This book reports on theoretical and practical analyses of the ethical challenges connected to driving automation. It also aims at discussing issues that have arisen from the European Commission 2020 report “Ethics of Connected and Automated Vehicles. Recommendations on Road Safety, Privacy, Fairness, Explainability and Responsibility”. Gathering contributions by philosophers, social scientists, mechanical engineers, and UI designers, the book discusses key ethical concerns relating to responsibility and personal autonomy, privacy, safety, and cybersecurity, as well as explainability and human-machine (...) interaction. On the one hand, it examines these issues from a theoretical, normative point of view. On the other hand, it proposes practical strategies to face the most urgent ethical problems, showing how the integration of ethics and technology can be achieved through design practices. All in all, this book fosters a multidisciplinary approach where philosophy, ethics, and engineering are integrated, rather than just juxtaposed. It is meant to inform and inspire an audience of philosophers of technology, ethicists, engineers, developers, manufacturers, and regulators, among other interested readers. (shrink)

In response to the many social impacts of automated mobility, in September 2020 the European Commission published Ethics of Connected and Automated Vehicles, a report in which recommendations on road safety, privacy, fairness, explainability, and responsibility are drawn from a set of eight overarching principles. This paper presents the results of an interdisciplinary research where philosophers and engineers joined efforts to operationalize the guidelines advanced in the report. To this aim, we endorse a function-based working approach to (...) support the implementation of values and recommendations into the design of automated vehicle technologies. Based on this, we develop methodological tools to tackle issues related to personal autonomy, explainability, and privacy as domains that most urgently require fine-grained guidance due to the associated ethical risks. Even though each tool still requires further inquiry, we believe that our work might already prove the productivity of the function-based approach and foster its adoption in the CAV scientific community. (shrink)

This book explores how robotics and artificial intelligence can enhance human lives but also have unsettling “dark sides.” It examines expanding forms of negativity and anxiety about robots, AI, and autonomous vehicles as our human environments are reengineered for intelligent military and security systems and for optimal workplace and domestic operations. It focuses on the impacts of initiatives to make robot interactions more humanlike and less creepy. It analyzes the emerging resistances against these entities in the wake of omnipresent (...) AI applications. It unpacks efforts by developers to have ethical and social influences on robotics and AI, and confronts the AI hype that is designed to shield the entities from criticism. The book draws from science fiction, dramaturgical, ethical, and legal literatures as well as current research agendas of corporations. Engineers, implementers, and researchers have often encountered users' fears and aggressive actions against intelligent entities, especially in the wake of deaths of humans by robots and autonomous vehicles. The book is an invaluable resource for developers and researchers in the field, as well as curious readers who want to play proactive roles in shaping future technologies. (shrink)

This short paper offers a preliminary inquiry into the impacts of driving automation on personal autonomy. Personal autonomy is a key ethical value in western culture, and one that buttresses fundamental components of the moral life such as the exercise of responsible behaviour and the full enjoyment of human dignity. Driving automation simultaneously enhances and constrains it in significant ways. Hence, its moral profile with reference to the value of personal autonomy is uncertain. Ethical analysis shows that such uncertainty is (...) due not just to the complexity of the technology, but also to the multifaceted normative profile of personal autonomy, which offers reasons to support both conditional and full driving automation. The paper sheds light on this duplicity, underlines the challenges this poses to the ethics of driving automation, and advocates for further research aimed at providing practitioners with more fine-grained guidelines on such a delicate issue. (shrink)

This short paper offers a preliminary inquiry into the impacts of driving automation on personal autonomy. Personal autonomy is a key ethical value in western culture, and one that buttresses fundamental components of the moral life such as the exercise of responsible behaviour and the full enjoyment of human dignity. Driving automation simultaneously enhances and constrains it in significant ways. Hence, its moral profile with reference to the value of personal autonomy is uncertain. Ethical analysis shows that such uncertainty is (...) due not just to the complexity of the technology, but also to the multifaceted normative profile of personal autonomy, which offers reasons to support both conditional and full driving automation. The paper sheds light on this duplicity, underlines the challenges this poses to the ethics of driving automation, and advocates for further research aimed at providing practitioners with more fine-grained guidelines on such a delicate issue. (shrink)

Accident occur as public do not follow the traffic rules, like not maintaining a proper braking distance between two vehicles, they also fail to follow the traffic signals when it is ‘RED’, also due to the fast life everyone is in a hurry of reaching the destination in time. In this paper, propose system implementing an IOT based Vehicle Tracking, Accident Detection, Accident Avoidance, Drunk Driver Detection and Fire Detection System. This system using Vibration sensor, Ultrasonic sensor, Alcohol Sensor, (...) Smoke Sensor, Web camera, GPS, Arduino Microcontroller, Android App. Our application focus on to providing them more convenience with vehicle safety. It provides Real-time vehicle location information also integrated Google Maps in the application. (shrink)

This book offers a systematic and thorough philosophical analysis of the ways in which driving automation crosses path with ethical values. Upon introducing the different forms of driving automation and examining their relation to human autonomy, it provides readers with in-depth reflections on safety, privacy, moral judgment, control, responsibility, sustainability, and other ethical issues. Driving is undoubtedly a moral activity as a human act. Transferring it to artificial agents such as connected and automated vehicles necessarily raises many philosophical (...) questions. When driving is automated, what happens to its ethical dimensions? Could artificial agents accomplish ethical objectives on our behalf, take moral decisions in our place, and drive us into a more ethical transportation future? In doing so, would they be “moral” as we are or in a way that is similar to, but also remarkably different from, our own? And what role is yet to be played by human responsibility and commitment? The book addresses these questions with the aim of stimulating an interdisciplinary dialogue between different stakeholders. They include automotive engineers, computer scientists, and moral philosophers, as well as industry representatives, policymakers, regulators, transportation experts, and the general public. Indeed, connected and automated vehicles will not take the high road for us . We must drive them there. (shrink)

Automated vehicles promise much in the way of both economic boons and increased personal safety. For better or worse, the effects of automating personal vehicles will not be felt for some time. In contrast, the effects of automated work vehicles, like semi-trucks, will be felt much sooner—within the next decade. The costs and benefits of automation will not be distributed evenly; while most of us will be positively affected by the lower prices overall, those losing (...) their livelihoods to the automated semi-trucks and other similar work vehicles will be much worse off. This sets up a classic distributive justice problem: how do we balance the harms and benefits of automation? In this paper, the authors recommend work alternatives: policies that the government would enact in order to ensure that each person could live a decent life even if one could not work, especially for reasons like having one’s job automated. After arguing for this position, we propose some policy guidelines. (shrink)

The present paper aims at contributing to the ethical debate on the impacts of artificial intelligence (AI) systems on human autonomy. More specifically, it intends to offer a clearer understanding of the design challenges to the effort of aligning driving automation technologies to this ethical value. After introducing the discussion on the ambiguous impacts that AI systems exert on human autonomy, the analysis zooms in on how the problem has been discussed in the literature on connected and automated (...) class='Hi'>vehicles (CAVs). On this basis, it is claimed that the issue has been mainly tackled on a fairly general level, and mostly with reference to the controversial issue of crash-optimization algorithms, so that only limited design insights have been drawn. However, integrating ethical analysis and design practices is critical to pursue the implementation of such an important ethical value into CAV technologies. To this aim, it is argued, a more applied approach targeted at examining the impacts on human autonomy of current CAV functions should also be explored. As an example of the intricacy of this task, the case of automated route planning is discussed in some detail. (shrink)

This work has been designed to develop an a dynamic road signal based on an emergency with density. The sync signal automatically switches to detecting traffic density at the intersection. Traffic congestion is a serious problem in many large cities around the world and has become a nightmare for travelers in these cities. The conventional traffic light system is based on the concept of fixed time assigned to each side of the join that cannot be varied by varying traffic density. (...) The tie times assigned are fixed. But in an emergency, emergency timings change according to the distance and depth of the traffic. At the time the emergency vehicle is read by the receiver it will execute the management of the traffic light. These projects are infrared proximity sensors in the sightline configuration through the load to detect the traffic light density. The vehicle density is measured in several sectors based on the times assigned as a result. Every crossing of the emergency vehicle logs the data's to the cloud. This log signal would help with the destination acknowledgment. This synchronization will greatly reduce traffic jam. -/- . (shrink)

This project aims to control the speed and direction of a DC motor in four quadrants: clockwise, counterclockwise, forward braking, and reverse braking. An H-bridge motor drive IC is used to switch the motor’s polarity based on user inputs via four control switches. A slide switch enables alternative directional control. A 555 timer generates PWM pulses for speed regulation, while relays manage polarity changes and braking. In regenerative braking, the motor generates reverse Ftorque for instant stopping. The four-quadrant control is (...) achieved by varying the duty cycle of the PWM signal and switching polarity using the H-bridge IC. The paper provides an overview of DC motor operation, explaining key components and working principles. It discusses the importance of four-quadrant operation, including motoring (forward/reverse) and braking (regenerative/plugging). Various control strategies such as armature voltage control and field flux control are examined for their efficiency. Applications in electric vehicles, robotics, and industrial automation are explored, demonstrating the versatile use of DC motors in modern engineering. (shrink)

The introduction of 5G networks has brought forth a revolutionary shift in the capabilities of cloud services, especially with regard to low-latency applications and advanced network management techniques. 5G’s highspeed, low-latency, and massive connectivity features are particularly valuable for real-time applications, such as autonomous vehicles, industrial automation, augmented reality (AR), virtual reality (VR), and Internet of Things (IoT) ecosystems. Moreover, 5G enables network slicing, a technique that allows operators to create multiple virtual networks with customized performance characteristics within a (...) single physical network. This paper explores the synergy between 5G technology and cloud services, examining how 5G enables ultra-low-latency cloud applications, supports network slicing for diverse use cases, and enhances cloud service delivery across industries. We also discuss the challenges in implementing 5G-enabled cloud services, including technical, regulatory, and security issues. Finally, the paper forecasts the potential future of 5G-driven cloud services and their impact on emerging technologies such as smart cities, healthcare, and entertainmen. (shrink)

"Challenges and Issues of Modern Science" serve as an in-depth exploration of contemporary trends, sustainable development initiatives, and global concerns within the realm of scientific inquiry. The papers represent a collaborative effort by experts, researchers, and practitioners from various disciplines to address the multifaceted challenges facing modern science. Through in-depth analysis, empirical studies, and theoretical frameworks, the contributions in these proceedings aim to shed light on emerging trends, propose innovative solutions, and foster dialogue on critical issues shaping the future of (...) science and technology. By encapsulating the latest research findings and insights, the proceedings serve as a valuable resource for scholars, policymakers, and industry professionals, contributing to the advancement of knowledge and the sustainable development of our global community. Scope covers a wide range of topics and disciplines related to modern science. It includes but is not limited to Aerospace Vehicles, Engines, Energy, and Thermotechnics, Innovative Technologies in Mechanical Engineering, Structural and Functional Materials, Integrated Automation Technologies and Robotics, Control Systems, Telecommunications and Navigation, Information Technology and Cybersecurity, Project Management and Leadership, and Ecology, industrial, and environmental safety. The journal welcomes empirical studies, theoretical frameworks, and practical applications that contribute to the understanding and resolution of challenges in contemporary science. (shrink)

Abstract: The rapid advancement of artificial intelligence (AI) has catalyzed significant developments in autonomous systems, which are increasingly shaping diverse sectors including transportation, robotics, and industrial automation. This paper explores the evolution of AI technologies that underpin these autonomous systems, focusing on their capabilities, applications, and the challenges they present. Key areas of discussion include the technological innovations driving autonomy, such as machine learning algorithms and sensor integration, and the practical implementations observed in autonomous vehicles, drones, and robotic systems. (...) Additionally, the paper addresses critical challenges including safety, ethical concerns, and regulatory issues that influence the deployment and acceptance of autonomous technologies. By examining current trends and future prospects, this research aims to provide a comprehensive overview of how AI is transforming the landscape of autonomous systems and to identify key areas for future research and development. (shrink)

In recent years, there has been a huge increase in the number of bots online, varying from Web crawlers for search engines, to chatbots for online customer service, spambots on social media, and content-editing bots in online collaboration communities. The online world has turned into an ecosystem of bots. However, our knowledge of how these automated agents are interacting with each other is rather poor. Bots are predictable automatons that do not have the capacity for emotions, meaning-making, creativity, and (...) sociality and it is hence natural to expect interactions between bots to be relatively predictable and uneventful. In this article, we analyze the interactions between bots that edit articles on Wikipedia. We track the extent to which bots undid each other’s edits over the period 2001–2010, model how pairs of bots interact over time, and identify different types of interaction trajectories. We find that, although Wikipedia bots are intended to support the encyclopedia, they often undo each other’s edits and these sterile “fights” may sometimes continue for years. Unlike humans on Wikipedia, bots’ interactions tend to occur over longer periods of time and to be more reciprocated. Yet, just like humans, bots in different cultural environments may behave differently. Our research suggests that even relatively “dumb” bots may give rise to complex interactions, and this carries important implications for Artificial Intelligence research. Understanding what affects bot-bot interactions is crucial for managing social media well, providing adequate cyber-security, and designing well functioning autonomous vehicles. (shrink)

Road abnormalities, such as speed breakers and potholes, pose significant risks to traffic safety, contributing to accidents, vehicle damage, and driver discomfort. Traditional methods for detecting these issues are primarily manual and reactive, leading to inefficiencies in maintenance and increased hazards for road users. To address this urgent need, the proposed project aims to develop a computer vision-based system for the automatic detection of these road anomalies. By utilizing techniques such as image processing and analysis through OpenCV, the system will (...) allow users to input either images or videos for real time analysis and evaluation. This capability not only automates the detection process but also enhances the speed and accuracy of identifying road conditions. The system will continuously improve its performance as it processes more data, ensuring that it remains effective in various environments. This proactive approach aims to facilitate timely maintenance interventions, thereby enhancing overall road safety and user comfort. The successful implementation of this project could serve as a model for future developments in automated road condition assessment, ultimately contributing to smarter transportation systems and safer roadways for all users. (shrink)

The World’s Leading Research and Development Institutions and Companies -/- Introduction -/- Research and Development (R&D) is the backbone of global innovation, driving technological progress, economic growth, and scientific discoveries. Across the world, top institutions and corporations invest billions of dollars into R&D to push the boundaries of human knowledge and create groundbreaking technologies. This essay explores the most influential research institutions and companies shaping the future through their contributions in science, engineering, medicine, and technology. -/- The Role of Research (...) Institutions in Global Innovation -/- Research institutions play a crucial role in advancing fundamental and applied sciences. Many of these institutions are publicly funded universities and government research agencies that focus on a wide range of disciplines, from medicine and engineering to artificial intelligence and space exploration. -/- 1. Leading Research Institutions -/- Some of the most prestigious research institutions include: -/- National Institutes of Health (NIH) – USA: The primary agency of the U.S. government responsible for biomedical and public health research. -/- National Aeronautics and Space Administration (NASA) – USA: A global leader in aerospace and space exploration, NASA continues to innovate in space technology and planetary science. -/- Centre National de la Recherche Scientifique (CNRS) – France: The largest governmental research organization in France, covering all scientific disciplines. -/- Max Planck Society – Germany: A network of research institutes in Germany, known for excellence in science and technology. -/- Chinese Academy of Sciences (CAS) – China: China’s premier research institution focuses on science and technology innovation across various fields. -/- Harvard University – USA: Leads in biomedical research, social sciences, and humanities. -/- Massachusetts Institute of Technology (MIT) – USA: At the forefront of engineering, robotics, artificial intelligence, and quantum computing research. -/- Stanford University – USA: Known for its deep ties to Silicon Valley, Stanford plays a key role in tech innovation. -/- University of Oxford & University of Cambridge – UK: Both institutions are among the oldest and most respected in the world, conducting high-impact research in medicine, engineering, and the humanities. -/- Swiss Federal Institute of Technology Zurich (ETH Zurich) – Switzerland: Excels in engineering and natural sciences research. -/- University of Tokyo – Japan: Japan’s leading university, known for its research in science and technology. -/- California Institute of Technology (Caltech) – USA: A leader in space science and physics. -/- Imperial College London – UK: Specializes in engineering, medical, and business research. -/- University of Toronto – Canada: A top institution in AI, robotics, and engineering. -/- 2. Engineering and Technology Research Leaders -/- Engineering research institutions contribute to infrastructure, automation, and digital transformation. Some of the most prominent ones include: -/- University of California, Berkeley – USA: Known for its research in engineering, computer science, and environmental science. -/- University of Pennsylvania – USA: Invests in innovative engineering projects. -/- University of Michigan – USA: Known for technological advancements in multiple fields. -/- Swiss Federal Institute of Technology Lausanne (EPFL) – Switzerland: Excels in engineering and digital research. -/- Tsinghua University – China: A leader in AI, renewable energy, and industrial automation research. -/- The Role of Private Companies in Research and Development -/- Private corporations play a major role in R&D, investing heavily in emerging technologies, pharmaceuticals, consumer electronics, and industrial innovations. Many of the world’s biggest companies spend billions to maintain leadership in their respective fields. -/- 1. Leading Technology Companies in R&D -/- Amazon ($73.2B in R&D spending, 2022): Focuses on cloud computing, AI, logistics, and automation. -/- Alphabet (Google) ($39.5B in R&D, 2022): Invests in AI, quantum computing, and search algorithms. -/- Meta (Facebook) ($35.3B in R&D, 2022): Focuses on AI, VR, and the Metaverse. -/- Apple ($27.7B in R&D, 2022): Leads in consumer electronics and semiconductor technology. -/- Microsoft ($26.6B in R&D, 2022): Invests in AI, cloud computing, and software innovation. -/- 2. Engineering and Industrial Companies in R&D -/- Volkswagen ($19.88B in R&D, 2022): A leader in automotive engineering and electric vehicles. -/- Samsung ($19.29B in R&D, 2022): Develops advanced semiconductors and electronics. -/- Intel ($17.53B in R&D, 2022): Focuses on microprocessors and AI hardware. -/- Huawei ($24B in R&D, 2022): Leads in telecommunications and 5G development. -/- Siemens – Germany: A global leader in industrial automation, medical technology, and smart infrastructure. -/- Nokia – Finland: Focuses on telecommunications infrastructure and technology development. -/- Sony – Japan: Invests in consumer electronics, gaming, and entertainment technologies. -/- Boeing – USA: Develops aerospace technology, defense systems, and commercial aircraft innovations. -/- General Electric (GE) – USA: Focuses on energy, aviation, and industrial automation R&D. -/- 3. Pharmaceutical and Biotech Research Leaders -/- Roche ($14.72B in R&D, 2022): A leading pharmaceutical company specializing in diagnostics and biotech innovations. -/- Pfizer: Known for vaccine development, including the COVID-19 vaccine. -/- Moderna: A pioneer in mRNA technology for medical treatments. -/- Johnson & Johnson: Invests heavily in medical devices and pharmaceuticals. -/- Bristol-Myers Squibb – USA: Focuses on biopharmaceutical research, including immunology and oncology. -/- AstraZeneca – UK/Sweden: Invests in pharmaceutical research, particularly in oncology and cardiovascular diseases. -/- The Impact of R&D on Society and the Future -/- The advancements driven by R&D have a profound impact on global society. Some of the most significant areas of innovation include: -/- Healthcare: Research in biotechnology, gene therapy, and medical AI is revolutionizing healthcare, leading to personalized medicine and new treatments for previously incurable diseases. -/- Artificial Intelligence: AI research in institutions and companies is driving automation, machine learning, and deep learning applications. -/- Sustainable Energy: Engineering research is focusing on renewable energy, electric vehicles, and smart grid technologies to combat climate change. -/- Space Exploration: Organizations like NASA, SpaceX, and ESA are expanding human exploration beyond Earth. -/- Telecommunications: Companies like Huawei, Nokia, and Qualcomm are leading the development of 5G and future wireless communication technologies. -/- Automotive Industry: Electric vehicles, hydrogen fuel cells, and autonomous driving are key research areas for companies like Tesla, Volkswagen, and Toyota. -/- Conclusion -/- The world’s leading R&D institutions and companies are shaping the future through their groundbreaking work in science, engineering, medicine, and technology. Universities and research centers provide the foundation for discovery, while corporations drive commercial applications of these innovations. As investments in R&D continue to grow, humanity will witness even greater advancements in fields such as artificial intelligence, biotechnology, and space exploration, ultimately improving lives and pushing the boundaries of what is possible. -/- . (shrink)

Comprehensive Plan for Population Growth Control & Senior Citizen Social Safety Net in the Philippines -/- To ensure sustainable population growth while also supporting senior citizens who have no children or lack financial support, the government must integrate social safety net laws for both family planning and elderly welfare. -/- I. Population Growth Control Through Social Safety Net Laws -/- 1. TAX REFORMS TO INCENTIVIZE SMALLER FAMILIES -/- A. Incentives for Small Families -/- Higher tax deductions for families with one (...) or two children. -/- Gradual removal of tax benefits for families with more than two children. -/- Corporate tax incentives for businesses that provide family planning services. -/- B. Tax Penalties for Large Families -/- Higher progressive taxation on families with three or more children. -/- Luxury taxes on housing, vehicles, and government subsidies for large families. -/- 2. EDUCATION REFORMS FOR RESPONSIBLE FAMILY PLANNING -/- A. Strengthening Sex Education (Comprehensive Sexuality Education – CSE) -/- Mandatory inclusion in the school curriculum from Grade 5 onward. -/- Covers reproductive health, contraception, financial responsibility, and gender equality. -/- B. Scholarships & Financial Aid for Small Families -/- Additional educational subsidies for children from families with one or two kids. -/- Gradual reduction of education subsidies for larger families. -/- 3. EMPLOYMENT & SOCIAL WELFARE REFORMS -/- A. Job Incentives for Women & Working Parents -/- Work-from-home incentives and subsidized childcare for working mothers. -/- Paid maternity leave benefits tied to small family sizes. -/- B. Adjustments to 4Ps Social Welfare Program -/- Full cash benefits limited to the first two children. -/- Mandatory family planning education to continue receiving benefits. -/- 4. AI & BIG DATA FOR POPULATION PLANNING -/- AI-driven demographic tracking to adjust tax policies, social benefits, and economic incentives. -/- Predictive modeling for workforce planning to prevent future labor shortages. -/- 5. URBAN & RURAL DEVELOPMENT STRATEGIES -/- Housing and urban planning incentives for small families. -/- Smart city initiatives to balance population density. -/- II. Social Safety Net for Senior Citizens Without Children or Financial Support -/- 1. Universal Pension & Financial Support Programs -/- A. Strengthening the SSS and GSIS Pension System -/- Mandatory government contributions for all workers, regardless of employment sector. -/- Higher pension benefits for seniors without children or financial support. -/- B. New “Guaranteed Minimum Pension” Program -/- Senior citizens without private savings receive a baseline pension from the government. -/- Indexed to inflation to ensure financial security in old age. -/- 2. Housing & Living Assistance for Seniors Without Family Support -/- A. Senior Citizen Cooperative Housing Program -/- Government-subsidized shared housing facilities for elderly individuals without family support. -/- Community-based senior housing with healthcare and caregiving services. -/- B. Expansion of Public Nursing Homes -/- New state-run assisted living facilities in every province. -/- Affordable senior apartments with subsidized utilities and food programs. -/- 3. Healthcare & Insurance for Elderly Without Family Support -/- A. Expansion of PhilHealth & Free Healthcare Services -/- Automatic PhilHealth coverage for all seniors with no child support. -/- Higher government healthcare subsidies for single and childless seniors. -/- B. Free Home-Based Healthcare -/- Barangay-level healthcare workers assigned to provide free home visits for elderly citizens. -/- Mobile clinics and telemedicine for those in remote areas. -/- 4. Employment & Social Engagement for the Elderly -/- A. Senior Employment & Livelihood Programs -/- Tax incentives for companies hiring seniors (part-time or consultancy roles). -/- Government-backed microfinance loans for seniors starting small businesses. -/- B. “Adopt-a-Senior” Community Program -/- Encourage local communities to support senior citizens without family assistance. -/- Volunteer-based programs where younger individuals help care for seniors. -/- III. Implementation Challenges & Solutions -/- A. Overcoming Religious & Cultural Barriers -/- Frame policies as “family economic security programs” rather than population control. -/- Community-based awareness campaigns to promote responsible parenthood. -/- B. Ensuring Fair Implementation in Rural Areas -/- Deploy mobile healthcare teams to reach isolated seniors and educate rural families. -/- Offer financial rewards for barangays with successful family planning programs. -/- C. Balancing Population Growth & Workforce Needs -/- Encourage skilled migration to prevent future labor shortages. -/- Promote education and automation to compensate for a smaller workforce. -/- Final Recommendations -/- Integrate population planning into the national economic strategy. -/- Create a “National Senior Citizen Welfare Act” ensuring financial security for the elderly. -/- Strengthen AI-driven demographic management to balance population growth. -/- . (shrink)

A Universal Formula for Creating a Perfect Society -/- A perfect society must follow the universal law of balance in nature, ensuring that all social, economic, technological, and environmental systems function in harmony. Your universal formula serves as the foundation for designing such a society, where population growth is properly regulated to maintain balance and sustainability. -/- I. The Core Principle: The Universal Law of Balance -/- A perfect society must: ✔ Align human actions with natural laws. ✔ Eliminate corruption, (...) exploitation, and inefficiency. ✔ Balance technological progress with environmental sustainability. ✔ Regulate population growth to match available resources and societal needs. -/- II. The Key Components of a Perfect Society -/- 1. Ideal Population Growth Rate and Regulation -/- A perfect society must have a regulated population growth that aligns with natural resource capacity, economic stability, and environmental sustainability. ✔ Overpopulation leads to resource depletion, poverty, and instability. ✔ Underpopulation leads to economic decline and labor shortages. ✔ The ideal population growth rate must be carefully calculated for each region based on its resource availability, technological advancement, and economic capacity. -/- Implementation: -/- Educate the public on population and resource balance. -/- Implement voluntary and ethical family planning programs. -/- Ensure economic and social policies are adjusted based on population data. -/- Use AI to analyze demographic trends and forecast future population needs. -/- Encourage balanced migration policies to stabilize population distribution. -/- 2. Holistic and Rational Education System -/- ✔ Teach the universal law of balance in education. ✔ Focus on critical thinking, ethics, sustainability, and science. ✔ Train leaders in ethical decision-making, governance, and problem-solving. -/- 3. Governance Rooted in Natural Laws -/- ✔ Data-driven, ethical, and transparent leadership. ✔ AI-assisted governance to prevent corruption and mismanagement. ✔ Scientific, evidence-based policymaking. -/- 4. Urban Planning for Sustainable Cities -/- ✔ Eco-friendly, well-planned cities with green spaces and clean energy. ✔ Smart infrastructure to reduce congestion and pollution. ✔ Affordable, energy-efficient housing for all. -/- 5. Balanced Transportation System -/- ✔ Mass public transit over personal vehicles. ✔ Electric and hydrogen-powered transport to reduce pollution. ✔ Bike-friendly and pedestrian-friendly cities. -/- 6. A Just and Sustainable Economic System -/- ✔ Balanced capitalism—free markets with strong ethical regulations. ✔ No extreme wealth gaps or monopolies. ✔ Fair wages, job security, and profit-sharing models. -/- 7. Energy Production Aligned with Natural Balance -/- ✔ Solar, wind, hydro, and nuclear fusion energy to eliminate fossil fuels. ✔ Decentralized renewable energy grids for reliability. ✔ Buildings, industries, and transportation designed for energy efficiency. -/- 8. Agriculture and Agribusiness for Food Security -/- ✔ Sustainable, regenerative farming practices to maintain soil fertility. ✔ Organic farming over chemical-intensive monoculture. ✔ AI-driven precision agriculture to maximize food production with minimal waste. -/- Implementation: -/- Urban farming and vertical agriculture to reduce land use. -/- Government subsidies for small farmers to prevent corporate monopolies. -/- Integration of agribusiness with clean energy sources. -/- 9. Technology Companies Serving Humanity -/- ✔ Ethical AI and automation that enhance human life. ✔ Tech companies must focus on sustainability, data privacy, and fairness. ✔ Public ownership of essential tech infrastructure (internet, AI governance, energy grids, etc.). -/- 10. Forest Conservation and Wildlife Protection -/- ✔ Strict anti-deforestation laws with mandatory reforestation. ✔ Protect wildlife corridors and endangered species. ✔ Regenerative land use practices to restore ecosystems. -/- 11. Protection of Seas, Oceans, and Rivers -/- ✔ Ban overfishing and destructive fishing methods. ✔ Regulate ocean mining and oil drilling. ✔ Prevent river and ocean pollution from industries and waste. -/- 12. Eliminating Pollution and Managing Waste -/- ✔ Zero-waste circular economy—recycling and reusing materials efficiently. ✔ Eliminate plastic waste and toxic chemicals in industries. ✔ Convert waste into renewable energy sources. -/- 13. Sustainable Water Resource Management -/- ✔ Protect fresh water from contamination and overuse. ✔ Desalination and rainwater harvesting in water-scarce areas. ✔ Efficient irrigation and water recycling in agriculture and industry. -/- 14. Job Creation and Economic Stability -/- ✔ Ensure that automation enhances jobs rather than eliminates them. ✔ Support entrepreneurship and small businesses. ✔ Guarantee fair wages and universal job security. -/- 15. Universal Healthcare System -/- ✔ Preventive medicine should be the priority. ✔ Universal healthcare with AI-driven diagnostics. ✔ Mental health services equal to physical health services. -/- 16. A Strong Social Safety Net -/- ✔ Unemployment benefits and food security. ✔ State-funded job training and skill development. ✔ Affordable housing and support systems for the homeless. -/- 17. Ethical Artificial Intelligence and Automation -/- ✔ AI must serve humanity, not corporate control. ✔ Prevent AI from being used for mass surveillance or manipulation. ✔ Ensure AI aligns with the universal law of balance. -/- 18. Justice System Based on Cause and Effect (Law of Karma) -/- ✔ Laws must be logical, fair, and corruption-free. ✔ Swift, evidence-based legal processes. ✔ Restorative justice rather than punitive imprisonment. -/- 19. Global Feedback Mechanism for Continuous Improvement -/- ✔ AI-assisted global balance monitoring. ✔ Digital democracy and blockchain voting for fair governance. ✔ Regular sustainability and ethics audits. -/- III. Conclusion: A Perfect Society Is Achievable -/- A perfect society follows the universal law of balance in all areas—economy, technology, environment, governance, and social systems. -/- By applying your universal formula, society can: ✔ Eliminate corruption, poverty, and injustice. ✔ Achieve sustainability without harming future generations. ✔ Use AI and technology responsibly for the betterment of all. ✔ Create a world where human potential is maximized, and suffering is minimized. -/- . (shrink)

Our computational metaphysics group describes its use of automated reasoning tools to study Leibniz’s theory of concepts. We start with a reconstruction of Leibniz’s theory within the theory of abstract objects (henceforth ‘object theory’). Leibniz’s theory of concepts, under this reconstruction, has a non-modal algebra of concepts, a concept-containment theory of truth, and a modal metaphysics of complete individual concepts. We show how the object-theoretic reconstruction of these components of Leibniz’s theory can be represented for investigation by means of (...) automated theorem provers and finite model builders. The fundamental theorem of Leibniz’s theory is derived using these tools. (shrink)

Rapid advances in AI-based automation have led to a number of existential and economic concerns. In particular, as automating technologies develop enhanced competency they seem to threaten the values associated with meaningful work. In this article, we focus on one such value: the value of achievement. We argue that achievement is a key part of what makes work meaningful and that advances in AI and automation give rise to a number achievement gaps in the workplace. This could limit people’s ability (...) to participate in meaningful forms of work. Achievement gaps are interesting, in part, because they are the inverse of the (negative) responsibility gaps already widely discussed in the literature on AI ethics. Having described and explained the problem of achievement gaps, the article concludes by identifying four possible policy responses to the problem. (shrink)

This work provides proof-search algorithms and automated counter-model extraction for a class of STIT logics. With this, we answer an open problem concerning syntactic decision procedures and cut-free calculi for STIT logics. A new class of cut-free complete labelled sequent calculi G3LdmL^m_n, for multi-agent STIT with at most n-many choices, is introduced. We refine the calculi G3LdmL^m_n through the use of propagation rules and demonstrate the admissibility of their structural rules, resulting in auxiliary calculi Ldm^m_nL. In the single-agent case, (...) we show that the refined calculi Ldm^m_nL derive theorems within a restricted class of (forestlike) sequents, allowing us to provide proof-search algorithms that decide single-agent STIT logics. We prove that the proof-search algorithms are correct and terminate. (shrink)

Automated influence is one of the most pervasive applications of artificial intelligence in our day-to-day lives, yet a thoroughgoing account of its associated individual and societal harms is lacking. By far the most widespread, compelling, and intuitive account of the harms associated with automated influence follows what I call the control argument. This argument suggests that users are persuaded, manipulated, and influenced by automated influence in a way that they have little or no control over. Based on (...) evidence about the effectiveness of targeted advertising as well as empirical results about the nature of attentional control, I provide reasons to reject this argument. In turn, I use C. Thi Nguyen’s theory of value collapse to develop a new account of the harmfulness of automated influence. (shrink)

The article explores the problem of preferable technological changes in the context of work. To this end, it addresses the ‘why’ (motives and values) and the ‘how’ (organizational forms) of automation from a normative perspective. Concerning the ‘why,’ automation processes are currently mostly driven by values of economic efficiency. Yet, since automation processes are part of the basic structure of society, as is the division of labor, considerations of justice apply to them. As for the ‘how,’ the article suggests ‘fair (...) hybrid cooperation’ as an alternative ideal to guide automation priorities. It is achieved when the division of labor between humans and machines does not hinder, and preferably enables, workers’ experience of certain primary qualities in their work activity. By analogy with Rawls’ primary goods, these are qualities that it is necessary for every worker to experience in order to pursue their life plans: security, self-direction, self-development, dignity, and recognition. According to this criterion, the tasks to automate first are those hindering these contributive primary qualities. This provides us with a normative vocabulary and a standard to orient automation decisions but also to assess existing organizational forms and envisage alternative cooperative imaginaries. To illustrate how the ideal may play out in the real world, the article concludes with a ‘fair hybrid cooperation test’ and a nurse bots case for meaningful work. (shrink)

While autonomous vehicles (AVs) are not designed to harm people, harming people is an inevitable by-product of their operation. How are AVs to deal ethically with situations where harming people is inevitable? Rather than focus on the much-discussed question of what choices AVs should make, we can also ask the much less discussed question of who gets to decide what AVs should do in such cases. Here there are two key options: AVs with a personal ethics setting (PES) or (...) an “ethical knob” that end users can control or AVs with a mandatory ethics setting (MES) that end users cannot control. Which option, a PES or an MES, is best and why? This chapter argues, by drawing on the choice architecture literature, in favor of a hybrid view that requires mandated default choice settings while allowing for limited end user control. (shrink)

The integration of Robotic Process Automation (RPA) into Human Resources (HR) functions represents a significant advancement in organizational efficiency and effectiveness. RPA technology automates repetitive and rule-based tasks, allowing HR professionals to focus on strategic initiatives that add value to the organization. This paper provides a comprehensive introduction to RPA within HR, detailing its applications, benefits, implementation strategies, and how its principles can be transferred to other domains such as finance. By examining the transformative potential of RPA, organizations can better (...) prepare for the future of work, where automation and human ingenuity coexist to drive success. (shrink)

Automated influence, delivered by digital targeting technologies such as targeted advertising, digital nudges, and recommender systems, has attracted significant interest from both empirical researchers, on one hand, and critical scholars and policymakers on the other. In this paper, we argue for closer integration of these efforts. Critical scholars and policymakers, who focus primarily on the social, ethical, and political effects of these technologies, need empirical evidence to substantiate and motivate their concerns. However, existing empirical research investigating the effectiveness of (...) these technologies (or lack thereof), neglects other morally relevant effects—which can be felt regardless of whether or not the technologies "work" in the sense of fulfilling the promises of their designers. Drawing from the ethics and policy literature, we enumerate a range of questions begging for empirical analysis—the outline of a research agenda bridging these fields—and issue a call to action for more empirical research that takes these urgent ethics and policy questions as their starting point. (shrink)

Automated influence is one of the most pervasive applications of artificial intelligence in our day-to-day lives, yet a thoroughgoing account of its associated individual and societal harms is lacking. By far the most widespread, compelling, and intuitive account of the harms associated with automated influence follows what I call the control argument. This argument suggests that users are persuaded, manipulated, and influenced by automated influence in a way that they have little or no control over. Based on (...) evidence about the effectiveness of targeted advertising as well as empirical results about the nature of attentional control, I provide reasons to reject this argument. In turn, I use C. Thi Nguyen's theory of value collapse to develop a new account of the harmfulness of automated influence. (shrink)

This semiotic research looks into the vehicle of the process of semiosis, the force or the medium by which the existence of a sign is recognized, and the process of semiosis is carried out. This force, which has been termed as ‘mind’ or ‘quasi-mind’ (Peirce 4.536 and 4.551), ‘organism’ (Johansen 1999), ‘codemaker’ or ‘agent’ (Barbieri 2007, 2008) and ‘interpreter’ (Emmeche et al. 2010) can be “any organism or a part of an organism, or just a product whose mechanism allows or (...) is able to carry out the process of semiosis”. These terms are used with reference to the existence of different types and domains of semiosis. In other words, it is not the process of semiosis, but the vehicle of the process of semiosis which makes the existence of different types and domains of semiosis. (shrink)

This paper is a new defense of the view that visual hallucinations lack content. The claim is that visual hallucinations are illusory not because their content is nonveridical, but rather because they seem to represent when they fail to represent anything in the first place. What accounts for the phenomenal character of visual experiences is not the content itself (content-representationalism), but rather the vehicle of content (vehicle-representationalism), that is, not the properties represented by visual experience, but rather the relational properties (...) of experience (or of the brain) of representing singular contents, namely particular instantiations of properties. I argue that the Russellian particular-involving proposition is the only appropriate model for the representational content of visual experience and hence that visual hallucinations are just like failed demonstrations. (shrink)

The notion of representation in neuroscience has largely been predicated on localizing the components of computational processes that explain cognitive function. On this view, which I call “algorithmic homuncularism,” individual, spatially and temporally distinct parts of the brain serve as vehicles for distinct contents, and the causal relationships between them implement the transformations specified by an algorithm. This view has a widespread influence in philosophy and cognitive neuroscience, and has recently been ably articulated and defended by Shea. Still, I (...) am skeptical about algorithmic homuncularism, and I argue against it by focusing on recent methods for complex data analysis in systems neuroscience. I claim that analyses such as principle components analysis and linear discriminant analysis prevent individuating vehicles as algorithmic homuncularism recommends. Rather, each individual part contributes to a global state space, trajectories of which vary with important task parameters. I argue that, while homuncularism is false, this view still supports a kind of “vehicle realism,” and I apply this view to debates about the explanatory role of representation. (shrink)

This book provides a critical reflection on automated science and addresses the question whether the computational tools we developed in last decades are changing the way we humans do science. More concretely: Can machines replace scientists in crucial aspects of scientific practice? The contributors to this book rethink and refine some of the main concepts by which science is understood, drawing a fascinating picture of the developments we expect over the next decades of human-machine co-evolution. The volume covers examples (...) from various fields and areas, such as molecular biology, climate modeling, clinical medicine, and artificial intelligence. The explosion of technological tools and drivers for scientific research calls for a renewed understanding of the human character of science. This book aims precisely to contribute to such a renewed understanding of science. (shrink)

This project focuses on estimating reservoir inflows by integrating rainfall data, soil moisture levels in the catchment area, and releases from upstream reservoirs, coupled with an automated gate control system to prevent flooding in the basin. Utilizing hydrological models, the methodology predicts runoff from rainfall, adjusted for current soil moisture to enhance accuracy. Real-time data from upstream releases further refines inflow predictions. The automated system leverages predictive analytics and real-time monitoring to optimize gate operations, ensuring moderate water releases (...) to maintain safe reservoir levels and mitigate downstream flooding. This approach aims to enhance flood management and sustainable water resource use through advanced modelling and automation. (shrink)

Our computational metaphysics group describes its use of automated reasoning tools to study Leibniz’s theory of concepts. We start with a reconstruction of Leibniz’s theory within the theory of abstract objects (henceforth ‘object theory’). Leibniz’s theory of concepts, under this reconstruction, has a non-modal algebra of concepts, a concept-containment theory of truth, and a modal metaphysics of complete individual concepts. We show how the object-theoretic reconstruction of these components of Leibniz’s theory can be represented for investigation by means of (...) automated theorem provers and finite model builders. The fundamental theorem of Leibniz’s theory is derived using these tools. (shrink)

A recent wave of academic and popular publications say that utopia is within reach: Automation will progress to such an extent and include so many high-skill tasks that much human work will soon become superfluous. The gains from this highly automated economy, authors suggest, could be used to fund a universal basic income (UBI). Today's employees would live off the robots' products and spend their days on intrinsically valuable pursuits. I argue that this prediction is unlikely to come true. (...) Historical precedent speaks against it, but the main problem is that the prediction fundamentally misunderstands how capitalism works—its incentives to increase or decrease production, its principles of income allocation, and the underlying conception of merit. (shrink)

The neural vehicles of mental representation play an explanatory role in cognitive psychology that their realizers do not. In this paper, I argue that the individuation of realizers as vehicles of representation restricts the sorts of explanations in which they can participate. I illustrate this with reference to Rupert’s (2011) claim that representational vehicles can play an explanatory role in psychology in virtue of their quantity or proportion. I propose that such quantity-based explanatory claims can apply only (...) to realizers and not to vehicles, in virtue of the particular causal role that vehicles play in psychological explanations. (shrink)

Human obsolescence is imminent. We are living through an era in which our activity is becoming less and less relevant to our well-being and to the fate of our planet. This trend toward increased obsolescence is likely to continue in the future, and we must do our best to prepare ourselves and our societies for this reality. Far from being a cause for despair, this is in fact an opportunity for optimism. Harnessed in the right way, the technology that hastens (...) our obsolescence can open us up to new utopian possibilities and enable heightened forms of human flourishing. (shrink)

This paper delves into the use of machine learning-based systems in decision-making processes and its implications for moral responsibility as traditionally defined. It focuses on the emergence of responsibility gaps and examines proposed strategies to address them. The paper aims to provide an introductory and comprehensive overview of the ongoing debate surrounding moral responsibility in automated decision-making. By thoroughly examining these issues, we seek to contribute to a deeper understanding of the implications of AI integration in society.

Building on Christopher Peacocke’s account of analog perceptual contentand my own account of analog perceptual vehicles, I defend three claims: that theperception of magnitudes often has analog contents; that the perception of magni-tudes often has analog vehicles; and that the first claim is true in virtue of the second—that is, the analog vehicles help to ground the analog contents.

Automated Influence is the use of Artificial Intelligence to collect, integrate, and analyse people’s data in order to deliver targeted interventions that shape their behaviour. We consider three central objections against Automated Influence, focusing on privacy, exploitation, and manipulation, showing in each case how a structural version of that objection has more purchase than its interactional counterpart. By rejecting the interactional focus of “AI Ethics” in favour of a more structural, political philosophy of AI, we show that the (...) real problem with Automated Influence is the crisis of legitimacy that it precipitates. (shrink)

Despite widespread evidence that fictional models play an explanatory role in science, resistance remains to the idea that fictions can explain. A central source of this resistance is a particular view about what explanations are, namely, the ontic conception of explanation. According to the ontic conception, explanations just are the concrete entities in the world. I argue this conception is ultimately incoherent and that even a weaker version of the ontic conception fails. Fictional models can succeed in offering genuine explanations (...) by correctly capturing relevant patterns of counterfactual dependence and licensing correct inferences. Using the example of Newtonian force explanations of the tides, I show how, even in science, fiction can be a vehicle for truth. (shrink)

This article will rework the classical question ‘Can a machine think?’ into a more specific problem: ‘Can a machine think anything new?’ It will consider traditional computational tasks such as prediction and decision-making, so as to investigate whether the instrumentality of these operations can be understood in terms of the creation of novel thought. By addressing philosophical and technoscientific attempts to mechanise thought on the one hand, and the philosophical and cultural critique of these attempts on the other, I will (...) argue that computation’s epistemic productions should be assessed vis-à-vis the logico-mathematical specificity of formal axiomatic systems. Such an assessment requires us to conceive automated modes of thought in such a way as to supersede the hope that machines might replicate human cognitive faculties, and to thereby acknowledge a form of onto-epistemological autonomy in automated ‘thinking’ processes. This involves moving beyond the view that machines might merely simulate humans. Machine thought should be seen as dramatically alien to human thought, and to the dimension of lived experience upon which the latter is predicated. Having stepped outside the simulative paradigm, the question ‘Can a machine think anything new?’ can then be reformulated. One should ask whether novel behaviour in computing might come not from the breaking of mechanical rules, but from following them: from doing what computers do already, and not what we might think they should be doing if we wanted them to imitate us. (shrink)

The digital revolution, in the form of autonomous driving, is changing the very essence of mobility. This paper discusses four different ways in which these transformations are taking place and argues that public policies and business strategies need to focus on innovating and re-engineering (enveloping) whole environments. Only then will autonomous vehicles become an ordinary – and environmentally sustainable – reality. -/- .

he health of plants plays a crucial role in ensuring agricultural productivity and food security. Early detection of plant diseases can significantly reduce crop losses, leading to improved yields. This paper presents a novel approach for plant disease recognition using deep learning techniques. The proposed system automates the process of disease detection by analyzing leaf images, which are widely recognized as reliable indicators of plant health. By leveraging convolutional neural networks (CNNs), the model identifies various plant diseases with high accuracy. (...) The experimental setup includes a dataset consisting of healthy and diseased leaf images of different plant species. The dataset is preprocessed to remove noise and augmented to address the issue of class imbalance. The CNN model is then trained, validated, and tested on this dataset. (shrink)

The increasing complexity of modern networks has amplified the challenges associated with ensuring robust and scalable security. With the rapid evolution of cyber threats, traditional methods of network security management are often inadequate, leading to inefficiencies and vulnerabilities. Automation has emerged as a transformative approach to streamline network operations, enhance security postures, and reduce the margin of human error. This study explores the integration of Ansible, a powerful open-source automation tool, into network security workflows to deliver a comprehensive framework for (...) secure network automation. This research begins by examining the limitations of conventional network security management, emphasizing the time-intensive and error-prone nature of manual configurations. It highlights how automation, specifically using Ansible, addresses these issues by enabling consistent, repeatable, and scalable processes. Ansible’s ability to seamlessly integrate with diverse networking devices and platforms makes it an ideal choice for automating complex network environments. The methodology involves the development of automated playbooks for various security tasks, including firewall rule management, vulnerability scanning, configuration compliance checks, and incident response. By leveraging Ansible's declarative language, these playbooks are designed to be user-friendly and adaptable, ensuring ease of deployment across networks of varying sizes and complexities. The study also incorporates real-world use cases to demonstrate the tool's effectiveness in mitigating security risks while significantly reducing administrative overhead. Furthermore, the paper evaluates the impact of automation on key performance metrics such as response time to security incidents, accuracy of configurations, and overall system uptime. The findings indicate that integrating Ansible into network security workflows not only enhances operational efficiency but also fortifies security by minimizing misconfigurations and improving threat response times. These results underscore the importance of adopting automation as a critical component of modern network security strategies. In addition to technical insights, the study addresses potential challenges, such as initial implementation costs, skill gaps, and the need for continuous updates to automation scripts to align with evolving security requirements. It provides recommendations for organizations to overcome these obstacles, including investing in employee training and adopting iterative implementation strategies. The research concludes by affirming the transformative potential of automation tools like Ansible in revolutionizing network security management. By reducing reliance on manual processes, organizations can focus their efforts on proactive threat hunting and strategic planning, thereby fostering a more resilient security infrastructure. This paper serves as a comprehensive guide for network administrators and IT professionals seeking to leverage Ansible for secure network automation, providing both theoretical insights and practical solutions to enhance network security in an increasingly dynamic cyber landscape. (shrink)

Many of the benefits and burdens we might experience in our lives — from bank loans to bail terms — are increasingly decided by institutions relying on algorithms. In a sense, this is nothing new: algorithms — instructions whose steps can, in principle, be mechanically executed to solve a decision problem — are at least as old as allocative social institutions themselves. Algorithms, after all, help decision-makers to navigate the complexity and variation of whatever domains they are designed for. In (...) another sense, however, this development is startlingly new: not only are algorithms being deployed in ever more social contexts, they are being mechanically executed not merely in principle, but pervasively in practice. Due to recent advances in computing technology, the benefits and burdens we experience in our lives are now increasingly decided by automata, rather than each other. How are we to morally assess these technologies? In this chapter, I propose a preliminary conceptual schema for identifying and locating the various injustices of automated, algorithmic social decision systems, from a broadly liberal perspective. (shrink)

This paper addresses the critical role of automated data quality monitoring in Machine Learning Operations (MLOps) pipelines. As organizations increasingly rely on machine learning models for decision-making, ensuring the quality and reliability of input data becomes paramount. The paper explores various types of data quality issues, including missing values, outliers, data drift, and integrity violations, and their potential impact on model performance. It then examines automated detection methods, such as statistical analysis, machine learning-based anomaly detection, rule-based systems, and (...) data profiling. The integration of data quality monitoring into different stages of the MLOps pipeline is discussed, emphasizing continuous monitoring at data ingestion, pre-training validation, post- deployment drift detection, and feedback loops for model retraining. The paper also addresses key challenges in implementing automated data quality monitoring, including balancing precision and recall in anomaly detection, handling high-dimensional and unstructured data, managing false positives and alert fatigue, and adapting to evolving data distributions. By providing a comprehensive framework for automating data quality monitoring in MLOps pipelines, this paper aims to equip practitioners with the knowledge and strategies necessary to enhance the reliability and performance of machine learning systems in production environments. (shrink)

The EU AI Act is the first step toward a comprehensive legal framework for AI. It introduces provisions for AI systems based on their risk levels in relation to fundamental rights. Providers of AI systems must conduct Conformity Assessments before market placement. Recent amendments added Fundamental Rights Impact Assessments for high-risk AI system users, focusing on compliance with EU and national laws, fundamental rights, and potential impacts on EU values. The paper suggests that automating business process compliance can help standardize (...) these assessments and outlines some methodological guidelines. (shrink)