Impact Of Artificial Intelligence Research Articles

Impact of Artificial Intelligence on RTVE: Verification of fake videos and Deep fakes, content generation, and new professional profiles

The emergence of technologies based on artificial intelligence is accelerating the digital transformation of media organizations, directly impacting work processes, the relationship with audiences, the generation of content, and the emergence of new professional profiles. It is also, and notably, transforming the processes of detecting and verifying false content. This descriptive-exploratory research analyzes the impact that the use of AI is having on the transformation of the public entity Radiotelevisión Española (RTVE). Through a literature review and interviews with RTVE executives and experts, it reveals the transformative impact of AI on the corporation, highlighting its use to generate new content and verify the authenticity of fake and deepfake videos. In this area, RTVE combines traditional methodologies with others based on AI and leads the development of several tools in collaboration with several universities. These tools have already yielded satisfactory results in detecting these misleading materials, reinforcing RTVE’s role as a guarantor of the veracity of information and increasing citizens’ trust in its content. Similarly, AI is reinforcing RTVE’s identity as a public service by facilitating the generation of automated content, which guarantees access to information in depopulated territories, and others that connect new generations with cultural content. The arrival of artificial intelligence will also generate in a short time a transformation of profiles and professional roles that adapt to this new reality.

Impact of artificial intelligence on health information literacy: guidance for healthcare professionals

Purpose This paper aims to explore the intricate relationship between artificial intelligence (AI) and health information literacy (HIL), examining the rise of AI in health care, the intersection of AI and HIL and the imperative for promoting AI literacy and integrating it with HIL. By fostering collaboration, education and innovation, stakeholders can navigate the evolving health-care ecosystem with confidence and agency, ultimately improving health-care delivery and outcomes for all. Design/methodology/approach This paper adopts a conceptual approach to explore the intricate relationship between AI and HIL, aiming to provide guidance for health-care professionals navigating the evolving landscape of AI-driven health-care delivery. The methodology used in this paper involves a synthesis of existing literature, theoretical analysis and conceptual modeling to develop insights and recommendations regarding the integration of AI literacy with HIL. Findings Impact of AI on health-care delivery: The integration of AI technologies in health-care is reshaping the industry, offering unparalleled opportunities for improving patient care, optimizing clinical workflows and advancing medical research. Significance of HIL: HIL, encompassing the ability to access, understand and critically evaluate health information, is crucial in the context of AI-driven health-care delivery. It empowers health-care professionals, patients and the broader community to make informed decisions about their health and well-being. Intersection of AI and HIL: The convergence of AI and HIL represents a critical juncture, where technological innovation intersects with human cognition. AI technologies have the potential to revolutionize how health information is generated, disseminated and interpreted, necessitating a deeper understanding of their implications for HIL. Challenges and opportunities: While AI holds tremendous promise for enhancing health-care outcomes, it also introduces new challenges and complexities for individuals navigating the vast landscape of health information. Issues such as algorithmic bias, transparency and accountability pose ethical dilemmas that impact individuals’ ability to critically evaluate and interpret AI-generated health information. Recommendations for health-care professionals: Health-care professionals are encouraged to adopt strategies such as staying informed about developments in AI, continuous education and training in AI literacy, fostering interdisciplinary collaboration and advocating for policies that promote ethical AI practices. Practical implications To enhance AI literacy and integrate it with HIL, health-care professionals are encouraged to adopt several key strategies. First, staying abreast of developments in AI technologies and their applications in health care is essential. This entails actively engaging with conferences, workshops and publications focused on AI in health care and participating in professional networks dedicated to AI and health-care innovation. Second, continuous education and training are paramount for developing critical thinking skills and ethical awareness in evaluating AI-driven health information (Alowais et al., 2023). Health-care organizations should provide opportunities for ongoing professional development in AI literacy, including workshops, online courses and simulation exercises focused on AI applications in clinical practice and research. Originality/value This paper lies in its exploration of the intersection between AI and HIL, offering insights into the evolving health-care landscape. It innovatively synthesizes existing literature, proposes strategies for integrating AI literacy with HIL and provides guidance for health-care professionals to navigate the complexities of AI-driven health-care delivery. By addressing the transformative potential of AI while emphasizing the importance of promoting critical thinking skills and ethical awareness, this paper contributes to advancing understanding in the field and promoting informed decision-making in an increasingly digital health-care environment.

Adoption and use factors of artificial intelligence and big data by citizens

The impact of artificial intelligence on people’s lives is demonstrated today. Previous literature has shown that the use of a specific technology is directly linked to the individuals’ intention to use it. The aim of this paper is to study the factors that determine the adoption and use of artificial intelligence and big data in Spain, using a research model based on the Unified Theory of Acceptance and Use of Technology (UTAUT), proposed by Venkatesh et al. (2003). This work addresses the specific gap in the validation of the original theoretical model of UTAUT in two dimensions, with respect to the adoption of artificial intelligence by citizens and with respect to the factors that influence this adoption, evaluating the previous ones and proposing some new ones considering the current context. The methodology used is based on a national survey, and it analyzes the research model using the statistical technique of Partial Least Squares Structural Equation Modelling (PLS-SEM), which details the mediating and moderating relationships between constructs. The results show that Intention to Use has a direct positive influence on the Use of artificial Intelligence and big data, confirming previous literature. Performance Expectancy is the strongest predictor of Intention to Use, and indirectly of the adoption of artificial intelligence and big data applications. Effort Expectancy, in its application to the adoption of AI and big data by citizens, is an indirect determinant mediated by the Intention to Use, but its total effect (direct + indirect) is not significant.

The impact of Artificial Intelligence on biliary and pancreatic surger

Artificial Intelligence (AI) has made substantial advancements across various medical specialties, revolutionizing healthcare delivery and outcomes. In recent years, AI has been increasingly applied to surgical disciplines, including biliary and pancreatic surgery. This research paper aims to explore the impact of AI on these surgical domains, including preoperative planning, intraoperative guidance, and postoperative care. The paper will also discuss the challenges and opportunities associated with the integration of AI in biliary and pancreatic surgery, providing insights into the potential future directions of this transformative technology.

Revitalizing Postoperative Pain Management in Enhanced Recovery After Surgery via Inter-departmental Collaboration Toward Precision Medicine: A Narrative Review.

This narrative review explores the crucial aspects of postoperative pain management within the framework of Enhanced Recovery After Surgery (ERAS). It emphasizes the significance of effective and secure pain management, highlighting its impact on patient well-being, surgical outcomes, and hospital stays. The inadequacy of perioperative pain relief increases the risk of persistent postoperative pain, emphasizing the need to challenge the notion that pain is expected after surgery. The goals of postoperative pain management extend beyond mere relief, encompassing comfortable sleep, pain-free rest, and liberation from pain during initial recovery. Inadequate pain management can lead to complications such as heightened postoperative bleeding and an increased risk of thrombosis. The review delves into various analgesic methods, their complications, and safety measures.ERASprograms, focused on reducing complications and medical costs, emphasize the importance of judicious postoperative pain management and active rehabilitation. The review discusses complications associated with analgesic methods like opioids, epidural analgesia, and adjuvant analgesics. Collaboration within the perioperative management team is crucial for effective postoperative pain relief. Interdepartmental collaboration is essential for evaluating surgical procedures, analgesic methods, and crisis management strategies. The review concludes by integrating precision medicine into postoperative pain management, emphasizing the potential of genetic information in assessing pain sensitivity. It underscores the importance of inter-departmental collaboration and information gathering for the successful implementation of precision medicine tailored to each facility's perioperative management systems. Additionally, the impact of artificial intelligence (AI) on preoperative risk assessment and innovative monitoring techniques is discussed, paving the way for the advancement of precision medicine in postoperative pain management.

Can artificial intelligence help accelerate the transition to renewable energy?

Artificial intelligence (AI) has enormous potential in improving the efficiency and reducing the cost of energy systems; however, it is unclear whether it can help accelerate the transition from traditional fossil energy to renewable energy (RE). Previous studies have primarily focused on the applications of AI in the energy sector from a technical perspective; in contrast, this paper identifies the process and mechanism of AI's impact on the energy transition, using the wavelet-based quantile-on-quantile approach to estimate the impact of various AI quantiles on energy structure quantiles in different periods. Using data from China, the paper finds that the upper quantiles of AI increase the share of RE in total energy in the long term, demonstrating that AI can, by unlocking its vast potential, accelerate the transition to RE. However, in the short and medium terms, AI negatively impacts RE share, primarily due to considerable challenges in integrating AI into the RE sector. Moreover, the non-RE sector may temporarily benefit more from AI than the RE sector. These findings provide crucial insights for policymakers in coordinating AI's short- and long-term effects on the energy transition to effectively harness RE's potential and achieve the goal of a low-carbon economy.

Modelling for disability: How does artificial intelligence affect unemployment among people with disability? An empirical analysis of linear and nonlinear effects

There is a growing debate among scholars regarding the impact of artificial intelligence (AI) on the employment opportunities and professional development of people with disability. Although there has been an increasing body of empirical research on the topic, it has generally yielded conflicting findings. This study contributes to the ongoing debate by examining the linear and nonlinear effects of AI on the unemployment of people with disability in 40 countries between 2007 and 2021. Using the system Generalized Methods of Moments and panel smooth transition regression, the main conclusions are as follows. First, AI reduces the unemployment of people with disability in the full sample. Second, upon disaggregating the sample based on income level (high income/non-high income) and gender (men/women), the linear model only detects an inverse correlation between AI and unemployment among people with disability in high-income countries and among men, whereas it does not influence unemployment in non-high-income countries and women. Third, the panel smooth transition regression model suggests that the effects of AI on the unemployment of people with disability and among women are only observed once artificial intelligence interest search exceeds a specific threshold level. The effects of AI in non-high-income economies and among women are not significant in the lower regime, which confirms the nonlinear association between AI and the unemployment rate of people with disability. These findings have important policy implications for facilitating the integration of people with disability into the labor market.

Navigating the Future Landscape: Probing the Mechanism and Feeding Model of AI within Theatrical Arts

This scholarly article explores the application and impact of artificial intelligence (AI) in the realm of theatrical art creation, providing an analysis of the current state, challenges, and future development of the integration of AI and theatre. Through comprehensive case studies of various theatrical works both domestically and abroad, the article delineates four major “feeding” models of AI in theatre creation, discussing the specific applications and effects of these modes within the sphere of artistic creation. The symbiotic relationship between human creators and AI during the creative process is emphasized, envisioning the potential of AI as an innovative collaborator advancing theatrical artsalongside human creators. Despite present challenges confronting AI in theatrical creation, such as emotional depth and data dependency, the potential demonstrated in enhancing creative efficiency and expanding the scope of artistic expression is noteworthy.

The impact of artificial intelligence on medical diagnostics: A letter to the editor

Madam, Artificial intelligence (AI) describes the generation of intelligent machines that are capable of carrying out activities that usually call for human intellect. (1) It involves creating algorithms and models that enable computers to learn from and analyze vast amounts of data, recognize patterns, make decisions, and even engage in natural language processing. (2) AI has become increasingly important in various fields due to its potential to automate complex processes, enhance efficiency, and drive innovation. It can transform industries, improve decision-making, and revolutionize how we live and work. In medical diagnostics, AI has had a profound impact on improving accuracy, efficiency, and patient outcomes. By leveraging machine learning algorithms, AI systems can process and analyze large volumes of medical data, including patient records, laboratory results, medical images, and genomic data. This allows for more accurate and timely diagnoses, as AI algorithms can detect subtle patterns and anomalies that may not be visible to human observers. AI-powered diagnostics can assist healthcare professionals in detecting diseases, predicting patient outcomes, and designing personalized treatment plans. (3) Furthermore, AI can contribute to the early detection of diseases, thereby enabling timely interventions and improving patient survival rates. For example, AI algorithms analyze medical imaging data, such as X-rays, MRIs, and CT scans, to detect abnormalities and potential signs of diseases like cancer. This helps radiologists and clinicians identify and diagnose conditions early when treatment options are more effective. (4) Additionally, AI aids in interpreting genetic data, allowing for the identification of genetic markers associated with specific diseases or drug responses. This information guides clinicians in selecting the most suitable treatment options for individual patients, leading to improved therapeutic outcomes. (5) AI in medical diagnostics also faces hurdles with data privacy and accessibility, as patient information must be handled securely. Ensuring AI algorithms are unbiased, and fair is a challenge to avoid disparities in healthcare outcomes. The interpretability of AI models is vital to building trust with healthcare professionals and facilitating their adoption. Regulatory compliance and ethical considerations are also significant factors that need to be addressed for the responsible and effective integration of AI in the medical field. In conclusion, Artificial Intelligence (AI) is a transformative technology with the potential to revolutionize various industries, including medical diagnostics. Its ability to analyze vast amounts of data, recognize patterns, and make intelligent decisions has proven invaluable in improving diagnostic processes accuracy, efficiency, and effectiveness. ---Continue

The Impact of Artificial Intelligence on Elections

The digital revolution, characterized by the proliferation of social media and the integration of Artificial Intelligence (AI), has significantly impacted the political landscape of every country where free and fair elections are conducted. AI has the potential to affect the elections both positively as well as negatively. It is an opportunity to improve the democratic process in our societies by helping citizens to gain a better understanding of politics and engage more easily in democratic debate. Politicians can also improve their ability to represent the people by getting to know them better. This kind of cooperation between voters and elected officials has the potential to transform political campaigns and significantly enhance the process of formulating public policy, rendering it more precise and effective. On the other hand, there are certain concerns over the use of AI in politics as it poses multiple risks to democracies like misinformation and disinformation campaigns including deep fakes, the amplification and weaponization of hate speech, micro-targeting of voters, racial and gender stereotyping, AI-driven campaigning and the possibility of aspects of electoral processes being targeted through automated messaging such as political bots and chatbots. These AI-driven disinformation tools have the capacity to distort public opinion, influence voter attitudes, and jeopardise the democratic process itself. This paper critically examines the influence of AI on elections and democracy and underscores the need for robust regulatory frameworks and digital literacy initiatives to safeguard the democratic ethos in the age of AI.

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.

The virtual reference radiologist: comprehensive AI assistance for clinical image reading and interpretation.

Large language models (LLMs) have shown potential in radiology, but their ability to aid radiologists in interpreting imaging studies remains unexplored. We investigated the effects of a state-of-the-art LLM (GPT-4) on the radiologists' diagnostic workflow. In this retrospective study, six radiologists of different experience levels read 40 selected radiographic [n = 10], CT [n = 10], MRI [n = 10], and angiographic [n = 10] studies unassisted (session one) and assisted by GPT-4 (session two). Each imaging study was presented with demographic data, the chief complaint, and associated symptoms, and diagnoses were registered using an online survey tool. The impact of Artificial Intelligence (AI) on diagnostic accuracy, confidence, user experience, input prompts, and generated responses was assessed. False information was registered. Linear mixed-effect models were used to quantify the factors (fixed: experience, modality, AI assistance; random: radiologist) influencing diagnostic accuracy and confidence. When assessing if the correct diagnosis was among the top-3 differential diagnoses, diagnostic accuracy improved slightly from 181/240 (75.4%, unassisted) to 188/240 (78.3%, AI-assisted). Similar improvements were found when only the top differential diagnosis was considered. AI assistance was used in 77.5% of the readings. Three hundred nine prompts were generated, primarily involving differential diagnoses (59.1%) and imaging features of specific conditions (27.5%). Diagnostic confidence was significantly higher when readings were AI-assisted (p > 0.001). Twenty-three responses (7.4%) were classified as hallucinations, while two (0.6%) were misinterpretations. Integrating GPT-4 in the diagnostic process improved diagnostic accuracy slightly and diagnostic confidence significantly. Potentially harmful hallucinations and misinterpretations call for caution and highlight the need for further safeguarding measures. Using GPT-4 as a virtual assistant when reading images made six radiologists of different experience levels feel more confident and provide more accurate diagnoses; yet, GPT-4 gave factually incorrect and potentially harmful information in 7.4% of its responses.

AI patenting and employment: evidence from the world’s top R&D investors

For assessing the overall impact of Artificial Intelligence (AI), it is crucial to continuously monitor large corporations. This paper delves into the examination of 42 corporations that rank among the world's largest investors in R&D, accounting for over one-third of AI patents globally. The focus is on their post-patenting performance, specifically in terms of employment changes, and comparing it with the outcomes of 42 similar companies operating in the same sectors. The latter also recorded substantial levels of R&D expenditures but were not significantly involved in AI patenting. The key findings reveal that, in the medium – and high-tech manufacturing sectors, companies with the highest proportions of AI patents incurred in employment reductions. Conversely, IT services companies experienced substantial employment growth. Along with tentative explanations of these findings, advantages, limitations, and possible developments of this type of analysis are illustrated in the concluding section.

The Impact of Artificial Intelligence on Education

Artificial Intelligence (AI) is an increasingly progressive field that aims to develop computer systems capable of producing inventive and creative content, including text, images, music, video, and audio, that closely resemble human-generated material. AI has significantly impacted education, with both positive and negative implications. While it has gained widespread popularity, it has also raised concerns about bias, misinformation, misuse, and risk, emphasising the need for the responsible implementation and development of generative AI in education. There have been discussions about whether it should be prohibited or whether teachers and students should receive adequate training to use it effectively and ethically. The purpose of AI in education should be to embrace the opportunities it presents while maintaining high academic standards. Renowned universities have developed guidelines and manuals for the responsible use of generative AI tools. This study examines the impact of generative AI on education, analysing its advantages and disadvantages in schools, its outcomes, and how teachers and students can use it for educational purposes. The study also emphasizes the effective use of AI in education, employing qualitative and quantitative methods to evaluate its usage. The results highlight the benefits and drawbacks of generative AI in education, concluding with recommendations and future applications of generative AI in education.

The impact of artificial intelligence on unemployment: a review

PurposeThe aim of this paper is to summarise the state-of-the-art debate on impact of artificial intelligence on unemployment and reporting up-to-date academic findings.Design/methodology/approachThe paper is designed as a review of the labour vs capital conundrum, the differences between industrial automation and artificial intelligence, threat to employment, the difficulty of substituting, role of soft skills and whether technology leads to the deskilling of human workers or favors increasing human capabilities.FindingsSome authors praise the bright future developments of artificial intelligence while others warn about mass unemployment. Therefore, it is paramount to present an up-to-date overview of the problem, compare and contrast its features with what happened in past innovation waves and contribute to academic discussion about the pros/cons of current trends.Originality/valueThe main value of this paper is presenting a balanced view of 100+ different studies, the vast majority from the last five years. Reading this paper will allow to quickly grasp the main issues around the thorny topic of artificial intelligence and unemployment.Peer reviewThe peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-05-2023-0338

The Impact of Artificial Intelligence on Human Resource Practices

This research investigates the effects of Artificial Intelligence on practices within Human Resources Management. It examines various important results, including precision, automation, computational ability and capacity, real-time interaction, customization, and time and cost savings. The aim is to identify the potential advantages of incorporating AI. Data was gathered from 274 IT workers in Chennai City through a well-designed online survey. The study introduces a new research framework using IBM SPSS version 21 software for analysis as well as AMOS version 21.The results show that factors such as Precision, Computational Ability & Capacity and Customization significantly impact Time-Saving & Cost Reduction while Automation and Real-Time Interaction do not have significant influence. This study's unique contribution lies in investigating specific outcomes when utilizing AI technologies in Human Resources Management Practices by focusing on key variables like Precision, Automation, Computing Power & Capacity Real-time experience, Customization, and Time-Saving Cost Saving capturing an extensive understanding of anticipated outcomes during AI implementation within Human resources management along with their interrelationships.

(WITHDRAWAL) THE IMPACT OF AI ON EMPLOYMENT AND ORGANISATION IN THE INDUSTRIAL WORKING ENVIRONMENT OF THE FUTURE

(Withdrawal) The publisher made the decision to withdraw the article after discovering that it is a copy of another source and that the document missing the necessary citations.

The Impact of Artificial Intelligence on Future Aviation Safety Culture

Artificial intelligence is developing at a rapid pace, with examples of machine learning already being used in aviation to improve efficiency. In the coming decade, it is likely that intelligent assistants (IAs) will be deployed to assist aviation personnel in the cockpit, the air traffic control center, and in airports. This will be a game-changer and may herald the way forward for single-pilot operations and AI-based air traffic management. Yet in aviation there is a core underlying tenet that ‘people create safety’ and keep the skies and passengers safe, based on a robust industry-wide safety culture. Introducing IAs into aviation might therefore undermine aviation’s hard-won track record in this area. Three experts in safety culture and human-AI teaming used a validated safety culture tool to explore the potential impacts of introducing IAs into aviation. The results suggest that there are indeed potential negative outcomes, but also possible safety affordances wherein AI could strengthen safety culture. Safeguards and mitigations are suggested for the key risk owners in aviation organizations, from CEOs to middle managers, to safety departments and frontline staff. Such safeguards will help ensure safety remains a priority across the industry.

A person’s right to be forgotten

The article examines in detail the concept of “a person’s right to be forgotten” as an important aspect of a natural person’s right to information about himself, which allows a person to demand the removal or destruction of his personal information. The question is also devoted to the main aspects of the history and development of the “right to be forgotten” concept.
 The author states that a significant contribution to the regulation of the right to be forgotten within the framework of the legislation on personal data protection was made by the European Union. After all, EU Regulation 2016/679 defines the conditions for obtaining this right, the conditions for fulfilling requests to delete information about yourself, and the circumstances under which this right may be limited. However, this Regulation does not take into account the entire amount of personal information, which complicates the process of realizing the human right to be forgotten.
 It has been determined that different countries develop their own approaches to the right to be forgotten. It was found that the current legislation of Ukraine provides for two stages of “forgetting”: a court decision and filing a complaint for violation of the terms of consent to the processing and storage of personal data.
 At the same time, the decision of the European Court, which became key in the world judicial practice regarding the human right to be forgotten, was considered. In addition, the balance between the right to be forgotten and freedom of information is described. The public interest and ethical aspects in the context of the right to be forgotten are studied. The need for transparency and a balanced approach to the researched law is substantiated.
 The technical aspects of the human right to be forgotten and the challenges they generate are also described. The complexity of technical data deletion and the challenges of data caching and indexing have been studied. The general aspects of ensuring the security and protection of data during deletion are identified, as well as the impact of artificial intelligence and automation on the human right to be forgotten.

Navigating in the Digital Age: The Impact of Artificial Intelligence on Distance Learning

This study investigates the integration of Artificial Intelligence (AI) in the context of distance learning, inspired by successful initiatives, such as the Frankie Project in Basic Education. Its objective is to analyze the practical implications, advantages and challenges of adopting AI in online educational environments. A detailed analysis is performed, highlighting examples of adaptive learning systems as promising models. These systems demonstrate the ability to personalize instruction to individual student needs while providing valuable insights through predictive analytics. However, when exploring these opportunities, important questions also arise to consider. For example, data privacy emerges as a significant concern, especially in the context of collecting and analyzing students’ personal information. Furthermore, the need for teacher training for the effective integration of AI into the educational curriculum is highlighted, as is the importance of ensuring equity in access to technology among all students. To overcome these challenges, it is concluded that a collaborative and multidisciplinary approach is essential. Collaboration between educators, researchers, technology developers, and other stakeholders can help address obstacles and maximize the benefits of AI in distance education. Ultimately, the study highlights the transformative potential of AI to improve the effectiveness and accessibility of distance learning, thus reinforcing the importance of a careful and ethical approach when integrating this technology into the educational environment.