Thematische Bibliographien / Responsible Artificial Intelligence

Inhaltsverzeichnis

  1. Zeitschriftenartikel
  2. Dissertationen
  3. Bücher
  4. Buchteile
  5. Konferenzberichte
  6. Berichte der Organisationen

Auswahl der wissenschaftlichen Literatur zum Thema „Responsible Artificial Intelligence“

Autor: Grafiati
Veröffentlicht am 16. November 2024
Zuletzt aktualisiert am 25. Juli 2025

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Zeitschriftenartikel zum Thema "Responsible Artificial Intelligence"

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Tawei Wang, Tawei Wang. "Responsible Use of Artificial Intelligen." International Journal of Computer Auditing 4, no. 1 (2022): 001–3. http://dx.doi.org/10.53106/256299802022120401001.

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<p>Artificial intelligence (AI) has once again attracted the public’s attention in the past decade. Riding on the wave of big data revolution, the development of AI is much more promising than that 50 years ago. One example is ChatGPT (https://openai.com/blog/chatgpt/), which has quickly become a hot topic in the past several months and has brought back all kinds of discussion about AI and decision making. In this editorial, I would like to highlight several perspectives that may help us rethink about the implications of using AI for decision making especially for audit profess
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NATASHA, ANJUM. "ARTIFICIAL INTELLIGENCE." GPH - International Journal Of Computer Science and Engineering 07, no. 01 (2024): 01–11. https://doi.org/10.5281/zenodo.10628529.

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<strong>This research paper provides a comprehensive examination of the evolution and impact of artificial intelligence (AI) across various domains. The study delves into the historical development of AI, tracing its origins from classical rule-based systems to the contemporary era of machine learning and deep neural networks. The paper explores the key technological advancements that have propelled AI research, discussing breakthroughs in natural language processing, computer vision, and reinforcement learning. This study's paper offers a nuanced exploration of the present-day state and futur
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Teng, C. L., A. S. Bhullar, P. Jermain, et al. "Responsible Artificial Intelligence in Radiation Oncology." International Journal of Radiation Oncology*Biology*Physics 120, no. 2 (2024): e659. http://dx.doi.org/10.1016/j.ijrobp.2024.07.1446.

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Gregor, Shirley. "Responsible Artificial Intelligence and Journal Publishing." Journal of the Association for Information Systems 25, no. 1 (2024): 48–60. http://dx.doi.org/10.17705/1jais.00863.

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The aim of this opinion piece is to examine the responsible use of artificial intelligence (AI) in relation to academic journal publishing. The work discusses approaches to AI with particular attention to recent developments with generative AI. Consensus is noted around eight normative themes for principles for responsible AI and their associated risks. A framework from Shneiderman (2022) for human-centered AI is employed to consider journal publishing practices that can address the principles of responsible AI at different levels. The resultant AI principled governance matrix (AI-PGM) for jou
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Haidar, Ahmad. "An Integrative Theoretical Framework for Responsible Artificial Intelligence." International Journal of Digital Strategy, Governance, and Business Transformation 13, no. 1 (2023): 1–23. http://dx.doi.org/10.4018/ijdsgbt.334844.

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The rapid integration of Artificial Intelligence (AI) into various sectors has yielded significant benefits, such as enhanced business efficiency and customer satisfaction, while posing challenges, including privacy concerns, algorithmic bias, and threats to autonomy. In response to these multifaceted issues, this study proposes a novel integrative theoretical framework for Responsible AI (RAI), which addresses four key dimensions: technical, sustainable development, responsible innovation management, and legislation. The responsible innovation management and the legal dimensions form the foun
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Shneiderman, Ben. "Responsible AI." Communications of the ACM 64, no. 8 (2021): 32–35. http://dx.doi.org/10.1145/3445973.

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Dignum, Virginia. "Responsible Artificial Intelligence --- From Principles to Practice." ACM SIGIR Forum 56, no. 1 (2022): 1–6. http://dx.doi.org/10.1145/3582524.3582529.

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The impact of Artificial Intelligence does not depend only on fundamental research and technological developments, but for a large part on how these systems are introduced into society and used in everyday situations. AI is changing the way we work, live and solve challenges but concerns about fairness, transparency or privacy are also growing. Ensuring responsible, ethical AI is more than designing systems whose result can be trusted. It is about the way we design them, why we design them, and who is involved in designing them. In order to develop and use AI responsibly, we need to work towar
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Rodrigues, Rowena, Anais Resseguier, and Nicole Santiago. "When Artificial Intelligence Fails." Public Governance, Administration and Finances Law Review 8, no. 2 (2023): 17–28. http://dx.doi.org/10.53116/pgaflr.7030.

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Diverse initiatives promote the responsible development, deployment and use of Artificial Intelligence (AI). AI incident databases have emerged as a valuable and timely learning resource and tool in AI governance. This article assesses the value of such databases and outlines how this value can be enhanced. It reviews four databases: the AI Incident Database, the AI, Algorithmic, and Automation Incidents and Controversies Repository, the AI Incident Tracker and Where in the World Is AI. The article provides a descriptive analysis of these databases, examines their objectives, and locates them
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Raso, Jennifer. "Responsible AI." McGill Law Journal 69, no. 4 (2024): 417–39. https://doi.org/10.26443/law.v69i4.1627.

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This article examines responsible AI as a public law-like movement that seeks to (self)regulate the design and use of AI systems. Using socio-legal methods, and the Montréal Declaration for a Responsible Development of Artificial Intelligence as an illustrate example, it explores responsible AI’s upshots for digital government. Responsible AI initiatives, this article argues, rely on two binary distinctions: (1) between artificial and natural intelligence, and (2) between the future and present/past effects of AI systems. These conceptual binaries “bind” such initiatives to an impoverished und
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Germanov, Nikolai S. "The concept of responsible artificial intelligence as the future of artificial intelligence in medicine." Digital Diagnostics 4, no. 1S (2023): 27–29. http://dx.doi.org/10.17816/dd430334.

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Active deployment of artificial intelligence (AI) systems in medicine creates many challenges. Recently, the concept of responsible artificial intelligence (RAI) was widely discussed, which is aimed at solving the inevitable ethical, legal, and social problems. The scientific literature was analyzed and the possibility of applying the RAI concept to overcome the existing AI problems in medicine was considered. Studies of possible AI applications in medicine showed that current algorithms are unable to meet the basic enduring needs of society, particularly, fairness, transparency, and reliabili
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Dissertationen zum Thema "Responsible Artificial Intelligence"

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Svedberg, Peter O. S. "Steps towards an empirically responsible AI : a methodological and theoretical framework." Thesis, Norwegian University of Science and Technology, Department of Computer and Information Science, 2004. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-246.

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<p>Initially we pursue a minimal model of a cognitive system. This in turn form the basis for the development of amethodological and theoretical framework. Two methodological requirements of the model are that explanation be from the perspective of the phenomena, and that we have structural determination. The minimal model is derived from the explanatory side of a biologically based cognitive science. Fransisco Varela is our principal source for this part. The model defines the relationship between a formally defined autonomous system and an environment, in such a way as to generate the world
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Ounissi, Mehdi. "Decoding the Black Box : Enhancing Interpretability and Trust in Artificial Intelligence for Biomedical Imaging - a Step Toward Responsible Artificial Intelligence." Electronic Thesis or Diss., Sorbonne université, 2024. http://www.theses.fr/2024SORUS237.

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À une époque dominée par l'IA, son processus décisionnel opaque, connu sous le nom de problème de la "boîte noire", pose des défis significatifs, particulièrement dans des domaines critiques comme l'imagerie biomédicale où la précision et la confiance sont essentielles. Notre recherche se concentre sur l'amélioration de l'interprétabilité de l'IA dans les applications biomédicales. Nous avons développé un cadre pour l'analyse d'images biomédicales qui quantifie la phagocytose dans les maladies neurodégénératives à l'aide de la microscopie vidéo à contraste de phase en accéléré. Les méthodes tr
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Haidar, Ahmad. "Responsible Artificial Intelligence : Designing Frameworks for Ethical, Sustainable, and Risk-Aware Practices." Electronic Thesis or Diss., université Paris-Saclay, 2024. https://www.biblio.univ-evry.fr/theses/2024/interne/2024UPASI008.pdf.

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L'intelligence artificielle (IA) transforme rapidement le monde, redéfinissant les relations entre technologie et société. Cette thèse explore le besoin essentiel de développer, de gouverner et d'utiliser l'IA et l'IA générative (IAG) de manière responsable et durable. Elle traite des risques éthiques, des lacunes réglementaires et des défis associés aux systèmes d'IA, tout en proposant des cadres concrets pour promouvoir une Intelligence Artificielle Responsable (IAR) et une Innovation Numérique Responsable (INR).La thèse commence par une analyse approfondie de 27 déclarations éthiques mondia
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Sugianto, Nehemia. "Responsible AI for Automated Analysis of Integrated Video Surveillance in Public Spaces." Thesis, Griffith University, 2021. http://hdl.handle.net/10072/409586.

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Understanding customer experience in real-time can potentially support people’s safety and comfort while in public spaces. Existing techniques, such as surveys and interviews, can only analyse data at specific times. Therefore, organisations that manage public spaces, such as local government or business entities, cannot respond immediately when urgent actions are needed. Manual monitoring through surveillance cameras can enable organisation personnel to observe people. However, fatigue and human distraction during constant observation cannot ensure reliable and timely analysis. Artificial int
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Kessing, Maria. "Fairness in AI : Discussion of a Unified Approach to Ensure Responsible AI Development." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-299936.

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Besides entailing various benefits, AI technologies have also led to increased ethical concerns. Due to the growing attention, a large number of frameworks discussing responsible AI development have been released since 2016. This work aims at analyzing some of these proposals to answer the question (1) “Which approaches can be found to ensure responsible AI development?” For this, the theory section of this paper is looking at various approaches, including (inter-)governmental regulations, research organizations and private companies.  Further, expert interviews have been conducted to answer t
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Umurerwa, Janviere, and Maja Lesjak. "AI IMPLEMENTATION AND USAGE : A qualitative study of managerial challenges in implementation and use of AI solutions from the researchers’ perspective." Thesis, Umeå universitet, Institutionen för informatik, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-187810.

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Artificial intelligence (AI) technologies are developing rapidly and cause radical changes in organizations, companies, society, and individual levels. Managers are facing new challenges that they might not be prepared for. In this work, we seek to explore managerial challenges experienced while implementing and using AI technologies from the researchers’ perspective. Moreover, we explore how appropriate ethical deliberations should be applied when using big data concerning AI and the meaning of understanding or defining it. We describe qualitative research, the triangulation that includes rel
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"Responsible Governance of Artificial Intelligence: An Assessment, Theoretical Framework, and Exploration." Doctoral diss., 2019. http://hdl.handle.net/2286/R.I.55667.

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abstract: While artificial intelligence (AI) has seen enormous technical progress in recent years, less progress has occurred in understanding the governance issues raised by AI. In this dissertation, I make four contributions to the study and practice of AI governance. First, I connect AI to the literature and practices of responsible research and innovation (RRI) and explore their applicability to AI governance. I focus in particular on AI’s status as a general purpose technology (GPT), and suggest some of the distinctive challenges for RRI in this context such as the critical importance of
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Arienti, João Henrique Leal. "Time series forecasting applied to an energy management system ‐ A comparison between Deep Learning Models and other Machine Learning Models." Master's thesis, 2020. http://hdl.handle.net/10362/108172.

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Project Work presented as the partial requirement for obtaining a Master's degree in Data Science and Advanced Analytics<br>A large amount of energy used by the world comes from buildings’ energy consumption. HVAC (Heat, Ventilation, and Air Conditioning) systems are the biggest offenders when it comes to buildings’ energy consumption. It is important to provide environmental comfort in buildings but indoor wellbeing is directly related to an increase in energy consumption. This dilemma creates a huge opportunity for a solution that balances occupant comfort and energy consumption. Within
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Voarino, Nathalie. "Systèmes d’intelligence artificielle et santé : les enjeux d’une innovation responsable." Thèse, 2019. http://hdl.handle.net/1866/23526.

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L’avènement de l’utilisation de systèmes d’intelligence artificielle (IA) en santé s’inscrit dans le cadre d’une nouvelle médecine « haute définition » qui se veut prédictive, préventive et personnalisée en tirant partie d’une quantité inédite de données aujourd’hui disponibles. Au cœur de l’innovation numérique en santé, le développement de systèmes d’IA est à la base d’un système de santé interconnecté et auto-apprenant qui permettrait, entre autres, de redéfinir la classification des maladies, de générer de nouvelles connaissances médicales, ou de prédire les trajectoires de santé des indiv
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Bücher zum Thema "Responsible Artificial Intelligence"

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Dignum, Virginia. Responsible Artificial Intelligence. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-30371-6.

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Schmidpeter, René, and Reinhard Altenburger, eds. Responsible Artificial Intelligence. Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-09245-9.

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Kumar Jain, Deepak, Kirti Raj Bhatele, Deepak Garg, and Gaurav Dhiman. A Compendium of Responsible Artificial Intelligence. CRC Press, 2025. https://doi.org/10.1201/9781003514497.

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Khoshnevisan, Mohammad. Artificial intelligence and responsive optimization. 2nd ed. Xiquan, 2003.

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Khoshnevisan, Mohammad. Artificial intelligence and responsive optimization. Xiquan, 2003.

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Khamparia, Aditya, Deepak Gupta, Ashish Khanna, and Valentina E. Balas, eds. Biomedical Data Analysis and Processing Using Explainable (XAI) and Responsive Artificial Intelligence (RAI). Springer Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-1476-8.

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Responsible Artificial Intelligence. Springer, 2020.

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Altenburger, Reinhard, and René Schmidpeter. Responsible Artificial Intelligence: Challenges for Sustainable Management. Springer International Publishing AG, 2022.

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Responsible Artificial Intelligence: Challenges for Sustainable Management. Springer International Publishing AG, 2024.

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Kaplan, Jerry. Artificial Intelligence. Oxford University Press, 2016. http://dx.doi.org/10.1093/wentk/9780190602383.001.0001.

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Over the coming decades, Artificial Intelligence will profoundly impact the way we live, work, wage war, play, seek a mate, educate our young, and care for our elderly. It is likely to greatly increase our aggregate wealth, but it will also upend our labor markets, reshuffle our social order, and strain our private and public institutions. Eventually it may alter how we see our place in the universe, as machines pursue goals independent of their creators and outperform us in domains previously believed to be the sole dominion of humans. Whether we regard them as conscious or unwitting, revere
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Buchteile zum Thema "Responsible Artificial Intelligence"

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Dignum, Virginia. "What Is Artificial Intelligence?" In Responsible Artificial Intelligence. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-30371-6_2.

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Leopold, Helmut. "Mastering Trustful Artificial Intelligence." In Responsible Artificial Intelligence. Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-09245-9_6.

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Altenburger, Reinhard. "Artificial Intelligence: Management Challenges and Responsibility." In Responsible Artificial Intelligence. Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-09245-9_1.

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Dignum, Virginia. "Introduction." In Responsible Artificial Intelligence. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-30371-6_1.

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Dignum, Virginia. "Ethical Decision-Making." In Responsible Artificial Intelligence. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-30371-6_3.

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Dignum, Virginia. "Taking Responsibility." In Responsible Artificial Intelligence. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-30371-6_4.

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Dignum, Virginia. "Can AI Systems Be Ethical?" In Responsible Artificial Intelligence. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-30371-6_5.

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Dignum, Virginia. "Ensuring Responsible AI in Practice." In Responsible Artificial Intelligence. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-30371-6_6.

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Dignum, Virginia. "Looking Further." In Responsible Artificial Intelligence. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-30371-6_7.

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Schindler, Matthias, and Frederik Schmihing. "Technology Serves People: Democratising Analytics and AI in the BMW Production System." In Responsible Artificial Intelligence. Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-09245-9_7.

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Konferenzberichte zum Thema "Responsible Artificial Intelligence"

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Herrera, Framcisco. "Responsible Artificial Intelligence Systems: From Trustworthiness to Governance." In 2024 Design, Automation & Test in Europe Conference & Exhibition (DATE). IEEE, 2024. http://dx.doi.org/10.23919/date58400.2024.10546553.

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Vaidya, Gauri, Meghana Kshirsagar, and Conor Ryan. "PurGE: Towards Responsible Artificial Intelligence Through Sustainable Hyperparameter Optimization." In 17th International Conference on Agents and Artificial Intelligence. SCITEPRESS - Science and Technology Publications, 2025. https://doi.org/10.5220/0013262100003890.

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Biswas, Debmalya. "Stateful Monitoring and Responsible Deployment of AI Agents." In 17th International Conference on Agents and Artificial Intelligence. SCITEPRESS - Science and Technology Publications, 2025. https://doi.org/10.5220/0013160300003890.

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Goh, Adison, Benjamin Chee, Matteo Vagnoli, Luca Baldassarre, and Akshay Narayan. "Scaling Responsible Generative AI: Automating Red Teaming of LLM Applications." In 2025 IEEE Conference on Artificial Intelligence (CAI). IEEE, 2025. https://doi.org/10.1109/cai64502.2025.00159.

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Kshirsagar, Meghana, Mihir Sontakke, Gauri Vaidya, Ahmad Alkhan, Aideen Killeen, and Conor Ryan. "Mitigating Algorithmic Bias in Prostate Cancer Risk Stratification with Responsible Artificial Intelligence and Machine Learning." In 17th International Conference on Agents and Artificial Intelligence. SCITEPRESS - Science and Technology Publications, 2025. https://doi.org/10.5220/0013262600003890.

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R, Sukumar, Vinima Gambhir, and Jyoti Seth. "Investigating the Ethical Implications of Artificial Intelligence and Establishing Guidelines for Responsible AI Development." In 2024 International Conference on Advances in Computing Research on Science Engineering and Technology (ACROSET). IEEE, 2024. http://dx.doi.org/10.1109/acroset62108.2024.10743915.

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Saeedi, Payam, Mahsa Goodarzi, and M. Abdullah Canbaz. "Heuristics and Biases in AI Decision-Making: Implications for Responsible AGI." In 2025 6th International Conference on Artificial Intelligence, Robotics and Control (AIRC). IEEE, 2025. https://doi.org/10.1109/airc64931.2025.11077505.

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Mo, Jiayun, and Ong Chin Ann. "Towards Responsible and Ethical AI Chatbot in Education: A Guideline for Developers." In 2024 4th International Conference on Robotics, Automation and Artificial Intelligence (RAAI). IEEE, 2024. https://doi.org/10.1109/raai64504.2024.10949557.

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Yeasin, Mohammed. "Keynote Speaker ICOM'24: Perspective on Convergence of Mechatronics and Artificial Intelligence in Responsible Innovation." In 2024 9th International Conference on Mechatronics Engineering (ICOM). IEEE, 2024. http://dx.doi.org/10.1109/icom61675.2024.10652385.

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Herrera Herbert, Juan, Roberto Arranz Revenga, Javier Angel Ramirez Masferrer, Juan Herrera Ruiz, and Balduino Ramírez García. "ETHICAL AND RESPONSIBLE USE OF ARTIFICIAL INTELLIGENCE IN KNOWLEDGE GENERATION AND TEACHING ACTIVITIES IN THE UNIVERSITY ENVIRONMENT." In 17th International Conference on Education and New Learning Technologies. IATED, 2025. https://doi.org/10.21125/edulearn.2025.2216.

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Berichte der Organisationen zum Thema "Responsible Artificial Intelligence"

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Pinchuk, Olga, and O. V. Kohan. Responsible use of artificial intelligence: a challenge for science and education. Ukrainian Institute of Scientific and Technical Expertise and Information, 2024. https://doi.org/10.33407/lib.naes.id/eprint/740813.

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An analysis of publications in Scopus was carried out, which testifies to the growth of scientific interest in the problems of academic integrity. Sources presenting research on the ethical aspects of the use of AI have been analyzed. Focus areas: pedagogical practices and student experiences, technological advances and ethical considerations, new assessment technologies and strategies, data for decision making, and educational applications.
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Stanley-Lockman, Zoe. Responsible and Ethical Military AI. Center for Security and Emerging Technology, 2021. http://dx.doi.org/10.51593/20200091.

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Allies of the United States have begun to develop their own policy approaches to responsible military use of artificial intelligence. This issue brief looks at key allies with articulated, emerging, and nascent views on how to manage ethical risk in adopting military AI. The report compares their convergences and divergences, offering pathways for the United States, its allies, and multilateral institutions to develop common approaches to responsible AI implementation. Download Full Report
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Pinchuk, Olga. Instructional and Methodological Guidelines on the Implementation and Use of Artificial Intelligence Technologies in Secondary Schools. Institute for Digitalisation of Education of the NAES of Ukraіne, 2024. https://doi.org/10.33407/lib.naes.id/eprint/742889.

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Instructional and Methodological Guidelines on the Implementation and Use of Artificial Intelligence Technologies in Secondary Schools - recommendations that, as of 2024, determine the approach to the responsible, ethical and effective use of generative artificial intelligence tools in general secondary education institutions.
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Lehoux, Pascale, Hassane Alami, Carl Mörch, Lysanne Rivard, Robson Rocha, and Hudson Silva. Can we innovate responsibly during a pandemic? Artificial intelligence, digital solutions and SARS-CoV-2. Observatoire international sur les impacts sociétaux de l’intelligence artificielle et du numérique, 2020. http://dx.doi.org/10.61737/ueti5496.

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As a part of the research project of the International Observatory on the societal impacts of AI and digital technology (OBVIA) regarding the societal effects of A.I. systems and digital tools deployed to combat the spread of COVID-19 and supported by the Québec Research Funds (FRQ), the In Fieri research team leaded by the professor Pascale Lehoux, have produced a policy brief for public decision-makers and developers of AI and digital solutions about responsible innovation during pandemic : Can we innovate responsibly during a pandemic? Artificial intelligence, digital solutions and SARS-CoV
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Narayanan, Mina, and Christian Schoeberl. A Matrix for Selecting Responsible AI Frameworks. Center for Security and Emerging Technology, 2023. http://dx.doi.org/10.51593/20220029.

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Process frameworks provide a blueprint for organizations implementing responsible artificial intelligence (AI), but the sheer number of frameworks, along with their loosely specified audiences, can make it difficult for organizations to select ones that meet their needs. This report presents a matrix that organizes approximately 40 public process frameworks according to their areas of focus and the teams that can use them. Ultimately, the matrix helps organizations select the right resources for implementing responsible AI.
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Artyukhov, Artem, Pavlo Demchuk, Oleg Dubno, et al. Recommendations for the responsible implementation and use of artificial intelligence technologies in higher education institutions. Ministry of Digital Transformation, 2025. https://doi.org/10.33407/lib.naes.id/eprint/745301.

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Документ містить поради для викладачів, студентів, адміністрацій ЗВО та дослідників, що допоможуть ефективно інтегрувати ШІ в освітній і науковий процес. Над розробкою цих порад працювали Міністерство цифрової трансформації та Міністерство освіти і науки України спільно з Робочою групою (в алфавітному порядку): Артем Артюхов; Павло Демчук; Олег Дубно; Тетяна Захарченко; Софія Климчук; Артем Кобрін; Олександр Краковецький; Марія Краснощок; Андрій Купін; Дмитро Мішкін; Тетяна Нанаєва; Ольга Пінчук; Тетяна Смирнова; Дмитро Чумаченко; Олексій Шебанов. Документ розроблено за сприяння проєкту «Цифро
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Vargas, Fernando, and Arturo Muente. Artificial Intelligence Framework for the Inter-American Development Group. Inter-American Development Bank, 2025. https://doi.org/10.18235/0013377.

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Artificial intelligence (AI) has the potential to become a transformative general-purpose technology, reshaping economic, social, and institutional frameworks globally. The Inter-American Development Bank Group (IDBG) recognizes the urgency of fostering AI adoption in Latin America and the Caribbean to catalyze productivity, inclusion, and sustainable development. This document provides a high-level strategic framework to guide IDBGs interventions in advancing AI adoption and responsible use across the region. The document reviews key challenges facing the three dimensions of AI institutions a
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Burstein, Jill. Duolingo English Test Responsible AI Standards. Duolingo, 2023. http://dx.doi.org/10.46999/vcae5025.

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Artificial intelligence (AI) is now instantiated in digital learning and assessment platforms. Many sectors, including tech, government, legal, and military sectors, now have used formalized principles to develop responsible AI standards. While there is a substantial literature around responsible AI more generally (e.g., Fjeld et al., 2020; Gianni et al., 2022; and, NIST, 20231 ), traditional validity frameworks (such as, Xi, 2010a; Chapelle et al., 2008; Kunnan, 2000; and, Kane, 1992) pre-date AI advances, and do not provide formal standards for the use of AI in assessment. The AERA/APA/NCME
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Pasupuleti, Murali Krishna. AI-Driven Marketing Innovations: Personalization and Ethics in the Digital Era. National Education Services, 2025. https://doi.org/10.62311/nesx/rr625.

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Abstract: This article explores the transformative impact of artificial intelligence (AI) on digital marketing, focusing on strategies for delivering personalized content and ensuring ethical advertising. By leveraging AI, marketers can now analyze consumer behavior with precision, enabling targeted content, automated ad placement, and real-time adjustments that enhance user engagement and conversions. The Article examines foundational AI techniques, such as recommendation engines, predictive analytics, and natural language processing, which drive personalization at scale. Additionally, it add
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Pasupuleti, Murali Krishna. AI and Quantum-Nano Frontiers: Innovations in Health, Sustainability, Energy, and Security. National Education Services, 2025. https://doi.org/10.62311/nesx/rr525.

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Abstract: This research report explores transformative advancements at the intersection of Artificial Intelligence (AI), Quantum Computing, and Nanotechnology, focusing on breakthrough innovations in health, sustainability, energy, and global security. By integrating quantum algorithms, AI-driven analytics, and advanced nanomaterials, this report highlights revolutionary solutions in precision medicine, predictive diagnostics, sustainable energy storage, universal water purification, and cybersecurity. Real-world case studies and emerging technologies such as graphene-based nanomaterials, quan
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