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This study addresses a novel perspective for analyzing the source of confidence in human behavior. The concept of confidence was examined via the relationship between two phenomena in the area of machine learning and psychology, namely the Dunning-Kruger effect and the curse of dimensionality. A relationship was established between these two phenom...
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... O is a finite set of objects identified by unique symbolic names, A is a finite set of attributes for characterizing each object, and R is a set of relations between objects and attributes. The illustration of OAR model is shown in Figure 3. As shown in the OAR model, the memory architecture of human is consist of the enormous number of networks. ...
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Incremental Learning is a particular form of machine learning that enables a model to be modified incrementally, when new data becomes available. In this way, the model can adapt to the new data without the lengthy and time-consuming process required for complete model re-training. However, existing incremental learning methods face two significant...
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... Крім загальновідомих проблем дослідження ефекту Даннінга-Крюгера ряд дослідників звертає увагу на фактор знань: політична компетентність залежить від якості політичних знань, від їхнього рівня обмеженості та широти охоплення [2], навіть ті, хто має навички, можуть покладатися на неправильну інформацію при оцінці своїх дій [15], впевненість тісно пов'язана із загальним часом, який потрібний для отримання конкретної інформації, і цей зв'язок обернено пропорційний [9], вирішення проблемце метакогнітивний процес мозку, що складається з їх когнітивних процесів абстракції, пошуку, навчання, прийняття рішень, висновку, аналізу та синтезу [52], досвідчені експерти не тільки дають більш точні оцінки різних ситуацій, ніж експерти-новачки, але й дають більш точні оцінки точності своїх оцінок [1], мета-невігластво буде завжди, поки люди не знатимуть всього [20], ефект Даннінга-Крюгера може статися з кожним, незалежно від рівня його інтелекту [42], погані виконавці в цілому прокляті подвійно: їм не вистачає знання матеріалу, і вони не усвідомлюють, які вони мають знання і які не мають [29]. ...
The nature of the emergence of the need to introduce computers, introduce digital technologies and conduct digital transformations is analyzed. It is proposed to consider digital transformation as a response to civilizational challenges, the essence of which is reduced to the existence of civilizational cognitive contradictions of mankind. It is the presence of civilizational cognitive contradictions that is a prerequisite for the systemic adoption of wrong decisions, the unrestrained accumulation of which is the source of degradation of civilization. An understanding of the civilizational mission of digital transformation has been formed.
... However, this raises a relevant link between the curse of dimensionality and overconfidence issues in machine learning models as described in other works (e.g. [27]). ...
The Rashōmon effect poses challenges for deriving reliable knowledge from machine learning models. This study examined the influence of sample size on explanations from models in a Rashōmon set using SHAP. Experiments on 5 public datasets showed that explanations gradually converged as the sample size increased. Explanations from <128 samples exhibited high variability, limiting reliable knowledge extraction. However, agreement between models improved with more data, allowing for consensus. Bagging ensembles often had higher agreement. The results provide guidance on sufficient data to trust explanations. Variability at low samples suggests that conclusions may be unreliable without validation. Further work is needed with more model types, data domains, and explanation methods. Testing convergence in neural networks and with model-specific explanation methods would be impactful. The approaches explored here point towards principled techniques for eliciting knowledge from ambiguous models.
The monograph titled "Digital Transformations of Society: Problems of Law" by Oleksandr Baranov et al. is a comprehensive investigation into the legal, social, and ethical ramifications of the rapid integration of digital technologies into various facets of human, societal, and state activities. This pivotal work delineates the theoretical and methodological underpinnings essential for crafting and reforming legal frameworks to adeptly govern the burgeoning types of social relations engendered by digital advancements. It scrutinizes the pressing challenges and prospects of digital transformation, underscoring the critical necessity for legal support in mitigating the complexities of modern decision-making processes and fostering large-scale social transformations.
The monograph is structured into four enlightening chapters that explore the intricate interplay between legal norms and digital innovations, such as artificial intelligence, robotics, and Web 3.0 technologies. It articulates the urgent need for legal systems to evolve in tandem with digital and social transformations, advocating for a "results-based economy" facilitated by Internet of Things technologies to ensure sustainable and high-quality life standards globally.
Furthermore, the work extends its analytical purview to the Metaverse, addressing the legal, technical, and ethical considerations for AI application within this burgeoning virtual realm. It highlights the lagging development and implementation of Metaverse technologies in Ukraine, compared to global strides, emphasizing the significant potential these technologies hold for the nation's development and recovery.
Moreover, the monograph delves into the ethical dimensions of AI and robotics development, supported by an empirical study of over 80 Codes of Ethical Principles. This section illuminates the evolving regulatory focus from hardware to software, spotlighting the ethical imperatives of fairness, responsibility, and accountability in technology implementation.
In sum, "Digital Transformations of Society: Problems of Law" presents a visionary perspective on the necessity for a holistic legal and ethical overhaul to adeptly navigate and harness the potentials of digital transformation. It calls for a concerted effort among governments, the private sector, and international bodies to forge comprehensive strategies that address the multifaceted challenges and opportunities presented by the digital age, ensuring a future that harmonizes technological innovation with ethical and legal integrity.
The Dunning Kruger Effect, which states that individuals with little or no knowledge about a subject have more self-confidence than experts, was first put forward as a result of a social experiment in 1999. Over time, the concept has become a theory that has been accepted in the literature and has been the subject of studies in some branches of science and has been translated into Turkish as Cahil Cesareti. In this direction, the aim of the study is to analyze the Google search frequencies of the words "Dunning Kruger Effect" and "Ignorant Courage" and to determine the level of awareness of the concepts in the USA and Turkey comparatively. As a result of the Google Trends data and literature review, it has been determined that the Dunning Kruger Effect theory is known in the USA both in the general category and in the finance category. In Turkey, it has been seen that the related concept is known in the general category and has been the subject of some studies. In addition, it was stated that the related concept does not have financial awareness, as a result of both Google Trends data and literature search. In this direction, the study adds originality to the national literature at the stage of determining the level of awareness of the Dunning Kruger Effect theory, whose Turkish equivalent is Ignorant Courage, in the finance literature.
