Regulation is nothing without enforcement. This particularly holds for the dynamic field of emerging technologies. Hence, this article has two ambitions. First, it explains how the EU´s new Artificial Intelligence Act (AIA) will be implemented and enforced by various institutional bodies, thus clarifying the governance framework of the AIA. Second, it proposes a normative model of governance, providing recommendations to ensure uniform and coordinated execution of the AIA and the fulfilment of the legislation. Taken together, the article explores how the (...) AIA may be implemented by national and EU institutional bodies, encompassing longstanding bodies, such as the European Commission, and those newly established under the AIA, such as the AI Office. It investigates their roles across supranational and national levels, emphasizing how EU regulations influence institutional structures and operations. These regulations may not only directly dictate the structural design of institutions but also indirectly request administrative capacities needed to enforce the AIA. (shrink)

Will AI take away your job? The answer is probably not. AI systems can be good predictive systems and be very good at pattern recognition. AI systems have a very repetitive approach to sets of data, which can be useful in certain circumstances. However, AI does make obvious mistakes. This is because AI does not have a sense of context. As Humans we have years of experience in the real world. We have vast amounts of contextual data stored in our (...) brains that make it possible to predict and to know boundaries of the real world so that even if we have never been in a particular situation, we are still able to deal with it. The unknown situation is where AI will fall down. In engineering, AI is being developed to monitor and control certain systems, this could extend to Nuclear Power Plants for example. If we examine control systems for Nuclear Power Plants on vessels, the system would likely be programmed using the safety of the reactor as the main priority. Automation is crucial in engineering systems like this, as the likelihood and cost of human error is high and human reaction times are slow in comparison to the system. However, there is always the possibility of unforeseen external factors that may override plant safety which cannot be programmed. If we look at a plant onboard a Submarine, for example, we see such additional factors as ship safety. In one example, the power plant might breach safety parameters, in which case an automatic system may shut down the reactor. However, there might be a greater urgency such as a flood in another compartment or an attack upon the vessel, that would override shutting down the reactor. The AI system can neither observe nor utilise information from the external environment to make this type of judgement, whereas the operator may be completely aware. To programme context into AI systems would be near impossible. We still need operators as we still need to understand the environment around us, which may contain an infinite number of possibilities. In a further example of this; if we examine the ICO (Information Commissioner's Office) guidance, it is clear that in clinical settings a human being will always be required to validate findings and to provide context. Sometimes having a lot of data just doesn't replace social interaction, intuition and experience. (shrink)

Mark Coeckelbergh starts his book with a very powerful picture based on a real incident: On the 9th of January 2020, Robert Williams was wrongfully arrested by Detroit police officers in front of his two young daughters, wife and neighbors. For 18 hours the police would not disclose the grounds for his arrest (American Civil Liberties Union 2020; Hill 2020). The decision to arrest him was primarily based on a facial detection algorithm which matched Mr. Williams’ driving license photo with (...) the picture of a man who was suspected of watch theft two years earlier. Not only did the computer ‘get it wrong’ as one of the detectives said, when Mr. Williams made them aware that the picture of the suspect obviously wasn’t resembling him, the probably unreliable algorithm very likely contributed to racial discrimination (Hill 2020). It is well documented that many available facial detection algorithms at this time had significant problems (e.g. a comparably high false positive rate) with respect to black persons, like Mr. Williams (NIST 2019). Multiple causes may exist, such as unbalanced training datasets and insufficient optimization. Coeckelbergh compares the disturbing case of Mr. Williams with a political interpretation of Franz Kafka’s The Trial, where the protagonist, Josef K., is accused of an unspecified crime by an opaque, oppressive and absurd bureaucracy: “In the 21st-century United States, Josef K. is black and is falsely accused by an algorithm, without explanation” (p. 2). (shrink)

The emergence of Thanabots —artificial intelligence systems designed to simulate deceased individuals—presents unprecedented challenges at the intersection of artificial intelligence, legal rights, and societal configuration. This short policy recommendations report examines the legal, social and psychological implications of these posthumous simulations and argues for their prohibition on ethical, sociological, and legal grounds.

Reasoning about mental states and processes is important in various subareas of the legal domain. A trial lawyer might need to reason and the beliefs, reasoning and other mental states and processes of members of a jury; a police officer might need to reason about the conjectured beliefs and reasoning of perpetrators; a judge may need to consider a defendant's mental states and processes for the purposes of sentencing and so on. Further, the mental states in question may themselves be (...) about the mental states and processes of other people. Therefore, if AI systems are to assist with reasoning tasks in law, they may need to be able to reason about mental states and processes. Such reasoning is riddled with uncertainty, and this is true in particular in the legal domain. The article discusses how various different types of uncertainty arise, and shows how they greatly complicate the task of reasoning about mental states and processes. The article concentrates on the special case of states of belief and processes of reasoning, and sketches an implemented, prototype computer program (ATT-Meta) that copes with the various types of uncertainty in reasoning about beliefs and reasoning. In particular, the article outlines the system's facilities for handling conflict between different lines of argument, especially when these lie within the reasoning of different people. The system's approach is illustrated by application to a real-life mugging example. [NB: The date on the archived preprint avail via this Phil* page has an incorrect date, 2011, on it. The correct date is 2001.]. (shrink)

Alternative Solutions to a Failed Democratic System Due to Ignorant Voters and Black Propaganda Politics -/- Introduction -/- Democracy is often considered the best form of government because it allows people to choose their leaders and influence policies. However, democracy is only as strong as the knowledge and wisdom of its citizens. When voters are ignorant and easily manipulated by black propaganda, democracy fails to serve its true purpose. Corrupt politicians take advantage of misinformation, and elections become a contest of (...) deceit rather than competence. In such cases, it becomes necessary to explore alternative governance systems that align with the universal law of balance in nature, ensuring societal stability and progress. This essay explores five potential solutions: meritocratic democracy, hybrid governance, decentralized governance with AI oversight, temporary educational dictatorship, and whole-process democracy with reforms. -/- 1. Meritocratic Democracy: A Government of the Competent -/- One of the main weaknesses of democracy is that it allows uninformed individuals to vote, often leading to the election of incompetent or corrupt leaders. Meritocratic democracy solves this by introducing a system where voters and candidates must meet certain educational or competency requirements. -/- In this system: -/- Voters must pass a basic competency test on political, economic, and social issues before they can vote. -/- Candidates must demonstrate expertise in governance, ethics, and leadership before being allowed to run for office. -/- Decision-making is guided by knowledge and logic, rather than emotional manipulation or populism. -/- By ensuring that only informed citizens and competent leaders participate in the electoral process, a meritocratic democracy prevents the spread of ignorance and manipulation, making governance more stable and effective. -/- 2. Hybrid Governance Model: Balancing Democracy and Technocracy -/- A pure democratic system, when controlled by an uninformed majority, can lead to poor decision-making. A hybrid governance model combines democratic participation with expert-driven decision-making. -/- This system includes: -/- Direct democracy for issues that require public participation, ensuring people still have a voice. -/- Technocratic leadership for areas that require expertise, such as economic planning, environmental policies, and legal reforms. -/- AI-assisted decision-making, where policies are analyzed based on logic, data, and the universal law of balance in nature. -/- By integrating democracy with technocracy, this model ensures that governance is based on both public engagement and expert knowledge, reducing the influence of ignorance and propaganda. -/- 3. Decentralized Governance with AI Oversight -/- Corruption and manipulation thrive in centralized political systems where power is concentrated in a few individuals. A decentralized governance model distributes power across local communities while maintaining oversight through artificial general intelligence (AGI) programmed with the universal formula to ensure balance and ethical governance. -/- This system includes: -/- Local decision-making councils that handle community affairs, reducing dependence on central authorities. -/- AI oversight to prevent misinformation, corruption, and propaganda in governance. -/- Policy-making based on natural balance, ensuring that human actions align with long-term sustainability and fairness. -/- By decentralizing power and using AI to monitor governance, this system prevents political elites from manipulating the public while ensuring that all decisions follow rational and ethical principles. -/- 4. Temporary Educational Dictatorship: A Path to Enlightened Democracy -/- If a democratic system is completely destroyed by ignorance and propaganda, a temporary educational dictatorship may be necessary to restore order. This approach involves: -/- A temporary leadership regime that enforces strict educational reforms before returning power to a well-informed electorate. -/- A governance structure that prioritizes truth, logic, and natural laws in policymaking. -/- A mandatory educational system focusing on critical thinking, ethics, and scientific reasoning to eliminate ignorance from the voting population. -/- This dictatorship would not be based on oppression but on restoring the intellectual foundation necessary for democracy to function properly. Once society reaches a stable level of awareness, democratic processes can be reinstated. -/- 5. Whole-Process People’s Democracy with Reforms -/- China’s whole-process people’s democracy is a system that allows both public participation and centralized decision-making. However, for it to be truly effective, it must integrate the universal law of balance in nature and eliminate ideological biases. -/- To reform whole-process democracy: -/- Education and critical thinking must be central to governance, ensuring the population is not easily misled. -/- Leaders must be selected based on knowledge and competence, not political loyalty. -/- Policies must align with natural balance, ensuring long-term societal stability. -/- By modifying this system with scientific and ethical principles, it can serve as a stable alternative to failing democracies. -/- Conclusion -/- Democracy is valuable, but when ignorant voters and black propaganda politics take control, it leads to instability and poor governance. To correct this failure, alternative systems must be considered. Meritocratic democracy ensures only informed citizens and competent leaders participate in elections. Hybrid governance balances democratic participation with expert decision-making. Decentralized governance with AI oversight prevents corruption and misinformation. A temporary educational dictatorship restores knowledge before returning to democracy. Whole-process democracy, when modified with the universal law of balance, can also serve as a viable alternative. -/- The best solution depends on the specific problems of a country, but the core principle remains the same: governance must follow the universal law of balance in nature, ensuring stability, truth, and progress. Only through such reforms can society escape the cycle of ignorance and manipulation, creating a future where human decisions align with natural laws and rational thought. -/- . (shrink)

News Rakshak is an advanced web application that monitors, analyzes, and verifies news related to government schemes in regional media across multiple platforms, including 200+ websites, e-papers, and YouTube channels. The application leverages Natural Language Processing (NLP) for sentiment analysis and integrates Artificial Intelligence (AI) to identify and flag fake news and videos. Sentiments are classified as positive, neutral, or negative, rated on a scale from 0 to 5, providing Public Information Bureau (PIB) officers with actionable insights. The system uses (...) Optical Character Recognition (OCR) for extracting text from image-based news formats and delivers real-time alerts to officials via multiple channels. The user-friendly interface, equipped with filtering options, enables effective trend visualization. News Rakshak serves as a comprehensive tool for tracking and verifying government-related news sentiment and authenticity, ensuring accurate feedback from regional media. (shrink)

-/- The End of Crime Syndicates: How the Universal Formula Will Reshape Society -/- Introduction -/- Crime syndicates have existed throughout human history, thriving on corruption, ignorance, and economic imbalance. Despite law enforcement efforts, they continue to evolve and adapt, making them seemingly indestructible. However, with the full implementation of the universal formula, the mechanisms that sustain crime syndicates will be dismantled. The universal formula, as the most powerful tool in mind programming, has the potential to eradicate criminal organizations by (...) reprogramming society to function in perfect alignment with natural laws. This essay explores how the universal formula will systematically eliminate crime syndicates and create a self-correcting, balanced civilization. -/- The Root Causes of Crime Syndicates -/- Before understanding how crime syndicates will disappear, it is essential to recognize why they exist: -/- 1. Ignorance and False Beliefs – Many people engage in crime because they lack a proper understanding of ethics, justice, and balance. Misinformation, emotional manipulation, and a lack of critical thinking allow crime to flourish. -/- 2. Corruption in Leadership – Governments, law enforcement, and businesses often protect crime syndicates due to bribery, personal interests, or threats. When leaders operate without a guiding universal principle, they become vulnerable to corruption. -/- 3. Economic Imbalances – Poverty, lack of opportunity, and wealth inequality push individuals into criminal activities. Crime becomes a survival mechanism in a world that does not provide balanced opportunities. -/- 4. Social Acceptance and Demand – Society plays a role in sustaining crime by consuming illegal goods and services, whether drugs, human trafficking, or underground markets. The demand fuels the supply. -/- 5. Lack of a Self-Correcting System – Current systems of justice react after crime has been committed instead of preventing it at its root cause. There is no universal guiding principle that ensures balance in all aspects of decision-making. -/- How the Universal Formula Will Eliminate Crime Syndicates -/- The universal formula will solve these problems by reprogramming the way society functions at every level. -/- 1. Mind Reprogramming Through Education -/- The most powerful transformation will happen through education. The universal formula will be implemented in basic education worldwide, ensuring that all individuals develop a deep understanding of balance, natural laws, and ethical decision-making. This will: -/- Remove ignorance and false beliefs, making it impossible for individuals to justify crime. -/- Train people in critical thinking, making them immune to manipulation and deception by crime syndicates. -/- Reprogram individuals to see justice and balance as the only rational way to operate in society. -/- As a result, future generations will reject crime as a viable option because their minds will be structured to seek equilibrium in all aspects of life. -/- 2. Corruption Becomes Impossible in Governance -/- With the universal formula guiding leadership training, all government officials, law enforcement officers, and judges will be required to follow natural laws of balance. This will make: -/- Bribery and extortion impossible, as leaders will be programmed to always seek universal balance. -/- Laws and policies aligned with natural laws, ensuring that no loopholes exist for crime syndicates to exploit. -/- Justice systems proactive, not reactive, eliminating crime before it takes root. -/- Without political and legal protection, crime syndicates will lose their power and collapse. -/- 3. Economic Balance Will Remove the Need for Crime -/- One of the biggest reasons crime syndicates exist is economic inequality. The universal formula will: -/- Ensure fair economic distribution, so individuals no longer need to turn to crime for survival. -/- Regulate business and trade using natural balance principles, eliminating black markets. -/- Remove the root cause of wealth-based crime, such as extortion and money laundering. -/- By balancing wealth, opportunity, and resources, crime will become economically illogical and unnecessary. -/- 4. No Demand for Criminal Markets -/- The universal formula will also remove the demand for illegal goods and services by: -/- Reprogramming individuals to reject harmful behaviors such as drug use and human exploitation. -/- Creating a society where needs are met ethically, removing the desire for black market solutions. -/- Using feedback mechanisms to detect and eliminate imbalances before they grow into full-scale criminal operations. -/- Without customers, crime syndicates will have no business model, forcing them into extinction. -/- 5. Self-Correcting Societies and AI Enforcement -/- A society governed by the universal formula will have a built-in self-correcting mechanism. Since all human decision-making follows natural balance, individuals and communities will: -/- Detect and eliminate imbalances before they lead to organized crime. -/- Hold each other accountable through collective awareness. -/- Use AGI technology programmed with the universal formula to analyze all societal systems, ensuring that no criminal organizations can form or sustain themselves. -/- With AI acting as an analytical enforcer, crime syndicates will have nowhere to hide, and any criminal attempts will be immediately corrected. -/- Final Outcome: A World Without Crime Syndicates -/- Once the universal formula is fully implemented, crime syndicates will no longer be sustainable. They rely on ignorance, corruption, economic imbalances, and public demand—all of which will be eliminated under a balanced system of natural laws. -/- 1. Future generations will be programmed for ethical and rational decision-making. -/- 2. Governments will be incorruptible and operate based on natural balance. -/- 3. Economic structures will remove incentives for crime. -/- 4. Society will self-regulate against criminal behavior. -/- 5. AI will ensure that all systems remain in universal balance, preventing crime from emerging. -/- In this world, crime syndicates will have no space to exist, making them extinct. -/- Conclusion -/- Crime syndicates have survived for centuries by exploiting human ignorance, economic instability, and corruption. However, with the universal formula, these root causes will be eliminated, leading to a fully balanced society. Education, governance, economy, and technology will all operate under natural laws, ensuring that crime syndicates can never return. -/- The universal formula is the most powerful tool in mind programming, and once implemented, it will create a world where crime is not just discouraged—but fundamentally impossible. -/- . (shrink)

When product design teams gather at the whiteboard in big-tech office parks and startup garages around the world, they ask themselves: How will customers use our technology? Is it better than our competitors’? How much money can we make? But one question that’s rarely asked: does our technology advance human flourishing? -/- In a new white paper by Harvard professor Danielle Allen and her colleagues Eli Frankel, Woojin Lim, Divya Siddarth, Josh Simons, and Glen Weyl entitled “The Ethics of (...) Decentralized Social Technologies: Lessons from Web3, the Fediverse, and Beyond,” the authors not only ask this question but offer a powerful framework for answering it. Drawing on the accumulated wisdom of democratic societies, the authors show that the values of democratic governance that have promoted human flourishing can be translated into a rubric for judging new technologies. -/- In this short research brief, we unpack and comment on the four-step logic at the core of their case. Ultimately, their argument demonstrates the power and the challenge – and above all, the urgency – of placing human flourishing at the center of technology governance. (shrink)

In the 21st century, transparency and efficiency in municipal management are essential. This study focusses on the GAD Municipal of Latacunga, Ecuador, assessing inefficiency in the Office of Valuation and Cadastres, proposing the use of AI to improve governance. The research reveals deficiencies in digitalization and transparency, identifying the need for effective mechanisms to optimize public services. AI is presented as a potential solution to automate tasks, detect irregularities, and increase administrative efficiency. This analysis, based on regional and local (...) data, highlights the potential of AI to transform public administration and strengthening citizen trust. (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)

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)

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)

Artificial intelligence has arrived. In the online world it is already a part of everyday life, sitting invisibly behind a wide range of search engines and online commerce sites. It offers huge potential to enable more efficient and effective business and government but the use of artificial intelligence brings with it important questions about governance, accountability and ethics. Realising the full potential of artificial intelligence and avoiding possible adverse consequences requires societies to find satisfactory answers to these questions. This report (...) sets out some possible approaches, and describes some of the ways government is already engaging with these issues. (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)

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)

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).

(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)

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)

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)

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)

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)

An advanced artificial intelligence could pose a significant existential risk to humanity. Several research institutes have been set-up to address those risks. And there is an increasing number of academic publications analysing and evaluating their seriousness. Nick Bostrom’s superintelligence: paths, dangers, strategies represents the apotheosis of this trend. In this article, I argue that in defending the credibility of AI risk, Bostrom makes an epistemic move that is analogous to one made by so-called sceptical theists in the debate about the (...) existence of God. And while this analogy is interesting in its own right, what is more interesting are its potential implications. It has been repeatedly argued that sceptical theism has devastating effects on our beliefs and practices. Could it be that AI-doomsaying has similar effects? I argue that it could. Specifically, and somewhat paradoxically, I argue that it could amount to either a reductio of the doomsayers position, or an important and additional reason to join their cause. I use this paradox to suggest that the modal standards for argument in the superintelligence debate need to be addressed. (shrink)

In today’s rapidly evolving financial landscape, the adoption of Artificial Intelligence (AI) and Machine Learning (ML) technologies, coupled with the deployment of Business Rules Management Systems (BRMS), has transformed how financial transactions are conducted, monitored, and secured. With fraud, particularly in check deposit transactions, becoming increasingly sophisticated, financial institutions are turning to AI and ML to enhance their risk management strategies. This paper explores the integration of AI-driven models and business rules in financial transactions, focusing on their application in fraud (...) detection and prevention. We also examine the associated challenges, such as data privacy, ethical concerns, and the need for regulatory frameworks, while outlining the opportunities that lie ahead for future financial innovation. (shrink)

The increasing demand for transparency in AI has recently come under scrutiny. The question is often posted in terms of “epistemic double standards”, and whether the standards for transparency in AI ought to be higher than, or equivalent to, our standards for ordinary human reasoners. I agree that the push for increased transparency in AI deserves closer examination, and that comparing these standards to our standards of transparency for other opaque systems is an appropriate starting point. I suggest that a (...) more fruitful exploration of this question will involve a different comparison class. We routinely treat judgments made by highly trained experts in specialized fields as fair or well-grounded even though—by the nature of expert/layperson division of epistemic labor—an expert will not be able to provide an explanation of the reasoning behind these judgments that makes sense to most other people. Regardless, laypeople are thought to be acting reasonably—and ethically—in deferring to the judgments of experts that concern their areas of specialization. I suggest that we reframe our question regarding the appropriate standards of transparency in AI as one that asks when, why, and to what degree it would be ethical to accept opacity in AI. I argue that our epistemic relation to certain opaque AI technology may be relevantly similar to the layperson’s epistemic relation to the expert in certain respects, such that the successful expert/layperson division of epistemic labor can serve as a blueprint for the ethical use of opaque AI. (shrink)

Does AI conform to humans, or will we conform to AI? An ethical evaluation of AI-intensive companies will allow investors to knowledgeably participate in the decision. The evaluation is built from nine performance indicators that can be analyzed and scored to reflect a technology’s human-centering. When summed, the scores convert into objective investment guidance. The strategy of incorporating ethics into financial decisions will be recognizable to participants in environmental, social, and governance investing, however, this paper argues that conventional ESG frameworks (...) are inadequate for AI-intensive companies. To fully account for contemporary technology, the following categories of evaluation will be developed and featured as vital investing criteria: autonomy, dignity, privacy, performance. With these priorities established, the larger goal is a model for humanitarian investing in AI-intensive companies that is intellectually robust, manageable for analysts, useful for portfolio managers, and credible for investors. (shrink)

Since the release of ChatGPT, there has been a lot of debate about whether AI systems pose an existential risk to humanity. This paper develops a general framework for thinking about the existential risk of AI systems. We analyze a two-premise argument that AI systems pose a threat to humanity. Premise one: AI systems will become extremely powerful. Premise two: if AI systems become extremely powerful, they will destroy humanity. We use these two premises to construct a taxonomy of ‘survival (...) stories’, in which humanity survives into the far future. In each survival story, one of the two premises fails. Either scientific barriers prevent AI systems from becoming extremely powerful; or humanity bans research into AI systems, thereby preventing them from becoming extremely powerful; or extremely powerful AI systems do not destroy humanity, because their goals prevent them from doing so; or extremely powerful AI systems do not destroy humanity, because we can reliably detect and disable systems that have the goal of doing so. We argue that different survival stories face different challenges. We also argue that different survival stories motivate different responses to the threats from AI. Finally, we use our taxonomy to produce rough estimates of ‘P(doom)’, the probability that humanity will be destroyed by AI. (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)

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

An AI winter may be defined as the stage when technology, business, and the media come to terms with what AI can or cannot really do as a technology without exaggeration. Through discussion of previous AI winters, this paper examines the hype cycle (which by turn characterises AI as a social panacea or a nightmare of apocalyptic proportions) and argues that AI should be treated as a normal technology, neither as a miracle nor as a plague, but rather as of (...) the many solutions that human ingenuity has managed to devise. (shrink)

The EU Artificial Intelligence Act (AIA) defines four risk categories for AI systems: unacceptable, high, limited, and minimal. However, it lacks a clear methodology for the assessment of these risks in concrete situations. Risks are broadly categorized based on the application areas of AI systems and ambiguous risk factors. This paper suggests a methodology for assessing AI risk magnitudes, focusing on the construction of real-world risk scenarios. To this scope, we propose to integrate the AIA with a framework developed by (...) the Intergovernmental Panel on Climate Change (IPCC) reports and related literature. This approach enables a nuanced analysis of AI risk by exploring the interplay between (a) risk determinants, (b) individual drivers of determinants, and (c) multiple risk types. We further refine the proposed methodology by applying a proportionality test to balance the competing values involved in AI risk assessment. Finally, we present three uses of this approach under the AIA: to implement the Regulation, to assess the significance of risks, and to develop internal risk management systems for AI deployers. (shrink)

The expanding integration of artificial intelligence (AI) in various aspects of society makes the infosphere around us increasingly complex. Humanity already faces many obstacles trying to have a better understanding of our own minds, but now we have to continue finding ways to make sense of the minds of AI. The issue of AI’s capability to have independent thinking is of special attention. When dealing with such an unfamiliar concept, people may rely on existing human properties, such as survival desire, (...) to make assessments. Employing information-processing-based Bayesian Mindsponge Framework (BMF) analytics on a dataset of 266 residents in the United States, we found that the more people believe that an AI agent seeks continued functioning, the more they believe in that AI agent’s capability of having a mind of its own. Moreover, we also found that the above association becomes stronger if a person is more familiar with personally interacting with AI. This suggests a directional pattern of value reinforcement in perceptions of AI. As the information processing of AI becomes even more sophisticated in the future, it will be much harder to set clear boundaries about what it means to have an autonomous mind. (shrink)

One objection to conventional AI ethics is that it slows innovation. This presentation responds by reconfiguring ethics as an innovation accelerator. The critical elements develop from a contrast between Stability AI’s Diffusion and OpenAI’s Dall-E. By analyzing the divergent values underlying their opposed strategies for development and deployment, five conceptions are identified as common to acceleration ethics. Uncertainty is understood as positive and encouraging, rather than discouraging. Innovation is conceived as intrinsically valuable, instead of worthwhile only as mediated by social (...) effects. AI problems are solved by more AI, not less. Permissions and restrictions governing AI emerge from a decentralized process, instead of a unified authority. The work of ethics is embedded in AI development and application, instead of functioning from outside. Together, these attitudes and practices remake ethics as provoking rather than restraining artificial intelligence. (shrink)

Advancements in machine learning have fuelled the popularity of using AI decision algorithms in procedures such as bail hearings, medical diagnoses and recruitment. Academic articles, policy texts, and popularizing books alike warn that such algorithms tend to be opaque: they do not provide explanations for their outcomes. Building on a causal account of transparency and opacity as well as recent work on the value of causal explanation, I formulate a moral concern for opaque algorithms that is yet to receive a (...) systematic treatment in the literature: when such algorithms are used in life-changing decisions, they can obstruct us from effectively shaping our lives according to our goals and preferences, thus undermining our autonomy. I argue that this concern deserves closer attention as it furnishes the call for transparency in algorithmic decision-making with both new tools and new challenges. (shrink)

The EU proposal for the Artificial Intelligence Act (AIA) defines four risk categories: unacceptable, high, limited, and minimal. However, as these categories statically depend on broad fields of application of AI, the risk magnitude may be wrongly estimated, and the AIA may not be enforced effectively. This problem is particularly challenging when it comes to regulating general-purpose AI (GPAI), which has versatile and often unpredictable applications. Recent amendments to the compromise text, though introducing context-specific assessments, remain insufficient. To address this, (...) we propose applying the risk categories to specific AI scenarios, rather than solely to fields of application, using a risk assessment model that integrates the AIA with the risk approach arising from the Intergovernmental Panel on Climate Change (IPCC) and related literature. This model enables the estimation of the magnitude of AI risk by considering the interaction between (a) risk determinants, (b) individual drivers of determinants, and (c) multiple risk types. We use large language models (LLMs) as an example. (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)

Urban lighting systems are essential for safety, security, and quality of life, but they often consume significant energy and lack adaptability to changing conditions. Traditional lighting systems rely on fixed schedules and manual adjustments, leading to inefficiencies such as over-illumination and energy waste. This paper explores how Artificial Intelligence (AI) and IoT technologies can optimize urban lighting by enabling real-time adjustments, energy savings, and adaptive illumination based on environmental conditions and human activity. By integrating data from motion sensors, weather forecasts, (...) and traffic systems, cities can reduce energy consumption, enhance safety, and improve the quality of life for residents. Experimental results demonstrate significant improvements in energy efficiency, lighting quality, and operational costs, offering a sustainable blueprint for smart urban lighting systems. (shrink)

Abstract: Artificial Intelligence (AI) is revolutionizing organizational dynamics by reshaping both structures and processes. This paper explores how AI-driven innovations are transforming organizational frameworks, from hierarchical adjustments to decentralized decision-making models. It examines the impact of AI on various processes, including workflow automation, data analysis, and enhanced decision support systems. Through case studies and empirical research, the paper highlights the benefits of AI in improving efficiency, driving innovation, and fostering agility within organizations. Additionally, it addresses the challenges associated with AI (...) integration, such as resistance to change, ethical concerns, and data security issues. The paper concludes by offering insights into future trends and implications for organizations navigating the evolving landscape of AI-driven change. (shrink)

Generative AI has proven itself as an efficient innovation in many fields including writing and even analyzing data. For spatial computing, it provides a potential solution for solving such issues related to data manipulation and analysis within the spatial computing domain. This paper aims to discuss the probabilities of applying generative AI to graph-based spatial computing; to describe new approaches in detail; to shed light on their use cases; and to demonstrate the value that they add. This technique thus incorporates (...) graph theory, generative models to model spatial relations, generate new spatial forms and improve on spatial decision-making processes. The paper surveys such methods, describes typical applications, and outlines further development of the subject. (shrink)

In this article, I attempt to provide a complete and exhaustive list of all of the offices and major political roles proposed within the constitution of Magnesia, detailing the title of the office, number of offices, method of appointment, age or gender restrictions, length of term, and explicit responsibilities assigned to that office. This tabulation is intended to be useful for new readers of the Laws and to scholars of various methodological approaches interested in the political arrangements of (...) Magnesia. (shrink)

The extended mind thesis maintains that the functional contributions of tools and artefacts can become so essential for our cognition that they can be constitutive parts of our minds. In other words, our tools can be on a par with our brains: our minds and cognitive processes can literally ‘extend’ into the tools. Several extended mind theorists have argued that this ‘extended’ view of the mind offers unique insights into how we understand, assess, and treat certain cognitive conditions. In this (...) chapter we suggest that using AI extenders, i.e., tightly coupled cognitive extenders that are imbued with machine learning and other ‘artificially intelligent’ tools, presents both new ethical challenges and opportunities for mental health. We focus on several mental health conditions that can develop differently by the use of AI extenders for people with cognitive disorders and then discuss some of the related opportunities and challenges. (shrink)

Since the launch of applications such as DALL-E, Midjourney, and Stable Diffusion, generative artificial intelligence has been controversial as a tool for creating artwork. While some have presented longtermist worries about these technologies as harbingers of fully automated futures to come, more pressing is the impact of generative AI on creative labour in the present. Already, business leaders have begun replacing human artistic labour with AI-generated images. In response, the artistic community has launched a protest movement, which argues that AI (...) image generation is a kind of theft. This paper analyzes, substantiates, and critiques these arguments, concluding that AI image generators involve an unethical kind of labour theft. If correct, many other AI applications also rely upon theft. (shrink)

Using artificial intelligence (AI) to make decisions in human resource management (HRM) raises questions of how fair employees perceive these decisions to be and whether they experience respectful treatment (i.e., interactional justice). In this experimental survey study with open-ended qualitative questions, we examine decision making in six HRM functions and manipulate the decision maker (AI or human) and decision valence (positive or negative) to determine their impact on individuals’ experiences of interactional justice, trust, dehumanization, and perceptions of decision-maker role appropriate- (...) ness. In terms of decision makers, the use of human decision makers over AIs generally resulted in better perceptions of respectful treatment. In terms of decision valence, people experiencing positive over negative decisions generally resulted in better perceptions of respectful treatment. In instances where these cases conflict, on some indicators people preferred positive AI decisions over negative human decisions. Qualitative responses show how people identify justice concerns with both AI and human decision making. We outline implications for theory, practice, and future research. (shrink)

AI companies are racing to create artificial general intelligence, or “AGI.” If they succeed, the result will be human-level AI systems that can independently pursue high-level goals by formulating and executing long-term plans in the real world. Leading AI researchers agree that some of these systems will likely be “misaligned”–pursuing goals that humans do not desire. This goal mismatch will put misaligned AIs and humans into strategic competition with one another. As with present-day strategic competition between nations with incompatible goals, (...) the result could be violent and catastrophic conflict. Existing legal institutions are unprepared for the AGI world. New foundations for AGI governance are needed, and the time to begin laying them is now, before the critical moment arrives. -/- This Article begins to lay those new legal foundations. It is the first to think systematically about the dynamics of strategic competition between humans and misaligned AGI. The Article begins by showing, using formal game-theoretic models, that, by default, humans and AIs will be trapped in a prisoner’s dilemma. Both parties’ dominant strategy will be to permanently disempower or destroy the other, even though the costs of such conflict would be high. -/- The Article then argues that a surprising legal intervention could transform the game theoretic equilibrium and avoid conflict: AI rights. Not just any AI rights would promote human safety. Granting AIs the right not to be needlessly harmed–as humans have granted to certain non-human animals–would, for example, have little effect. Instead, to promote human safety, AIs should be given those basic private law rights–to make contracts, hold property, and bring tort claims–that law already extends to non-human corporations. Granting AIs these economic rights would enable long-run, small-scale, mutually-beneficial transactions between humans and AIs. This would, we show, facilitate a peaceful strategic equilibrium between humans and AIs for the same reasons economic interdependence tends to promote peace in international relations. Namely, the gains from trade far exceed those from war. Throughout, we argue that human safety, rather than AI welfare, provides the right framework for developing AI rights. This Article explores both the promise and the limits of AI rights as a legal tool for promoting human safety in an AGI world. (shrink)

This paper focuses on the fact that AI is predominantly portrayed as white—in colour, ethnicity, or both. We first illustrate the prevalent Whiteness of real and imagined intelligent machines in four categories: humanoid robots, chatbots and virtual assistants, stock images of AI, and portrayals of AI in film and television. We then offer three interpretations of the Whiteness of AI, drawing on critical race theory, particularly the idea of the White racial frame. First, we examine the extent to which this (...) Whiteness might simply reflect the predominantly White milieus from which these artefacts arise. Second, we argue that to imagine machines that are intelligent, professional, or powerful is to imagine White machines because the White racial frame ascribes these attributes predominantly to White people. Third, we argue that AI racialised as White allows for a full erasure of people of colour from the White utopian imaginary. Finally, we examine potential consequences of the racialisation of AI, arguing it could exacerbate bias and misdirect concern. (shrink)

Personal AI assistants are now nearly ubiquitous. Every leading smartphone operating system comes with a personal AI assistant that promises to help you with basic cognitive tasks: searching, planning, messaging, scheduling and so on. Usage of such devices is effectively a form of algorithmic outsourcing: getting a smart algorithm to do something on your behalf. Many have expressed concerns about this algorithmic outsourcing. They claim that it is dehumanising, leads to cognitive degeneration, and robs us of our freedom and autonomy. (...) Some people have a more subtle view, arguing that it is problematic in those cases where its use may degrade important interpersonal virtues. In this article, I assess these objections to the use of AI assistants. I will argue that the ethics of their use is complex. There are no quick fixes or knockdown objections to the practice, but there are some legitimate concerns. By carefully analysing and evaluating the objections that have been lodged to date, we can begin to articulate an ethics of personal AI use that navigates those concerns. In the process, we can locate some paradoxes in our thinking about outsourcing and technological dependence, and we can think more clearly about what it means to live a good life in the age of smart machines. (shrink)

Better instruments to predict the future evolution of artificial intelligence (AI) are needed, as the destiny of our civilization depends on it. One of the ways to such prediction is the analysis of the convergent drives of any future AI, started by Omohundro. We show that one of the convergent drives of AI is a militarization drive, arising from AI’s need to wage a war against its potential rivals by either physical or software means, or to increase its bargaining power. (...) This militarization trend increases global catastrophic risk or even existential risk during AI takeoff, which includes the use of nuclear weapons against rival AIs, blackmail by the threat of creating a global catastrophe, and the consequences of a war between two AIs. As a result, even benevolent AI may evolve into potentially dangerous military AI. The type and intensity of militarization drive depend on the relative speed of the AI takeoff and the number of potential rivals. We show that AI militarization drive and evolution of national defense will merge, as a superintelligence created in the defense environment will have quicker takeoff speeds, but a distorted value system. We conclude with peaceful alternatives. (shrink)