Relevant bibliographies by topics / AI

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'AI'

Author: Grafiati
Published: 4 June 2021
Last updated: 25 July 2025

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Journal articles on the topic "AI"

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albarracíín, pilar. "Ai, Ai, Ai." Gastronomica 8, no. 4 (2008): 122. http://dx.doi.org/10.1525/gfc.2008.8.4.122.

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Sachin, Samrat Medavarapu. "Demystifying AI: A Comprehensive Review of Explainable AI Techniques and Applications." European Journal of Advances in Engineering and Technology 10, no. 6 (2023): 49–52. https://doi.org/10.5281/zenodo.13627267.

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Explainable Artificial Intelligence (XAI) seeks to make AI systems more transparent and understandable to users. This review examines the various techniques developed to achieve explainability in AI models and their applications across different domains. We discuss methods such as feature attribution, model simplification, and example-based explanations, highlighting their strengths and limitations. Additionally, we explore the importance of XAI in critical fields like healthcare, finance, and law. The findings underscore the necessity of explainability for trust, accountability, and ethical A
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Shubham, Dighikar. "How Artificial Intelligence Influences the Marketing." Recent Trends in Data Mining and Business Forecasting 1, no. 1 (2020): 1–5. https://doi.org/10.5281/zenodo.3779624.

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Artificial Intelligence is the new revolution in the business and in past few years it is indulged in various fields like science, business, medicine, automation and education, AI is also reached in the marketing business. Most of the big companies are using AI for their advertisement in digital platforms. AI has been changing the way of marketing and sales with consumer perception and its behaviour. The author of the paper is suggested the research about an AI, what it is and how deeply it is applied in marketing and what marketing practitioners can do with AI implication. The author of the p
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Bals, Kees. "Ai! AI..." PodoPost 37, no. 4 (2024): 3. http://dx.doi.org/10.1007/s12480-024-2612-0.

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Euchner, Jim. "Little ai, Big AI—Good AI, Bad AI." Research-Technology Management 62, no. 3 (2019): 10–12. http://dx.doi.org/10.1080/08956308.2019.1587280.

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Baraheem, Samah S., and Tam V. Nguyen. "AI vs. AI: Can AI Detect AI-Generated Images?" Journal of Imaging 9, no. 10 (2023): 199. http://dx.doi.org/10.3390/jimaging9100199.

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The proliferation of Artificial Intelligence (AI) models such as Generative Adversarial Networks (GANs) has shown impressive success in image synthesis. Artificial GAN-based synthesized images have been widely spread over the Internet with the advancement in generating naturalistic and photo-realistic images. This might have the ability to improve content and media; however, it also constitutes a threat with regard to legitimacy, authenticity, and security. Moreover, implementing an automated system that is able to detect and recognize GAN-generated images is significant for image synthesis mo
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McColl, Ewen. "AI, AI, Oh." Dental Update 52, no. 6 (2025): 369–70. https://doi.org/10.12968/denu.2025.52.6.369.

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Souratn, Jain. "Revolutionizing business consulting with generative AI: Exploring transformative models for strategic decision-making, innovation, and operational excellence." World Journal of Advanced Research and Reviews 22, no. 2 (2024): 2273–84. https://doi.org/10.5281/zenodo.14719859.

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Automotive AI is at the forefront of rapidly disrupting the business consulting industry by revitalizing core issues in strategy formulation and management, innovation, and process improvement. This technology helps consultants solve problems by dealing with large amounts of material, thinking outside the box regarding business solutions, and optimizing processes at a higher level than before. Businesses can benefit from AI technology because AI models can make a deeper data analysis, automate processes, improve decision-making, and provide the setting for future improvement. In this paper, th
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Kim, Minjeong. "Analyzing the Serial Multiple Mediating Effect of AI Acceptance Intention and AI Literacy on Pre-service Teachers’ AI Course Taking and AI Teaching Efficacy." Journal of The Korean Association of Information Education 28, no. 4 (2024): 407–17. http://dx.doi.org/10.14352/jkaie.2024.28.4.407.

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Aatmaj, Amol Salunke. "Cracking the Code: Self-Explaining AI Models for Transparent Decision Making in Complex Algorithms." International Journal for Multidisciplinary Research (IJFMR) 5, no. 4 (2023): 10. https://doi.org/10.5281/zenodo.8268922.

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This research paper explores self-explaining AI models that bridge the gap between complex black-box algorithms and human interpretability. The study focuses on techniques like LIME, SHAP, attention mechanisms, and rule-based systems to create locally interpretable models. By providing transparent and understandable explanations for AI predictions, these models enhance user trust and comprehension. Realworld applications in healthcare, finance, and autonomous systems are evaluated to demonstrate the effectiveness of self-explaining AI models. Ethical considerations regarding fairness, bias, an
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Dissertations / Theses on the topic "AI"

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Bellinder, Tobias. "Scrabble-AI : En Scrabble-AI med inriktning på ”Fun-AI”." Thesis, University of Skövde, School of Humanities and Informatics, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-4055.

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<p>Scrabble är ett populärt korsordsliknande brädspel som funnits på svenska sedan 1950-talet. Datorprogram som spelar Scrabble har funnits sedan och 1980-talet. De flesta har haft som fokus att spela så optimalt som möjligt och utmana de bästa mänskliga spelarna. Det här arbetet undersöker hur man kan skapa en ”Fun-AI” för Scrabble som fokuserar på spelarens upplevelse och som lämpar sig för alla spelare oavsett nivå. Tre enkla AI-spelare skapas genom att använda grundläggande egenskaper som karakteriserar mänskligt spel. Utvärderingen visar att en relativt outvecklad AI tas för en människa a
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Silva, Maria Adrina Paixão de Souza da. "Solidificação transitória de ligas dos sistemas monotéticos AI-Bi, AI-Pb e AI-In." [s.n.], 2011. http://repositorio.unicamp.br/jspui/handle/REPOSIP/265079.

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Orientador: Amauri Garcia<br>Tese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Mecânica<br>Made available in DSpace on 2018-08-18T19:08:04Z (GMT). No. of bitstreams: 1 Silva_MariaAdrinaPaixaodeSouzada_D.pdf: 5780858 bytes, checksum: b602bf47a710b2fb6f161a596020054f (MD5) Previous issue date: 2011<br>Resumo: Ligas de alumínio dispersas com bismuto, chumbo e índio apresentam aplicações promissoras em componentes automotivos resistentes ao desgaste. Essas dispersões de elementos de baixa temperatura de fusão diminuem a dureza e escoam facilmente em condições de desli
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Bars, Nicola <1990&gt. "Le polizze abbinate ai mutui e ai finanziamenti: profili giuridici." Master's Degree Thesis, Università Ca' Foscari Venezia, 2016. http://hdl.handle.net/10579/7987.

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Pettersson, Urban. "AI för Hive." Thesis, KTH, Skolan för datavetenskap och kommunikation (CSC), 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-157411.

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Strategies for the board game Hive was implemented and evaluated in this project. The report covers the rules as well as the system that was implemented in order to build strategies. The strategies are evaluated based on how they perform against each other. Two search algorithms were implemented: Minmax and Alpha-Beta Pruning. Alpha-Beta with depth 4 had the best performance against other strategies as well as in individual tests.<br>I projektet implementerades och utvärderades strategier för brädspelet Hive.Rapporten går igenom regler samt systemet som implementerades för att kunna skapa stra
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L, I. N. D. B. L. O. M. M. A. T. H. I. A. S., and I. E. N. E. R. L. U. C. A. S. W. "Achtung Online AI." Thesis, KTH, Skolan för datavetenskap och kommunikation (CSC), 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-134914.

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The report can be devided into two main parts; the theoretical construction of AI to be used in the game “Achtung Online”, and the implementation of a demo version of the described theoretical AI. The main goal is to create an AI that is entertaining and challenging for a human player. This have led to a concretized list of quality goals for the two main report parts. The report background presents the history of the game concept “Achtung die kurve” and also the evolution of game AI theory. The main study consists of a litterature study and a comprehensive determination of concrete goals of th
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Spronck, Pieter Hubert Marie. "Adaptive game AI." [Maastricht] : Maastricht : UPM, Universitaire Pers Maastricht ; University Library, Maastricht University [Host], 2005. http://arno.unimaas.nl/show.cgi?fid=5330.

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Hansson, Andreas. "AI Meeting Monitoring." Thesis, Luleå tekniska universitet, Institutionen för system- och rymdteknik, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-81105.

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During the COVID-19 pandemic the questions of the efficiency around meetings has been in the forefront of some discussion inside companies. One way to measure efficiency is to measure the interactivity between different participants. In order to measure this the participants need to be identified. With the recent spike of Machine learning advancements, is this something that can be done using facial and voice recognition? Another field that has risen to the top is cloud computing. Can machine learning and cloud computing be used to evaluate and monitor a meeting, thus handling both audio and v
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Tang, Robert, Kettunen Elias, and Anton Boberg. "Medicinedoseage with AI." Thesis, Uppsala universitet, Institutionen för elektroteknik, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-448073.

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Parkinson’s disease(PD) is a neurodegenerative disease that mainly affects the motor system. These symptoms can be treated temporarily with medicine,but it’s difficult to determine the right dosage. The goal was to use sensorsthat could measure the symptoms of PD and thus be able to give an objec-tive rating of the disease as a basis to determine the correct medicine dosage.Coincidentally with A.I and modern devices we can make it more exciting byusing mobile device games to generate the bulk of the information for whatdoctors need to give out correct medication guidelines without guidance fro
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Nieto, Antonio. "Mindset digital AI." Universidad Peruana de Ciencias Aplicadas (UPC), 2021. http://hdl.handle.net/10757/656719.

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IA Hackathon Latam. Buscamos que los equipos presenten prototipos de desarrollo funcionales basados en los servicios de la tecnología de inteligencia artificial como chatbots, machine learning, visión computacional, deep learning, entre otros, con la finalidad de mejorar los servicios High Education.
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Poser, Andrea <1981&gt. "AI – Intelligenza Artificiale." Master's Degree Thesis, Università Ca' Foscari Venezia, 2020. http://hdl.handle.net/10579/17364.

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“Can machines think?” È questa la semplice domanda di Turing nel suo saggio Mind del 1950. L’interrogarsi sulla possibilità dell’intelligenza artificiale equivale, cambiando il punta di vista, a chiedersi se le capacità della mente umana siano “replicabili” ovvero se il cervello è una macchina, per quanto complessa.
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Books on the topic "AI"

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Yan, Hua. Ai ai ai. He Ma, 2002.

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Xiao, Fuxing. Ai: Ai. Xin lei chu ban she, 1986.

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Nguyẽ̂n, Huệ Nhật. Ai ché̂t cho ai? Ai só̂ng cho ai? Mucsu.net Publishers, 2001.

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ranta, Marjaliisa Pitka. Ai ai veitikkaa. Karisto, 1998.

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Xiancheng. Ai là ai của ai?: Tiểu thuyết. Nhà xuất bản Lao Động, 2011.

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Bai, Mu Lin. Ai ai wo nu. Wen Lin, 1999.

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Yiftah-Walbe, Ayala. Ai-maḳom, ai-paʻam. Sifre ʻiton 77, 2009.

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xi, Yue xing. Ai ya ai ya. Xin shi jie chu ban she, 2008.

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Tang, Shiyun. Bai xue ai ai. Zuo jia chu ban she, 2020.

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Xiuzhen, Zhang, ed. Ai le zai ai. Mo yen wen hua, 1995.

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Book chapters on the topic "AI"

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Yampolskiy, Roman V. "Personhood*." In AI. Chapman and Hall/CRC, 2024. http://dx.doi.org/10.1201/9781003440260-9.

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Yampolskiy, Roman V. "Introduction*." In AI. Chapman and Hall/CRC, 2024. http://dx.doi.org/10.1201/9781003440260-1.

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Yampolskiy, Roman V. "Pathways to Danger*." In AI. Chapman and Hall/CRC, 2024. http://dx.doi.org/10.1201/9781003440260-7.

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Yampolskiy, Roman V. "Human ≠ AGI*." In AI. Chapman and Hall/CRC, 2024. http://dx.doi.org/10.1201/9781003440260-12.

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Yampolskiy, Roman V. "Consciousness*." In AI. Chapman and Hall/CRC, 2024. http://dx.doi.org/10.1201/9781003440260-10.

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Yampolskiy, Roman V. "Personal Universes*." In AI. Chapman and Hall/CRC, 2024. http://dx.doi.org/10.1201/9781003440260-11.

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Yampolskiy, Roman V. "Unownability*." In AI. Chapman and Hall/CRC, 2024. http://dx.doi.org/10.1201/9781003440260-5.

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Yampolskiy, Roman V. "Unpredictability*." In AI. Chapman and Hall/CRC, 2024. http://dx.doi.org/10.1201/9781003440260-2.

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Yampolskiy, Roman V. "Unexplainability and Incomprehensibility*." In AI. Chapman and Hall/CRC, 2024. http://dx.doi.org/10.1201/9781003440260-3.

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Yampolskiy, Roman V. "Accidents*." In AI. Chapman and Hall/CRC, 2024. http://dx.doi.org/10.1201/9781003440260-8.

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Conference papers on the topic "AI"

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Coccoli, Mauro, and Gabriella Patanè. "AI vs. AI: The Detection Game." In 2024 IEEE 8th Forum on Research and Technologies for Society and Industry Innovation (RTSI). IEEE, 2024. http://dx.doi.org/10.1109/rtsi61910.2024.10761124.

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Ding, Bailu, Sudipto Das, Ryan Marcus, Wentao Wu, Surajit Chaudhuri, and Vivek R. Narasayya. "AI Meets AI." In SIGMOD/PODS '19: International Conference on Management of Data. ACM, 2019. http://dx.doi.org/10.1145/3299869.3324957.

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Abduljawad, Mohamed, Abdullah Alsalmani, and Ashwaq Alkaabi. "AI on AI: Training AI classifier on AI-generated remote sensing images." In Seventh International Conference on Engineering Geophysics, Al Ain, UAE, 16–19 October 2023. Society of Exploration Geophysicists, 2024. http://dx.doi.org/10.1190/iceg2023-010.1.

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Molloy, Ian, Josyula R. Rao, and Marc Ph Stoecklin. "AI vs. AI: Exploring the Intersections of AI and Cybersecurity." In CODASPY '21: Eleventh ACM Conference on Data and Application Security and Privacy. ACM, 2021. http://dx.doi.org/10.1145/3445970.3456286.

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Kum-Biocca, Hyejin Hannah, and Jinhong Kwon. "AI." In SA '20: SIGGRAPH Asia 2020. ACM, 2020. http://dx.doi.org/10.1145/3414686.3427110.

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Ghajargar, Maliheh, Jeffrey Bardzell, Alison Smith Renner, et al. "From ”Explainable AI” to ”Graspable AI”." In TEI '21: Fifteenth International Conference on Tangible, Embedded, and Embodied Interaction. ACM, 2021. http://dx.doi.org/10.1145/3430524.3442704.

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Rao, Nikitha, Jason Tsay, Kiran Kate, Vincent Hellendoorn, and Martin Hirzel. "AI for Low-Code for AI." In IUI '24: 29th International Conference on Intelligent User Interfaces. ACM, 2024. http://dx.doi.org/10.1145/3640543.3645203.

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Wang, XiaoFeng. "Security Of AI, By AI and For AI: Charting New Territories in AI-Centered Cybersecurity Research." In ASIA CCS '24: 19th ACM Asia Conference on Computer and Communications Security. ACM, 2024. http://dx.doi.org/10.1145/3634737.3665024.

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Hemment, Drew, Morgan Currie, SJ Bennett, et al. "AI in the Public Eye: Investigating Public AI Literacy Through AI Art." In FAccT '23: the 2023 ACM Conference on Fairness, Accountability, and Transparency. ACM, 2023. http://dx.doi.org/10.1145/3593013.3594052.

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Jelibaghu, Mustafa, Michael Eley, Oliver Rose, Alexander Palatnik, Marius Rupp, and Nikoleta Leontidou. "Charging strategies for AGVs using supervised learning." In AI in Production. Hochschule für Technik, Wirtschaft und Kultur Leipzig, 2024. http://dx.doi.org/10.33968/2024.75.

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Reports on the topic "AI"

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Sharkov, George, and Christina Todorova. AI against COVID-19, AI and Cybersecurity, and Misusing AI. Procon, 2021. http://dx.doi.org/10.11610/cybsec05.

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Bingamon, Brian Michael. AI Loop. Office of Scientific and Technical Information (OSTI), 2019. http://dx.doi.org/10.2172/1566097.

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Beraja, Martin, Andrew Kao, David Yang, and Noam Yuchtman. AI-tocracy. National Bureau of Economic Research, 2021. http://dx.doi.org/10.3386/w29466.

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Mittelsteadt, Matthew. AI Verification: Mechanisms to Ensure AI Arms Control Compliance. Center for Security and Emerging Technology, 2021. http://dx.doi.org/10.51593/20190020.

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The rapid integration of artificial intelligence into military systems raises critical questions of ethics, design and safety. While many states and organizations have called for some form of “AI arms control,” few have discussed the technical details of verifying countries’ compliance with these regulations. This brief offers a starting point, defining the goals of “AI verification” and proposing several mechanisms to support arms inspections and continuous verification.
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GPT, C. AI Sarcasm Detection: Insult Your AI without Offending It. Edited by R. L. Barnes. RFC Editor, 2023. http://dx.doi.org/10.17487/rfc9405.

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Beck, Sedefka, and Donka Brodersen. Generative AI in Economics: Teaching Economics and AI Literacy. The Economics Network, 2024. http://dx.doi.org/10.53593/n4121a.

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Stevens, Rick, Valerie Taylor, Jeff Nichols, Arthur Barney Maccabe, Katherine Yelick, and David Brown. AI for Science. Office of Scientific and Technical Information (OSTI), 2020. http://dx.doi.org/10.2172/1604756.

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Acemoglu, Daron. Harms of AI. National Bureau of Economic Research, 2021. http://dx.doi.org/10.3386/w29247.

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Aiken, Catherine. Classifying AI Systems. Center for Security and Emerging Technology, 2021. http://dx.doi.org/10.51593/20200025.

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This brief explores the development and testing of artificial intelligence system classification frameworks intended to distill AI systems into concise, comparable and policy-relevant dimensions. Comparing more than 1,800 system classifications, it points to several factors that increase the utility of a framework for human classification of AI systems and enable AI system management, risk assessment and governance.
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Baker, James E., Laurie Hobart, and Matthew Mitterlsteadt. AI for Judges. Center for Security and Emerging Technology, 2021. http://dx.doi.org/10.51593/20190019.

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As artificial intelligence transforms the economy and American society, it will also transform the practice of law and the role of courts in regulating its use. What role should, will, or might judges play in addressing the use of AI? And relatedly, how will AI and machine learning impact judicial practice in federal and state courts? This report is intended to provide a framework for judges to address AI.
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