Relevant bibliographies by topics / Interaction with AI

Contents

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

Academic literature on the topic 'Interaction with AI'

Author: Grafiati
Published: 7 June 2025
Last updated: 16 July 2025

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Journal articles on the topic "Interaction with AI"

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van Berkel, Niels, Mikael B. Skov, and Jesper Kjeldskov. "Human-AI interaction." Interactions 28, no. 6 (2021): 67–71. http://dx.doi.org/10.1145/3486941.

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Pituxcoosuvarn, Mondheera, Midori Tanimura, Yohei Murakami, and Jeremy Stewart White. "Enhancing EFL Speaking Skills with AI-Powered Word Guessing: A Comparison of Human and AI Partners." Information 16, no. 6 (2025): 427. https://doi.org/10.3390/info16060427.

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This study explores the effects of interacting with AI vs. human interlocutors on English language learners’ speaking performance in a game-based learning context. We developed Taboo Talks, a word-guessing game in which learners alternated between giving and guessing clues with either an AI or a human partner. To evaluate the impact of interaction mode on oral proficiency, participants completed a story retelling task, assessed using complexity, accuracy, and fluency (CAF) metrics. Each participant engaged in both partner conditions, with group order counterbalanced. The results from the retel
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Renza, Victor. "AI Generated Art." Morals & Machines 2, no. 2 (2022): 32–39. http://dx.doi.org/10.5771/2747-5174-2022-2-32.

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Human-robot interaction (HRI) through the practice of different types of art is bringing to the table new perspectives on innovative interactions where the cooperation between artists and robots not only deliver original works of art but also novel communication mechanisms beyond spoken and written-based forms. Generative art, that is, artworks mediated by the interaction with computers in codes and art generated by artificial intelligence (AI), are having a profound impact in different fields of the arts, including visual arts, performative arts, music and literature. This research proposes t
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Wang, Qiaosi, Ida Camacho, Shan Jing, and Ashok K. Goel. "Understanding the Design Space of AI-Mediated Social Interaction in Online Learning: Challenges and Opportunities." Proceedings of the ACM on Human-Computer Interaction 6, CSCW1 (2022): 1–26. http://dx.doi.org/10.1145/3512977.

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Our online interactions are constantly mediated through Artificial Intelligence (AI), especially our social interactions. AI-mediated social interaction is the AI-facilitated process of building and maintaining social connections between individuals through information inferred from people's online posts. With its impending application across a number of contexts, the challenges and opportunities of AI-mediated social interaction remain underexplored. This paper seeks to understand the design space of AI-mediated social interaction in the context of online learning, where students frequently f
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Aksoyalp, Zinnet Şevval, and Betül Rabia Erdoğan. "COMPARATIVE EVALUATION OF ARTIFICIAL INTELLIGENCE AND DRUG INTERACTION TOOLS: A PERSPECTIVE WITH THE EXAMPLE OF CLOPIDOGREL." Ankara Universitesi Eczacilik Fakultesi Dergisi 48, no. 3 (2024): 22. http://dx.doi.org/10.33483/jfpau.1460173.

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Objective: The study aims to compare the ability of free artificial intelligence (AI) chatbots to detect drug interactions with freely available drug interaction tools, using clopidogrel as an example. Material and Method: The Lexicomp database was used as a reference to determine drug interactions with clopidogrel. ChatGPT-3.5 AI and Bing AI were selected as the free AI chatbots. Medscape Drug Interaction Checker, DrugBank Drug Interaction Checker and Epocrates Interaction Check were selected as free drug interaction tools. Accuracy score and comprehensiveness score were calculated for each d
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Bennett, Casey, Benjamin Weiss, Jaeyoung Suh, Eunseo Yoon, Jihong Jeong, and Yejin Chae. "Exploring Data-Driven Components of Socially Intelligent AI through Cooperative Game Paradigms." Multimodal Technologies and Interaction 6, no. 2 (2022): 16. http://dx.doi.org/10.3390/mti6020016.

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The development of new approaches for creating more “life-like” artificial intelligence (AI) capable of natural social interaction is of interest to a number of scientific fields, from virtual reality to human–robot interaction to natural language speech systems. Yet how such “Social AI” agents might be manifested remains an open question. Previous research has shown that both behavioral factors related to the artificial agent itself as well as contextual factors beyond the agent (i.e., interaction context) play a critical role in how people perceive interactions with interactive technology. A
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Etibar Aliyev, Oluyinka Adedokun, Adetutu Temitope Fabusoro, and Babatunde Keshinro. "AI-enhanced conversational avatars for immersive interaction." World Journal of Advanced Research and Reviews 26, no. 1 (2025): 627–34. https://doi.org/10.30574/wjarr.2025.26.1.1101.

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This paper reviews the significance of key technologies of AI-enhanced conversational avatars and their applications for immersive interaction, including increased AI system adoption, enhanced trustworthiness, and personalized and engaging interactions. Using empirical data and case studies, this paper provides evidence regarding recent advancements that facilitate high-fidelity and style-controllable avatar generation, providing customizable options for users for online social interactions. This is possible by integrating several AI modules like text-to-speech, speech recognition, and open-do
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Lushyn, Pavlo, and Yana Sukhenko. "Metacommunications and Artificial Intelligence: The ECPF Approach for International Management." Організаційна психологія Економічна психологія 35, no. 2 (2025): 161–73. https://doi.org/10.31108/2.2025.2.35.15.

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Introduction. The article addresses the development of metacommunicative competence among international management professionals amid rapid AI integration. Based on analysis of contemporary human-AI interaction research, it establishes theoretical foundations of metacommunication in cognitive heterogeneous environments and substantiates the eco-facilitative approach as a methodological basis for developing this competence in hybrid management contexts. Aim. The aim is to conceptualize metacommunication as a key mechanism for interacting with AI agents within interface-based reality, and to jus
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Choudhury, Avishek, and Onur Asan. "Human factors: bridging artificial intelligence and patient safety." Proceedings of the International Symposium on Human Factors and Ergonomics in Health Care 9, no. 1 (2020): 211–15. http://dx.doi.org/10.1177/2327857920091007.

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The recent launch of complex artificial intelligence (AI) in the domain of healthcare has embedded perplexities within patients, clinicians, and policymakers. The opaque and complex nature of artificial intelligence makes it challenging for clinicians to interpret its outcome. Incorrect interpretation and poor utilization of AI might hamper patient safety. The principles of human factors and ergonomics (HFE) can assist in simplifying AI design and consecutively optimize human performance ensuring better understanding of AI outcome, their interaction with the clinical workflow. In this paper, w
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Ismailova, R., K. Abysheva, and M. Sadykova. "RADICAL FORGIVENESS AND ARTIFICIAL INTELLIGENCE: PSYCHOLOGICAL ASPECTS OF INTERACTION." Scientific heritage, no. 146 (October 7, 2024): 43–45. https://doi.org/10.5281/zenodo.13896864.

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This article explores the impact of interaction with artificial intelligence on cognitive processes, emotional states, and social relationships. Based on the theoretical framework of Colin Tipping's method of Radical Forgiveness, the article analyzes how forgiveness can influence a person's perception of AI interaction and emotional adaptation. The focus is on how AI affects emotional stability, interpersonal relationships, and social interactions. The research includes stages such as a literature review on the psychological aspects of AI interaction, surveys, and interviews with participants
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Dissertations / Theses on the topic "Interaction with AI"

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Uga, Brenda. "Towards Trustworthy AI : A proposed set of design guidelines for understandable, trustworthy and actionable AI." Thesis, Uppsala universitet, Institutionen för informatik och media, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-385392.

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Artificial intelligence is used today in both everyday applications and specialised expert systems. In situations where relying on the output of the AI brings about the risk of negative consequences, it becomes important to understand why the AI system has produced its output. Previous research in human-computer trust has identified trust antecedents that contribute to formation of trust in an AI artifact, understanding of the system being one of them. In the context of Pipedrive, a sales management system, this thesis investigates how can AI predictions be designed as understandable and trust
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Strineholm, Philippe. "Exploring Human-Robot Interaction Through Explainable AI Poetry Generation." Thesis, Mälardalens högskola, Akademin för innovation, design och teknik, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-54606.

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As the field of Artificial Intelligence continues to evolve into a tool of societal impact, a need of breaking its initial boundaries as a computer science discipline arises to also include different humanistic fields. The work presented in this thesis revolves around the role that explainable artificial intelligence has in human-robot interaction through the study of poetry generators. To better understand the scope of the project, a poetry generators study presents the steps involved in the development process and the evaluation methods. In the algorithmic development of poetry generators, t
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Houtsma, Meile Jacob. "Perceived AI Performance and Intended Future Use in AI-based Applications." Thesis, Uppsala universitet, Institutionen för informatik och media, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-414835.

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This case study explored perceived artificial intelligence (AI) performance and intended future use (IFU) in users of AI-based applications. Users could become less motivated to use these applications if AIs do not clearly communicate their actions. A prototype, a user test, and a structured interview were iteratively developed. Eight students participated in the final iteration, which was thematically analyzed. The results indicate that an AI-based application that shows recommendations can positively affect perceived AI performance and IFU. Possibly, the recommendations increased users’ unde
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Axelsson, Mattis, and Sara Larsson. "Utvecklande AI : En studie i hur man skapar ett system för lärande AI." Thesis, Blekinge Tekniska Högskola, Sektionen för planering och mediedesign, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-4587.

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AI är något som blir allt viktigare inom dagens spel och får allt högre krav på att agera mänskligt och intelligent. Detta kandidatarbete undersöker vilken metod som är att föredra för att skapa en AI som kan lära sig av sina tidigare erfarenheter. Några av de metoder som undersöks är trädstrukturer, Artificial Neural Network och GoCap. Genom att skapa en applikation med en av metoderna samt göra en undersökning på hur AI:n i applikationen upplevdes fick vi resultat om denna metod var användbar. Utifrån detta diskuteras det ifall andra metoder hade varit mer effektiva, hur man hade kunnat förb
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Borgstrand, Richard, and Patrik Servin. "Reinforcement Learning AI till Fightingspel." Thesis, Blekinge Tekniska Högskola, Sektionen för datavetenskap och kommunikation, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-3113.

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Utförandet av projektet har varit att implementera två stycken fightingspels Artificiell Intelligens (kommer att förkortas AI). En oadaptiv och mer deterministisk AI och en adaptiv dynamisk AI som använder reinforcement learning. Detta har utförts med att skripta beteendet av AI:n i en gratis 2D fightingsspels motor som heter ”MUGEN”. AI:n använder sig utav skriptade sekvenser som utförs med MUGEN’s egna trigger och state system. Detta system kollar om de skriptade specifierade kraven är uppfyllda för AI:n att ska ”trigga”, utföra den bestämda handlingen. Den mer statiska AI:n har blivit uppby
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Karlsson, Simon, and Christopher Jensen. "Jämförelse mellan neurala nätverk baserad AI och state-of-the-art AI i racing spel." Thesis, Blekinge Tekniska Högskola, Sektionen för datavetenskap och kommunikation, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-4831.

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Denna rapport jämför prestandan mellan state-of-the-art AI-botar i racing spelet TORCS och en AI-bot som kör med hjälp av ett artificiellt neuralt nätverk (ANN-bot). ANN-boten, som implementerades som en del av arbetet, använder en feedforward arkitektur och backpropagation för inlärning. Ett separat program som användes för att träna det neurala nätverket med träningdata som spelats in från TORCS implementerades också. Som state-of-the-art AI-botar användes AI-botar som har använts i en tävling. De fyra AI-botarna testades på åtta olika banor och data om hur lång tid varje varv tog och hur sn
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Nordling, Rasmus, and Robin Rietz Berntsson. "AI in Neverwinter Nights using Dynamic Scripting." Thesis, Blekinge Tekniska Högskola, Sektionen för datavetenskap och kommunikation, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-3911.

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In this paper research about dynamic scripting and the top culling difficulty scaling enhancement in the game Neverwinter Nights is investigated. A comparison between both a static and a dynamic opponent is made. The human opinion about dynamic scripting is also highlighted. To get an understanding of what the players think about and how they approach an opponent, two experiments were made. One where tests are made on a static opponent and a dynamic opponent, then a second where differences in behavior of the dynamic opponent using top culling and an ordinary dynamic opponent are analyzed. Res
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Ryrberg, Tobias. "Hur påverkar AI-rekommendationer beslutsfattandet? : En kvantitativ studie om hur AI-rekommendationer påverkar mänskligt beslutsfattande under osäkerhet." Thesis, Linköpings universitet, Institutionen för datavetenskap, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-176265.

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Människor fattar varje dag olika beslut. Dessa beslut sker oftast under situationer med osäkerhet, där sannolikheterna och konsekvenserna inte är kända. Med den nya tekniken och ständiga samhällsutvecklingen ställs människor inför beslut i allt mer komplexa situationer. Det finns därför en efterfrågan på beslutsstöd till människor. Ett av dessa beslutsstöd som har utvecklas är med hjälp av artificiell intelligens (AI) och då i form av AI-rekommendationer. Dessa AI-rekommendationer finns redan i situationer som exempelvis i trafiken, sjukvården och finansmarknaden. Det som dock inte har undersö
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Cornwell, Jeffrey M. "The Interaction of Sire Fertility and Timing of AI in a Synchronization Protocol." Thesis, Virginia Tech, 2005. http://hdl.handle.net/10919/42357.

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The objectives of this study were to determine if fixed-timed artificial insemination (FTAI) at two different times, 0 or 24 h after GnRH administration, in a Presynch-Ovsynch protocol influenced the pregnancy rate (PR) when average and high fertility sires were used. Additionally, a second experiment was conducted to determine the effectiveness of CIDR inserts to allow for resynchronization of estrus in cows that did not conceive or maintain the conceptus at FTAI. Lactating Holstein cows (n = 1,457) from two well-managed dairy herds located in the piedmont region of North Carolina were util
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Kory-Westlund, Jacqueline M. (Jacqueline Marie). "Relational AI : creating long-term interpersonal interaction, rapport, and relationships with social robots." Thesis, Massachusetts Institute of Technology, 2019. https://hdl.handle.net/1721.1/123627.

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Thesis: Ph. D., Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2019<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (pages 266-294).<br>Children are now growing up with Al-enabled, socially interactive technology. As such, we need to deeply understand how children perceive, interact, and relate to this kind of technology, especially given the many ethical concerns that arise in the context of human-machine interactions, most of which are most contentious with children. To this end, I explore questi
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Books on the topic "Interaction with AI"

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Sreedharan, Sarath, Anagha Kulkarni, and Subbarao Kambhampati. Explainable Human-AI Interaction. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-03767-2.

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Stoyanchev, Svetlana, Stefan Ultes, and Haizhou Li, eds. Conversational AI for Natural Human-Centric Interaction. Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-5538-9.

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author, Kim Chi-ho, and Pak Chong-gu author, eds. In'gan chŏngsŏ wa AI. Hanul Ak'ademi, 2021.

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Stock, Oliviero, and Marco Schaerf, eds. Reasoning, Action and Interaction in AI Theories and Systems. Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11829263.

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Associazione italiana per l'intelligenza artificiale. Congress. AI*IA 2011: Artificial Intelligence Around Man and beyond. Springer, 2011.

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1960-, Cassell Justine, ed. Embodied conversational agents. MIT Press, 2000.

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Mendel, Jerry M. Perceptual computing: Aiding people in making subjective judgments. John Wiley & Sons, 2010.

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Associazione Italiana Per L'intelligenza Artificiale. Congress. AI*IA 2009: Emergent perspectives in artificial intelligence : XIth international conference of the Italian Association for Artificial Intelligence, Reggio Emilia, Italy, December 9-12, 2009 : proceedings. Springer, 2009.

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Nicholas, Graham, Jorge, J. A. (Joaquim Armando), Nunes Nuno, Palanque Philippe 1966-, Winckler Marco, and SpringerLink (Online service), eds. Human-Computer Interaction – INTERACT 2011: 13th IFIP TC 13 International Conference, Lisbon, Portugal, September 5-9, 2011, Proceedings, Part IV. IFIP International Federation for Information Processing, 2011.

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Jean-Michel, Hoc, Cacciabue Pietro C, and Hollnagel Erik 1941-, eds. Expertise and technology: Cognition & human-computer cooperation. Lawrence Erlbaum Associates, 1994.

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Book chapters on the topic "Interaction with AI"

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Wang, Dong, and Daniel ‘Yue’ Zhang. "Human-AI Interaction." In Social Edge Computing. Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-26936-3_6.

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Lombana Diaz, Camila. "AI Ethics." In Human–Computer Interaction Series. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-61375-3_5.

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Giannopoulos, Giorgos, and Dimitris Sacharidis. "Responsible AI." In Human–Computer Interaction Series. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-61375-3_12.

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Liu, Yuxin, and Keng L. Siau. "Human-AI Interaction and AI Avatars." In HCI International 2023 – Late Breaking Papers. Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-48057-7_8.

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Akhtar, Md Haseen, and Janakarajan Ramkumar. "AI in Interaction Design." In AI for Designers. Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-6897-8_6.

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Aïmeur, Esma. "Privacy in AI." In Human–Computer Interaction Series. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-61375-3_9.

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Kense, Jasper, and Shilpa Tripathi Jurinek. "Creativity and Generative AI." In Human–Computer Interaction Series. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-61375-3_13.

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Fauquet-Alekhine, Philippe. "Human interaction with robots." In AI and Common Sense. Routledge, 2024. http://dx.doi.org/10.4324/9781032626192-8.

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Burema, Dafna. "Studying Interaction Indirectly." In Communicative AI in (Inter-)Action. transcript Verlag, 2024. https://doi.org/10.14361/9783839475010-009.

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Sreedharan, Sarath, Anagha Kulkarni, and Subbarao Kambhampati. "Conclusion." In Explainable Human-AI Interaction. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-03767-2_11.

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Conference papers on the topic "Interaction with AI"

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Lal, Mily, S. Neduncheliyan, Akanksha Goel, Poi Tamrakar, Saurabh Saoji, and Manisha Bhende. "Healthcare Interaction Through Conversational AI." In 2024 International Conference on Integrated Intelligence and Communication Systems (ICIICS). IEEE, 2024. https://doi.org/10.1109/iciics63763.2024.10859494.

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Katta, Jithendra, Nikhil Reddy Kodumuru, and Swathi Katta. "InterACT: Enhancing Human-AI Interaction." In 2025 International Conference on Machine Learning and Autonomous Systems (ICMLAS). IEEE, 2025. https://doi.org/10.1109/icmlas64557.2025.10967771.

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HN, Tanmayee, Kushie P. Gowda, Ritu Jaiswal R, and Amarnath J. L. "Empathy AI: Leveraging Emotion Recognition for Enhanced Human-AI Interaction." In 2024 7th Asia Conference on Cognitive Engineering and Intelligent lnteraction (CEII). IEEE, 2024. https://doi.org/10.1109/ceii65291.2024.00053.

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Ronit, Parth Agrawal, and Manni Kumar. "Enhancing Human-Computer Interaction with Generative AI." In 2024 IEEE 4th International Conference on ICT in Business Industry & Government (ICTBIG). IEEE, 2024. https://doi.org/10.1109/ictbig64922.2024.10911352.

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Li, Kunyan, Yipeng Zhu, Shuxuan Yu, and Jinwu Wei. "Ai-Driven Terminals: Advances in Intent Recognition, Multimodal Interaction, and AI Collaboration." In 2025 IEEE 6th International Seminar on Artificial Intelligence, Networking and Information Technology (AINIT). IEEE, 2025. https://doi.org/10.1109/ainit65432.2025.11035635.

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B, Yeswanth N., David Samuel Azariya S, Hari Hrithik R, and Cibi Jegan A. "An AI-Powered Interactive Assistant: Integrating Multimodal Interaction for Enhanced User Experience." In 2024 International Conference on Emerging Research in Computational Science (ICERCS). IEEE, 2024. https://doi.org/10.1109/icercs63125.2024.10895433.

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Villa, Steeven, Robin Welsch, Alena Denisova, and Thomas Kosch. "Evaluating Interactive AI: Understanding and Controlling Placebo Effects in Human-AI Interaction." In CHI '24: CHI Conference on Human Factors in Computing Systems. ACM, 2024. http://dx.doi.org/10.1145/3613905.3636304.

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Dangol, Aayushi, Robert Wolfe, Runhua Zhao, et al. "Children's Mental Models of AI Reasoning: Implications for AI Literacy Education." In IDC '25: Interaction Design and Children. ACM, 2025. https://doi.org/10.1145/3713043.3728856.

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Amershi, Saleema, Dan Weld, Mihaela Vorvoreanu, et al. "Guidelines for Human-AI Interaction." In CHI '19: CHI Conference on Human Factors in Computing Systems. ACM, 2019. http://dx.doi.org/10.1145/3290605.3300233.

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Madumal, Prashan, Ronal Singh, Joshua Newn, and Frank Vetere. "Interaction design for explainable AI." In OzCHI '18: 30th Australian Computer-Human Interaction Conference. ACM, 2018. http://dx.doi.org/10.1145/3292147.3293450.

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Reports on the topic "Interaction with AI"

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Pasupuleti, Murali Krishna. Empathetic AI in Action: Transforming Customer Service with Emotional Intelligence. National Education Services, 2025. https://doi.org/10.62311/nesx/rr725.

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Abstract: This article explores the transformative impact of Emotionally Intelligent AI on customer service, focusing on how AI systems are designed to understand and respond to human emotions with empathy and precision. It delves into the core technologies, such as sentiment analysis, emotion recognition models, and reinforcement learning, that enable AI to provide emotionally aware interactions. Practical applications are discussed, including AI-powered customer support, personalized experiences, and crisis management solutions. The Article also covers the psychological foundations of AI-dri
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Fang, Chen. Unsettled Issues in Vehicle Autonomy, Artificial Intelligence, and Human-Machine Interaction. SAE International, 2021. http://dx.doi.org/10.4271/epr2021010.

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Artificial intelligence (AI)-based solutions are slowly making their way into our daily lives, integrating with our processes to enhance our lifestyles. This is major a technological component regarding the development of autonomous vehicles (AVs). However, as of today, no existing, consumer ready AV design has reached SAE Level 5 automation or fully integrates with the driver. Unsettled Issues in Vehicle Autonomy, AI and Human-Machine Interaction discusses vital issues related to AV interface design, diving into speech interaction, emotion detection and regulation, and driver trust. For each
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Benitez-Rueda, Miguel, and Eric Parrado. Research Insights: Which Jobs Are Most Likely to Be Affected by Artificial Intelligence? Inter-American Development Bank, 2024. https://doi.org/10.18235/0013323.

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There is an increasing likelihood of job replacement by AI over time, with significant implications for workforce planning and policy development. Women and lower-skilled workers face disproportionately higher exposure to AI replacement. Office and administrative roles exhibit the highest exposure levels, while roles requiring complex problem-solving, interpersonal skills, or human interaction remain less affected.
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Jakobsen, Tor Georg. Using ChatGPT with Stata: Regression Analysis (Part II). Instats Inc., 2025. https://doi.org/10.61700/2w5b85mmn916t1568.

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This comprehensive 3-day workshop focuses on refining statistical modeling and regression analysis skills by integrating advanced AI tools like ChatGPT with traditional software such as Stata. Participants will gain practical competencies in various regression techniques, including interaction effects (or 'moderation'), logistic regression, missing data, scale construction, transformations, weighting, and how to deal with regression assumptions, along with AI-powered assistance from ChatGPT to clarify concepts and troubleshoot commands.
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Pasupuleti, Murali Krishna. Quantum Cognition: Modeling Decision-Making with Quantum Theory. National Education Services, 2025. https://doi.org/10.62311/nesx/rrvi225.

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Abstract Quantum cognition applies quantum probability theory and mathematical principles from quantum mechanics to model human decision-making, reasoning, and cognitive processes beyond the constraints of classical probability models. Traditional decision theories, such as expected utility theory and Bayesian inference, struggle to explain context-dependent reasoning, preference reversals, order effects, and cognitive biases observed in human behavior. By incorporating superposition, interference, and entanglement, quantum cognitive models offer a probabilistic framework that better accounts
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Pasupuleti, Murali Krishna. Next-Generation Extended Reality (XR): A Unified Framework for Integrating AR, VR, and AI-driven Immersive Technologies. National Education Services, 2025. https://doi.org/10.62311/nesx/rrv325.

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Abstract: Extended Reality (XR), encompassing Augmented Reality (AR), Virtual Reality (VR), and Mixed Reality (MR), is evolving into a transformative technology with applications in healthcare, education, industrial training, smart cities, and entertainment. This research presents a unified framework integrating AI-driven XR technologies with computer vision, deep learning, cloud computing, and 5G connectivity to enhance immersion, interactivity, and scalability. AI-powered neural rendering, real-time physics simulation, spatial computing, and gesture recognition enable more realistic and adap
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Shukla, Indu, Rajeev Agrawal, Kelly Ervin, and Jonathan Boone. AI on digital twin of facility captured by reality scans. Engineer Research and Development Center (U.S.), 2023. http://dx.doi.org/10.21079/11681/47850.

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The power of artificial intelligence (AI) coupled with optimization algorithms can be linked to data-rich digital twin models to perform predictive analysis to make better informed decisions about installation operations and quality of life for the warfighters. In the current research, we developed AI connected lifecycle building information models through the creation of a data informed smart digital twin of one of US Army Corps of Engineers (USACE) buildings as our test case. Digital twin (DT) technology involves creating a virtual representation of a physical entity. Digital twin is created
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Theofanos, Mary Frances. AI Use Taxonomy. National Institute of Standards and Technology, 2024. http://dx.doi.org/10.6028/nist.ai.200-1.

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As artificial intelligence (AI) systems continue to be developed, humans will increasingly participate in human-AI interactions. Humans interact with AI systems to achieve particular goals. To ensure that AI systems contribute positively to human-AI interactions, it is important to examine human-AI tasks with an emphasis on human goals and outcomes. The AI Use Taxonomy aims to provide a flexible means of classifying how an AI system contributes to an outcome. The taxonomy sets forward 16 AI use “activities” which are independent of AI techniques and domains. Tasks are combinations of one or mo
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Greene Nolan, Ph.D., Hillary, Merijke Coenraad, Ph.D., and Viki Young, Ph.D. Teaching Partner, Grading Assistant, Substitute Teacher: Three Ways Teachers Positioned an Artificial Intelligence Tool in Writing Instruction. Digital Promise, 2024. http://dx.doi.org/10.51388/20.500.12265/226.

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This study investigates how teachers understand and position AI tools in middle school writing instruction, drawing on 27 teacher interviews collected during a study called Project Topeka that used an interactive argumentative writing platform with AI-generated scores and feedback. Based on the interviews, we generate an initial theoretical framework of how teachers position AI tools — and therefore themselves — in their teaching. We found that some teachers leveraged AI as a “teaching partner” that provided insights to help enhance teaching and learning while remaining central to instruction
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Pasupuleti, Murali Krishna. Augmented Human Intelligence: Converging Generative AI, Quantum Computing, and XR for Enhanced Human-Machine Synergy. National Education Services, 2025. https://doi.org/10.62311/nesx/rrv525.

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Abstract: Augmented Human Intelligence (AHI) represents a paradigm shift in human-AI collaboration, leveraging Generative AI, Quantum Computing, and Extended Reality (XR) to enhance cognitive capabilities, decision-making, and immersive interactions. Generative AI enables real-time knowledge augmentation, automated creativity, and adaptive learning, while Quantum Computing accelerates AI optimization, pattern recognition, and complex problem-solving. XR technologies provide intuitive, immersive environments for AI-driven collaboration, bridging the gap between digital and physical experiences.
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