A series of recent developments points towards auditing as a promising mechanism to bridge the gap between principles and practice in AI ethics. Building on ongoing discussions concerning ethics-based auditing, we offer three contributions. First, we argue that ethics-based auditing can improve the quality of decision making, increase user satisfaction, unlock growth potential, enable law-making, and relieve human suffering. Second, we highlight current best practices to support the design and implementation of ethics-based auditing: To be feasible and effective, ethics-based auditing (...) should take the form of a continuous and constructive process, approach ethical alignment from a system perspective, and be aligned with public policies and incentives for ethically desirable behaviour. Third, we identify and discuss the constraints associated with ethics-based auditing. Only by understanding and accounting for these constraints can ethics-based auditing facilitate ethical alignment of AI, while enabling society to reap the full economic and social benefits of automation. (shrink)

An increasing number of regulations propose the notion of ‘AI audits’ as an enforcement mechanism for achieving transparency and accountability for artificial intelligence (AI) systems. Despite some converging norms around various forms of AI auditing, auditing for the purpose of compliance and assurance currently have little to no agreed upon practices, procedures, taxonomies, and standards. We propose the ‘criterion audit’ as an operationalizable compliance and assurance external audit framework. We model elements of this approach after financial auditing practices, (...) and argue that AI audits should similarly provide assurance to their stakeholders about AI organizations’ ability to govern their algorithms in ways that mitigate harms and uphold human values. We discuss the necessary conditions for the criterion audit, and provide a procedural blueprint for performing an audit engagement in practice. We illustrate how this framework can be adapted to current regulations by deriving the criteria on which ‘bias audits’ for hiring algorithms can be performed, as required by the recently effective New York City Local Law 144 of 2021. We conclude by offering critical discussion on the benefits, inherent limitations, and implementation challenges of applying practices of the more mature financial auditing industry to AI auditing where robust guardrails against quality assurance issues are only starting to emerge. Our discussion as informed by experiences in performing these audits in practice highlights the critical role that an audit ecosystem plays in ensuring the effectiveness of such methodology. (shrink)

In recent years, the ethical impact of AI has been increasingly scrutinized, with public scandals emerging over biased outcomes, lack of transparency, and the misuse of data. This has led to a growing mistrust of AI and increased calls for mandated ethical audits of algorithms. Current proposals for ethical assessment of algorithms are either too high level to be put into practice without further guidance, or they focus on very specific and technical notions of fairness or transparency that do not (...) consider multiple stakeholders or the broader social context. In this article, we present an auditing framework to guide the ethical assessment of an algorithm. The audit instrument itself is comprised of three elements: a list of possible interests of stakeholders affected by the algorithm, an assessment of metrics that describe key ethically salient features of the algorithm, and a relevancy matrix that connects the assessed metrics to stakeholder interests. The proposed audit instrument yields an ethical evaluation of an algorithm that could be used by regulators and others interested in doing due diligence, while paying careful attention to the complex societal context within which the algorithm is deployed. (shrink)

An increasing number of financial services (FS) companies are adopting solutions driven by artificial intelligence (AI) to gain operational efficiencies, derive strategic insights, and improve customer engagement. However, the rate of adoption has been low, in part due to the apprehension around its complexity and self-learning capability, which makes auditability a challenge in a highly regulated industry. There is limited literature on how FS companies can implement the governance and controls specific to AI-driven solutions. AI auditing cannot be performed in (...) a vacuum; the risks are not confined to the algorithm itself, but rather permeates the entire organization. Using the risk of unfairness as an example, this paper will introduce the overarching governance strategy and control framework to address the practical challenges in mitigating risks AI introduces. With regulatory implications and industry use cases, this framework will enable leaders to innovate with confidence. (shrink)

AI systems that demonstrate significant bias or lower than claimed accuracy, and resulting in individual and societal harms, continue to be reported. Such reports beg the question as to why such systems continue to be funded, developed and deployed despite the many published ethical AI principles. This paper focusses on the funding processes for AI research grants which we have identified as a gap in the current range of ethical AI solutions such as AI procurement guidelines, AI impact assessments and (...) AI audit frameworks. We highlight the responsibilities of funding bodies to ensure investment is channelled towards trustworthy and safe AI systems and provides case studies as to how other ethical funding principles are managed. We offer a first sight of two proposals for funding bodies to consider regarding procedures they can employ. The first proposal is for the inclusion of a Trustworthy AI Statement’ section in the grant application form and offers an example of the associated guidance. The second proposal outlines the wider management requirements of a funding body for the ethical review and monitoring of funded projects to ensure adherence to the proposed ethical strategies in the applicants Trustworthy AI Statement. The anticipated outcome for such proposals being employed would be to create a ‘stop and think’ section during the project planning and application procedure requiring applicants to implement the methods for the ethically aligned design of AI. In essence it asks funders to send the message “if you want the money, then build trustworthy AI!”. (shrink)

To create fair and accountable AI and robotics, we need precise regulation and better methods to certify, explain, and audit inscrutable systems.

AI and the Universal Law of Economic Balance: A Homeostatic Model for Sustainable Prosperity -/- Introduction -/- Modern economies are primarily driven by the profit motive, which, while encouraging innovation and efficiency, often leads to wage stagnation, wealth inequality, and resource exploitation. The imbalance between corporate profits, wages, purchasing power, and market demand has resulted in recurring economic crises, social unrest, and environmental degradation. -/- To resolve these systemic issues, economic policies must align with the universal law of balance in (...) nature, ensuring that financial systems function as self-regulating ecosystems rather than unstable, profit-driven markets. Achieving this balance requires both gradual reform and fundamental restructuring, first at the national level and then integrated into a global economic framework. -/- The key to Implementing and maintaining this balance lies in artificial intelligence (AI), which can analyze economic conditions in real time and adjust wages, prices, taxation, and resource distribution to maintain stability. However, to prevent AI from becoming a tool of economic control for powerful entities, it must be open-source, decentralized, and governed by ethical principles. -/- This essay explores how AI-driven economic balance can replace market-driven instability with a self-regulating, sustainable model that ensures fair wages, stable prices, and equitable wealth distribution. -/- The Problem: Profit Motive and Economic Imbalance -/- The traditional economic system relies on profit margins to sustain businesses. However, when companies focus on maximizing profits, several imbalances emerge: -/- 1. Lower Wages Reduce Purchasing Power -/- When businesses lower costs to remain competitive, wages stagnate. -/- Lower wages mean consumers cannot afford the products they produce. -/- 2. Weaker Demand Forces Businesses to Cut Costs Further -/- If people cannot buy goods, businesses cut jobs and wages further, deepening the problem. -/- Economic growth becomes dependent on debt, leading to financial instability. -/- 3. Wealth Concentration Creates Social and Political Instability -/- Extreme profit accumulation among a small elite leads to economic inequality. -/- Governments either increase taxes (which businesses resist) or cut social services (which leads to public unrest). -/- This cycle of imbalance proves that unregulated profit-seeking is unsustainable. Instead, an economy must be structured to self-regulate, ensuring a balance between wages, prices, profits, and demand. -/- A Homeostatic Economic Model: Balancing Wages, Prices, and Profits -/- A homeostatic economic model ensures that all components of the economy—wages, prices, profit margins, taxation, and demand—adjust dynamically to maintain stability. The following reforms would create this balance: -/- 1. Wage-Price Equilibrium -/- Wages must be indexed to productivity and inflation, ensuring purchasing power remains stable. -/- Profit-sharing incentives should be standardized, allowing workers to benefit from company success. -/- 2. Profit Regulation Without Killing Innovation -/- Essential industries (e.g., healthcare, food, energy) should have profit caps to prevent price exploitation. -/- Businesses that reinvest in worker wages, technology, or sustainability should receive tax breaks. -/- 3. Market Demand and Supply Stability -/- Governments and businesses must collaborate to prevent artificial scarcity and price manipulation. -/- Tax policies should support lower-income groups, ensuring their purchasing power remains intact. -/- 4. Dynamic Feedback Mechanism for Economic Stability -/- Economic decisions must be based on real-time data, avoiding speculation-based policies. -/- Policies should be adjustable based on changes in market conditions, preventing booms and busts. -/- These policies require both national reforms and global cooperation, ensuring that no single country or corporation can disrupt the balance for personal gain. -/- AI as the Key to Homeostatic Economic Balance -/- Maintaining economic balance in real time is too complex for human policymakers alone. This is where artificial intelligence (AI) can play a critical role in: -/- 1. Real-Time Wage and Price Adjustments -/- AI can analyze inflation, productivity, and cost of living to dynamically adjust wages and prices. -/- 2. Profit Optimization Without Exploitation -/- AI can track corporate profits and suggest profit-reinvestment policies that benefit workers and society. -/- 3. Smart Taxation and Wealth Redistribution -/- AI-driven progressive taxation models ensure fair wealth distribution while preventing economic stagnation. -/- 4. Market Demand and Supply Optimization -/- AI can predict consumer demand shifts and help businesses adjust production to prevent shortages or oversupply. -/- 5. Global Trade and Resource Management -/- AI can analyze trade patterns to ensure fair pricing and sustainable resource allocation worldwide. -/- 6. Public Awareness and Education -/- AI can identify economic misconceptions and suggest educational initiatives to promote financial literacy. -/- For AI to function effectively in this role, it must operate under ethical and decentralized governance to serve humanity rather than corporate or political interests. -/- Ensuring AI Remains Open-Source and Decentralized -/- To prevent AI from being misused as a tool of economic control, its development and governance must follow these principles: -/- 1. Open-Source AI for Economic Balance -/- AI models should be transparent and publicly auditable to prevent hidden biases. -/- Developers from multiple disciplines should contribute to ensure fairness and accuracy. -/- 2. Decentralized Governance Model -/- AI should be managed through global economic councils, not a single government or corporation. -/- Blockchain technology can ensure transparency in AI-driven economic decisions. -/- 3. Ethical Safeguards Against Manipulation -/- AI decisions should prioritize sustainability and human well-being over profit. -/- Economic policies should be auditable in real-time by independent researchers and civil organizations. -/- Failsafe mechanisms must prevent AI from implementing harmful policies due to data misinterpretation. -/- By ensuring AI-driven economic balance is open-source, decentralized, and ethically governed, it can create a self-correcting system that prevents economic crises, stabilizes wealth distribution, and ensures long-term prosperity. -/- Implementation Strategy: Gradual Reform Leading to Systemic Change -/- Since economic transition cannot happen overnight, a phased approach is necessary: -/- Phase 1: National-Level Reforms -/- 1. Implement wage-price indexing and profit-sharing policies. -/- 2. Reduce corporate taxes for businesses that reinvest in workers and sustainability. -/- 3. Introduce regulated price stabilization for essential goods. -/- Phase 2: Global Economic Integration -/- 1. Establish international economic councils to guide balance-driven policies. -/- 2. Reform global trade agreements to prioritize fair wages and sustainability. -/- 3. Create a universal economic sustainability index to track progress. -/- Phase 3: AI-Governed Dynamic Economic System -/- 1. Develop real-time AI monitoring for wage-price adjustments. -/- 2. Implement AI-driven smart taxation to prevent wealth inequality. -/- 3. Ensure AI operates under decentralized, transparent governance. -/- Conclusion: The Future of an AI-Driven Balanced Economy -/- By integrating AI with economic policy, we can create a self-regulating economic system that follows the universal law of balance, preventing both extreme poverty and extreme wealth accumulation. This homeostatic economic model ensures that profits, wages, prices, and demand remain in equilibrium, fostering sustainable prosperity for all. -/- . (shrink)

In the era of big data and distributed ecosystems, understanding the origin, flow, and transformation of data across complex infrastructures is critical for ensuring transparency, accountability, and informed decision-making. As data-driven enterprises increasingly rely on hybrid cloud architectures, data lakes, and real-time pipelines, the complexity of tracking data movement and transformations grows exponentially. Traditional data lineage solutions, often based on static metadata extraction or rule-based approaches, are insufficient in dynamically evolving environments and fail to provide granular, context-aware insights. This research (...) introduces an AI-augmented, cognitive graph-based framework for autonomous data lineage, designed to enhance data traceability in large-scale and heterogeneous data ecosystems. The framework leverages cutting-edge machine learning (ML), natural language processing (NLP), and graph-based reasoning techniques to enable intelligent discovery, semantic interpretation, and continuous monitoring of data assets throughout their lifecycle. The core of the solution lies in the construction of a dynamic cognitive graph that represents relationships between datasets, processes, systems, and users, enriched with contextual annotations and temporal dimensions. Our architecture incorporates self-learning mechanisms, enabling adaptive lineage discovery and automated anomaly detection. By applying reinforcement learning and stream analytics, the framework not only maps data flows in real time but also evolves with system changes, schema variations, and business logic updates. It provides both forward and backward traceability, supports impact analysis, and enhances compliance auditing capabilities. Furthermore, our system is capable of processing both structured and unstructured metadata, employing advanced NLP models to extract implicit lineage information from data dictionaries, SQL queries, and documentation. The result is a holistic, intelligent, and scalable data lineage solution that reduces manual intervention, mitigates operational risks, and supports regulatory compliance frameworks such as GDPR, HIPAA, and SOX. Experimental evaluations conducted in hybrid cloud environments using tools such as Apache Kafka, Neo4j, Spark, and Python-based ML libraries demonstrate a significant improvement in lineage coverage, anomaly detection accuracy, and system scalability. Compared to conventional lineage tools, our AI-augmented framework delivers a 30% increase in traceability precision and a 40% reduction in manual effort required for lineage tracking and governance. This research lays the foundation for a new paradigm in data governance, where AI not only enhances observability but enables autonomous cognition within data infrastructure. The framework is poised to play a critical role in enabling data democratization, operational agility, and enterprise-wide data literacy. (shrink)

Artificial Intelligence (AI) and Machine Learning (ML) are transforming the insurance industry by optimizing risk assessment, fraud detection, and customer service. However, the rapid adoption of these technologies raises significant ethical concerns, particularly regarding bias and fairness. This chapter explores the ethical challenges of using AI and ML in insurance risk management, focusing on bias mitigation and fairness enhancement strategies. By analyzing real-world case studies, regulatory frameworks, and technical methodologies, this chapter aims to provide a roadmap for developing ethical AI/ML (...) systems in the insurance sector. It highlights the importance of transparency, accountability, and inclusivity in ensuring equitable outcomes. (shrink)

In recent years, the combination of Artificial Intelligence (AI) and Blockchain technology has garnered significant attention, especially in the healthcare domain. With the increasing reliance on biomedical signal processing for disease diagnosis and treatment, ensuring the security, privacy, and integrity of data has become paramount. Biomedical signals, including electrocardiograms (ECG), electroencephalograms (EEG), and other physiological data, often contain sensitive information. AI models have shown great promise in processing and interpreting these signals, enabling accurate disease detection and personalized healthcare. However, the (...) potential for data tampering, unauthorized access, and privacy concerns pose significant challenges. Blockchain, with its decentralized, tamper-resistant, and secure framework, offers a solution to these challenges. By integrating Blockchain with AI for biomedical signal processing, data can be securely stored, verified, and accessed, ensuring that healthcare providers can rely on the integrity and accuracy of the signals used in AI-based diagnostics. This paper explores the role of Blockchain-enhanced AI solutions for secure biomedical signal processing and data integration, addressing both the technical and ethical challenges in this space. We propose a system that leverages Blockchain to manage the secure transfer and storage of biomedical signals while utilizing AI to analyze and interpret these signals in real time. Blockchain provides an immutable ledger for auditing and validating data provenance, ensuring that the data remains secure throughout the healthcare pipeline. The integration of these two technologies not only enhances the security of biomedical data but also enables more trustworthy AI-driven diagnostics and decision-making in healthcare. (shrink)

For more than two decades, police in the United States have used facial recognition to surveil civilians. Local police departments deploy facial recognition technology to identify protestors’ faces while federal law enforcement agencies quietly amass driver’s license and social media photos to build databases containing billions of faces. Yet, despite the widespread use of facial recognition in law enforcement, there are neither federal laws governing the deployment of this technology nor regulations settings standards with respect to its development. To make (...) matters worse, the Fourth Amendment—intended to limit police power and enacted to protect against unreasonable searches—has struggled to rein in new surveillance technologies since its inception. -/- This Article examines the Supreme Court’s Fourth Amendment jurisprudence leading up to Carpenter v. United States and suggests that the Court is reinterpreting the amendment for the digital age. Still, the too-slow expansion of privacy protections raises challenging questions about racial bias, the legitimacy of police power, and ethical issues in artificial intelligence design. This Article proposes the development of an algorithmic auditing and accountability market that not only sets standards for AI development and limitations on governmental use of facial recognition but encourages collaboration between public interest technologists and regulators. Beyond the necessary changes to the technological and legal landscape, the current system of policing must also be reevaluated if hard-won civil liberties are to endure. (shrink)

Artificially Intelligent (AI) systems have ushered in a transformative era across various domains, yet their inherent traits of unpredictability, unexplainability, and uncontrollability have given rise to concerns surrounding AI safety. This paper aims to demonstrate the infeasibility of accurately monitoring advanced AI systems to predict the emergence of certain capabilities prior to their manifestation. Through an analysis of the intricacies of AI systems, the boundaries of human comprehension, and the elusive nature of emergent behaviors, we argue for the impossibility of (...) reliably foreseeing some capabilities. By investigating these impossibility results, we shed light on their potential implications for AI safety research and propose potential strategies to overcome these limitations. (shrink)

This paper examines two prominent formal trade-offs in artificial intelligence (AI)---between predictive accuracy and fairness, and between predictive accuracy and interpretability. These trade-offs have become a central focus in normative and regulatory discussions as policymakers seek to understand the value tensions that can arise in the social adoption of AI tools. The prevailing interpretation views these formal trade-offs as directly corresponding to tensions between underlying social values, implying unavoidable conflicts between those social objectives. In this paper, I challenge that prevalent (...) interpretation by introducing a sociotechnical approach to examining the value implications of trade-offs. After providing a set-theoretic understanding of these model trade-offs, I argue that their implications cannot be understood in isolation from the technical, psychological, organizational, and social factors that shape the integration of AI models into decision-making pipelines. Specifically, I identify three key considerations---validity and instrumental relevance, compositionality, and dynamics---for contextualizing and characterizing these implications. These considerations reveal that the relationship between model trade-offs and corresponding values depends on critical choices and assumptions. Crucially, judicious sacrifices in one model property for another can, in fact, promote both sets of corresponding values. The proposed sociotechnical perspective thus shows that we can and should aspire to higher epistemic and ethical possibilities than the prevalent interpretation suggests, while offering practical guidance for achieving those outcomes. Finally, I draw out the broader implications of this perspective for AI design and governance, highlighting the need to broaden normative engagement across the AI lifecycle, develop legal and auditing tools sensitive to sociotechnical considerations, and rethink the vital role and appropriate structure of interdisciplinary collaboration in fostering a responsible AI workforce. (shrink)

This paper examines two prominent formal trade-offs in artificial intelligence (AI)---between predictive accuracy and fairness, and between predictive accuracy and interpretability. These trade-offs have become a central focus in normative and regulatory discussions as policymakers seek to understand the value tensions that can arise in the social adoption of AI tools. The prevailing interpretation views these formal trade-offs as directly corresponding to tensions between underlying social values, implying unavoidable conflicts between those social objectives. In this paper, I challenge that prevalent (...) interpretation by introducing a sociotechnical approach to examining the value implications of trade-offs. After providing a set-theoretic understanding of these model trade-offs, I argue that their implications cannot be understood in isolation from the technical, psychological, organizational, and social factors that shape the integration of AI models into decision-making pipelines. Specifically, I identify three key considerations---validity and instrumental relevance, compositionality, and dynamics---for contextualizing and characterizing these implications. These considerations reveal that the relationship between model trade-offs and corresponding values depends on critical choices and assumptions. Crucially, judicious sacrifices in one model property for another can, in fact, promote both sets of corresponding values. The proposed sociotechnical perspective thus shows that we can and should aspire to higher epistemic and ethical possibilities than the prevalent interpretation suggests, while offering practical guidance for achieving those outcomes. Finally, I draw out the broader implications of this perspective for AI design and governance, highlighting the need to broaden normative engagement across the AI lifecycle, develop legal and auditing tools sensitive to sociotechnical considerations, and rethink the vital role and appropriate structure of interdisciplinary collaboration in fostering a responsible AI workforce. (shrink)

One of the predominant debates in AI Ethics is the worry and necessity to create fair, transparent and accountable algorithms that do not perpetuate current social inequities. I offer a critical analysis of Reuben Binns’s argument in which he suggests using public reason to address the potential bias of the outcomes of machine learning algorithms. In contrast to him, I argue that ultimately what is needed is not public reason per se, but an audit of the implicit moral assumptions (...) of societies within which algorithms are built and applied. Public justification is appealing since it offers us the possibility to align the decision-making outcomes of the algorithm with the core moral values of stakeholders within a constitutional democratic society. My concern is that the common moral principles that form the foundation of public reason are not necessarily neutral, as they still express specific moral ideals and normative standards even if there is moral agreement by society as a whole, or among different stakeholders within society. Appealing to such normative standards may thus still lead to algorithmic outcomes being biased as common moral values may very well still be discriminatory even though they are formed from a consensus, and even if public reason is applied as a kind of filter for potential algorithmic outcomes. Hence, I argue that these implicit moral norms within society that we take as a given in public reasoning, need to be audited from generation to generation in order to effectively mitigate potential algorithmic bias. (shrink)

: Financial institutions are required to ensure data accuracy, integrity, and compliance when reporting to regulatory authorities. Reports such as FR 2052a (Liquidity Monitoring), Y-14Q (Stress Testing) necessitate robust data reconciliation (Recon) strategies to maintain regulatory compliance and mitigate risks. This paper explores technical and functional aspects of data reconciliation, highlighting key automation techniques, AI-driven solutions, and statistical methodologies for optimizing financial compliance processes. We analyze data integration challenges, anomaly detection models, and best practices in recon automation to enhance efficiency. (...) Furthermore, case studies demonstrate how leveraging machine learning, cloud computing, and robotic process automation (RPA) can significantly improve financial data integrity. The future of reconciliation strategies is discussed, focusing on real-time monitoring, AI-driven decision intelligence, and blockchain-based audit trails. By implementing these strategies, financial institutions can reduce compliance costs, improve operational efficiency, and enhance regulatory transparency. (shrink)

Over the years, companies have adopted hiring algorithms because they promise wider job candidate pools, lower recruitment costs and less human bias. Despite these promises, they also bring perils. Using them can inflict unintentional harms on individual human rights. These include the five human rights to work, equality and nondiscrimination, privacy, free expression and free association. Despite the human rights harms of hiring algorithms, the AI ethics literature has predominantly focused on abstract ethical principles. This is problematic for two reasons. (...) First, AI principles have been criticized for being vague and not actionable. Second, the use of vague ethical principles to discuss algorithmic risks does not provide any accountability. This lack of accountability creates an algorithmic accountability gap. Closing this gap is crucial because, without accountability, the use of hiring algorithms can lead to discrimination and unequal access to employment opportunities. This paper makes two contributions to the AI ethics literature. First, it frames the ethical risks of hiring algorithms using international human rights law as a universal standard for determining algorithmic accountability. Second, it evaluates four types of algorithmic impact assessments in terms of how effectively they address the five human rights of job applicants implicated in hiring algorithms. It determines which of the assessments can help companies audit their hiring algorithms and close the algorithmic accountability gap. (shrink)

This publication forms a basis for the interdisciplinary development of a certification system for artificial intelligence. In view of the rapid development of artificial intelligence with disruptive and lasting consequences for the economy, society, and everyday life, it highlights the resulting challenges that can be tackled only through interdisciplinary dialogue between IT, law, philosophy, and ethics. As a result of this interdisciplinary exchange, it also defines six AI-specific audit areas for trustworthy use of artificial intelligence. They comprise fairness, transparency, (...) autonomy and control, data protection as well as security and reliability while addressing ethical and legal requirements. The latter are further substantiated with the aim of operationalizability. (shrink)

Întrebarea de bază este, ce este o pseudoştiinţă? Una din cele mai disputate delimitări ale ştiinţei. Mulţi savanţi de renume mondial, unanim recunoscuţi (ca de ex. Charles Darwin) au cochetat de-a lungul timpului cu diverse aspecte ale pseudoştiinţei considerându-le, cu bună credinţă, drept ştiinţă. Şi multe domenii ale pseudoştiinţei actuale au fost, la vremea lor, considerate drept domenii onorabile ale ştiinţei. Chiar şi în prezent, practicanţii pseudoştiinţelor nu recunosc valabilitatea etichetei puse domeniului lor de activitate. Oamenii de ştiinţă au tendinţa (...) să claseze pe loc un domeniu de activitate, în funcţie de cunoştinţele şi cultura lor, drept ştiinţă sau pseudoştiinţă. Dar graniţa dintre ştiinţă şi pseudoştiinţă este în multe cazuri foarte vagă. Într-un fel, această problemă seamănă cu problema filozofică a stabilirii a ce e bine şi ce e rău. Filosofii ştiinţei, cum ar fi Paul Feyerabend, au susţinut că nu este nici posibil, nici de dorit, o distincţie între ştiinţă şi non-ştiinţă. Printre problemele care pot face distincţia dificilă este viteza variabilă de evoluţie între teoriile şi metodologiile ştiinţei ca răspuns la noile date. În plus, standardele specifice aplicabile unui domeniu al ştiinţei ar putea să nu fie aplicabile în alte domenii. După cum se spune în diferite cursuri despre introducerea în ştiinţe, pseudoştiinţa este oricare subiect care pare a fi ştiinţific la prima vedere, sau ai cărui susţinători susţin că este ştiinţific, dar care contravine condiţiilor de testare sau deviază mult de la alte aspecte fundamentale ale metodelor ştiinţifice. Pseudoştiinţa este caracterizată de folosirea unor afirmaţii vagi, exagerate sau care nu se pot testa, supralicitarea confirmării în detrimentul argumentării, lipsa transparenţei pentru teste realizate de alţi experţi, şi o stagnare în dezvoltarea teoriei. CUPRINS: Pseudoştiinţa - Ştiinţa şi pseudoştiinţa - - Metodologie ştiinţifică - - Falsificabilitatea - - Normele Merton - - Refuzul de a recunoaşte problemele - - Critica termenului - Identificarea pseudoştiinţei - Ştiinţa patologică - - Exemplele lui Langmuir - - - Raze N - - - Exemple ulterioare - - Exemple mai noi - - - Poliapa - - - Fuziunea la rece - - - Memoria apei - Antropomorfism - - În preistorie - - În religie şi mitologie - - - Critici - - În ştiinţă - - - Antonim - Criptozoologia - - Referinţe - - Critici - Pseudomatematica - - Unele taxonomii ale pseudomatematicii - - - Încercările de rezolvare a problemelor clasice imposibil de rezolvat - - Practicanţii - - Un exemplu ilustrativ - Radiestezia - - Originea radiesteziei - - Dispozitivele de detecţie - - - Anse - - Evaluarea ştiinţifică a radiesteziei - - - Studiul Kassel - - - Studiu Betz - - - Explicaţii sugerate - Scientologia - - Credinţe - - - Puntea Libertăţii Totale - - - Morala şi etica - - - Triunghiurile ARC şi KRC - - - Viaţa de apoi - - - Dumnezeu - - - Ştiinţa - - Învăţături şi practici - - - Terminologie - - - Interpretare şi context - - - Învăţarea treptată - - - Audit - - - Organismul - - - Naşterea silenţioasă - - - Sărbători - Sincronicitatea - - Principiul - - Exemplu - - Relaţia cu cauzalitatea - - Critici - Programarea neuro-lingvistică - - Tehnici sau set de practici - - Aplicaţii - - - Psihoterapie - - - Alte utilizări - - NLP ca o cvasi-religie - Manipularea şi automanipularea prin cuvinte - - Aflaţi când şi unde se folosesc cuvintele - - Testaţi pentru a vedea cum reacţionaţi la cuvinte - - Controlul sau manipularea prin cuvinte - - Uitaţi-vă la nivelul cuvintelor - - Vedeţi cum vă pot ajuta cuvintele, făcându-se nu doar utile, ci şi frumoase - - Exploraţi lumea mentală a cuvintelor - - - Încercaţi să exploraţi lumea fără cuvinte - - Priviţi din nou totul, pentru prima dată fără cuvinte Pseudofizica - Anti-gravitaţia - - Efecte convenţionale care imită efectele anti-gravitaţiei - - Soluţii ipotetice - - - Scuturi gravitaţionale - - - Cercetări în relativitatea generală în anii 1950 - - - A cincea forţă - - - "Unităţi distorsionate" în relativitatea generală - - - Breakthrough Propulsion Physics Program - - Încercări experimentale şi comerciale - - - Dispozitive giroscopice - - - Gravitatorul lui Thomas Townsend Brown - - - Cuplarea gravitoelectrică - - - Premiul Göde - Energia orgonică - - Dezvoltarea de către Reich a teoriilor sale orgonice - - Cărţile lui Reich - - Evaluarea teoriei - Eter luminifer - - Dezavantaje şi critici - Fuziunea la rece - - Fuziunea cu bule - - Rezultate - - - Producţia de energie şi căldura în exces - - - Heliu, elemente grele, şi neutroni - - Mecanisme propuse - Planete ipotetice: X / Nibiru - - Teorii ale conspiraţiei - - Reacţii publice - - Influenţa culturală - Poliapa (Apa polimerizată) - Maşini alimentate cu apă - - Ce nu sunt maşini alimentate cu apă - - Extragerea energiei din apă - - Hidrogenul ca supliment - - Pilula de benzină şi aditivi Pseudoarheologia - Caracteristici - - Lipsa metodei ştiinţifice - - Opoziţia la regulile arheologice - - Motivaţii naţionaliste - - Motivaţii religioase - Rasele de bază - - Rase de bază, epoci şi subrase - - - Prima rasă de bază (eterică) - - - A doua rasă de bază (hiperboreană) - - - A treia rasă de bază (lemuriană) - - - A patra rasă de bază (atlantidă) - - - A cincea rasă de bază (ariană) - - - A şasea rasă de bază - - - A şaptea rasă de bază - - Migrarea spre Mercur - - Credinţa teosofică în fraternitatea umanităţii - Protocronism - - Istoria protocronismului - - Scrierea dacică - Pământul gol (Intratereştrii) - - Ipoteza Pământului gol concav - Fenomenul 2012 - - Tortuguero - - Chilam Balam - Creaţia inteligentă - - Concepte - - - Complexitatea ireductibilă - - - Complexitatea specifică - - - Universul bine pus la punct - - - Creatorul inteligent - - Mişcarea creaţia inteligentă - - - Religia şi susţinătorii importanţi - Creaţionismul ştiinţific - - Abordări ale ştiinţei creaţiei - - - Religia - - - Afilieri religioase moderne - - - Abordări ştiinţifice - - Critici - - - Ipoteze metafizice - - - Critici religioase - - - Critici ştiinţifice - - - Critici istorice, filozofice, şi sociologice - - Domenii de studiu - - - Biologia creaţionistă - - - Ştiinţele Pământului şi Geofizica - - - Astronomia şi cosmologia - Ufologia - - Statutul ca disciplină ştiinţifică - - - Pseudoştiinţă - - - Aspecte metodologice - Teoria astronautului extraterestru - - Argumente şi susţinători - - Erich von Däniken - - Ipoteza creaţiei - - - Argumentul genetic - - - Cercetarea genetică şi evoluţia creierului Medicina alternativă - Tipuri de medicină alternativă - - Sisteme bazate pe convingeri neştiinţifice sau practici tradiţionale - - Energii supranaturale şi interpretări eronate ale energiilor fizice - Ayurveda - Homeopatia - - Remedii şi tratamente - - - Pregătirea - - - Diluţii - - - Patogeneza - - Reglementări şi prevalenţe - - Opoziţia publică - Medicina energetică - - Clasificarea metodelor - - Convingeri - - Cercetări ştiinţifice - - - Vindecarea la distanţă - - - Vindecarea prin contact - - - Baza de date - - Explicaţii alternative pentru rapoarte pozitive - Reiki - - Practica - - - Vindecarea - - - Tratamentul întregului organism - - - Tratament localizat - - - Respiraţia - - - Trei piloni de bază - Terapia de conversie - Metoda Bates pentru îmbunătăţirea vederii - - Concepte - - - Acomodarea - - - Cauze ale problemelor de vedere - Detoxifierea - - Detoxifierea în medicina alternativă - - - Istoric - - - Tampoane de curăţare şi detoxifiere - - Tipuri de detoxifiere - - - Dezintoxicarea de alcool - - - Dezintoxicarea de droguri - - - Detoxifiere metabolică - - - Medicina alternativă - - Modalităţi de detoxifiere - - - Diete de detoxifiere - - - Curăţirea colonului - - - Metale grele - - - Dispozitive de detoxifiere - - Terapia de chelare - - - Detoxifierea proteică - - Detoxifierea anusului şi intestinelor cu cafea - - - Efecte şi riscuri - - Plasturi (tampoane) de detoxifiere aplicate pe picioare - - - Ce sunt plasturii de detoxifiere (tampoanele de detoxifiere) pentru picior? - - - De ce se aplică plasturii pe picioare? - Fizionomia - - Origini moderne - - Perioada de popularitate - - Ştiinţa modernă - - Utilizarea modernă - Frenologia Paranormal - Activităţi paranormale - - Fantome şi alte entităţi spirituale - - Viaţa extraterestră şi OZN-urile - - Criptide - Cercetări în paranormal - - Abordări anecdotice - - Abordarea observaţiilor participanţilor - - Anomalistica - - Neuroştiinţa - - Critici - Vitalism - - Filozofia - - Ştiinţa - - - Relaţia cu emergentismul - - Mesmerism - - Medicina complementară şi alternativă - Aura - - Tradiţii spirituale - - Teste - - Explicaţii - Profeţii - - Definiţii - - Civilizaţii antice - - Credinţa Bahá'í - - Budism - - China - Religiile abrahamice - - Iudaism - - - She'ol - Experienţe aproape de moarte - - Caracteristici - Viaţa de Apoi (Viaţa de după moarte) - - Filozofia vieţii de Apoi - - - Filozofia modernă - - - Filozofia procesului - - Ştiinţa despre viaţa de Apoi - Modele metafizice ale Vieţii de Apoi - - Reîncarnarea - - Raiul şi iadul - - Limbo - - Purgatoriul - Nemurirea - - Abordări ştiinţifice - - Abordări religioase - - Nemurirea biologică - - - Specii biologice nemuritoare - - - Evoluţia îmbătrânirii - - Speranţe privind nemurirea biologică umană - - - Substanţe care prelungesc durata de viaţă - - - Nemurirea tehnologică - - - Crionica - - - Încărcarea minţii la calculator - - - Cibernetica - - - Nemurirea evoluţionară - Strigoi - Fantome - - Tipologia - - - Context antropologic - - Fantomele şi viaţa de apoi - - Teama de fantome - - Atribute comune - - Locaţii - Locaţii paranormale - România - - Judeţul Bacău - - - Conacul Zarifopol, în Filipeşti - - Bucureşti - - - Mănăstirea Chiajna - - - Hotel Cişmigiu - - - "Casa Diavolului", pe strada General Praporgescu - - - Orfelinatul pe strada Franceză - - - Casa Vernescu pe Calea Victoriei - - - Iazul Vrăjitoarelor - - Judeţul Călăraşi - - - Pădurea Călugăreasa - - Judeţul Cluj - - - Castelul Bánffy - - - Pădurea Hoia - - Judeţul Dâmboviţa - - - Trinitatea Miresei pe DN7 - - Judeţul Dolj - - - Pădurea Radovan - - Judeţul Iaşi - - - Casa Gavril Buzatu pe Manta Roşie - - - Dealul Lunganilor - - Judeţul Maramureş - - - Drumul European E58 lângă Cicărlău Parapsihologia - Terminologie - Cercetări - - Domenii - - Metodologie - - Cercetări experimentale - Percepţiile extrasenzoriale - - Investigarea parapsihologică - - Percepţiile extrasenzoriale şi hipnoza - Psihochinezia (telechinezia) - - Credinţa - - - Subdomenii ale telechineziei - - - Aptitudini notabile ale capabilităţilor psihocinetice Ezoterism - Etimologie - Cosmologia ezoterică - - Gnosticism - - Cabala - - Neoplatonism - - Teosofia şi antroposofia - - Max Theon şi "filosofia cosmică" - Ocultism - - Ştiinţă şi ocultism - - - Calităţi oculte - Magia - - Caracteristici comune în practica magiei - - - Ritualuri - - - Simboluri magice - - - Limbajul magiei - - - Magicieni - - - Vrăjitoria - - Teorii - - - Origini antropologice şi psihologice - Clarviziunea - - Aspecte ale clarviziunii - - Vizualizarea de la distanţă - Geomanţia - Tarot - - Arcana mare şi arcana mică - - Utilizare - - - Cărţi inversate - - - Desfăşurări - Masoneria - - Istoria masoneriei - - Loja masonică - - Structura masoneriilor - - - Recunoaşterea masonică reciprocă - Taoism - - Categorisire - - Ceaiul şi taoismul - - Credinţe taoiste - - Principii - - - Tao - - - De (Te) - - - Wu wei - - - Pu - - Spiritualitatea - - Escatologia Astrologia - Principii şi practici - - Astrologia occidentală - - Astrologia hindusă - - Astrologia chineză şi din Asia de Est - Astrologia şi ştiinţa - - Delimitarea - Astrohărţi - Principiile de bază ale astrologiei - - Modele astrologice - - Astrologia predictivă - Tradiţii în astrologie - - Tradiţii istorice - - Tradiţii ezoterice - Horoscop - - Etimologie - - Concepte în astrologia occidentală - - - Unghiuri - - - Zodiacul - - - Case - - Construcţia unui horoscop în astrologia occidentală - - - Case - - - Plasamente ale planetelor - - - Aspecte - - - Ascendentul - - Horoscopul chinez - Bioritm - - Teoria - - Calculul - - Plauzibilitate Vrăjitoria - Definiţii - Practici invocate de vrăjitoare - - Descântece - - Invocarea morţii - Vrăjitoarele bune - Demonologia Referinţe Despre autor - Nicolae Sfetcu - - De același autor - - Contact Editura - MultiMedia Publishing . 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Applying Modern Monetary Theory to the Philippines: Achieving Economic Balance Through Natural Laws -/- Introduction -/- The Philippines faces persistent economic challenges, including slow GDP growth, high income inequality, inflationary pressures, and overpopulation. Traditional economic policies often focus on austerity, borrowing limits, and foreign investments, but these approaches fail to address the root causes of economic imbalance. -/- Modern Monetary Theory (MMT) offers an alternative by allowing the government to issue money to finance public spending without relying on foreign debt (...) or excessive taxation. However, to prevent inflation and ensure long-term stability, government spending must be directed toward productive investments. This aligns with my universal formula, which is based on the universal law of balance in nature—ensuring that all systems, including economic ones, function without defects. -/- By integrating MMT with GDP growth, GDP per capita, the Gini coefficient (income equality), population regulation, and good governance, the Philippines can achieve sustainable economic progress while maintaining balance. -/- The Role of a Good and Non-Corrupt Government in Implementing MMT -/- MMT gives governments the power to create money, making it an incredibly powerful tool—but also a dangerous one if misused. A corrupt government can misallocate funds, cause hyperinflation, and worsen inequality. Therefore, strong leadership, transparency, and accountability are essential for MMT to work. -/- Eliminating corruption ensures that newly created money is invested in productive sectors rather than being stolen or wasted. -/- Strict financial oversight and independent institutions must monitor government spending. -/- A well-structured economic plan, free from political interests, must be followed to ensure MMT benefits all Filipinos, not just the elite. -/- If MMT is implemented by a corrupt government, it will only lead to inflation, economic collapse, and further inequality. The law of karma teaches that every action has consequences—if government spending is abused, the entire economy will suffer. -/- Using MMT to Increase the Philippines’ GDP Without Inflation -/- 1. Infrastructure Development -/- The Philippines suffers from poor infrastructure, leading to high transportation and electricity costs. Government investment in roads, ports, and energy projects would improve economic efficiency, reducing production costs and increasing business competitiveness. -/- The government can print money under MMT to fund major infrastructure projects, provided the projects enhance productivity. -/- Improved infrastructure will increase GDP by facilitating trade, reducing delays, and boosting industrial growth. -/- With proper planning, this investment will not cause inflation because it adds real value to the economy. -/- However, for infrastructure spending to be effective, the government must eliminate corruption in project implementation. Ghost projects, overpricing, and political kickbacks will waste public money and increase inflation without creating real economic value. -/- 2. Investing in Renewable Energy -/- The Philippines relies heavily on imported fossil fuels, making it vulnerable to price fluctuations. A shift toward solar, wind, and geothermal energy would: -/- Reduce long-term electricity costs, helping businesses expand without raising prices. -/- Make the country energy independent, lowering the need for foreign currency reserves. -/- Increase GDP by creating green energy jobs and technological innovations. -/- A good government will prioritize long-term energy security over short-term political interests. Corrupt officials, however, may block renewable energy projects in favor of profit-driven deals with fossil fuel industries, preventing the country from achieving energy independence. -/- 3. Expanding Manufacturing and Industrialization -/- The Philippine economy is heavily dependent on services (such as BPOs) and overseas remittances. To create long-term stability, the country must expand its manufacturing sector. -/- Government spending should prioritize local industries, such as electronics, semiconductors, and agribusiness processing. -/- Subsidies and incentives should be given to businesses that create jobs and produce high-value goods. -/- Export-oriented manufacturing would increase GDP while keeping money circulation within productive sectors, preventing inflation. -/- A corrupt government, however, may award subsidies and contracts based on political favors rather than economic merit, leading to inefficiency and wasted resources. A good and competent government will ensure that industrial policies are based on merit, efficiency, and long-term economic benefits. -/- 4. Research, Innovation, and Digital Transformation -/- Government investment in science, technology, and artificial intelligence (AI) would drive sustainable economic growth. -/- A national AI and automation strategy can improve industries such as agriculture, logistics, and healthcare, leading to higher GDP. -/- Government-funded research and technology parks can support Filipino startups and entrepreneurs. -/- This will help the country move from a consumer-driven economy to a technology and knowledge-based economy, increasing long-term wealth. -/- Without strong governance and anti-corruption measures, however, research funding may be misused, misallocated, or given to unqualified individuals. The universal law of balance requires that public resources be managed efficiently and fairly to maximize their benefits. -/- GDP Per Capita: Ensuring Growth Benefits Every Filipino -/- While GDP growth is important, it must translate to real improvements in people’s lives. A high GDP with a rapidly growing population leads to a lower GDP per capita, keeping the majority poor. -/- Government policies must regulate population growth through education and family planning. -/- Higher GDP per capita ensures that public investments in healthcare, education, and housing can meet the needs of citizens. -/- A well-balanced population ensures that economic growth does not lead to overconsumption of resources. -/- The Gini Coefficient: Reducing Income Inequality in the Philippines -/- The Philippines has one of the highest income inequality rates in Southeast Asia. The Gini coefficient reveals that wealth is concentrated in the hands of a few, while many struggle to survive. -/- MMT can be used to: -/- Fund free quality education and vocational training, allowing Filipinos to get better-paying jobs. -/- Provide universal healthcare, ensuring that people are not trapped in poverty due to medical expenses. -/- Invest in affordable housing and social safety nets for vulnerable populations. -/- Without addressing inequality, economic growth will only benefit the elite, leading to social unrest and instability. However, corrupt leaders often resist wealth redistribution because they benefit from maintaining economic inequality. A non-corrupt government is necessary to ensure fair wealth distribution. -/- Ensuring MMT Aligns with the Universal Law of Balance -/- The Philippines must apply MMT carefully to prevent economic imbalance. Simply printing money without strategic allocation will lead to inflation and instability. -/- Strict anti-corruption policies must be enforced to ensure MMT is used only for productive investments. -/- Public funds should be managed transparently, with regular audits and independent oversight. -/- Government leaders must be held accountable for economic decisions, ensuring they act in the best interest of all Filipinos. -/- A corrupt and incompetent government will lead to economic collapse under MMT, while a good, disciplined, and visionary government can use it to create lasting prosperity and stability. -/- Conclusion -/- Modern Monetary Theory, when properly applied, aligns with the universal law of balance in nature by ensuring that economic systems function without defects. The Philippines can use MMT to: -/- Increase GDP by investing in infrastructure, renewable energy, and industrialization. -/- Ensure GDP per capita growth by regulating population and creating sustainable jobs. -/- Reduce income inequality through education, healthcare, and wealth redistribution. -/- Maintain economic balance by applying feedback mechanisms such as taxation, productivity growth, and responsible government spending. -/- However, MMT requires a government that is competent, transparent, and corruption-free. Without ethical leadership, MMT will be abused and lead to inflation, economic collapse, and inequality. The law of balance demands that all systems—including governance—function properly to achieve economic stability. -/- By ensuring good governance, economic discipline, and strategic spending, the Philippines can use MMT to build a just, prosperous, and balanced society. -/- . (shrink)

The Universal Formula for Eliminating Government Corruption: A Natural Law-Based Approach -/- Introduction -/- Government corruption is one of the most persistent obstacles to societal progress, leading to economic decline, weakened institutions, and widespread inequality. Traditional anti-corruption measures—such as stricter laws, transparency initiatives, and public awareness campaigns—have failed to fully eliminate corruption because they do not address the problem at a systemic and scientific level. -/- By applying the universal formula, which is based on the universal law of balance in (...) nature, we can understand corruption as a systemic defect—a violation of natural equilibrium that causes inefficiency and societal suffering. This essay will provide a comprehensive scientific explanation of corruption, supported by research, and propose a complete solution that integrates education, institutional reforms, AGI-driven governance, cultural adaptation, and strategic implementation. -/- 1. The Science Behind Corruption: A Systemic Imbalance -/- A. Psychological and Biological Causes → Internal Homeostasis -/- Scientific research suggests that corruption is rooted in human psychology and biology, particularly in: -/- Evolutionary survival instincts – Studies indicate that self-preservation and resource hoarding behaviors evolved to ensure survival but can also lead to greed and corruption in modern societies. (Reference: Trivers, 1971 – Evolutionary theory of reciprocity) -/- Cognitive biases – Research in behavioral psychology shows that self-justification, moral disengagement, and in-group favoritism make individuals rationalize corrupt behavior. (Reference: Bandura, 1999 – Moral disengagement theory) -/- Neurological reward systems – Studies using fMRI scans reveal that bribery activates brain regions associated with pleasure, reinforcing corrupt behaviors. (Reference: Ariely & Loewenstein, 2006 – Neurological basis of unethical behavior) -/- Universal Formula Solution: -/- Educational reprogramming is needed to counteract these internal imbalances. -/- Schools should instill ethical reasoning, self-regulation, and critical thinking from an early age. -/- Leaders must be trained to recognize that corruption leads to long-term systemic instability, disrupting both individual and societal balance. -/- B. Economic Incentives and Systemic Defects → Structural Homeostasis -/- Economists have long observed that corruption is often a rational response to flawed systems where: -/- Low salaries and financial insecurity create incentives for bribery. (Reference: Becker & Stigler, 1974 – Economics of crime and punishment) -/- Weak regulatory oversight allows corruption to persist with minimal consequences. -/- Lack of transparency in financial systems enables embezzlement and fraud. -/- Universal Formula Solution: -/- The economic system must be free of defects—governments should: -/- Ensure fair wages for public officials to reduce bribery incentives. -/- Use blockchain-based transparency systems to track public spending. -/- Implement AI-driven financial audits to detect corruption in real time. -/- C. Political and Institutional Weakness → Governance Homeostasis -/- Corruption thrives when institutions fail to enforce accountability and transparency. -/- The Principal-Agent Problem: Public officials (agents) may act in their own interests rather than serving the public (principals). (Reference: Rose-Ackerman, 1978 – Corruption and governance theory) -/- Legal Loopholes: Weak anti-corruption laws allow elites to manipulate the system. -/- Lack of Whistleblower Protections: Fear of retaliation prevents corruption from being exposed. -/- Universal Formula Solution: -/- Governments must function like biological systems, with constant monitoring and correction mechanisms: -/- Real-time transparency tools (AI-driven monitoring of government transactions). -/- Independent anti-corruption agencies with full enforcement powers. -/- Legal frameworks based on the principle of natural balance, where punishments restore equilibrium rather than being arbitrary. -/- D. Cultural Normalization of Corruption → Collective Homeostasis -/- In some societies, corruption is seen as an accepted norm due to: -/- Patronage networks and nepotism embedded in political cultures. -/- Religious and social justifications for bribery (“gifts” given in exchange for favors). -/- Distrust in the justice system, leading to reliance on informal corruption-based solutions. -/- Universal Formula Solution: -/- A holistic education system must be implemented to reprogram societal attitudes toward corruption. -/- Schools should teach: -/- The universal law of balance and its ethical implications. -/- The cause-and-effect nature of corruption—how even small acts of dishonesty contribute to systemic collapse. -/- Critical thinking skills to challenge corrupt norms and misinformation. -/- 2. Case Studies: Applying the Universal Formula to Real-World Corruption -/- Case Study 1: Singapore’s Zero-Tolerance Approach -/- Singapore successfully reduced corruption by: -/- Increasing public sector salaries to remove bribery incentives. -/- Strict enforcement of anti-corruption laws, ensuring accountability. -/- Cultural reprogramming through education and public campaigns. -/- Universal Formula Connection: Singapore’s model aligns with systemic homeostasis, ensuring a balance between economic incentives, strong institutions, and ethical education. -/- Case Study 2: Scandinavian Countries – Transparency and Trust -/- Nordic countries (Denmark, Sweden, Norway) maintain low corruption levels through: -/- Public trust in institutions based on long-term systemic balance. -/- High transparency in government spending. -/- Strong legal frameworks with immediate corrective feedback mechanisms. -/- Universal Formula Connection: These countries maintain governance homeostasis, preventing corruption through self-correcting institutional designs. -/- 3. Implementing the Universal Formula to Eliminate Corruption -/- A. Education Reform: The Foundation of Ethical Governance -/- Integrate the universal law of balance into curricula from elementary to higher education. -/- Teach cause-and-effect relationships in governance (e.g., how small bribes lead to systemic collapse). -/- Develop leadership training programs that emphasize ethical decision-making based on natural balance. -/- B. Institutional Reforms: Creating a Self-Correcting System -/- Implement blockchain-based transparency systems for public finance. -/- Strengthen whistleblower protections to ensure safe reporting of corruption. -/- Decentralize power to reduce opportunities for monopolistic corruption. -/- C. AGI-Driven Ethical Governance -/- Artificial General Intelligence (AGI) can be programmed with the universal formula to: -/- Monitor government transactions and detect corruption patterns. -/- Ensure transparent decision-making based on systemic balance. -/- Remove human cognitive biases from governance. -/- D. Cultural Adaptation: Tailoring Solutions to Different Societies -/- In high-corruption societies, initial reforms should focus on education and small wins to shift cultural attitudes. -/- In developing countries, AGI-driven transparency tools can bypass weak institutions. -/- In democratic nations, citizen engagement should be emphasized to create self-regulating governance. -/- --- -/- 4. Addressing Challenges and Counterarguments -/- Objection: “Corruption is inevitable in human nature.” Response: Human nature includes both corruption and ethical reasoning—education determines which dominates. -/- Objection: “Elites will resist systemic reforms.” Response: AGI-driven transparency tools and mass education campaigns can reduce elite control. -/- Objection: “Implementing these changes is unrealistic.” Response: Small-scale pilots in cities or institutions can demonstrate success before national adoption. -/- --- -/- Conclusion: The Universal Formula as the Ultimate Solution to Corruption -/- Corruption is a systemic defect—a violation of the universal law of balance in nature. By applying scientific principles of homeostasis, cause and effect, and feedback regulation, we can create a corruption-free governance model. The universal formula offers the only complete solution, integrating education, institutional reform, AGI-driven oversight, and cultural adaptation. -/- If implemented, this model could lead to a world where governance functions as a perfectly balanced system—free of defects, ethical, and in harmony with natural law. -/- . (shrink)

Typically, fair machine learning research focuses on a single decision maker and assumes that the underlying population is stationary. However, many of the critical domains motivating this work are characterized by competitive marketplaces with many decision makers. Realistically, we might expect only a subset of them to adopt any non-compulsory fairness-conscious policy, a situation that political philosophers call partial compliance. This possibility raises important questions: how does partial compliance and the consequent strategic behavior of decision subjects affect the allocation outcomes? (...) If k% of employers were to voluntarily adopt a fairness-promoting intervention, should we expect k% progress (in aggregate) towards the benefits of universal adoption, or will the dynamics of partial compliance wash out the hoped-for benefits? How might adopting a global (versus local) perspective impact the conclusions of an auditor? In this paper, we propose a simple model of an employment market, leveraging simulation as a tool to explore the impact of both interaction effects and incentive effects on outcomes and auditing metrics. Our key findings are that at equilibrium: (1) partial compliance by k% of employers can result in far less than proportional (k%) progress towards the full compliance outcomes; (2) the gap is more severe when fair employers match global (vs local) statistics; (3) choices of local vs global statistics can paint dramatically different pictures of the performance vis-a-vis fairness desiderata of compliant versus non-compliant employers; (4) partial compliance based on local parity measures can induce extreme segregation. Finally, we discuss implications for auditors and insights concerning the design of regulatory frameworks. (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)

As organizations increasingly adopt cloud computing to enhance scalability, efficiency, and costeffectiveness, securing cloud-based applications and data storage has become a paramount concern. This shift has redefined the role of network engineers, who are now at the forefront of implementing and managing secure cloud infrastructures. This research paper examines the critical responsibilities of network engineers in safeguarding cloud environments, focusing on the challenges, strategies, and tools they employ to mitigate risks and ensure data integrity. The paper identifies key challenges associated (...) with cloud security, including data breaches, misconfigured systems, insecure interfaces, and insider threats. These vulnerabilities are further exacerbated by the dynamic and decentralized nature of cloud ecosystems, which often involve multi-tenant architectures and complex integrations. The study underscores the need for network engineers to adapt to these complexities by acquiring specialized skills in cloud security protocols and emerging technologies. A significant focus is placed on the implementation of robust network security frameworks, such as zero-trust architecture, which emphasizes the principle of "never trust, always verify." Network engineers play a crucial role in deploying access control measures, encryption mechanisms, and intrusion detection systems to safeguard sensitive data. Additionally, the research highlights the importance of continuous monitoring and threat intelligence to identify and address vulnerabilities proactively. The integration of automation and artificial intelligence (AI) in cloud security is another critical area explored in this study. Automation tools enable network engineers to streamline routine tasks, such as patch management and configuration audits, thereby reducing human error and response time. AI-driven solutions, on the other hand, enhance threat detection capabilities by analyzing large datasets for anomalous patterns and potential attacks. The paper also discusses the collaborative responsibilities of network engineers, who must work closely with developers, cloud providers, and organizational stakeholders to align security measures with business objectives. This includes implementing secure DevOps practices, ensuring compliance with industry regulations, and conducting regular security audits. Case studies of successful cloud security implementations are presented to illustrate the effectiveness of these collaborative approaches. In conclusion, this research emphasizes the evolving role of network engineers as pivotal defenders of cloud-based systems. It calls for continuous professional development to stay abreast of emerging threats and technologies, as well as fostering a culture of shared responsibility for security within organizations. By adopting a proactive and comprehensive approach, network engineers can significantly enhance the resilience of cloud infrastructures, ensuring the confidentiality, integrity, and availability of critical data and applications. This study aims to provide actionable insights and a strategic framework for network engineers and organizations striving to navigate the complexities of securing cloud environments. Through a combination of technological expertise, innovative tools, and collaborative practices, network engineers are positioned to address the unique challenges posed by cloud computing and play a central role in shaping the future of secure digital ecosystems. (shrink)

The contribution of this paper is a comprehensive cybersecurity framework to secure cloud hosted Guidewire implementations by addressing critical security challenges such as threat detection, incident response, compliance, and system performance. Based on advanced technologies like machine learning, behavioral analytics and auto patching, the framework detects and mitigates known and unknown threats, incidentally zero-day exploit. The system does this through micro segmenting, behavioral anomaly detection, and automated patch orchestration in a way that does not render the system unperforming. Key performance (...) metrics of threat detection time (less than 3 seconds), incident response (patching within 5 minutes) and system availability (99.95% uptime) are all tested as the framework outperforms in all of these. Additionally, the framework ascertains industry standards such as GDPR and HIPAA via automated audit trails and ongoing monitoring. Compared to the currently deployed cloud security, the proposed approach, with a special focus on more secure the Guidewire application deployed in the cloud, offers a multi layered security approach to the modules specific to the Guidewire. Though powerful, the framework also suffers from complexity in its deployment, overhead in terms of performance and a reliance on cloud provider-specific features. The scalability will need to improve, and the product will need to support multiple clouds and integrate advanced technology such as quantum computing and AI-powered threat intelligence. This work sets a solid basis for the protection of cloud-based Guidewire systems against future cyber threats while maintaining operational continuity and system compliance. (shrink)

The rise of remote work has redefined the modern workplace, driven by advancements in technology and the global need for flexible work environments. While remote work offers increased productivity and employee satisfaction, it has also introduced a host of network security challenges. Organizations must contend with securing sensitive data and critical applications across distributed networks, many of which extend beyond traditional corporate perimeters. This research paper explores the multifaceted security threats associated with remote work environments, including phishing attacks, unpatched software (...) vulnerabilities, unsecured home networks, and the misuse of personal devices. These challenges are exacerbated by a lack of centralized control and the increasing sophistication of cybercriminals exploiting these vulnerabilities. Key findings highlight the importance of robust authentication protocols, such as multi-factor authentication (MFA), to ensure secure access to corporate resources. Endpoint security solutions, including encryption and antivirus software, play a critical role in safeguarding data on remote devices. Moreover, the paper emphasizes the significance of implementing virtual private networks (VPNs) and zero-trust security frameworks to reduce attack surfaces and limit unauthorized access. Another critical focus is the role of employee training and awareness programs in mitigating human error, which remains a leading cause of data breaches. This study also underscores the necessity of proactive threat detection and response mechanisms to identify and address breaches in real-time. Advanced technologies, such as artificial intelligence (AI) and machine learning (ML), are pivotal in enhancing these capabilities, enabling organizations to adapt to the rapidly evolving cyber threat landscape. Furthermore, comprehensive network segmentation strategies are discussed to isolate critical systems and minimize the impact of potential breaches. The research incorporates case studies of successful implementations of these solutions, demonstrating their effectiveness in fortifying network security for remote operations. A comparative analysis is presented to evaluate the cost-effectiveness and scalability of various approaches, catering to organizations of different sizes and industries. The findings suggest that a multi-layered defense strategy is essential for achieving resilience in remote work environments. The paper concludes with actionable recommendations for organizations seeking to enhance their security posture. These include prioritizing regular updates and patches, adopting secure cloud-based collaboration tools, and conducting periodic security audits. Additionally, fostering a culture of cybersecurity awareness among employees is paramount to addressing the human factor in cyber risks. By addressing the unique challenges posed by remote work, this study provides a comprehensive roadmap for protecting data and applications in decentralized environments. The insights gained aim to equip organizations with the tools and knowledge necessary to navigate the complexities of securing remote work infrastructures while maintaining business continuity and trust. (shrink)

Organizations are increasingly relying on data to inform decision making, as we progress to ever more advanced digital economy and a world where data creates competitive advantages. This may be challenging in the presence of data siloes—that is, having the data stored and managed in isolation by departments as opposed to on a centralized database. This approach leads to inefficiencies, duplications and lost opportunities for a more integrated picture. This causes challenges both in having aligned strategies across departments but it (...) is also severely limiting the capacity of organisations to actualise the transformative potential that data and data innovation has to offer their customers. Data, a separate source, is evolving into a contiguous environment that nurtures and merges its findings, overcoming its silos. Data silos pose an Albatross because they lead to an information asymmetry and have become the new norm thanks to legacy systems, the independence of individual departments and lapses in governance practices. Thus resulting in jagged data architectures where useful insights are being locked in these silos and out of reach for the relevant stake holders. Addressing these problems will require a coordinated effort that includes technological innovation and organizational change. Data lakes, data meshes and advanced analytics technologies allow businesses to aggregate heterogenous data sources to create a single source of truth across the organization. Structured and unstructured information storing in data lakes for business scalability and access Data meshes, on the other hand, emphasize decentralized ownership and domainoriented architectures so that teams can treat data like a product. Likewise, at a higher-level analytics and AI enhance the ability to converge data from various sources, automate insights and enable pre-decision making. The analysis offers a detailed overview of the problem of data silos, outlining their implications for operational efficiency, collaboration and regulatory compliance. It also suggests effective integration approaches, which include both technical fixes and cultural changes. Organizational buy-in is noted as a key enabler of success as IT hardware/software is no real remedy for the deeper root cause of silos created by human and cultural factors. To promote adoption, training programs, collaboration and communication of the advantages of integration are vital. Real-world case studies and quantitative analyses illustrate key benefits of unified data insights. For instance, 20-30% improvement in operational efficiency, decision-making agility, and better customer experience seems to be the new norm for organizations embarking on their journey with unified data platforms. With unified insights, organizations can recognize trends, anticipate changes in the market, and react accordingly, providing them with a competitive advantage as data-driven worlds continue to emerge. Unified data platforms also bring value to regulatory compliance, especially to audits before bodies such as the GDPR; they also ensure compliance with data protection laws (i.e. protecting private data from being leaked). Unified data platforms require technology and can be challenging, but we'll also see their revolutionary potential illustrated by real-world case studies. Moreover, a case in point is a multinational company that leveraged a data lake approach that led to 25% savings in recurring operational expenses and reduced time taken to drive data-based decisions. One such case study shows that silo breaking through aggregating customer relationship management (CRM) across business units resulted in 15% increased customer retention, making it clear how data synergy can translate directly to business objective. (shrink)

As organizations increasingly adopt cloud computing to enhance scalability, efficiency, and costeffectiveness, securing cloud-based applications and data storage has become a paramount concern. This shift has redefined the role of network engineers, who are now at the forefront of implementing and managing secure cloud infrastructures. This research paper examines the critical responsibilities of network engineers in safeguarding cloud environments, focusing on the challenges, strategies, and tools they employ to mitigate risks and ensure data integrity. The paper identifies key challenges associated (...) with cloud security, including data breaches, misconfigured systems, insecure interfaces, and insider threats. These vulnerabilities are further exacerbated by the dynamic and decentralized nature of cloud ecosystems, which often involve multi-tenant architectures and complex integrations. The study underscores the need for network engineers to adapt to these complexities by acquiring specialized skills in cloud security protocols and emerging technologies. A significant focus is placed on the implementation of robust network security frameworks, such as zero-trust architecture, which emphasizes the principle of "never trust, always verify." Network engineers play a crucial role in deploying access control measures, encryption mechanisms, and intrusion detection systems to safeguard sensitive data. Additionally, the research highlights the importance of continuous monitoring and threat intelligence to identify and address vulnerabilities proactively. The integration of automation and artificial intelligence (AI) in cloud security is another critical area explored in this study. Automation tools enable network engineers to streamline routine tasks, such as patch management and configuration audits, thereby reducing human error and response time. AI-driven solutions, on the other hand, enhance threat detection capabilities by analyzing large datasets for anomalous patterns and potential attacks. The paper also discusses the collaborative responsibilities of network engineers, who must work closely with developers, cloud providers, and organizational stakeholders to align security measures with business objectives. This includes implementing secure DevOps practices, ensuring compliance with industry regulations, and conducting regular security audits. Case studies of successful cloud security implementations are presented to illustrate the effectiveness of these collaborative approaches. In conclusion, this research emphasizes the evolving role of network engineers as pivotal defenders of cloud-based systems. It calls for continuous professional development to stay abreast of emerging threats and technologies, as well as fostering a culture of shared responsibility for security within organizations. By adopting a proactive and comprehensive approach, network engineers can significantly enhance the resilience of cloud infrastructures, ensuring the confidentiality, integrity, and availability of critical data and applications. This study aims to provide actionable insights and a strategic framework for network engineers and organizations striving to navigate the complexities of securing cloud environments. Through a combination of technological expertise, innovative tools, and collaborative practices, network engineers are positioned to address the unique challenges posed by cloud computing and play a central role in shaping the future of secure digital ecosystems. (shrink)

The Salivaomics Knowledge Base (SKB) is designed to serve as a computational infrastructure that can permit global exploration and utilization of data and information relevant to salivaomics. SKB is created by aligning (1) the saliva biomarker discovery and validation resources at UCLA with (2) the ontology resources developed by the OBO (Open Biomedical Ontologies) Foundry, including a new Saliva Ontology (SALO). We define the Saliva Ontology (SALO; http://www.skb.ucla.edu/SALO/) as a consensus-based controlled vocabulary of terms and relations dedicated to the salivaomics (...) domain and to saliva-related diagnostics following the principles of the OBO (Open Biomedical Ontologies) Foundry. The Saliva Ontology is an ongoing exploratory initiative. The ontology will be used to facilitate salivaomics data retrieval and integration across multiple fields of research together with data analysis and data mining. The ontology will be tested through its ability to serve the annotation ('tagging') of a representative corpus of salivaomics research literature that is to be incorporated into the SKB. Background Saliva (oral fluid) is an emerging biofluid for non-invasive diagnostics used in the detection of human diseases. The need to advance saliva research is strongly emphasized by the National Institute of Dental and Craniofacial Research (NIDCR), and is included in the NIDCR's 2004- 2009 expert panel long-term research agenda [1]. The ability to monitor health status, disease onset, progression, recurrence and treatment outcome through noninvasive means is highly important to advancing health care management. Saliva is a perfect medium to be explored for personalized individual medicine including diagnostics, offering a non-invasive, easy to obtain means for detecting and monitoring diseases. Saliva testing potentially allows the patient to collect their own saliva samples at home, yielding convenience for the patient and savings in health costs, and facilitating multiple sampling. Specimen collection is less objectionable to patients and easier in children and elderly individuals. Due to these advantages. (shrink)

There is a need recognized by the National Institute of Dental & Craniofacial Research and the National Cancer Institute to advance basic, translational and clinical saliva research. The goal of the Salivaomics Knowledge Base (SKB) is to create a data management system and web resource constructed to support human salivaomics research. To maximize the utility of the SKB for retrieval, integration and analysis of data, we have developed the Saliva Ontology and SDxMart. This article reviews the informatics advances in saliva (...) diagnostics made possible by the Saliva Ontology and SDxMart. (shrink)

We describe the rationale for an application ontology covering the domain of human body fluids that is designed to facilitate representation, reuse, sharing and integration of diagnostic, physiological, and biochemical data, We briefly review the Blood Ontology (BLO), Saliva Ontology (SALO) and Kidney and Urinary Pathway Ontology (KUPO) initiatives. We discuss the methods employed in each, and address the project of using them as starting point for a unified body fluids ontology resource. We conclude with a description of how the (...) body fluids ontology initiative may provide support to basic and translational science. (shrink)

This article sheds light on managing and utilizing scientific and technological funds (Sci-Tech funds) in Vietnam.

On 24th February 2025, Justin Mike (United States) wrote a review for Wild Wise Weird as follows: “Wild Wise Weird celebrates the wild spirit, the wisdom gained from unusual experiences, and the eccentric qualities that define us as individuals, thereby capturing the beauty of embracing authenticity. It serves as a reminder that being unique is something to be proud of, not just acceptable.” The review made me feel really relevant to the content of the book. I was curious what AI (...) would think of Mike’s review, so I asked Gemini “what do you think of the review?”. (shrink)

This article proposes a unified solution to the mind-body problem, grounded in the philosophical framework of Ethical Empirical Rationalism. By presenting a mathematical model of the mind-body interaction, we oƯer a dynamic feedback loop that resolves the traditional dualistic separation between mind and body. At the core of our model is the concept of essence—an eternal, metaphysical truth that sustains both the mind and body. Through coupled diƯerential equations, we demonstrate how the mind and body are two expressions of the (...) same essence, interacting in a continuous and harmonious relationship. This approach provides a new perspective on the mind-body relationship, grounded in both empirical evidence and metaphysical insight. Keywords: Mind-body problem, Unmoved Mover, Essence, Unified Theory, Feedback Loop, Ethical Empirical Rationalism, Mathematical Modeling. (shrink)

Hiện nay, chế độ sở hữu ở Việt Nam đã có những đổi mới cơ bản, nhưng vẫn còn những khác biệt rất lớn so với chế độ sở hữu ở các nền kinh tế thị trường hiện đại. Trong cơ cấu của chế độ sở hữu ở Việt Nam, tỷ trọng của sở hữu nhà nước còn quá lớn; kinh tế nhà nước giữ vai trò chủ đạo… Chính những khác biệt này đã làm cho nền kinh tế thị (...) trường Việt Nam bị méo mó và giảm lợi thế cạnh tranh quốc gia. Do vậy, công cuộc đổi mới và hoàn thiện chế độ sở hữu ở Việt Nam phải hướng tới việc khắc phục những hạn chế trên và đạt tới sức cạnh tranh ngang hàng với các nền kinh tế thị trường hiện đại khác. (shrink)

Climate change is affecting communities across the globe, yet those most vulnerable to its impacts are often the last to receive the financial assistance they need. A recent critical review by Venner, García-Lamarca, and Olazabal (2024) examines how climate adaptation finance—funding intended to help societies adjust to the impacts of climate change—is distributed. The findings are concerning: despite repeated global commitments to prioritize those most at risk, adaptation finance tends to benefit the most powerful and well-resourced actors rather than the (...) communities that need it most. (shrink)

ĐỀ CƯƠNG HỌC PHẦN VĂN HÓA KINH DOANH 1. Tên học phần: VĂN HÓA KINH DOANH (BUSINESS CULTURE) 2. Mã học phần: BMGM1221 3. Số tín chỉ: 2 (24,6) (để học được học phần này, người học phải dành ít nhất 60 giờ chuẩn bị cá nhân).

Tại Việt Nam và trong lĩnh vực giáo dục nói riêng, ChatGPT ngày càng được chấp nhận và sử dụng rộng rãi trong rất nhiều hoạt động học tập. Chính vì thế, nghiên cứu này nhằm đánh giá mức độ phổ biến của ChatGPT đối sinh viên tại Hà Nội, đồng thời xem xét sự khác biệt giữa các đặc điểm cá nhân trong việc cải thiện kết quả học tập sau khi sử dụng ChatGPT. Nghiên cứu được thực hiện (...) bằng phương pháp định lượng với dữ liệu thu thập từ 401 sinh viên tại Hà Nội. Từ kết quả nghiên cứu, có 389 sinh viên (chiếm 97,01%) biết và sử dụng ChatGPT trong các hoạt động học tập của mình. Ngoài ra, sinh viên năm nhất, năm hai, năm ba, năm tư sau khi sử dụng ChatGPT có cải thiện trong hoạt động học tập khác nhau, tuy nhiên yếu tố giới tính lại không có ảnh hưởng. Trên cơ sở kết quả nghiên cứu, nhóm tác giả đưa ra một số nguyên nhân và đề xuất giúp ChatGPT được ứng dụng rộng rãi hơn nữa tại các trường đại học. (shrink)

(Mặt trận) - Chế độ sở hữu trong nền kinh tế thị trường định hướng xã hội chủ nghĩa Việt Nam trước hết phải tuân theo các nguyên tắc của nền kinh tế thị trường hiện đại. Trong các nguyên tắc của nền kinh tế thị trường hiện đại, nguyên tắc sở hữu tư nhân là nền tảng của nền kinh tế thị trường - là nguyên tắc quan trọng. Xa rời nguyên tắc này, dù chúng ta cố gắng xây (...) dựng nền kinh tế thị trường thì đó vẫn là một nền kinh tế thị trường khó được quốc tế công nhận. Sở hữu tư nhân hiện đại là chế độ sở hữu được cổ phần hóa, được xã hội hóa rất cao, công khai, minh bạch trên các thị trường chứng khoán. Tính xã hội cao của chế độ cổ phần hóa đã được C.Mác đánh giá, xem như là chế độ sở hữu quá độ sang hình thái kinh tế - xã hội mới. (shrink)

Xây dựng nền kinh tế xanh tiến đến mục tiêu phát triển bền vững đang từng bước trở thành xu thế của thời đại và là xu hướng ngày càng rõ nét trên toàn cầu. Hành vi xanh của doanh nghiệp có vốn đầu tư trực tiếp nước ngoài (doanh nghiệp FDI) có mối quan hệ chặt chẽ và tác động tích cực đáng kể đến sự phát triển bền vững của địa phương/quốc gia, bao gồm cả các nước phát (...) triển và đang phát triển, trong đó có Việt Nam. Bài viết tập trung phân tích những tác động của các doanh nghiệp FDI đến phát triển bền vững của Việt Nam thông qua các hành vi xanh, cụ thể là các hành vi đầu tư gắn với phát triển bền vững của quốc gia, từ đó đề xuất các nhóm giải pháp thúc đẩy hành vi xanh của doanh nghiệp FDI tại Việt Nam. (shrink)

Despite the importance of human blood to clinical practice and research, hematology and blood transfusion data remain scattered throughout a range of disparate sources. This lack of systematization concerning the use and definition of terms poses problems for physicians and biomedical professionals. We are introducing here the Blood Ontology, an ongoing initiative designed to serve as a controlled vocabulary for use in organizing information about blood. The paper describes the scope of the Blood Ontology, its stage of development and some (...) of its anticipated uses. (shrink)

What are the sensory individuals of audition? What are the entities our auditory system attributes properties to? We examine various proposals about the nature of the sensory individuals of audition, and show that while each can account for some aspects of auditory perception, each also faces certain difficulties. We then put forward a new conception of sensory individuals according to which auditory sensory individuals are composite individuals. A feature shared by all existing accounts of sounds and sources is that they (...) postulate sensory individuals that are non-composite. They identify the sensory individual of sound hearing or source hearing with one type of entity in the environment, be they sound waves, vibrations, or interactions. We question this assumption and argue that our perceptual systems represent two or more aspects of the environment as a single sensory individual. Finally, we show that taking auditory individuals to be composite sensory individuals allows for an account of audition that is less problematic than its existing alternatives. (shrink)

Nghiên cứu này được thực hiện với mục tiêu đo lường mức độ hữu hiệu của hệ thống kiểm soát nội bộ tại Công ty Cổ phần Kết cấu thép GSB thông qua các yếu tố cấu thành gồm: Môi trường kiểm soát; Đánh giá rủi ro; Hoạt động kiểm soát; Thông tin và truyền thông và Giám sát. Kết quả nghiên cứu cho thấy yếu tố Giám sát có mức độ ảnh hưởng mạnh nhất đến sự hữu hiệu của (...) hệ thống kiểm soát nội bộ. Trên cơ sở đó, nghiên cứu đưa ra các hàm ý quản trị dựa trên kết quả phân tích hồi quy, góp phần nâng cao chất lượng hệ thống kiểm soát nội bộ tại đơn vị. (shrink)

Abstract: This research paper presents a novel approach to predict audit risks using a neural network model. The dataset used for this study was obtained from Kaggle and comprises 774 samples with 18 features, including Sector_score, PARA_A, SCORE_A, PARA_B, SCORE_B, TOTAL, numbers, marks, Money_Value, District, Loss, Loss_SCORE, History, History_score, score, and Risk. The proposed neural network architecture consists of three layers, including one input layer, one hidden layer, and one output layer. The neural network model was trained and validated, (...) achieving an impressive accuracy of 100% and an average error of 0.000015, indicating its robust predictive capability. Moreover, we conducted feature importance analysis to identify the most influential features for predicting audit risk. The key features found to be critical for classifying fraudulent activities in audit risk prediction are Sector_score, PARA_A, SCORE_A, PARA_B, SCORE_B, TOTAL, numbers, marks, Money_Value, District, Loss, Loss_SCORE, History, and History_score. This research contributes to the field of audit risk prediction by demonstrating the effectiveness of a neural network-based approach and highlighting the importance of specific features in detecting fraudulent activities. The findings have significant implications for auditors and organizations seeking to enhance their audit risk assessment processes, ultimately leading to improved financial transparency and fraud detection. (shrink)

Artificial intelligence (AI) research enjoyed an initial period of enthusiasm in the 1970s and 80s. But this enthusiasm was tempered by a long interlude of frustration when genuinely useful AI applications failed to be forthcoming. Today, we are experiencing once again a period of enthusiasm, fired above all by the successes of the technology of deep neural networks or deep machine learning. In this paper we draw attention to what we take to be serious problems underlying current views of artificial (...) intelligence encouraged by these successes, especially in the domain of language processing. We then show an alternative approach to language-centric AI, in which we identify a role for philosophy. (shrink)

Randomization is an integral part of well-designed statistical trials, and is also a required procedure in legal systems. Implementation of honest, unbiased, understandable, secure, traceable, auditable and collusion resistant randomization procedures is a mater of great legal, social and political importance. Given the juridical and social importance of randomization, it is important to develop procedures in full compliance with the following desiderata: (a) Statistical soundness and computational efficiency; (b) Procedural, cryptographical and computational security; (c) Complete auditability and traceability; (d) Any (...) attempt by participating parties or coalitions to spuriously influence the procedure should be either unsuccessful or be detected; (e) Open-source programming; (f) Multiple hardware platform and operating system implementation; (g) User friendliness and transparency; (h) Flexibility and adaptability for the needs and requirements of multiple application areas (like, for example, clinical trials, selection of jury or judges in legal proceedings, and draft lotteries). This paper presents a simple and easy to implement randomization protocol that assures, in a formal mathematical setting, full compliance to the aforementioned desiderata for randomization procedures. (shrink)

Abstract: This research focuses on utilizing Artificial Neural Networks (ANNs) to predict Audit Risk accurately, a critical aspect of ensuring financial system integrity and preventing fraud. Our dataset, gathered from Kaggle, comprises 18 diverse features, including financial and historical parameters, offering a comprehensive view of audit-related factors. These features encompass 'Sector_score,' 'PARA_A,' 'SCORE_A,' 'PARA_B,' 'SCORE_B,' 'TOTAL,' 'numbers,' 'marks,' 'Money_Value,' 'District,' 'Loss,' 'Loss_SCORE,' 'History,' 'History_score,' 'score,' and 'Risk,' with a total of 774 samples. Our proposed neural network architecture, consisting (...) of three layers (1 input, 1 hidden, and 1 output), forms the core of this study. While it may seem simple, the power of ANNs lies not in complexity but in their ability to uncover intricate data patterns. The model underwent rigorous training and validation, resulting in remarkable outcomes—an accuracy of 100% and an average error rate of 0.000015. In addition to performance metrics, our research investigates feature importance, revealing the key contributors to Audit Risk prediction. Notably, 'Sector_score,' 'PARA_A,' 'SCORE_A,' 'PARA_B,' 'SCORE_B,' 'TOTAL,' 'numbers,' 'marks,' 'Money_Value,' 'District,' 'Loss,' 'Loss_SCORE,' 'History,' and 'History_score' emerged as the most influential factors, shedding light on the elements crucial for precise risk assessment. This study advances Audit Risk prediction models and highlights the potential of ANNs in strengthening financial system integrity and fraud prevention. The insights gained from our findings offer practical guidance for stakeholders in the audit and financial sectors. (shrink)

Generative AI technologies have the potential to be socially and politically transformative. In this paper, we focus on exploring the potential impacts that Generative AI could have on the functioning of our democracies and the nature of citizenship. We do so by drawing on accounts of deliberative democracy and the deliberative virtues associated with it, as well as the reciprocal impacts that social media and Generative AI will have on each other and the broader information landscape. Drawing on this background (...) theory, we outline some of the key positive and negative impacts that Generative AI is likely to have on democratic citizenship. The political significance of these impacts suggests the need for further regulation. (shrink)

Since the release of OpenAI's ChatGPT, the world has entered a race to develop more capable and powerful AI, including artificial general intelligence (AGI). The development is constrained by the dependency of AI on the model, quality, and quantity of training data, making the AI training process highly costly in terms of resources and environmental consequences. Thus, improving the effectiveness and efficiency of the AI training process is essential, especially when the Earth is approaching the climate tipping points and planetary (...) boundaries. It is evident that AI can function better when trained to mimic certain human mental processes. Based on insights from quantum mechanics and the informational entropy-based notion of value, we suggest AI developers can enhance the AI training processes' effectiveness and efficiency by creating and implementing parameter systems that are capable of effectively assigning probabilities to informational quanta. Such systems can help reduce entropy within the system, which lowers the energy required for data storage and processing while decreasing the likelihood of information loss during training. Successfully applying the concept of information entropy-based value in AI development will be crucial for advancing generative AI and achieving AGI in a sustainable manner. (shrink)