal positive acceptance of AI by library professionals, increased user satisfaction, and the potential for more dynamic library services. However, challenges such as staff training and data privacy issues exist. AI's role in collection management is also highlighted. This research contributes to understanding AI's implications for libraries and underscores the need for responsible AI implementation.

Rethinking Plagiarism in the Era of Generative AI

The emergence of generative artificial intelligence (AI) technologies, such as large language models (LLMs) like ChatGPT, has precipitated a paradigm shift in the realms of academic writing, plagiarism, and intellectual property. This article explores the evolving landscape of English composition courses, traditionally designed to develop critical thinking through writing. As AI becomes increasingly integrated into the academic sphere, it necessitates a reevaluation of originality in writing, the purpose of learning research and writing, and the frameworks governing intellectual property (IP) and plagiarism. The paper commences with a statistical analysis contrasting the actual use of LLMs in academic dishonesty with educator perceptions. It then examines the repercussions of AI-enabled content proliferation, referencing the limitation of three books self-published per day in September 2023 by Amazon due to a suspected influx of AI-generated material. The discourse extends to the potential of AI in accelerating research akin to the contributions of digital humanities and computational linguistics, highlighting its accessibility to the general public. The article further delves into the implications of AI on pedagogical approaches to research and writing, contemplating its impact on communication and critical thinking skills, while also considering its role in bridging the digital divide and socio-economic disparities. Finally, it proposes revisions to writing curricula, adapting to the transformative influence of AI in academic contexts.

Exploring the Use and Implications of AI in Sexual and Reproductive Health and Rights: Protocol for a Scoping Review.

Artificial intelligence (AI) has emerged as a transformative force across the health sector and has garnered significant attention within sexual and reproductive health and rights (SRHR) due to polarizing views on its opportunities to advance care and the heightened risks and implications it brings to people's well-being and bodily autonomy. As the fields of AI and SRHR evolve, clarity is needed to bridge our understanding of how AI is being used within this historically politicized health area and raise visibility on the critical issues that can facilitate its responsible and meaningful use. This paper presents the protocol for a scoping review to synthesize empirical studies that focus on the intersection of AI and SRHR. The review aims to identify the characteristics of AI systems and tools applied within SRHR, regarding health domains, intended purpose, target users, AI data life cycle, and evidence on benefits and harms. The scoping review follows the standard methodology developed by Arksey and O'Malley. We will search the following electronic databases: MEDLINE (PubMed), Scopus, Web of Science, and CINAHL. Inclusion criteria comprise the use of AI systems and tools in sexual and reproductive health and clear methodology describing either quantitative or qualitative approaches, including program descriptions. Studies will be excluded if they focus entirely on digital interventions that do not explicitly use AI systems and tools, are about robotics or nonhuman subjects, or are commentaries. We will not exclude articles based on geographic location, language, or publication date. The study will present the uses of AI across sexual and reproductive health domains, the intended purpose of the AI system and tools, and maturity within the AI life cycle. Outcome measures will be reported on the effect, accuracy, acceptability, resource use, and feasibility of studies that have deployed and evaluated AI systems and tools. Ethical and legal considerations, as well as findings from qualitative studies, will be synthesized through a narrative thematic analysis. We will use the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) format for the publication of the findings. The database searches resulted in 12,793 records when the searches were conducted in October 2023. Screening is underway, and the analysis is expected to be completed by July 2024. The findings will provide key insights on usage patterns and evidence on the use of AI in SRHR, as well as convey key ethical, safety, and legal considerations. The outcomes of this scoping review are contributing to a technical brief developed by the World Health Organization and will guide future research and practice in this highly charged area of work. OSF Registries osf.io/ma4d9; https://osf.io/ma4d9. PRR1-10.2196/53888.

Implications of AI in land management

This study sought to find out implications of Artificial Intelligence (AI) in land management. Artificial Intelligence (AI) offers significant benefits for land development and decision-making, ethical concerns regarding data privacy, bias, and social impact necessitate frameworks to ensure its responsible application. The increasing use of AI models in land management raises ethical concerns about data ownership, privacy, algorithmic bias, environmental impact, and social displacement. Traditional research ethics frameworks may not be sufficient for AI-driven land management practices. This paper examines critical issues arising from data governance, algorithmic transparency, and environmental and social impact assessment. It proposes frameworks that consider established research ethics principles and advocate for community engagement. The paper highlights the potential for AI to contribute to sustainable and equitable land management. However, it also identifies potential negative consequences such as job losses, unequal access to technology, and exacerbation of existing social divides. The paper emphasizes the need for collaboration between researchers, policymakers, communities, and developers to construct ethical frameworks that ensure AI contributes to sustainable land management practices. These frameworks should address data governance, algorithmic transparency, environmental and social impact assessments, and community engagement.

Embracing the Era of Artificial Intelligence: Innovation and Preparation in Nursing Education

Rapid recent advances in information technology have opened the door for artificial intelligence (AI)-related technologies to be applied extensively across many industries. The Ministry of Education has emphasized the importance of cultivating advanced-level professionals in diverse fields, particularly in smart machinery, the Asia-Silicon Valley sector, green energy technology, biotechnology, national defense, new agricultural, and circular economy industries, to enhance innovation and promote industrial competitiveness (Kuo, 2019). While interdisciplinary talent in AI and digital innovation is being actively developed elsewhere, nursing education remains in the exploratory phase of AI and digital technology talent cultivation. Although AI is now a well-known term, the competencies required for its application in nursing remain unclear. Moreover, most nursing professionals are unfamiliar with how to best integrate AI into nursing expertise or practice settings. With the application of AI in the healthcare industry now unstoppable, it is vital to consider how to help nursing students adapt to healthcare's new technology landscape (Huang et al., 2021). AI facilitates the digital simulation of human thought patterns, logic, and behaviors with the goal of assisting human users solve problems, especially those that are time-consuming and require repetitive processing. The development of AI requires interdisciplinary collaboration among domain experts, data scientists, software engineers, robotics experts, and computer programmers. Such collaboration is essential to developing products able to meet the demands of the times and to help students become competent future nursing professionals (Murray, 2018). Nurses spend the most time interacting with patients and are thus best able to understand the perceptions and challenges of patients and their families. Collaborating with professionals from interdisciplinary fields is the best strategy for achieving optimal healthcare outcomes. However, nursing schools have yet to provide a clear response to the impact of AI on nursing education. Nursing educational institutions must enable nursing students to comprehend the concepts and principles of AI and equip them with AI literacy to allow them to unleash their potential, continuously innovate, and stay abreast with the times (Ng et al., 2021). In this issue, experts and scholars currently engaged in AI-related research in the nursing discipline share their research findings in the realms of machine learning, deep learning, emotional recognition, and natural language application. These articles offer insights into the implications of AI, suggest how nursing education may best respond to emerging AI trends, and provide the authors' perspectives on nursing education reform. The editor hopes readers will be inspired to explore new concepts, gain a deeper understanding of the application and significance of AI, and apply AI to address clinical and educational challenges to foster competent nursing professionals for tomorrow.

Vinsers’ Initiatives: Perceptions on the use of AI in ESL Learning among Selected Grade 11 Learners

Artificial Intelligence (AI) is emerging as a useful tool in helping to improve the quality of education. However, studies on student perceptions of the use of AI in learning English as a Second Language are scarce (ESL). The purpose of this study is to investigate the attitudes of Vinschool Ocean Park Grade 11 students on the employment of AI in ESL in terms of orientation, use, and impact. A qualitative-descriptive method was adopted to gain in-depth insights into the perceptions of Grade 11 students. The data was gathered through semi-structured interviews, and the transcribed data were subjected to content analysis. Findings suggested that selected Grade 11 learners have a moderate level of familiarity with AI in education. The learners want to know more and have some reservations regarding the use and implications of AI. They have used only a few AI applications in their learning of ESL, with varying expectations and satisfaction levels of the outcomes. In light of the results, this research recommends a broader integration of AI in the classroom, accompanied by adequate training to improve teacher and student understanding and usage. Future studies on AI in learning ESL should focus more on student perspectives to evaluate how AI can be used to enhance educational experiences.

Preparing healthcare leaders of the digital age with an integrative artificial intelligence curriculum: a pilot study

ABSTRACT Artificial intelligence (AI) is rapidly being introduced into the clinical workflow of many specialties. Despite the need to train physicians who understand the utility and implications of AI and mitigate a growing skills gap, no established consensus exists on how to best introduce AI concepts to medical students during preclinical training. This study examined the effectiveness of a pilot Digital Health Scholars (DHS) non-credit enrichment elective that paralleled the Dartmouth Geisel School of Medicine’s first-year preclinical curriculum with a focus on introducing AI algorithms and their applications in the concurrently occurring systems-blocks. From September 2022 to March 2023, ten self-selected first-year students enrolled in the elective curriculum run in parallel with four existing curricular blocks (Immunology, Hematology, Cardiology, and Pulmonology). Each DHS block consisted of a journal club, a live-coding demonstration, and an integration session led by a researcher in that field. Students’ confidence in explaining the content objectives (high-level knowledge, implications, and limitations of AI) was measured before and after each block and compared using Mann-Whitney U tests. Students reported significant increases in confidence in describing the content objectives after all four blocks (Immunology: U = 4.5, p = 0.030; Hematology: U = 1.0, p = 0.009; Cardiology: U = 4.0, p = 0.019; Pulmonology: U = 4.0, p = 0.030) as well as an average overall satisfaction level of 4.29/5 in rating the curriculum content. Our study demonstrates that a digital health enrichment elective that runs in parallel to an institution’s preclinical curriculum and embeds AI concepts into relevant clinical topics can enhance students’ confidence in describing the content objectives that pertain to high-level algorithmic understanding, implications, and limitations of the studied models. Building on this elective curricular design, further studies with a larger enrollment can help determine the most effective approach in preparing future physicians for the AI-enhanced clinical workflow.

The role of artificial intelligence in corporate digital strategies: evidence from China

PurposeIn the rapidly evolving digital economy, businesses face formidable pressures to maintain their competitive standing, prompting a surge of interest in the intersection of artificial intelligence (AI) and digital transformation (DT). This study aims to assess the impact of AI technologies on corporate DT by scrutinizing 3,602 firm-year observations listed on the Shanghai and Shenzhen stock exchanges. The research delves into the extent to which investments in AI drive DT, while also investigating how this relationship varies based on firms' ownership structure.Design/methodology/approachTo explore the influence of AI technologies on corporate DT, the research employs robust quantitative methodologies. Notably, the study employs multiple validation techniques, including two-stage least squares (2SLS), propensity score matching and an instrumental variable approach, to ensure the credibility of its primary findings.FindingsThe investigation provides clear evidence that AI technologies can accelerate the pace of corporate DT. Firms strategically investing in AI technologies experience faster DT enabled by the automation of operational processes and enhanced data-driven decision-making abilities conferred by AI. Our findings confirm that AI integration has a significant positive impact in propelling DT across the firms studied. Interestingly, the study uncovers a significant divergence in the impact of AI on DT, contingent upon firms' ownership structure. State-owned enterprises (SOEs) exhibit a lesser degree of DT following AI integration compared to privately owned non-SOEs.Originality/valueThis study contributes to the burgeoning literature at the nexus of AI and DT by offering empirical evidence of the nexus between AI technologies and corporate DT. The investigation’s examination of the nuanced relationship between AI implementation, ownership structure and DT outcomes provides novel insights into the implications of AI in the diverse business contexts. Moreover, the research underscores the policy significance of supporting SOEs in their DT endeavors to prevent their potential lag in the digital economy. Overall, this study accentuates the imperative for businesses to strategically embrace AI technologies as a means to bolster their competitive edge in the contemporary digital landscape.

Exploring the Broad Impact of AI Technologies on Student Engagement and Academic Performance in University Settings in Afghanistan

This article explores the pivotal intersection of Artificial Intelligence (AI), student engagement, and academic performance in higher education, specifically at Kabul University. As technology evolves, understanding AI's implications on education becomes critical for effective pedagogical strategies and student readiness. The research aims to bridge the gap between technological advancements and educational practices, comprehensively investigating AI's impact on student engagement and academic performance. The study addresses awareness, ethical considerations, autonomy perceptions, and AI integration into curricula. Employing a quantitative approach, the study involves 200 students from various Kabul University faculties, utilizing SPSS version 23 for analysis. Regression analyses, ANOVA, and structured questionnaires allow a nuanced exploration of AI engagement dimensions. Key findings indicate commendable AI awareness in students' daily lives, with room for improvement in academic integration. Ethical considerations emphasize a baseline for ethical AI use. Autonomy perceptions and AI tool engagement reveal nuanced layers, emphasizing a holistic AI education approach. In conclusion, this research advocates a balanced AI integration in education, offering implications for pedagogical strategies, curriculum development, and institutional policies. The findings guide educators, policymakers, and institutions in navigating AI-enhanced learning environments, ensuring students' technological literacy and ethical grounding.

Artificial Intelligence in the Future Landscape of Pediatric Neuroradiology: Opportunities and Challenges.

This paper will review how artificial intelligence (AI) will play an increasingly important role in pediatric neuroradiology in the future. A safe, transparent, and human-centric AI is needed to tackle the quadruple aim of improved health outcomes, enhanced patient and family experience, reduced costs, and improved well-being of the healthcare team in pediatric neuroradiology. Equity, diversity and inclusion, data safety, and access to care will need to always be considered. In the next decade, AI algorithms are expected to play an increasingly important role in access to care, workflow management, abnormality detection, classification, response prediction, prognostication, report generation, as well as in the patient and family experience in pediatric neuroradiology. Also, AI algorithms will likely play a role in recognizing and flagging rare diseases and in pattern recognition to identify previously unknown disorders. While AI algorithms will play an important role, humans will not only need to be in the loop, but in the center of pediatric neuroimaging. AI development and deployment will need to be closely watched and monitored by experts in the field. Patient and data safety need to be at the forefront, and the risks of a dependency on technology will need to be contained. The applications and implications of AI in pediatric neuroradiology will differ from adult neuroradiology.

Artificial intelligence in the information ecosystem: Affordances for everyday information seeking

AbstractIn this conceptual article, we argue that artificial intelligence (AI) systems are contributing to the generation of an environment of affordances for everyday information practices through which they exert influence on people and the planet in ways that often are left unrecognized. We illustrate our insights by focusing on the practices of information seeking in everyday life, suggesting that the affordances of AI systems integrated into search engines, social media platforms, streaming services, and media generation, shape such practices in ways that may, paradoxically, result both in the increase and reduction of diversity of and access to information. We discuss the potential implications of these developments in terms of the sustainability of information ecosystems and suggest solutions for addressing them through regulation and education. Drawing from the fields of library and information science and science and technology studies and research on affordances, everyday information practices, and sustainability, the article seeks to respond to the need for more nuanced theoretical insights on the impact and implications of AI on information practices and to develop conceptual tools with which to examine the co‐evolution of humans and information systems from a systemic perspective.