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In recent years, there has been significant growth in research related to Agile software development (ASD), accompanied by a notable rise in the adoption of artificial intelligence (AI) tools and techniques. AI is believed to have the potential to bring about a transformation in agile software development, leading to improved product quality, increased production efficiency, and higher project success rates. Consequently, there is a compelling need to incorporate AI methods and tools into the agile software development process. This study presents the results of a literature review and answers research questions on AI techniques and tools, their purposes, and their benefits when used in the context of ASD. In a multi-phased process, a total of 374 documents were gathered and examined. 28 papers satisfied the inclusion and quality assessment requirements. A total of 7 different AI techniques were identified, of which machine learning (ML) was the one predominantly used. The purposes and benefits of AI techniques were identified and discussed. Recommendations for future research were given to tackle detected research gaps. [ABSTRACT FROM AUTHOR]

Our EU-funded project, conducted in Jönköping County, Sweden from 2021-2023, aimed to advance AI in the local business sector through collaboration between academia, industry, and business promotion systems. Using a stepwise approach, we transitioned 88 companies from basic AI knowledge to implementing AI functions. This included assessing AI maturity and developing tailored educational materials. Collaborating with Jönköping University, we engaged 19 SMEs, integrating real-world AI challenges with academic courses. Emphasizing sustainable and ethical AI practices, we educated companies on possible alternatives to AI usage. In this paper we report on the results of an evaluative study of the participating partners, revealing key parameters for advancing AI implementation. [ABSTRACT FROM AUTHOR]

As societies rely increasingly on computers for critical functions, the importance of cybersecurity becomes ever more paramount. Even in recent months there have been attacks that halted oil production, disrupted online learning at the height of COVID, and put medical records at risk at prominent hospitals. This constant threat of privacy leaks and infrastructure disruption has led to an increase in the adoption of artificial intelligence (AI) techniques, mainly machine learning (ML), in state-of-the-art cybersecurity approaches. Oftentimes, these techniques are borrowed from other disciplines without context and devoid of the depth of understanding as to why such techniques are best suited to solve the problem at hand. This is largely due to the fact that in many ways cybersecurity curricula have failed to keep up with advances in cybersecurity research and integrating AI and ML into cybersecurity curricula is extremely difficult. To address this gap, we propose a new methodology to integrate AI and ML techniques into cybersecurity education curricula. Our methodology consists of four components: i) Analysis of Literature which aims to understand the prevalence of AI and ML in cybersecurity research, ii) Analysis of Cybersecurity Curriculum that intends to determine the materials already present in the curriculum and the possible intersection points in the curricula for the new AI material, iii) Design of Adaptable Modules that aims to design highly adaptable modules that can be directly used by cybersecurity educators where new AI material can naturally supplement/substitute for concepts or material already present in the cybersecurity curriculum, and iv) Curriculum Level Evaluation that aims to evaluate the effectiveness of the proposed methodology from both student and instructor perspectives. In this paper, we focus on the first component of our methodology - Analysis of Literature and systematically analyze over 5000 papers that were published in the top cybersecurity conferences during the last five years. Our results clearly indicate that more than 78% of the cybersecurity papers mention AI terminology. To determine the prevalence of the use of AI, we randomly selected 300 papers and performed a thorough analysis. Our results show that more than 19% of the papers implement ML techniques. These findings suggest that AI and ML techniques should be considered for future integration into cybersecurity curriculum to better align with advancements in the field. [ABSTRACT FROM AUTHOR]

This paper examines the challenge industrial companies face in transforming pilot AI projects into successful, scalable new businesses models. An evaluation of international industrial firms has revealed common difficulties in maintaining the objectives of AI business models and achieving alignment between AI initiatives and overarching strategic goals. These misalignments result in significant challenges, including scalability issues, unclear return on investment (ROI), and a general misalignment with business objectives. To address these challenges, a comprehensive methodical framework is introduced that guides companies through the complexity of scalable AI implementation in industrial domain. This framework not only provides use-case-specific guidelines, but also defines AI-specific strategies and addresses critical cultural and organizational considerations necessary for successful AI integration. [ABSTRACT FROM AUTHOR]

This paper aims to select the AI-based methods that have the potential to be adapted for the assessment of the European Union R&I policy impact on the member states' innovation performance. A structured scientific literature analysis is employed to review the most recent 1,544 papers published in the Web of Science database from 2017 to 2021. The primary findings reveal that there is a growing interest in the usage of artificial and computational intelligence, seeking to improve the decision-making processes. Such methods as Bayesian neural network, fuzzy-set qualitative comparative analysis, self-organizing neural maps, multi-output neural networks, and data envelopment analysis can be well-applicable for the case of the European Union research and innovation investment efficiency evaluation. [ABSTRACT FROM AUTHOR]

In the current wave of AI innovation, the European Commission has defined Testing and Experimentation Facilities to be established to facilitate AI innovation in the context of new legislation such as the AI act. Within this paper, we investigate the CitCom.ai TEF in an attempt to link these TEFs to longer existing concepts such as testbeds, Living Labs and Regulatory Sandboxes. Our analysis reveals 7 service categories that can be linked to these three innovation concepts. In the 26 analysed experiments, there was a clear dominance of services linked to the concept of AI testbeds. In second place came three service categories that can be attributed to Living Labs. Remarkably, the service category linked to AI regulatory sandboxes appeared to be the least popular. This reflects the 'in development' status of this concept. [ABSTRACT FROM AUTHOR]

When only women turn up to a panel on challenges for women in technology, how do we then reach out to industry, academia and government to encourage them to listen to the current challenges experienced by women in tech. Technology is rapidly changing and we are seeing women disadvantaged by less training opportunities, lack of role models, perceived penalties for taking time off to have children or discharge caring responsibilities as well as the risk that their jobs are subject to more automation. Multiple workshops at the Institute of Science and Technology highlighted significant challenges for women in tech, the data from our empirical study illustrates these challenges in detail. With the workplace still male dominated and the landscape changing rapidly, women have a significant role to play and we need to ensure that role is not only facilitated but the existing challenges are mitigated. This is a discussion paper with empirical data that illustrates challenges currently experienced by women in tech and how we can move forward to ensure not only equal opportunity but remove some of the challenges currently experienced. In this paper we have not considered the same impact on men who take career breaks for reasons of caring responsibilities. [ABSTRACT FROM AUTHOR]

In this study, a systematic literature review is conducted to more thoroughly understand the context surrounding the emerging implementation of artificial intelligence (AI) in organisations. An Input-Process-Output model is adopted as the research framework to investigate the antecedences, processes and consequences of AI implementation in organisations. The preliminary results of the research are presented after analysing 50 peer-reviewed full papers. Although the research is still in progress, it is expected the findings of this study can contribute to the already existing body of literature and identify implications for practitioners. [ABSTRACT FROM AUTHOR]

While AI remains chip based and part of both commercial and national strategic superiority goals, it is useful to examine the security and risks associated with achieving those goals. The future strategy rests perilously on an unstable inverted triangle of financial and economic reality. This paper presents the AI chip supply chain as an inverted triangle which base/apex is dependent on a global single supplier with the capability of producing equipment essential for their manufacture. It highlights the dependence on a single company for the fabrication of those chips, and the security risks associated with that supplier being Taiwanese in limited foreign ownership. It is suggested that the increasing tensions between China and the USA have resulted, in part, from this dependence, which was demonstrated by the supply chain crisis resulting from Covid-19. The attempt to reduce this dependence led to the CHIPS and Science Act 2022, signed into law by President Biden. In part of the inverted triangle are found Big Tech and the major Cloud Service Providers. They vary between 60% - 80% of their market capital being in financial institutional ownership, most of which is held by a very limited number of institutions, not all of whom are publicly quoted. To doubt the influence wielded by those financial institutions, just a single institution with major Big Tech and Cloud holdings has, at 31 December 2022, USD 8.59 trillion of assets under management. This represents economic power and places it between the equivalent Gross Domestic Product of China (USD 19.37 trillion) and Japan (USD 4.41 trillion) the second and third entries behind the USA in the GDP rankings. Financial institutions are market driven to achieve growth, contribute to economic stability, and are to an extent regulated by unelected vested interests and organisations. The battlefield for national supremacy of AI may concern chips, until the arrival of quantum AI. Current Chinese economic woes are providing the momentum for pre-emptive strikes at the semiconductor industry, and an inverted triangle is neither a secure nor stable structure for a supply chain. [ABSTRACT FROM AUTHOR]

Artificial Intelligence (AI) has swiftly emerged as a transformative, dynamism and reforming numerous facets our lives. According to the International Data Corporation report spending on AI is projected to reach $97.9 billion by 2023. It means businesses across different industries embrace AI technology to improve their operations, gain a competitive edge, and unlock new opportunities for business. However, the increasing adoption of AI in business also pretence some challenges that must be addressed. In this article discussed the future of artificial intelligence, its opportunities, and identified major challenges in presents for business. This paper delivers insights into the current state of AI adoption and its potential for future growth to drive important progresses in business operations, including enlarged production, cost savings, and enriched decision-making. The paper concludes by providing recommendations for businesses looking to accept AI and highlights the need for a collective approach between businesses, policymakers, and other stakeholders. [ABSTRACT FROM AUTHOR]

The lockdowns of covid-19 contributed to accelerating the developments within distance work and collaboration. This development impressive in terms of organizations’ and employees’ rapid adaption of digital tools, as well as to the extensive shift of attitude towards working from home. In this paper, we ask how we might exploit findings on digitalisation to prepare innovation management for the impeding developments within AI-based technologies to facilitate their exploration and the exploitation of its potential productivity contribution. [ABSTRACT FROM AUTHOR]

New AI techniques are available for a variety of applications, including ChatGPT, BARD, and Perplexity. ChatGPT is a chatbot that can generate text on almost any topic or theme, while BARD is a generative AI chatbot that can take written inputs and generate human-like responses to text inputs in a conversational manner. Perplexity is a conversational search engine that enhances the user experience and management decisions. These AI tools can be used separately or combined to form an AI Swarm to assist in strategic foresight within the scenario technique. However, the reliability of large language models like ChatGPT is highly unreliable, and they can generate misinformation and falsehoods. The practical impacts of these models are investigated to evaluate AI-generated results against an existing automotive scenario project. This paper aims to demonstrate AI's capacity to enhance the scenario technique, which streamlines and expedites management decisions. [ABSTRACT FROM AUTHOR]

Artificial intelligence (AI) technology innovations are predicted to drive the greatest evolutionary progress in human history, accelerating the emergence of new technology innovations and affecting the way we humans live and act. In this situation, it is important to address how we can use these technologies and service innovations enabling the beneficial impacts, possibly by exceeding the human performance levels. Despite of the importance of the AI innovations and their impact in healthcare, there is still only little advance research about long-term effects on healthcare practitioners. This paper provides a literature review looking at the AI impacts to the healthcare experts. In the paper it is shown, that the field is lacking empirical evidence, but there is an indication of positive impact through communication enhancement between physician and patient, but also possibilities for clinical and cognitive skills deterioration. [ABSTRACT FROM AUTHOR]

This paper aims to outline primary objectives and methods underpinned during the development of HayAnksi! App -based on a pun, derived from the Turkish exclamation "Hay aksi!/Whoops!". HayAnksi! is a computerized Cognitive Behavioral Therapy (cCBT) application elaborated with other therapeutic approaches and information technologies. HayAnksi! incorporates solutions based on wearable technologies and the usage of artificial intelligence with more conventional cCBT modules. The target group of the said interventions is adolescents with anxiety. The objectives are to increase the awareness of participants about anxiety disorders with psychoeducation and to encourage them to apply the therapeutic techniques via wearable devices. The app collects physiological and psychological data through smartwatch integration and the data collected through the app informs the direction of available interventions and tailors personalized treatment regarding anxiety. [ABSTRACT FROM AUTHOR]

On December 8th, 2021, Professor Stuart Russell delivered the second of that year's Reith Lectures, presented under the banner title 'Living With Artificial Intelligence'. This specific talk dealt with 'The Future Role of AI in Warfare', and in this paper I propose a reading of Russell's address which both summarises and critiques his argument and stance, to determine what, if anything, can be taken from his position as effectively a public philosopher and applied in the realm of modern warfare, where ethical questions are taken from the seminar room and enacted in battlespace. The Reith lectures occupy a unique place in public discourse; given each year by a leading figure in the field under discussion, they help to shape opinion and debate. In considering the role of AI, and in particular its deployment in combat, there is undoubtedly a need for multi- and transdisciplinary thought, but the choice of Russell as the lecturer is not unproblematic. He is undoubtedly an expert in the field of AI, but he has no direct experience of working with the military, and is clearly not a neutral witness. He has been a leading figure in the campaign to ban research into autonomous weapon systems, and was closely involved in the production of Slaughterbots, a short film which presents a nightmare vision of swarming drones as agents of political repression. There are deep and serious questions to be asked about the role of AI in warfare, but Russell's position that we must stop all research in the field is arguably naïve. Our adversaries will surely not be as punctilious. At the heart of the debate lie complex issues concerning human agency and control (and 'control' lies at the etymological root of 'cyber'); this paper will use Russell's lecture as a starting point for the consideration of how we might develop an ethical doctrine for the use of AI, resting on the idea of human-machine teaming. It will, in short, argue for a cybernetic solution to the problems of cyber warfare. [ABSTRACT FROM AUTHOR]

The escalating complexity of cyber attacks demands innovative intrusion detection systems (IDS) to safeguard critical assets and data. The study aims to explore the potential of Artificial Intelligence (AI) in enhancing the IDS's ability to identify and classify network traffic and detect anomalous behavior. The paper offers a concise overview of IDS and AI and examines the existing literature on the subject, highlighting the significance of integrating advanced language models for cybersecurity enhancement. The research outlines the methodology employed to assess the efficacy of AI within IDS. Furthermore, the study considers key performance metrics such as detection accuracy, false positive rate, and response time to ensure a comprehensive evaluation. Findings indicate that AI is a valuable asset in enhancing the accuracy of AI for detecting and responding to cyber attacks. Nonetheless, the study also brings to light certain limitations and challenges associated with incorporating AI into IDS, such as computational complexity and potential biases in training data. This research emphasizes the potential of advanced language models like ChatGPT in augmenting cybersecurity solutions and offers insights into overcoming associated challenges for a more robust and effective defense against sophisticated cyber attacks. [ABSTRACT FROM AUTHOR]

With the advent of digital technology, disruptive innovation is a strategy that is being adopted both by the manufacturing as well as the service industry. Disruptive digital technology like smartphone technology, social media, internet, and mobile applications have led to Business to Business (B2B), Peer to Peer (P2P), and Business to Consumer (B2C) strategies promising shared economy for tourism destinations. Technological disruptions such as IoT, Artificial Intelligence and rich media like virtual and augmented reality, parallel reality have created smarter environments that transformed tourism in terms of its structure, processes, and practices. It is a relatively modern form of technology, introduced to the existing tourism market which enables service providers in creating a unique experience for their customers. Here the customers motivate others in order to reap the benefits of technology-driven product (Danneels, 2004). These technologies create entirely new products and services that are dramatically cheaper, better, and more convenient forcing change in the whole new competitive industrial workforce. Such innovations are because of continuous scientific discoveries for a more technology-driven competitive paradigm (Kostoff et.al. 2004). The emergence of such smart environments will redefine the tourism sector as customer experience solely prevails on varying levels of infrastructure, organization, and cultural constraints (Buhalis et.al. 2019). The paper tries to explore various disruptive technologies that could be used for promoting tourism in a destination, forcing stakeholders to rethink and reengineer their services in this competitive ever-changing world. [ABSTRACT FROM AUTHOR]

This study aims to gain a comprehensive understanding of the differences between classic IT and AI artefacts. To achieve this objective, the study employs a grounded theory literature review approach and analyses 81 papers related to the application of classic IT and AI artefacts in the auditing industry. Drawing on the Technology Affordances and Constraints Theory, we examine the actions that can be potentially enabled or restricted by using classic IT and AI artefacts. This analysis allows us to conceptualise and compare the affordances and constraints associated with these two types of artefacts. The study addresses the need for more research on AI from both social and technical perspectives. Our findings may facilitate practitioners in improving their business processes and promoting effective collaboration between humans and AI. [ABSTRACT FROM AUTHOR]

The Internet of Things (IoT) often refers to the addition of network connectivity to ordinary objects or equipment that was previously not internet enabled. It is about connecting everyday objects to the internet and letting them communicate with each other, including humans. The IoT makes technologies smarter by enabling automation, personalization, and remote control via networks of Internet-connected sensors. At the same time, IoT technologies raise significant privacy concerns, which may hinder their wider adoption. IoT applications range from smart homes and wearable gadgets to industrial automation, agriculture, healthcare, transportation, ecosystem, warfare, business, education, etc. The IoT has the potential and prospects to completely transform our lives by enabling smarter, more connected, flexible, more relaxed, and more efficient systems. IoT has the potential to develop industries' efficiency, increase productivity, and improve our daily lives. IoT will be more global technology, and more things will become internet-connected in the future. It is an analytical paper to evaluate the IoT as a global technology, as well as depict its domains, challenges, and future consequences. [ABSTRACT FROM AUTHOR]

Artificial Intelligence (AI) allows computer programs to learn from experience through iterative processing and algorithmic training and represents human intelligence. Now, AI has become a hot topic and important debates have risen like, how it might affect the job market and what is the end of global civilization. Many people will lose their jobs due AI. On the other hand, few technology lovers think that it will lead to the creation of lots of diversified and interesting jobs. Many experts think that it will have a big impact on the workplace and all aspects of human life in the near future. In reality, AI can make jobs more creative, lucrative, and flexible, and will lead definitely to a more creative and skilled economy. However, history says, that advanced technologies are usually starting to take away more jobs than they create, and unfortunately, this trend will continue. Nowadays, there have been many ideas for how to solve this problem, and there should be updated education and skill develop program with new schooling system and that need to be introduced very soon. As there isn't enough work for everyone in the world, so the whole lifestyle and education system needs to be changed and to reorganize every aspect to make total human resource development system more purposeful. It is an analytical paper to analyze the potentials and challenges of AI along with the consequences of global future and way forward. [ABSTRACT FROM AUTHOR]

Narratives about intelligent artefacts have influenced both the public's imaginary and the actual development of the AI field since its foundation. Yet, in times where the field seems to be flourishing on the one hand, but rushing into an AI winter on the other, factual narratives about AI applications and advancements are more essential than ever. What is the gap between the actual capabilities of today's AI and the vocabulary used to report about them? In particular, what is the AI lingua used in official, legal documents in business? To find out, we analysed leading share index companies' annual reports from a representative fraction of the German economy (DAX 30), as a starting step in this direction. In this paper, we present a fact-based methodology for systematically assessing the true state of enterprise AI of those companies. Our initial empirical investigation covers only the annual reports of leading listed German enterprises in the DAX 30 as of May 2021 (i.e. before the DAX's expansion to 40 members). For this concrete example, we collected their annual reports from 2010 to 2020 (N=312). We then built upon previous work by extending natural language processing (NLP) algorithms we developed for these purposes. The idea is to systematically process and automatically detect the use of AI-related terminology in those annual reports. Such a terminology is part of a classification schema we introduce for differentiating concrete types of Air-elated terms. We also compare different NLP libraries regarding their suitability and speculate on the reasons behind the poor performance of some of them. Furthermore, we look at relevant AI keywords and phrases, thereby conducting a human-based semantic analysis of the context -- tasks that machines still cannot do effectively. We also give guidance on how to proceed in similar studies, i.e. on how to extend our methodology and the key findings to other national economies. This way, we are contributing not only to an informed perception about the state of enterprise AI, but also to filling the gap between the narratives it uses and the actual state of AI development. [ABSTRACT FROM AUTHOR]

In this paper, we examine the use of text mining for the discovery of business opportunities. Specifically, we are interested in the combination of two text mining techniques, topic modeling and chance discovery. Topic modeling is an unsupervised machine learning technique for discovering latent themes in a corpus of documents. Chance discovery is an approach to discover chances or "breaking events" from documents. It is based on the co-occurrence of words in documents and clustering related words. As a use case, we apply the combined approach to identify business opportunities for an e-tourism startup from customer comments on the Reddit social media platform. The audience of this paper includes entrepreneurs interested in new tools for opportunity discovery, and innovation researchers interested in applying text mining approaches. [ABSTRACT FROM AUTHOR]

AI has had a significant impact on marketing, transforming the way companies approach advertising and customer engagement. But we are not talking only about the business sphere, marketing tools are transformed and applied also in regional conditions and in the marketing communication of cities. Artificial intelligence and its use therefore also concern this area. Its use can be found in various spheres of city services, one of these services is communication with target groups operating in the given territory. These target groups primarily include citizens, tourists, entrepreneurs, students and working people in the given area. One of the main tasks of the city is that the primary target groups are informed about current events and information is provided to them in the most modern, efficient and fast way possible, which reflects the current technological progress in marketing communication. The aim of this contribution is to point out the possibilities and ways of using artificial intelligence in the communication of cities in Slovakia. AI can help city marketers to create more targeted and effective marketing communication, improve the customer experience, and build stronger relationships with residents and visitors. By analyzing data and providing insights, AI can also help city marketers to make data-driven decisions and measure the impact of their marketing communication efforts. In general, Slovakia belongs to the countries in which the development and advancement of city marketing is difficult from the point of view of financing and lack of human resources. However, one does not always think about the fact that current online and digital tools can be beneficial only if we know about them and know how to use what they offer. In the paper, we will look at the current use of artificial intelligence in the communication of selected Slovak cities with tourists and at the possibilities that artificial intelligence brings in the field of city marketing development. [ABSTRACT FROM AUTHOR]

Context: The knowledge domain of software engineering (SE) gradually expands due to fast emerging technologies and complex organisational processes. The software industry represents a special focus of interest from a Knowledge Management (KM) perspective, as it is characterized by high employee turnover, a high level of outsourced projects, and an accelerated pace of technology innovations. Knowledge management can substantially influence SE knowledge's life cycle, contributing to better structuring of organisational processes of knowledge creation, knowledge transfer, and knowledge sharing. Reflecting on the trends for SE automation with artificial intelligence tools, KM approaches can enable companies and professionals to reconsider the future of SE work. Purpose: The present research aims to identify and investigate how implementing knowledge management principles and processes within the software engineering domain can facilitate the future transformation of software-related jobs. Based on a conceptual model, built upon the literature review, the paper analyses the quantitative data, collected from 91 software experts. Evaluating the impact of both organizational and domain types of SE knowledge, the discussion evaluates the unique value-adding SE processes along with models of how to explore AI applications to automate the SE domain. Results: The outcomes of the analysis identify the models of structuring knowledge management processes in SE both within the technological domain and organisational layers. The discussion section establishes suitable KM methods and approaches for supporting SE job transformation. It identifies the main knowledge management integration practices, demonstrating how combining KM with AI-based innovations may change the SE knowledge flow, improving substantially SE activities like onboarding new team members, monitoring software documentation, version control, and error tracking. [ABSTRACT FROM AUTHOR]

The Covid-19 pandemic of 2020 is not the first such public health crisis we have faced, nor indeed the most lethal; however, it has occurred at the perfect time to foreground a number of key issues central to the role of AI in society at individual, national, and global levels. This paper will examine the use of AI-driven systems to respond to the current situation, arguing that it marks a limit case for the employment of new technologies (most notably pervasive telecommunication). It will focus on three main concerns: UTILITY: what might AI systems offer as tools for risk/harm mitigation in situations such as these? A pandemic is the perfect domain for Big Data analysis, but there is also huge potential for transnational coordination of research, logistics, and necessary manufacture. MORALITY: AI-supported contact tracking apps (as used in Singapore and Australia) enable rapid mapping of infection spread, and the possibility of identifying key vectors, but there is a vital debate to be had about surveillance, consent, and government control of citizens through the bulk collection of data. Any discussion of AI is always an ethical conversation. AUTHORITY: we have already seen a proliferation of misinformation concerning Covid-19 distributed online; much of this, it seems, comes from utterly unreliable sources, as deliberate acts of of Information Warfare by State actors. AI offers the potential to generate highly specific messages designed to influence their targets, and distribute them further and faster than at any time in history. 'Fake News' has become literally lethal; how can nations and individuals employ AI systems to inoculate themselves against highly infectious, harmful ideas? The paper discusses key components of a Code of Conduct for the use of AI balancing the need for effective and rapid threat mitigation with essential human rights. The British Prime Minister has quoted Cicero's 'Salus populi suprema lex esto' [the health of the people is the supreme law']; the severity of the current crisis must not blind us to the fact that the health of the body politic is a matter of morality as much as medicine. [ABSTRACT FROM AUTHOR]

As the research process, i.e. how researchers conduct research, may be disrupted by Artificial Intelligence (AI)-based tools, this research in progress stresses the need for research on the future role of researchers. Prior research on AI-based tools used in the research process, focuses primarily on technological development related to, for example, language recognition, text extraction, and paper summaries. Recently, scientific texts are generated by AI. In this research in progress, four sub-areas of interest are identified: Black-box dilemma. What part or parts of the research process, if any, can trustfully be replaced by AIbased tools? Quality. What is required for AI-based tools to become an integrated part of the research process? Benefits/limitations. What are the potential benefits and limitations with AI-based tools as an integrated part of the research process? Progress in use: What is the progress of the use and development of AI-based tools for research? Research design, potential contribution, and practical implications of this research are discussed. [ABSTRACT FROM AUTHOR]

Fiction is replete with tales of machine minds overthrowing their human creators. These archetypes are powerful, and durable, but they must be confronted and challenged if we are to truly address the real issues that the wholesale introduction of AI presents. This paper will argue that the problem lies not with AI in itself, but in its ability to act as a force multiplier for our own innately human biases and prejudices; as Safiya Noble and Caroline Criado Perez among others have shown, the underlying algorithms driving much of today's AI are based on entirely prejudiced assumptions, and build racism and sexism into the automated systems on which the modern world relies. As with so much within the cyber domain, the problem is not technological, but human, and it requires a human solution. What will be argued here is that greater use of AI is both inevitable and potentially hugely beneficial, but that it requires close examination of the underlying assumptions on which the fundamental programming of machine intelligences is/will be based. More than that, the paper will suggest that a truly successful future will lie in humans working with non-human intelligences, rather than in their exploitation. [ABSTRACT FROM AUTHOR]

There are growing interests and concerns regarding the wider application of Artificial Intelligence (AI) in all spheres of work and life including education. Computer systems with 'intelligence' are already performing a wide range of tasks commonly associated with humans. Conversations are taking place about how AI will reshape curriculum, teaching and assessment as well as its positive and negative impacts on education. Also, considerable uncertainty exists surrounding the roles of instructor and student in the impending AI regime. Scholars and professionals are apprehensive about whether an extensive involvement of AI in education will greatly eliminate the need for human-human interaction in teaching and learning. We believe that AI adoption is unavoidable, and it will certainly have major implications for education in the future, but our focus is on how to effectively blend AI into traditional education system for the benefit of teachers, students and the society. Nevertheless, there is a paucity of literature about how to integrate AI's unique capabilities with human capital to enhance teaching and improve student learning experience. To fill this gap, in this theoretical paper, we place more emphasis on an in-depth exploration of an optimal combination of human-human interaction and human-computer interaction in education. Accordingly, first, drawing from the socio cultural theory of education, we provide an analysis of education as a socio-cultural phenomenon and the inevitability of family, schools, teachers and peers in promoting learner autonomy and metacognitive awareness, which is followed by a review of the existing gaps in teaching and learning that are hindering us to achieve common academic and social goals relating to education such as subject knowledge, job skills, creativity, leadership, moral behaviour, discipline and self-esteem. We argue that a well-planned instructor-AI collaboration can contribute to high quality teaching and learning and hence minimise the gaps in academic and social outcomes relating to education. As a theoretical contribution, the paper presents a detailed framework for an effective instructor-AI collaboration in education in key dimensions of teaching and learning, namely curriculum design, instruction, assessment and feedback. [ABSTRACT FROM AUTHOR]

This paper discusses the feasibility and potential risks of artificial emotions. It is an era of worrying about the overtaking of artificial intelligence from a cognitive point of view, which is considered to be a human domain, and people are now trying to find out human nature with emotion, not reason. Recently, the task of infusing emotions into artificial intelligence robots is emerging as a new topic. First, let's take a look at the development of emotional robots and their main motivations, and why robots' emotions matter. In order to examine whether a robot possessing true emotions is possible, we do not define emotions a priori, but introduce some important roles that emotions play and propose criteria for giving emotions to certain objects. Against these criteria, true emotional robots are unlikely to become a reality in the near future. However, even before robots possessing emotions appear, unilateral emotional communication with robots with a certain degree of autonomy is potentially dangerous, and it is thought that it is good to prepare for it. [ABSTRACT FROM AUTHOR]

Digital technologies and the 'invisible hand' of digitalization, or digital transformation, have been a catalyst for the new industrial revolution manifested through creation of a digital economy - Economy 4.0. Some of the key tenets of traditional economic theory, such as scarcity, had been challenged by the attention-driven mechanics of the new economy so educational system faces a major reconfiguration too, metamorphosing to the outlines of Education 4.0, where not only students have to understand and deal with high technology, but the teaching staff often requires a re-training too, facing the technology that bids to transform the human cognitive process to the extent that hadn't been done since the invention of printing press. Due to these new rules, lifelong learning stops being a luxury and becomes a required necessity. When it comes to digital disruption in scientific disciplines, it's reasonable to say that marketing has been going through a very significant one ever since the advent of Internet. The education in marketing, on the other hand, still hasn't been able to properly adjust to its pace. This paper covers the history of academic opinion on marketing education, ever since it became a major scientific interest in the 1970s, all the way to the days of its digital disruption in the 2010s, which led to expansion of experiential learning, paradigm shift and alternative educational models built in order to keep up with the pace of technological progress. The coverage is focused on the most important research from the field, including key ideas regarding the curriculum development, as well as its critical flaws and shortcomings in regard to student training for the real-world problem-solving and market competency. Finally, the paper positions marketing education in context of digital economy's Education 4.0 and covers of-the-moment Artificial Intelligence (AI), such as ChatGPT, implementation in the educational practice; a practice where a sudden disruption led to the growing importance of human skills and foundational meta-skills, a priority for those seeking the future success. [ABSTRACT FROM AUTHOR]

This paper explores the dynamic interplay between cybersecurity, legislation, and SaaS platforms, focusing on the current landscape, potential future threats, and emerging legal challenges. SaaS providers, acting as custodians of considerable amounts of personal data, are significantly impacted by diverse legal frameworks such as the GDPR, CCPA, HIPAA, and PCI-DSS. These frameworks mandate stringent data protection and security measures. The paper further elucidates the sector-specific regulations and discusses the complex issue of cross-border data transfers, underscoring the need for adequate safeguards. This work examines how laws deal with cybersecurity threats and emphasizes the importance of complying with them to reduce these risks. It addresses challenges and conflicts that arise when SaaS and cybersecurity laws intersect, including issues related to data ownership and protection responsibilities. This paper makes suggestions to improve legal protections through international collaboration, adapting laws to keep up with technology, and ensuring transparency in data processing. It also explores potential future threats and legal challenges, such as cyber threats powered by AI, quantum computing, privacy paradoxes, and questions about data sovereignty. Therefore, the paper stresses the necessity of staying ahead of regulatory changes and fostering a comprehensive cybersecurity strategy that blends technology, people, processes, and legislation. [ABSTRACT FROM AUTHOR]

In this research in progress paper, we consider how two major trends drive digitalization. First, software product management focuses on fast and iterative development where users are involved in the design phase of products through product managers. Second, there is a push toward applying AI in knowledge domains. We show how these trends intensify the need to focus on relations between IS development and use. Through an interpretative case study of digitalization, drawing on ethnographic methods, we investigate key relations and how they compound into constellations of relations. We discuss key constellations of relations, how the data flow between constellations of relations functions, and how we can zoom in and out to understand relations--allowing for a reposition of IS development for AI, both theoretically and practically. [ABSTRACT FROM AUTHOR]

Since the dawn of evolutionary technological civilisation, analytics has promised to revolutionise healthcare and enable more efficient patient care delivery. However, after the applications of AI tools in healthcare, doctors and patients are no longer the sole players in the doctor-patient relationship. AI emerges as the third player, which creates unique opportunities in this relationship. By examining the impact of non-human actor-AI on the doctor-patient relationship and exploring the related concepts, such as human-AI augmentation and human-in-the-loop, valuable insights can be gained regarding the use of AI in healthcare. Following this background, based on a systematic literature review and the methodological approach of Lebovitz et al. (2022), this paper seeks to enhance the knowledge and expertise in healthcare by examining how AI tools shape and are shaped by the doctor-patient relationship when three players (AI, doctors, and patients) are present. [ABSTRACT FROM AUTHOR]

The public availability of sophisticated AI content generators based on large -scale language models achieved enormous media attention in recent months. AI content generators are expected to have a major impact on future information sy stems developments as well as private and business life. Particularly in the field of education, the question arises as to how these innovations in AI technology will impact teaching, learning, and examination. With a specific focus on examinations in the information systems di scipline, we show in this research-in-progress paper, based on an experimental field study, how a today’s AI content generator performs in solving a fundamental information systems exam. Based on our preliminary results, we found that the quality varies ac ross different exam question ty pes. With this research project, we offer start points and initial guidance on how educators can deal with the availability of AI content generators. [ABSTRACT FROM AUTHOR]

Rural SMEs are generally at a digital disadvantage due to their size and location. The addition of AI to many business processes has the potential to minimize the existing divide. However, without access to this technology and its responsible usage, Rural SMEs could be placed at a more significant disadvantage. To understand the current situation we conducted interviews with Rural SMEs and related stakeholders. This paper draws on Activity Theory to develop a holistic understanding of the influence AI is having on the business processes of rural SMEs. We also consider the role of AI in terms of the existing digital divide frameworks, as well as the newly proposed fourth wave that captures the novel forms of disadvantage AI can perpetuate. [ABSTRACT FROM AUTHOR]

A few years ago, I start asking myself how my profession (i.e. accountant) will change under the IT impact and how AI would affect humanity. I consider this article provides important answers for the accounting profession since last technologies are capturing new horizons and particularly, accounting is changing under the IT signature. This paper intends to emphasize the changes which accounting will support under the emergence of new technologies and how much AI marks accounting in this technological environment. After a careful exploration of relevant articles concerning this paradigm shift in accounting, literature asks for further and deeper investigation on this topic. Moreover, ICAEW (2018) asks for a better understanding of how AI can be part of solving accounting and business issues. This article aims to respond to this crucial and necessary question. I choose to interview the CEOs of small IT companies who have good knowledge of AI. The research methodology applied finds support in the qualitative research method in order to respond to this inquiry. Additionally, future directions about how AI through IT is implemented in accounting as an important key in the future revolution of financial area are revealed. [ABSTRACT FROM AUTHOR]

Recent problems and projected future challenges require an increased integration of digital technologies and smart manufacturing methods in addressing issues. In this regard, industry 4.0, which combines information collection, storage, and analysis, has enabled intermachine communication, flexibility, and operational efficiency at a reduced cost. Although this technology comes with increasing opportunities in various sectors, there are still some limitations to its full adoption. Therefore, this paper focuses on the present manufacturing technologies associated with industry 4.0 to highlight the opportunities they present, challenges encountered in their implementation and the readiness of industries and small-scale businesses towards its adoption. Unfortunately, no paper or research work has discussed and reviewed these issues of Industry 4.0 and the associated technologies in an integrated way. Therefore, this paper makes an original contribution to the literature on Industry 4.0. [ABSTRACT FROM AUTHOR]

This paper explores the complex interaction between AI and customs procedures, aiming to uncover the legal ramifications associated with the integration of AI technologies in this field. With the rapid advancement of AI, customs authorities worldwide are increasingly adopting automated systems to improve the efficiency, accuracy, and security of cross-border trade operations. However, as AI systems take on significant roles in decision-making processes traditionally overseen by humans, concerns regarding legality, accountability, and transparency become prominent. Through a thorough examination of existing legal frameworks, international agreements, and relevant case law related to AI implementation in customs procedures, this research conducts a comprehensive analysis. It seeks to shed light on the evolving legal landscape surrounding AI in customs operations through a comparative study of various regulatory approaches and interpretations. [ABSTRACT FROM AUTHOR]

Technological progress has had both benefits and negative effects over time. The road to civilization was paved by scientists through hard work. Today we enjoy the results produced over a long period of time when civilizations and empires succeeded each other. Man has always sought to lead a better life, to explore territories and seek new opportunities. The institutionalisation of people's power in the form of the state led to some limitations on the freedom of free movement. The establishment of states led to the emergence of borders. This paper seeks to analyse how today's most advanced advancement, AI, can have both beneficial and negative contributions to society. In a world where basic human rights are no longer a novelty, regulation of new technologies has become a necessity. The lack of clear regulations leads to abuses by the state or its members. Ethics is a basic pillar in any field of activity. Scientific discoveries led to economic progress. Competitiveness has bred efficiency. Even if in a first stage there are systemic changes in certain economic branches, with the possibility of technology replacing certain activities carried out until then by man, the economic prosperity of the last two centuries was only possible through a mass development of production. The political factor, through its representative bodies, has the mission of ensuring a balance between technological development and society as a whole. The balance is ensured through regulation, legislation. Technologies must have a positive impact on the democratic world. This article examines new technologies in the context of refugees. Displacement of populations is not new, but in correlation with new technologies and fundamental human rights it acquires a new dimension. [ABSTRACT FROM AUTHOR]

The concept of „automated decision making" (ADM) is currently a key vector reshaping industries in the era of technology-based decision making, and the use of artificial intelligence (AI) in this process is a hot topic worldwide with the adoption of generative AI tools like ChatGPT. ADM enables companies to use technology for tasks that were not long ago the domain of human judgment. AI is essential in financial services, such as credit worthiness assessment, automated investment advice (often called robo-advice) or insurance. The regulation of activities related to ADM is contained in various acts and regulations, including the Sale of Goods Directive 2019/771, the Digital Contracts Directives 2019/770 and the EU General Regulation on Data Protection. However, these directives do not contain special rules for new technologies such as Artificial Intelligence (AI). Although recently, the EU has moved forward with regulations on product liability laws affecting digital products and services, with the EU Data Act, the EU Cyber Resilience Act and the highly publicized EU AI Act - regulations with a transition period of two years for compliance, the speed with which in practice the ADM tools are developed and trained make the legislative efforts slow and incomprehensible. In light of this issue, this article explores the relationship between AI, ADM and discusses whether existing EU consumer law is equipped to deal with situations where AI systems are either used for internal purposes by companies or offered to consumers as the main subject of the contract. The paper will reveal a number of gaps in current EU consumer law and briefly discuss future legislation. This article also reviews the efficiency of key EU consumer law directives for the conclusion of contracts with consumers through the use of AI, with recommendations for clarifications and additions to improve the use of ADM. [ABSTRACT FROM AUTHOR]

In this paper, although photovoltaic power generation has recently shown the most remarkable growth in the field of renewable energy worldwide, defects may occur if power outages or manufacturing facilities remain despite the increase in demand and demand for photovoltaic power generation. A machine learning algorithm that predicts the optimal development to solve these problems was obtained through experiments. By implementing the algorithm in the system, it will be able to contribute to reducing operating costs and popularizing it. Neural network, SVM, and deep learning are used as prediction algorithms, and the optimal algorithm is selected by using the root mean square error (RMSE), which is the most used when identifying prediction errors. We propose a predictive model whose prediction rate is expanded by changing the algorithm structure and modifying constants. Then, a defect detection system is developed by applying the predicted results to the domestic regional data. [ABSTRACT FROM AUTHOR]

A daily use of Artificial Intelligence (AI) is becoming a fact in many fields today, and two of them are psychology and social work. At the same time as AI systems are used for predicting psychological treatments and for decisions in social welfare, higher education has few AI courses for these professions. Moreover, there are several examples in these fields where AI can make unethical decisions that need to be corrected by humans. To better understand the possibilities and challenges of AI in psychology and social work, professional users of AI services need a tailored education on how the underlying technology works. The aim of this paper is to present a project concept for the design and evaluation of a novel course in AI for professional development in psychology and social work. For the design and development of the course the guiding research question should be: What are the strengths and challenges with contemporary AI techniques regarding prediction, adaptivity and decision systems? The suggested AI course should be given as a technology enhanced online training to enable the idea of anytime and anywhere for full-time working participants. Course content and activities are divided into the four separate sections of: 1) The history of AI structured around the 'Three waves of AI', with o focus on the current third wave. 2) A section with a focus on AI techniques for prediction and adaptivity. Underlying techniques such as machine learning, neural networks, and deep learning will be conceptually described and discussed, but not on a detailed level. 3) An elaborated discussion on the relevance, usefulness and trust, and the at the difference between AI-based decision systems and AI-based decision support systems. 4) Finally, the fourth section should comprise the ethical aspects of AI, and discuss transparency and Explainable AI. An innovative approach of the project is to use a neuroscientific assessment of the education to understand how the education changes brain function relevant to evaluate AI based decision. This should be complemented with a qualitative evaluation based on semi-structured interviews. [ABSTRACT FROM AUTHOR]

Cheating in computer games can cause legit players to feel deprived, lose their interest and in time leave the game - which further leads to the decrease of profit in the gaming industry. Avoiding such a scenario is the main focus of research papers dealing with game cheating and cheat detection mechanisms within computer games, where there is a seemingly simple question to answer - is this player a legit human player, or an artificial bot? Most of the research is trying to identify patterns that could give away the presence of the bot, and in the same time, research is being done on building the bots with human-like behaviours which might deceive such mechanisms. In this paper, we present an active bot detection method implemented within a "security bot" - an artificial player which is infiltrated within the game and is able to identify suspicious game players, approach them, and perform a form of the Turing test on them, in order to identify possible cheating bots which have successfully deceived all the existing passive detection methods. [ABSTRACT FROM AUTHOR]

The enormous transformational power of AI and its radical and comprehensive impact find application in the field of natural resource management and ecosystem maintenance in protected areas. In this paper, we analyze the possibilities and challenges of the application of AI in protected areas, especially from the aspect of supporting the management of natural resources and achieving sustainability of ecosystems, which are of great importance for local socioeconomic development based on ecotourism. [ABSTRACT FROM AUTHOR]

This paper provides empirical concerns about post-hoc explanations of black-box ML models, one of the major trends in AI explainability (XAI), by showing its lack of interpretability and societal consequences. Using a representative consumer panel to test our assumptions, we report three main findings. First, we show that post-hoc explanations of black-box model tend to give partial and biased information on the underlying mechanism of the algorithm and can be subject to manipulation or information withholding by diverting users' attention. Secondly, we show the importance of tested behavioral indicators, in addition to self-reported perceived indicators, to provide a more comprehensive view of the dimensions of interpretability. This paper contributes to shedding new light on the actual theoretical debate between intrinsically transparent AI models and post-hoc explanations of black-box complex models - a debate which is likely to play a highly influential role in the future development and operationalization of AI systems. [ABSTRACT FROM AUTHOR]

Ethics of Artificial Intelligence (AI) in recent times has captured the attention of practitioners and researchers alike. Recent events such as Chinese Scientist, He Jiankui proudly accepting to editing genes of twin girls using CRISPR technology has raised questions on the ethical use of AI. While most researchers argue the need for machines to be ethical, there is an alternative line of argument that most humans have some degree of bias and therefore the data fed into machines and algorithms generated reflect these biases in AI decision making. Through this conceptual working paper, we posit our research question, i.e., how can we minimize the impact of ethical issues in AI? As the scope of this working paper is short, our aim here is to highlight some of the existing ethical concerns in AI decision making and provide some potential solutions to reduce the impact of these concerns. In particular, we share some real-world examples that demonstrate the ethical concerns in decision making and suggest how could these ethical concerns be avoided in the future. In saying that, the reality of the matter is good and evil have always co-existed together since the beginning of time. Therefore, we take a pragmatic approach by acknowledging the fact that we understand ethics in AI is a myth, which may never be a reality. As ethics falls into a grey area, a decision for one person may be ethical however the other person may feel it as unethical and therefore we argue that instead of obsessing about making AI ethical, the first step should be to address the existing biases in humans who are at the forefront of developing AI i.e. the coders, the software developers, and the computer scientists. We hope that this paper will benefit both the researchers and practitioners to consciously start exploring and delving deeper into understanding ways to reduce bias in AI decision making. [ABSTRACT FROM AUTHOR]

The need for a systematic approach to work with artificial intelligence (AI) is current and rapidly growing. It is important that Information Systems researchers get ahead of public sentiment and be able to provide proactive commentary about the current state-of-the-art, as well as solutions for future systems. One critical question is how can we ensure value alignment between AI and human values through AI operations from design to use? For the purposes of this discussion, we adopt the phenomenological theories of material values and technological mediation to be that beginning step. In this paper, we firstly analyze the AI phenomenon from selected resources from the top IS research outlets (basket of 8 journals and 5 AI journals in IS). Secondly, we briefly present what are material values and technological mediation and reflect on the AI value alignment principle through the lenses of these theories. Supported by these new understandings and reflections, we propose to build a common principle of human values to understand the AI value alignment principle through phenomenological theories. The paper contributes the unique aspect of material values to the discourse within current AI research. [ABSTRACT FROM AUTHOR]

The article focuses on exploring the impact of Artificial Intelligence (AI) service failure on consumer perceptions, forgiveness, and rebuy intention in the context of avatars with single or multi-interaction modalities. The research employs the expectation disconfirmation model and presents findings from five experiments, revealing that AI's service failure adversely affects consumer perceptions, and interactions with various modalities yield different experiences.