Intro -- Series Page -- Title Page -- Copyright -- Dedication -- Preface -- Organization of the Book -- Acknowledgments -- About the Author -- Part One: Personalize Personal Finance -- Chapter 1: The Theory of Innovation: From Robo-Advisors to Goal Based Investing and Gamification -- 1.1 Introduction -- 1.2 A Vibrant FinTech Ecosystem -- 1.3 Some Definitions, Ladies and Gentlemen -- 1.4 Personalization is King -- 1.5 The Theory of Innovation -- 1.6 My Robo-Advisor is an iPod -- 1.7 What Incumbents should Consider when Thinking about FinTech Innovation -- 1.8 Conclusions -- Part Two: Automated Long-Term Investing Means Robo-Technology -- Chapter 2: Robo-Advisors: Neither Robots Nor Advisors -- 2.1 Introduction -- 2.2 What is a Robo-Advisor? -- 2.3 Automated Digital Businesses for Underserved Markets -- 2.4 Passive Investment Management with ETFs -- 2.5 Algorithms of Automated Portfolio Rebalancing -- 2.6 Personalized Decision-Making, Individual Goals, and Behaviour -- 2.7 Single Minded Businesses -- 2.8 Principles of Tax-Loss Harvesting -- 2.9 Conclusions -- Chapter 3: The Transformation of the Supply-Side -- 3.1 Introduction -- 3.2 The Investment Management Supply-Demand Chain -- 3.3 How Intermediaries make Money -- 3.4 Issuers of Direct Claims (Debt Owners) -- 3.5 The Institutionalization of the Private Banking Relationship -- 3.6 The Digital Financial Advisor -- 3.7 Asset Management is being Disintermediated -- 3.8 ETF Providers and the Pyrrhic Victory -- 3.9 Vertically Integrated Solutions Challenge Traditional Platforms -- 3.10 Conclusions -- Chapter 4: Social and Technology Mega Trends Shape a New Family of Taxable Investors -- 4.1 Introduction -- 4.2 Generational Shift (X, Y, Z, and HENRYs) -- 4.3 About Transparency, Simplicity, and Trust -- 4.4 The Cognitive ERA -- 4.5 Conclusions.
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Relevance. Artificial intelligence (AI) has become one of the most discussed and rapidly developing technologies in recent years. Its potential and capabilities have a significant impact on various spheres of life, including business. AI algorithms are used to analyze huge amounts of data and make forecasts, which helps companies make more efficient and rational decisions.The purpose is to study the main trends in the use of artificial intelligence in business and determine its potential and advantages.Objectives: to consider various aspects of the use of AI in business, to investigate its impact on the efficiency and effectiveness of business processes, as well as to identify the challenges and limitations associated with the use of this technology.Methodology.The research methodology includes empirical and analytical methods, statistical analysis is also used, revealing the features of the introduction of artificial intelligence in the business sphere.Results. It has been revealed that the main areas of application of artificial intelligence in business are sales and communication with customers, marketing, content creation, and personnel management. The important aspects that companies should pay attention to when implementing artificial intelligence are indicated.Conclusions. The results of the study showed that artificial intelligence (AI) has huge potential to improve business efficiency and productivity. Data security is a key aspect when using AI in business. Companies should pay special attention to the protection of information, ensuring confidentiality and data integrity. It is also important to keep in mind the ethical aspects of using AI in business, such as fairness, transparency and responsibility for decisions.
Artificial Intelligence (AI) integration in education has evolved significantly, with today's AI systems surpassing conventional computer-assisted teaching methods by providing more dynamic and interactive learning environments. This study aims to design and implement an Ethical AI-based teaching assistant tailored for IoT security education, marking a new milestone in the advancement of AI in educational settings. The system focused on ethical considerations such as data privacy, transparency, and accountability, fostering a learning environment where students can think critically, explore diverse perspectives, and engage meaningfully with AI technology. Central to the project's success was a robust design phase that included carefully selecting AI algorithms, a modular and scalable architecture, an intuitive user interface, and efficient data flow mechanisms. Thorough testing and continuous improvements ensured seamless integration with existing educational technologies, enhancing learning and teaching experiences. As a result, students demonstrated a 35% increase in their ability to identify and mitigate IoT security threats, a 30% improvement in engagement, and educators saw a 45% reduction in grading time due to the AI's automated assessment capabilities. Additionally, the project increased student satisfaction, greater utilization of learning resources, and the publication of research papers on IoT security. This study highlights the transformative potential of AI in education and underscores the importance of ethical considerations in its application. With its comprehensive approach to design, scalability, and security, this project serves as a model for the future of Ethical AI-driven education, offering valuable insights into how AI can enhance learning outcomes and teaching effectiveness while maintaining academic integrity and data security.
This article provides a theoretical examination of the utilization of artificial intelligence (AI) by the Associated Press (AP), focusing on the ethical considerations inherent in its AI practices. With a historical legacy spanning 170 years, AP has evolved into a global news agency that embraces AI across various facets of its operations. The study explores AP's integration of AI in areas such as content generation, data journalism, language translation, and audience engagement, emphasizing the ethical dimensions of these applications. The ethical framework employed by AP is scrutinized through an analysis of its coverage depth, content quality, and transparency. The study also delves into the ethical implications of AP's automatic content generation processes, which leverage AI algorithms for expeditious news production. Emphasizing the symbiotic relationship between AI and journalism, the research contemplates how technology can augment human capacities while necessitating vigilance against potential biases and misinformation. Furthermore, the study scrutinizes how AP navigates ethical challenges in language translation, audience engagement, and market analysis through AI. The agency's use of AI to enhance multimedia elements, personalize content, and forecast audience interests prompts an exploration of the ethical implications of tailoring information to individual preferences. By examining the agency's multifaceted use of AI, the study contributes valuable insights into the evolving relationship between journalism, technology, and ethical responsibility. Ultimately, it underscores the imperative for news organizations to adopt principled approaches to AI integration, ensuring that advancements in technology align with ethical journalism practices.
A civil servant or civil servant (English: civil servant, Dutch: ambtenaar) is a person employed by a government agency to provide public services. As a profession, civil servants are positions that are pursued through career paths and not based on general elections involving the people's vote. Quoted from the Regulation of the Head of BKN No. 35 of 2011 concerning Guidelines for the Preparation of PNS Careers, the career pattern of civil servants is arranged based on the principles of certainty, professionalism, and transparency. One of the requirements to achieve the desired career is through the promotion process. The promotion or class of a civil servant cannot be separated from the recommendation of the leadership. A leader in providing recommendations must look at several important points that must be possessed by employees who will be given recommendations such as Attendance, Integrity, Cooperation and Insight or Knowledge. In the process, there are still problems in terms of technical and effectiveness because manual assessments sometimes still assess subjectively. Therefore, a study was carried out for the classification of the determination of the status of giving recommendations using the Naïve Bayes method. Naive Bayes is one method of probabilistic reasoning. The Naive Bayes algorithm aims to classify data in certain classes, then the pattern can be used to estimate the employee who will be given a recommendation, so that the leader can make a decision to give recommendation or not to the employee
The social impacts of computer technology are often glorified in public discourse, but there is growing concern about its actual effects on society. In this article, we ask: how does "consent" as an analytical framework make visible the social dynamics and power relations in the capture, extraction, and labor of data science knowledge production? We hypothesize that a form of boundary violation in data science workplaces—gender harassment—may correlate with the ways humans' lived experiences are extracted to produce Big Data. The concept of consent offers a useful way to draw comparisons between gender relations in data science and the means by which machines are trained to learn and reason. Inspired by how Big Tech leaders describe unsupervised machine learning, and the co-optation of "revolutionary" rhetoric they use to do so, we introduce a concept we call "techniques of invisibility." Techniques of invisibility are the ways in which an extreme imbalance between exposure and opacity, demarcated along fault lines of power, are fabricated and maintained, closing down the possibility for bidirectional transparency in the production and applications of algorithms. Further, techniques of invisibility, which we group into two categories—epistemic injustice and the Brotherhood—include acts of subjection by powerful actors in data science designed to quell resistance to exploitative relations. These techniques may be useful in making further connections between epistemic violence, sexism, and surveillance, sussing out persistent boundary violations in data science to render the social in data science visible, and open to scrutiny and debate.
AbstractAI governance is like one of those mythical creatures that everyone speaks of but which no one has seen. Sometimes, it is reduced to a list of shared principles such as transparency, non-discrimination, and sustainability; at other times, it is conflated with specific mechanisms for certification of algorithmic solutions or ways to protect the privacy of personal data. We suggest a conceptual and normative approach to AI governance in the context of a global digital public goods ecosystem to enable progress on the UN Sustainable Development Goals (SDGs). Conceptually, we propose rooting this approach in the human capability concept—what people are able to do and to be, and in a layered governance framework connecting the local to the global. Normatively, we suggest the following six irreducibles: a. human rights first; b. multi-stakeholder smart regulation; c. privacy and protection of personal data; d. a holistic approach to data use captured by the 3Ms—misuse of data, missed use of data and missing data; e. global collaboration ('digital cooperation'); f. basing governance more in practice, in particular, thinking separately and together about data and algorithms. Throughout the article, we use examples from the health domain particularly in the current context of the Covid-19 pandemic. We conclude by arguing that taking a distributed but coordinated global digital commons approach to the governance of AI is the best guarantee of citizen-centered and societally beneficial use of digital technologies for the SDGs.
Prozesse algorithmischer Entscheidungsfindung berühren in vielen Bereichen gesellschaftliche Teilhabe. Daraus ergeben sich Herausforderungen auf vier Feldern: 1. Gesellschaftliche Angemessenheit (Haben algorithmische Systeme sinnvolle Optimierungsziele?) 2. Überprüfen und erklären der Umsetzung (Verwirklichen algorithmische Systeme die sinnvollen Ziele?) 3. Schaffen von Diversität (Ist die Vielfalt der Systeme und Betreibermodelle groß genug, um gesellschaftlich angemessen zu sein?) 4. Übergreifende Rahmenbedingungen für teilhabeförderliche algorithmische Systeme (Genügen staatliche und individuelle Gestaltungskompetenzen dem gesellschaftlichen Anspruch?) Der Beitrag stellt eine Auswahl von Lösungsideen in allen vier skizzierten Handlungsfeldern vor. Die Auswahl ist nicht umfassend und abschließend. Sie veranschaulicht aber auch in dieser Form, dass Akteure aus allen drei Sektoren Möglichkeiten haben, algorithmische Entscheidungsfindung für mehr gesellschaftliche Teilhabe zu gestalten. Es gibt viele Ideen für Maßnahmen und Methoden bzgl. der gesellschaftlichen Gestaltung, Intervention und Kontrolle algorithmischer Entscheidungsfindung. Keineswegs scheint der Mensch der Maschine ausgeliefert.
UK: Обґрунтовано роль та місце бюджету участі в умовах фінансової децентралізації. Визначено, що бюджет участі є дієвим засобом взаємодії влади та громадськості, який поєднує в собі принципи демократії та прозорості. Узагальнено зарубіжний і вітчизняний досвід реалізації процесу партиципаторного бюджетування на місцях. Доведено, що впровадження бюджету участі, як дієвого інструменту розвитку територіальних громад, надає значні переваги, зокрема: сприяє прозорості бюджетного процесу в цілому і, як наслідок, зниженню корупції у витрачанні бюджетних коштів, підвищенню громадської свідомості, зростанню обізнаності в питаннях місцевого самоврядування серед населення, збільшує довіру між владою та громадою, що дає можливість успішної реалізації спільних програм і проектів сталого розвитку громади. Наведено алгоритм і рекомендації щодо ефективного впровадження та реалізації бюджету участі в територіальних громадах. RU: Обоснована роль и место бюджета участия в условиях финансовой децентрализации. Определено, что бюджет участия является действенным средством взаимодействия власти и общественности, который сочетает в себе принципы демократии и прозрачности. Обобщен зарубежный и отечественный опыт реализации процесса партиципаторного бюджетирования на местах. Доказано, что внедрение бюджета участия, как действенного инструмента развития территориальных общин, предоставляет значительные преимущества, в частности: способствует прозрачности бюджетного процесса в целом и, как следствие, снижению коррупции в расходовании бюджетных средств, повышению общественного сознания, повышению осведомленности в вопросах местного самоуправления среди населения, увеличивает доверие между властью и обществом, что дает возможность успешной реализации совместных программ и проектов устойчивого развития общества. Приведен алгоритм и рекомендации по эффективному внедрению и реализации бюджета участия в территориальных общинах. EN: Introduction. The reform of public finances in Ukraine involves implementing measures to increase the openness and transparency of the budget system. Ensuring the transparency of the budget process and the participation of the population in its organization envisages timely and accurate disclosure of information on the use of budget funds, as well as the ability of the public to participate in the formation and implementation of the budget, which is indisputable sign of democracy in many countries around the world. Purpose. The purpose of the article is to study the issues of effective implementation of the participation budget in the context of decentralization, also the development of practical recommendations for improving the dialogue between local authorities and society on the basis of cooperation in the context of participative budgeting. Results. The role and place of the participation budget in the system of public finance in terms of financial decentralizations are justified. Foreign and domestic experience of introducing participatory budgeting in the field is generalized. The algorithm for implementation and implementation of participatory budgeting and recommendations for effective implementation of the budget for participation in the community are presented. Conclusions. The participation budget is an effective tool for interaction between government and society, which combines the principles of democracy and transparency. Of course, the introduction of a budget for participation in the context of decentralization reform offers significant benefits. Particularly relevant is the introduction of the participation budget for newly formed united territorial communities. If previously small financially unprofitable communities were not able to use participatory budgeting in their territory, now, with voluntary unions, they are getting new financial opportunities for their development, using best practices in the participation budget in large and small cities.
Цель исследования оценка организации работы специалиста в области судебной медицины на месте происшествия с позиции построения системы менеджмента качества. Одновременно была проанализирована регламентирующая указанную деятельность нормативная документация, подробно разобраны задачи, стоящие перед судебно-медицинским экспертом, функциональные взаимосвязи участников процесса. Материал и методы. В исследовании изучался опыт судебно-экспертного учреждения по выездам на места происшествия. Применялся метод моделирования бизнес-процессов (BPM Business Process Management), использовался процессный подход при организации работы. Результаты и их обсуждение. Анализ работы врача судебно-медицинского эксперта на месте происшествия с позиции процессного подхода показал, что осмотр места происшествия и трупа в конкретном учреждении требует регламентации внутриведомственными, межведомственными нормативными документами. Разработанная модель алгоритма выявила важнейшие аспекты организации работы на месте происшествия, не имеющие законодательной базы, выявила риски при организации этой деятельности. Заключение. Авторы предлагают внедрить на всей территории Татарстана разработанный с позиции процессного подхода алгоритм организации работы на месте происшествия. Представленная модель является хорошей памяткой для врача судебно-медицинского эксперта, позволяющей организовать и обеспечить качественную работу на месте происшествия, в том числе для вновь принятых сотрудников, и прозрачность процессуальных действий для родных и близких умерших.Aim. Assessment of the work activity management of forensic medicine specialists on emergency site from perspective of the quality management system. Normative documents regulating this activity were analyzed; the duties of forensic pathologist were discussed in detail as well as their functional relationships. Material and methods. The study was aiming to investigate the experience of forensic institutions for inspections on the emergency site. The authors have used business process modeling method (Business Process Management) and process approach to the work activity management. Results and discussion. Analysis of the work of forensic pathologist at emergency site from perspective of the process approach has shown that the inspections of the site and of the dead body requires intraand interdepartmental regulations. The model (algorithm) identifies the most important aspects of the work at the site that does not have a legislative framework. The risks were identified in organization of this activity. Conclusion. The authors propose to implement the algorithm developed from perspective of the process approach for the work activity management at the site in the whole territory of Tatarstan. The model is a good reminder to forensic pathologists, for newly hired employees as well, which allows organizing and providing high quality of work at the site as well as the transparency of proceedings for relatives and friends of the dead person.
The article presents an analysis of the institutional support for the development of investment activity in the agricultural sector of Ukraine, which is considered as a set of legislative, regulatory, organizational and management mechanisms aimed at forming a favorable investment environment. It is proven that effective institutional support is an important factor for ensuring the development of the industry, its modernization and integration into global economic processes. It is determined that the modern system of regulation of investment activity is characterized by fragmentation, lack of clear coordination between state authorities, insufficient transparency of procedures and limited state support for small and medium-sized business entities. Existing management mechanisms need optimization, especially in terms of adaptation to modern challenges and conditions of international partnership. An integrated approach to improving institutional support is proposed, which considers the creation of a single coordinating body for managing financial flows, distributing resources and attracting international assistance. The introduction of such an institution, which will cooperate with international organizations (IMF, World Bank, EBRD), will allow achieving transparency of management processes, increasing the efficiency of resource allocation and reducing the risks of corruption. The article also substantiates the need to form agricultural technology parks as centers of innovative development, which will contribute to the introduction of modern technologies of precision agriculture, ecological production and energy saving, which will ensure increased efficiency of the agricultural sector and its export potential. Special attention is paid to the systematization of the decision-making process within the framework of institutional regulation. An algorithm of management actions is proposed, which covers the stages from problem analysis to monitoring of implementation and evaluation of results. It is summarized that the improvement of institutional support should be based on the introduction of modern monitoring technologies, such as digital platforms, geographic information systems, blockchain and big data. The results of the study can be the basis for developing strategies for the development of the agricultural sector aimed at improving the investment climate, stimulating innovation and integrating into international markets. Further research should focus on adapting best international practices, assessing the effectiveness of the proposed innovation mechanisms and developing a system of indicators for monitoring changes in the investment environment. The implementation of the proposed measures will ensure the sustainable development of the agricultural sector of Ukraine, strengthen its economic potential and contribute to food security. Keywords: agricultural sector, institutional support, innovation mechanisms, investment monitoring, public-private partnership, economic stability.
The corporate discourse on the circular economy holds that the growth of the electronics industry, driven by continuous innovation, does not imperil ecological sustainability. To achieve sustainable growth, its advocates propose optimizing recycling by means of artificial intelligence and sets of interrelated datacentric and algorithmic technologies. Drawing on critical data and algorithm studies, theories of waste, and empirical research, this paper investigates ecological ethics in the context of the datacentric and algorithmically mediated circular economy. It foregrounds the indeterminate and fickle material nature of waste as well as the uncertainties inherent in, and stemming from, datafication and computation. My question is: how do the rationalities, affordances, and dispositions of datacentric and algorithmic technologies perform and displace notions of corporate responsibility and transparency? In order to answer this question, I compare the smart circular economy to the informal recycling practices that it claims to replace, and I analyze relations between waste matter and data as well as distributions of agency. Specifically, I consider transitions and slippages between response-ability and responsibility. Conceptually, I bring process-relation or immanence-based philosophies such as Bergson's and Deleuze's into a debate about relations between waste matter and data and the ambition of algorithmic control over waste. My aim is not to demand heightened corporate responsibility enacted through control but to rethink responsibility in the smart circular economy along the lines of Amoore's cloud ethics to carve out a position of critique beyond either a deontological perspective that reinforces corporate agency or new-materialist denunciation of the concept.
Abstract This article examines the requirements of the right to a fair trial in the context of the use of machine-learning algorithms (MLAs) in judicial proceedings, with a focus on a core component of this right, the right to be heard. Though NGOs and scholars have begun to note that the right to a fair trial may be the best framework to address the challenges raised by MLAs, the actual requirements of the right in this novel context are underdeveloped. This article evaluates two normative approaches to filling this gap. The first approach, the argument from fairness, produces three broad categories of measures for ensuring fairness: measures for increasing the transparency and accountability of MLAs, measures for ensuring the participation of litigants, and measures for securing the impartiality of the human judge. However, this article argues that the argument from fairness cannot provide the necessary normative grounding for the right to a fair trial in the context of MLAs, as it collapses into the concept of 'algorithmic fairness'. The second approach is based on the concept of human dignity as a status. The primary argument of this article is that the concept of human dignity as a status can provide better normative grounding for the right to a fair trial because it offers an account of human personhood that resists the de-humanization of data subjectification. That richer account of human personhood allows us to think of the trial not only as a vehicle for accurate outcomes, but also as a forum for the expression of human dignity.
