We study how artificial intelligence (AI) affects firms' incentives to pursue incremental versus radical knowledge recombinations. We develop a model of recombinant innovation embedded in a Schumpeterian quality-ladder framework, in which innovation arises from recombining ideas across varying distances in a knowledge space. R&D consists of multiple tasks, a fraction of which can be performed by AI. AI facilitates access to distant knowledge domains, but at the same time it also increases the aggregate rate of creative destruction, shortening the monopoly duration that rewards radical innovations. Moreover, excessive reliance on AI may reduce the originality of research and lead to duplication of research efforts. We obtain three main results. First, higher AI productivity encourages more distant recombinations, if the direct facilitation effect is stronger than the indirect effect due to intensified competition from rivals. Second, the effect of increasing the share of AI-automated R&D tasks is non-monotonic: firms initially target more radical innovations, but beyond a threshold of human-AI complementarity, they shift the focus toward incremental innovations. Third, in the limiting case of full automation, the model predicts that optimal recombination distance collapses to zero, suggesting that fully AI-driven research would undermine the very knowledge creation that it seeks to accelerate.
Inovasi teknologi dalam sektor pelayanan publik saat ini menjadi kebutuhan yang sangat mendesak, terutama dalam upaya meningkatkan kualitas layanan kepada masyarakat. Salah satu bentuk inovasi tersebut diwujudkan oleh PT PLN melalui peluncuran aplikasi PLN Mobile. Aplikasi ini bertujuan untuk mempermudah masyarakat dalam mengakses berbagai layanan kelistrikan, mulai dari pendaftaran sambungan baru hingga penyampaian keluhan secara daring. Namun, meskipun aplikasi ini cukup bermanfaat, masih diperlukan sosialisasi dan edukasi agar masyarakat, khususnya yang belum akrab dengan teknologi, dapat memanfaatkannya secara optimal. Pengabdian kepada masyarakat ini dilakukan dengan tujuan utama, pertama, untuk memberikan edukasi mengenai penggunaan aplikasi PLN Mobile secara tepat dan efektif. Kedua, untuk mengedukasi masyarakat bahwa penggunaan aplikasi ini juga mengandung nilai-nilai Islam atau Islamic Values dalam praktik pelayanan publik. Metode yang digunakan dalam kegiatan ini adalah pendekatan kolaboratif antara institusi pendidikan, yakni UIN Kiai Haji Achmad Siddiq Jember, dengan PT PLN Unit Layanan Banyuwangi. Kolaborasi ini memperkuat sinergi antara dunia akademik dan praktisi dalam memberikan pemahaman kepada masyarakat. Hasil dari pengabdian menunjukkan bahwa aplikasi PLN Mobile mampu menjadi solusi pelayanan yang modern dan efisien, walaupun tantangan teknis seperti koneksi internet masih dirasakan oleh sebagian masyarakat. Lebih dari itu, aplikasi ini mampu menginternalisasi nilai-nilai Islam dalam pelayanan publik, seperti nilai nubuwwah yang mencakup siddiq (jujur), amanah (dapat dipercaya), tabligh (komunikatif), dan fathonah (cerdas dan inovatif).
Jesús Gerardo Ávila-Sánchez, Manuel de Jesús López-Martínez, Valeria Maeda-Gutiérrez
et al.
The Cutting Development Chamber (CDC) design is presented as an innovative solution to crucial human challenges, such as food and plant medicinal production. Unlike conventional propagation chambers, the CDC is a much more comprehensive research tool, specifically designed to optimize plant reproduction from cuttings. It maintains precise control over humidity, temperature, and lighting, which are essential parameters for plant development, thus maximizing the success rate, even in difficult-to-propagate species. Its modular design is one of its main strengths, allowing users to adapt the chamber to their specific needs, whether for research studies or for larger-scale propagation. The most distinctive feature of this chamber is its ability to collect detailed, labeled data, such as images of plant growth and environmental parameters that can be used in artificial intelligence tasks, which differentiate it from chambers that are solely used for propagation. A study that validated and calibrated the chamber design using cuttings of various species demonstrated its effectiveness through descriptive statistics, confirming that CDC is a powerful tool for research and optimization of plant growth. In validation experiments (<i>Aloysia citrodora</i> and <i>Stevia rebaudiana</i>), the system generated 6579 labeled images and 67,919 environmental records, providing a robust dataset that confirmed stable control of temperature and humidity while documenting cutting development.
Engineering machinery, tools, and implements, Technological innovations. Automation
The Innovation Delusion: How Our Obsession with the New Has Disrupted the Work That Matters Most (2020), by Lee Vinsel and Andrew L. Russell, presents a blistering critique of the contemporary ideology of innovation, exposing what the authors call «innovation-speak» – a hegemonic discourse that glorifies disruptive change and marginalises the essential work of maintenance.
The Innovation Delusion, by Lee Vinsel and Andrew L. Russell, published not many years ago (2020), is among the scholar books one must read, especially for younger generations and policymakers around the world. Many years ago, Steven Shapin (1989) unearthed the role of the technician in modern science. Innovation Delusion does the same for hidden activities in innovation — i.e., activities related to technology and engineering. Maintenance, upkeep and care is the motto behind Vinsel and Russell’s book.
The implementation of Artificial Intelligence (AI) in household environments, especially in the form of proactive autonomous agents, brings about possibilities of comfort and attention as well as it comes with intra or extramural ethical challenges. This article analyzes agentic AI and its applications, focusing on its move from reactive to proactive autonomy, privacy, fairness and user control. We review responsible innovation frameworks, human-centered design principles, and governance practices to distill practical guidance for ethical smart home systems. Vulnerable user groups such as elderly individuals, children, and neurodivergent who face higher risks of surveillance, bias, and privacy risks were studied in detail in context of Agentic AI. Design imperatives are highlighted such as tailored explainability, granular consent mechanisms, and robust override controls, supported by participatory and inclusive methodologies. It was also explored how data-driven insights, including social media analysis via Natural Language Processing(NLP), can inform specific user needs and ethical concerns. This survey aims to provide both a conceptual foundation and suggestions for developing transparent, inclusive, and trustworthy agentic AI in household automation.
Maaz Qureshi, Mohammad Omid Bagheri, Abdelrahman Elbadrawy
et al.
Accurate characterization of modern on-chip antennas remains challenging, as current probe-station techniques offer limited angular coverage, rely on bespoke hardware, and require frequent manual alignment. This research introduces RAPTAR (Radiation Pattern Acquisition through Robotic Automation), a portable, state-of-the-art, and autonomous system based on collaborative robotics. RAPTAR enables 3D radiation-pattern measurement of integrated radar modules without dedicated anechoic facilities. The system is designed to address the challenges of testing radar modules mounted in diverse real-world configurations, including vehicles, UAVs, AR/VR headsets, and biomedical devices, where traditional measurement setups are impractical. A 7-degree-of-freedom Franka cobot holds the receiver probe and performs collision-free manipulation across a hemispherical spatial domain, guided by real-time motion planning and calibration accuracy with RMS error below 0.9 mm. The system achieves an angular resolution upto 2.5 degree and integrates seamlessly with RF instrumentation for near- and far-field power measurements. Experimental scans of a 60 GHz radar module show a mean absolute error of less than 2 dB compared to full-wave electromagnetic simulations ground truth. Benchmarking against baseline method demonstrates 36.5% lower mean absolute error, highlighting RAPTAR accuracy and repeatability.
Henry Beuster, Kevin Tebbe, Thomas Doebbert
et al.
In the past few years, there has been a growing significance of interactions between human workers and automated systems throughout the factory floor. Wherever static or mobile robots, such as automated guided vehicles, operate autonomously, a protected environment for personnel and machines must be provided by, e.g., safe, deterministic and low-latency technologies. Another trend in this area is the increased use of wireless communication, offering a high flexibility, modularity, and reduced installation and maintenance efforts. This work presents a testbed implementation that integrates a wireless framework, employing IO-Link Wireless (IOLW) and a private 5G cellular network, to orchestrate a complete example process from sensors and actuators up into the edge, represented by a programmable logic controller (PLC). Latency assessments identify the systems cycle time as well as opportunities for improvement. A worst-case estimation shows the attainable safety function response time for practical applications in the context of functional safety.
Hamied Nabizada, Tom Jeleniewski, Felix Gehlhoff
et al.
Manually creating Planning Domain Definition Language (PDDL) descriptions is difficult, error-prone, and requires extensive expert knowledge. However, this knowledge is already embedded in engineering models and can be reused. Therefore, this contribution presents a comprehensive workflow for the automated generation of PDDL descriptions from integrated system and product models. The proposed workflow leverages Model-Based Systems Engineering (MBSE) to organize and manage system and product information, translating it automatically into PDDL syntax for planning purposes. By connecting system and product models with planning aspects, it ensures that changes in these models are quickly reflected in updated PDDL descriptions, facilitating efficient and adaptable planning processes. The workflow is validated within a use case from aircraft assembly.
This study explores the intersection of technological innovation and environmental sustainability in the context of Bitcoin mining. With Bitcoin's growing adoption, concerns surrounding the energy consumption and environmental impact of mining activities have intensified. The study examines the core process of Bitcoin mining, focusing on its energy-intensive proof-of-work mechanism, and provides a detailed analysis of its ecological footprint, especially in terms of carbon emissions and electronic waste. Various models estimate that Bitcoin's energy consumption rivals that of entire nations, highlighting serious sustainability concerns. To address these issues, the paper unearths potential technological innovations, such as energy-efficient mining hardware and the integration of renewable energy sources, as viable strategies to reduce environmental impact. Additionally, the study reviews current sustainability initiatives, including efforts to lower carbon footprints and manage electronic waste effectively. Regulatory developments and market-based approaches are also discussed as possible pathways to mitigate the environmental harm associated with Bitcoin mining. Ultimately, the paper advocates for a balanced approach that fosters technological innovation while promoting environmental responsibility, suggesting that, with appropriate policy and technological interventions, Bitcoin mining can evolve to be both innovative and sustainable.
SK Golam Saroar, Waseefa Ahmed, Elmira Onagh
et al.
GitHub, renowned for facilitating collaborative code version control and software production in software teams, expanded its services in 2017 by introducing GitHub Marketplace. This online platform hosts automation tools to assist developers with the production of their GitHub-hosted projects, and it has become a valuable source of information on the tools used in the Open Source Software (OSS) community. In this exploratory study, we introduce GitHub Marketplace as a software marketplace by comprehensively exploring the platform's characteristics, features, and policies and identifying common themes in production automation. Further, we explore popular tools among practitioners and researchers and highlight disparities in the approach to these tools between industry and academia. We adopted the conceptual framework of software app stores from previous studies to examine 8,318 automated production tools (440 Apps and 7,878 Actions) across 32 categories on GitHub Marketplace. We explored and described the policies of this marketplace as a unique platform where developers share production tools for the use of other developers. Furthermore, we systematically mapped 515 research papers published from 2000 to 2021 and compared open-source academic production tools with those available in the marketplace. We found that although some of the automation topics in literature are widely used in practice, they have yet to align with the state of practice for automated production. We discovered that practitioners often use automation tools for tasks like "Continuous Integration" and "Utilities," while researchers tend to focus more on "Code Quality" and "Testing". Our study illuminates the landscape of open-source tools for automation production in industry and research.
Technological innovations in energy and information technology (IT) are transforming global societies, driving advancements in efficiency, sustainability, and connectivity. From renewable energy systems to smart grids and blockchain-based energy trading platforms, these innovations are reshaping how energy is produced, consumed, and distributed. Likewise, the integration of information technology into everyday life is revolutionizing communication, commerce, healthcare, and governance. This article explores the role of energy and IT innovations in shaping modern society, with a focus on key developments in renewable energy, energy storage, smart grids, and IT applications such as artificial intelligence (AI), the Internet of Things (IoT), and blockchain. Through examining these technological trends, we discuss their potential societal impacts and explore how they are enabling new models of governance, business, and personal interaction.
Due to species barriers and poor adaptability to new host environments, few pathogens cause global pandemics. But, SARS-CoV-2 is one exception with its high transmissivity and delayed onset of symptoms. Fortunately, the world was able to tap on the technologies especially the maturing RT-qPCR designed to combat SARS to launch an initial offensive on SARS-CoV-2. These initial efforts may have bought time for scientists to develop more refined diagnostic tests that specifically target SARS-CoV-2. This article describes the effort put forth by the biotech industry and academia in Singapore to develop diagnostic tests that aid the early detection of positive cases, and thereby help contain the virus. Direct tests such as RT-qPCR and antigen rapid test profile the virus nucleic acid and surface proteins, respectively. But, of equal importance in case detection and treatment is serological tests that measure the relative abundance of IgM and IgG which is indicative of infection phase and quality of immune response in positive cases. Other tests such as isothermal amplification, CRISPR-based diagnostics and breath tests are also in development or at initial field deployment, and would undoubtedly provide valuable use experience useful for the development of molecular assays to detect and combat the next pathogen of global concern.
Senni Kirjavainen, Simo Lahdenne, Tua A. Björklund
Prototyping is a core activity in developing new products, processes, and organisations alike. This paper describes the prototyping activities of 31 engineering design professionals in a high-technology industrial company, examining the distribution of different types of activities across different phases of development based on thematic interviews. Examining 62 prototyping and testing pathways, we found that most prototyping paths started with the practitioners’ own activities, which was also more likely to lead to paths with more prototyping steps than if the first prototyping activity took place with a stakeholder. Overall, the paths were short, indicating a lack of iteration. Both internal and external stakeholders were involved in collaborative prototyping. This collaboration was enabled by personal and unit level relationships, and different stakeholders were involved in different phases of development. Taken together, our results suggest that practitioner attention in prototyping may focus on latter development phases and demonstrate less iteration than what literature might suggest, with opportunities for prototyping highly dependent on personal networks in the high-technology context in the absence of flexible prototyping budgets.
Kimberly Do, Rock Yuren Pang, Jiachen Jiang
et al.
Computer science research has led to many breakthrough innovations but has also been scrutinized for enabling technology that has negative, unintended consequences for society. Given the increasing discussions of ethics in the news and among researchers, we interviewed 20 researchers in various CS sub-disciplines to identify whether and how they consider potential unintended consequences of their research innovations. We show that considering unintended consequences is generally seen as important but rarely practiced. Principal barriers are a lack of formal process and strategy as well as the academic practice that prioritizes fast progress and publications. Drawing on these findings, we discuss approaches to support researchers in routinely considering unintended consequences, from bringing diverse perspectives through community participation to increasing incentives to investigate potential consequences. We intend for our work to pave the way for routine explorations of the societal implications of technological innovations before, during, and after the research process.
Blockchain technology is recognised as a digital tool that contributes to increasing the competitiveness of a business organisation, and it is most often applied in the financial sector and supply chains. The technology is widely used in developed countries, but it is also gradually entering developing economies. Attention to technology is provoked under the influence of factors determining innovation development and penetration into the entrepreneurial ecosystem. Some of them are psychological, the others are economical, but in general, they influence the management decision-making to use the technology in the enterprises. The primary purpose of the research is to reveal and group the factors provoking the implementation of blockchain technology in Bulgarian companies. In order to collect the necessary data, an empirical study of the Bulgarian entrepreneurial ecosystem was conducted using a survey method. A factor analysis of the two groups of reasons motivating and limiting the application of blockchain technology was performed with a view to uncovering the hidden factors influencing its implementation in organisations. A regression analysis was then performed to answer the question of which factors most affect the interest in implementing BCT in the business organisation to increase their competitiveness in the supply chain. The research data can be used as a working framework for implementing decentralised software applications in companies that are not informed about the pros and cons of blockchain technology but are looking for a position in the global digitised world.
Despite the fact that population ageing in the European Union is in full swing, and policy makers are pushing for exdenting of working lives, there is a group of older people, whose employment potential in labor market ends up dormant. The phenomenon of early retirement is worthy of a deeper research from the point of view of human resources management, as employers facing issues of digital economy often lose a skilled workforce and labor market is depleted of the potential of this group. The article is focused on the research of three factors in relation to the desire to retire early: "job satisfaction", "job physical demands" and "afraid health limits ability to work before regular retirement in job". The influence of selected factors on the desire of workers to retire early is specified through quantitative analysis of data from the SHARE - Survey of Health, Aging and Retirement in Europe. Chi-squared test of independence, Cramér`s V for dependence tightness and standardized (adjusted) Pearson residuals are used for analyzes. Results show the strongest intensity of dependence in relation to the desire to retire early with the job satisfaction factor. There is a weak dependence tightness in factors of the job physical demands and the individuals` health limits within professional performance. The analysis shows that it is very important that employers try to make their employees satisfied with job, because the consequences of such an effort are reflected in the employees` decision making whether to stay in job or to leave labor market through early retirement.