Yapay Zekâ Araçlarının Akademik Araştırmalardaki Rolü: Fırsatlar, Riskler ve Etik Yansımalar

Adler, J. M. (2025). “Artificial Intelligence” and Library Subject Guides: Impacting the Academic Research Space. In AI Use in Social Sciences (pp. 181-204). IGI Global Scientific Publishing.

Ahmed, Z., Wan, S., Zhang, F., & Zhong, W. (2024). Artificial intelligence for omics data analysis. BMC Methods, 1(1), 4.

Alves, A., Pires, J. M., & Santos, M. Y. (2025). AI-Assisted Analytics. In Advances in Conceptual Modeling: ER 2024 Workshops, AISA, CMLS, EmpER, QUAMES, JUSMOD, LLM4Modeling, Pittsburgh, PA, USA, October 28–31, 2024, Proceedings (Vol. 14932, p. 343). Springer Nature.

Ashley, J. (2025). Is the literature review paper dead? How AI is transforming the research landscape in DNA research. Nucleic acid insights, 3(1), 7-10.

Aydin, O., Karaarslan, E., Erenay, F. S., & Bacanin, N. (2025). Generative AI in Academic Writing: A Comparison of DeepSeek, Qwen, ChatGPT, Gemini, Llama, Mistral, and Gemma. arXiv preprint arXiv:2503.04765.

Barrot, J. S. (2025). Trinka: Facilitating academic writing through an intelligent writing evaluation system. Assessing Writing, 65, 100953.

Basavaraja, M. T., & Rajashekara, S. N. (2025). Navigating Scholarly Literature with ResearchRabbit: A Comprehensive Analysis. Journal of Science &Technology Metrics. 6 (1) https://doi.org/10.6025/jstm/2025/6/1/1-9

Bender, E. M., Gebru, T., McMillan-Major, A., & Shmitchell, S. (2021). On the dangers of stochastic parrots: Can language models be too big? Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency (FAccT), 610–623. https://doi.org/10.1145/3442188.3445922

Bernard, N., Sagawa Jr, Y., Bier, N., Lihoreau, T., Pazart, L., & Tannou, T. (2025). Using artificial intelligence for systematic review: the example of elicit. BMC medical research methodology, 25(1), 75.

Bilal, A., Ebert, D., & Lin, B. (2025). Llms for explainable ai: A comprehensive survey. arXiv preprint arXiv:2504.00125.

Biondi-Zoccai, G., Cazzaro, A., Cobalchin, E., D’Auria, D., Ardizzone, G., Giordano, S., ... & Muraru, D. (2025). Artificial Intelligence Tools for Scientific Writing: The Good, The Bad and The Ugly. Top Italian Scientists Journal, 2(1).

Bordalejo, B., Pafumi, D., Onuh, F., Khalid, A. I., Pearce, M. S., & O’Donnell, D. P. (2025). “Scarlet Cloak and the Forest Adventure”: a preliminary study of the impact of AI on commonly used writing tools. International Journal of Educational Technology in Higher Education, 22(1), 6.

Borovick, H. (2024). AI and Academia. In AI and the Law: A Practical Guide to Using Artificial Intelligence Safely (pp. 19-49). Berkeley, CA: Apress.

Chanpradit, T. (2025). Generative artificial intelligence in academic writing in higher education: A systematic review. Edelweiss Applied Science and Technology, 9(4), 889-906.

Cheng, A., Calhoun, A., & Reedy, G. (2025). Artificial intelligence-assisted academic writing: recommendations for ethical use. Advances in Simulation, 10(1), 22.

COPE Council (2023). COPE position - Authorship and AI - English. https://doi.org/10.24318/cCVRZBms

Debnath, R., Tkachenko, N., & Bhattacharyya, M. (2025). Enabling people-centric climate action using human-in-the-loop artificial intelligence: a review. Current Opinion in Behavioral Sciences, 61, 101482.

Delgado-Quirós, L., & Ortega, J. L. (2025). Citation counts and inclusion of references in seven free-access scholarly databases: A comparative analysis. Journal of Informetrics, 19(1), 101618.

Dong, D., & Leow, B. (2024). Try it Together-Qualitative coding with Atlas. ti.

Eswaran, U., & Eswaran, V. (2025). AI-Driven Cross-Platform Design: Enhancing Usability and User Experience. In Navigating Usability and User Experience in a Multi-Platform World (pp. 19-48). IGI Global.

Faix, A. (2025). Consensus: Using AI to Analyze Scientific Literature. Library Trends, 73(3), 344-354.

Floridi, L. (2014). The Fourth Revolution: How the infosphere is reshaping human reality. Oxford University Press.

Foley, K., McLean, C., De Zylva, R., Asa, G., Maio, J., Batchelor, S., ... & Dimassi, A. (2025). Developing a Critical Imagination for How Researchers can use Artificially Intelligent Tools Reflexively and Responsibly During Qualitative Literature Reviews. International Journal of Qualitative Methods, 24, 16094069251316249.

Fricker, M. (2007). Epistemic injustice: Power and the ethics of knowing. Oxford University Press.

Ganjavi, C., Eppler, M. B., Pekcan, A., Biedermann, B., Abreu, A., Collins, G. S., ... & Cacciamani, G. E. (2024). Publishers’ and journals’ instructions to authors on use of generative artificial intelligence in academic and scientific publishing: bibliometric analysis. BMJ, 384:e077192

Ghosh, S., Venkit, P. N., Gautam, S., Wilson, S., & Caliskan, A. (2024). Do Generative AI Models Output Harm while Representing Non-Western Cultures: Evidence from A Community-Centered Approach. In Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society (Vol. 7, pp. 476-489).

Gil, Y., Greaves, M., Hendler, J., & Hirsh, H. (2014). Amplify scientific discovery with artificial intelligence. Science, 346(6206), 171-172.https://doi.org/10.1126/science.1259439

Goddard, K., Roudsari, A., & Wyatt, J. C. (2012). Automation bias: a systematic review of frequency, effect mediators, and mitigators. Journal of the American Medical Informatics Association, 19(1), 121-127.https://doi.org/10.1136/amiajnl-2011-000089

Gross, N. (2023). What ChatGPT tells us about gender: a cautionary tale about performativity and gender biases in AI. Social Sciences, 12(8), 435.

Helczman, M., & Kovacik, A. (2025). Comparıson of AI Tools For Creation of Scıentıfıc Texts In Biology: Balancing Innovation with Integrity and Transparency. Journal of Microbiology, Biotechnology and Food sciences, e12509.

Herrera, F. (2025). Reflections and attentiveness on eXplainable Artificial Intelligence (XAI). The journey ahead from criticisms to human–AI collaboration. Information Fusion, 121, 103133.

Holmes, W., & Porayska-Pomsta, K. (2023). The ethics of artificial intelligence in education. Lontoo: Routledge. http://dx.doi.org/10.1136/

Huang, H., Ravi, S., Warrington, T., Cui, H., Wang, C., McCreary, M., ... & Lu, C. (2025). A comparison of data visualization tools: A case study in health-related research. Information Visualization, 24(1), 62-78.Krishnan, A. R. (2025). Research trends in criteria importance through intercriteria correlation (CRITIC) method: a visual analysis of bibliographic data using the Tableau software. Information Discovery and Delivery, 53(2), 233-247.

Izuchukwu, C. C. (2025). Application of Machine Learning and Large Language Models in Healthcare for Data Prediction and Summarization.

Kabir, N. (2025). Adapting Open-Source LLMs for Finnish Digital Scribe Systems: A Performance Evaluation.

Kay, J., Kasirzadeh, A., & Mohamed, S. (2024). Epistemic injustice in generative AI. In Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society (Vol. 7, pp. 684-697).

Khan, H., Alzabut, J., Almutairi, D. K., & Alqurashi, W. K. (2025). The Use of Artificial Intelligence in Data Analysis with Error Recognitions in Liver Transplantation in HIV-AIDS Patients Using Modified ABC Fractional Order Operators. Fractal & Fractional, 9(1).

Knox, J. (2023). Artificial intelligence and the ethics of academic knowledge. AI & Society, 38, 195–206. https://doi.org/10.1007/s00146-022-01414-1

Kostenko, I. S., & Andreieva, K. S. (2025). Analysis and Visualizatıon of Exchange Rate Dynamics Using Power BI to Improve Decision-Making Efficiency. Publishing House “Baltija Publishing”.

Kotek, H., Dockum, R., & Sun, D. (2023, November). Gender bias and stereotypes in large language models. In Proceedings of the ACM collective intelligence conference (pp. 12-24).

Kumar, S., Datta, S., Singh, V., Datta, D., Singh, S. K., & Sharma, R. (2024). Applications, challenges, and future directions of human-in-the-loop learning. IEEE Access.

Larionov, D., Takeshita, S., Zhang, R., Chen, Y., Leiter, C., Wang, Z., ... & Eger, S. (2025). DeepSeek vs. o3-mini: How Well can Reasoning LLMs Evaluate MT and Summarization?. arXiv preprint arXiv:2504.08120.

Liebling, D. J., Kane, M., Grunde-Mclaughlin, M., Lang, I. J., Venugopalan, S., & Brenner, M. P. (2025). Towards AI-assisted Academic Writing. arXiv preprint arXiv:2503.13771.

Lim, B., Seth, I., Maxwell, M., Cuomo, R., Ross, R. J., & Rozen, W. M. (2025). Evaluating the efficacy of large language models in generating medical documentation: A comparative study of chatgpt-4, chatgpt-4o, and claude. Aesthetic Plastic Surgery, 1-12.

Lipton, Z. C. (2018). The mythos of model interpretability: In machine learning, the concept of interpretability is both important and slippery. Queue, 16(3), 31-57.

Liu, S., Yang, W., Wang, J., & Yuan, J. (2025). Visualization for Artificial Intelligence. Springer International Publishing AG.

Liu, Y., Kong, W., & Merve, K. (2025). ChatGPT applications in academic writing: a review of potential, limitations, and ethical challenges. Arquivos Brasileiros de Oftalmologia, 88(3), e2024-0269.

Lixandru, D. (2024). The Use of Artificial Intelligence for Qualitative Data Analysis: ChatGPT. Informatica Economica, 28(1).

Magesh, V., Surani, F., Dahl, M., Suzgun, M., Manning, C. D., & Ho, D. E. (2025). Hallucination‐Free? Assessing the Reliability of Leading AI Legal Research Tools. Journal of Empirical Legal Studies, 22(2), 216-242.

Mahmood, S., Hasan, R., Hussain, S., & Adhikari, R. (2025). An Interpretable and Generalizable Machine Learning Model for Predicting Asthma Outcomes: Integrating AutoML and Explainable AI Techniques. World, 6(1), 15.

Messeri, L., & Crockett, M. J. (2024). Artificial intelligence and illusions of understanding in scientific research. Nature, 627(8002), 49-58.

Miao, F. ve Holmes, W. (2023). Guidance for generative AI in education and research. United Nations Educational, Scientific and Cultural Organization (UNESCO). https://unesdoc.unesco.org/ark:/48223/pf0000386097

Michael, M. ve Lupton, D. (2016). Toward a manifesto for the ‘public understanding of big data’. Public Understanding of Science, 25(1), 104-116.https://doi.org/10.1177/0963662515609005

Mickel, J., De-Arteaga, M., Liu, L., & Tian, K. (2025). More of the Same: Persistent Representational Harms Under Increased Representation. arXiv preprint arXiv:2503.00333.

Minglani, D., Pal, M., Shanker, U., & Kumar, A. (2025). Ethical Considerations and Challenges in Human-AI Collaboration. In Humans and Generative AI Tools for Collaborative Intelligence (pp. 53-86). IGI Global Scientific Publishing.

Mo, Z., & Crosthwaite, P. (2025). Exploring the affordances of generative AI large language models for stance and engagement in academic writing. Journal of English for Academic Purposes, 75, 101499.

Morgan, D. L. (2025). Query-based analysis: A strategy for analyzing qualitative data using ChatGPT. Qualitative Health Research, 10497323251321712.

Mortelmans, D. (2024). NVivo and AI:(Semi)-Automatic Coding. In Doing Qualitative Data Analysis with NVivo (pp. 229-250). Cham: Springer Nature Switzerland.

Nature Editorial. (2023). Tools such as ChatGPT threaten transparent science; Here are our ground rules for their use. Nature, 613(7945), Article 612. https://doi.org/10.1038/d41586-023-00191-1

Nesterov, V. (2024). Optimization of big data processing and analysis processes in the field of data analytics through the integration of data engineering and artificial intelligence. Computer-integrated technologies: education, science, production, (54), 160-164.

OpenAI Achiam, J., Adler, S., Agarwal, S., Ahmad, L., Akkaya, I., Aleman, F. L., ... & Anadkat, S. (2023). GPT-4 technical report. arXiv. arXiv preprint arXiv:2303.08774.

Park, S. G. (2025). AI and Systematic Reviews: Can AI Tools Replace Librarians in the Systematic Search Process?. Science & Technology Libraries, 1-22.

Paulus, T. M., & Marone, V. (2025). “In minutes instead of weeks”: discursive constructions of generative ai and qualitative data analysis. Qualitative Inquiry, 31(5), 395-402.

Perkins, M., & Roe, J. (2024). The use of Generative AI in qualitative analysis: Inductive thematic analysis with ChatGPT. Journal of Applied Learning and Teaching, 7(1).

Peters, U., & Chin-Yee, B. (2025). Generalization bias in large language model summarization of scientific research. Royal Society Open Science, 12(4), 241776.

Prillaman, M. (2024). Is ChatGPT making scientists hyper-productive? The highs and lows of using AI. Nature, 627(8002), 16-17.

Qiao, S., Fang, X., Garrett, C., Zhang, R., Li, X., & Kang, Y. (2024). Generative AI for Qualitative Analysis in a Maternal Health Study: Coding In-depth Interviews using Large Language Models (LLMs). medRxiv, 2024-09.

Rajit, D., McDonald, S., Tay, C. T., Du, L., Enticott, J., & Teede, H. (2025). Assessing the Coverage of PubMed, Embase, OpenAlex and Semantic Scholar for Automated Single Database Searches in Living Guideline Evidence Surveillance: A Case Study of the International PCOS Guidelines 2023. Journal of Clinical Epidemiology, 111789.

Ratmelia, B., Leow, B., & Dong, D. (2024). Streamlined workflow for qualitative data analysis with Whisper and ATLAS. ti.

Seele, P. (2024). AI ethics inflation, Delphi and the restart of theory: Why Big Data, Delphi, GPT3 and AI in general does not mean the “end of theory”, but a boost for a restart. AI & SOCIETY, 39(1), 403-405.

Shin, S., Hong, S., & Elmqvist, N. (2025). Visualizationary: Automating design feedback for visualization designers using llms. IEEE Transactions on Visualization and Computer Graphics.

Silva, N., & Wickramaarachchi, D. (2025, February). Enhancing Systematic Literature Reviews: Evaluating the Performance of LLM-Based Tools Across Key Systematic Literature Review Stages. In 2025 5th International Conference on Advanced Research in Computing (ICARC) (pp. 1-6). IEEE.

Song, L., Ding, X., Zhang, J., Shi, T., Shimizu, R., Gupta, R., ... & Zhao, J. (2025). Discovering knowledge deficiencies of language models on massive knowledge base. arXiv preprint arXiv:2503.23361.

Sontake, P. (2025). A Review on Artificial Intelligence (AI) Tools in Research Writing. International Journal of Scientific Research and Technology.

Talukdar, R., Ajayan, R., Gupta, S., Biswas, S., Parveen, M., Sadhukhan, D., ... & Parameswaran, S. (2025). Chronic Kidney Disease Prevalence in India: A Systematic Review and Meta‐Analysis From Community‐Based Representative Evidence Between 2011 to 2023. Nephrology, 30(1), e14420.

Thurzo, A., & Varga, I. (2025). Revisiting the role of review articles in the age of AI-agents: integrating AI-reasoning and AI-synthesis reshaping the future of scientific publishing. Bratislava Medical Journal, 1-13.

Valdez, J. P. M., Datu, J. A. D., ve Chu, S. K. W. (2022). Gratitude intervention optimizes effective learning outcomes in Filipino high school students: A mixed-methods study. Computers & Education, 176, 104268.

Valerdi Zárate, J. C. (2025). Evaluative language in undergraduate academic writing: expressions of attitude as sources of text effectiveness in English as a Foreign Language. International Review of Applied Linguistics in Language Teaching, 63(2), 1139-1168.

Villarroel Ordenes, F., Packard, G., Hartmann, J., & Proserpio, D. (2025). Using Traditional Text Analysis and Large Language Models in Service Failure and Recovery. Journal of Service Research, 10946705241307678.

Walters, W. H., & Wilder, E. I. (2023). Fabrication and errors in the bibliographic citations generated by ChatGPT. Nature Scientific Reports, 13, 14045.

Watermeyer, R., Lanclos, D., & Phipps, L. (2024). Does generative AI help academics to do more or less?. Nature, 625(7995), 450.

Whitfield, S., & Hofmann, M. A. (2023). Elicit: AI literature review research assistant. Public Services Quarterly, 19(3), 201-207.

Windarsari, W. R., Ridha, A., Mangga, A. R., & Haruna, H. (2025). Systematic Literature Mapping and Bibliometric Synthesis: Study of The Impact of Artifıcial Intelligence on Marketing Performance. Jurnal Maneksi (Management Ekonomi Dan Akuntansi), 14(2), 529-546.

Xu, Y., Liu, X., Cao, X., Huang, C., Liu, E., Qian, S., ... & Zhang, J. (2021). Artificial intelligence: A powerful paradigm for scientific research. The Innovation, 2(4).

Yan, L., Echeverria, V., Fernandez-Nieto, G. M., Jin, Y., Swiecki, Z., Zhao, L., ... & Martinez-Maldonado, R. (2024, May). Human-AI collaboration in thematic analysis using ChatGPT: A user study and design recommendations. In Extended Abstracts of the CHI Conference on Human Factors in Computing Systems (pp. 1-7).

Yuan, D., Liu, B., & Liang, G. A (2025). Framework for Comparing Reasoning between Chatgpt and Deepseek During Code Generation Tasks. Available at SSRN 5206623.

Yusuf, M. (2025). Using AI-Powered Tools to Enhance Article Retrieval Processes: Locating Quality Resources Quickly.

Adler, J. M. (2025). “Artificial Intelligence” and Library Subject Guides: Impacting the Academic Research Space. In AI Use in Social Sciences (pp. 181-204). IGI Global Scientific Publishing.

Ahmed, Z., Wan, S., Zhang, F., & Zhong, W. (2024). Artificial intelligence for omics data analysis. BMC Methods, 1(1), 4.

Alves, A., Pires, J. M., & Santos, M. Y. (2025). AI-Assisted Analytics. In Advances in Conceptual Modeling: ER 2024 Workshops, AISA, CMLS, EmpER, QUAMES, JUSMOD, LLM4Modeling, Pittsburgh, PA, USA, October 28–31, 2024, Proceedings (Vol. 14932, p. 343). Springer Nature.

Ashley, J. (2025). Is the literature review paper dead? How AI is transforming the research landscape in DNA research. Nucleic acid insights, 3(1), 7-10.

Aydin, O., Karaarslan, E., Erenay, F. S., & Bacanin, N. (2025). Generative AI in Academic Writing: A Comparison of DeepSeek, Qwen, ChatGPT, Gemini, Llama, Mistral, and Gemma. arXiv preprint arXiv:2503.04765.

Barrot, J. S. (2025). Trinka: Facilitating academic writing through an intelligent writing evaluation system. Assessing Writing, 65, 100953.

Basavaraja, M. T., & Rajashekara, S. N. (2025). Navigating Scholarly Literature with ResearchRabbit: A Comprehensive Analysis. Journal of Science &Technology Metrics. 6 (1) https://doi.org/10.6025/jstm/2025/6/1/1-9

Bender, E. M., Gebru, T., McMillan-Major, A., & Shmitchell, S. (2021). On the dangers of stochastic parrots: Can language models be too big? Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency (FAccT), 610–623. https://doi.org/10.1145/3442188.3445922

Bernard, N., Sagawa Jr, Y., Bier, N., Lihoreau, T., Pazart, L., & Tannou, T. (2025). Using artificial intelligence for systematic review: the example of elicit. BMC medical research methodology, 25(1), 75.

Bilal, A., Ebert, D., & Lin, B. (2025). Llms for explainable ai: A comprehensive survey. arXiv preprint arXiv:2504.00125.

Biondi-Zoccai, G., Cazzaro, A., Cobalchin, E., D’Auria, D., Ardizzone, G., Giordano, S., ... & Muraru, D. (2025). Artificial Intelligence Tools for Scientific Writing: The Good, The Bad and The Ugly. Top Italian Scientists Journal, 2(1).

Bordalejo, B., Pafumi, D., Onuh, F., Khalid, A. I., Pearce, M. S., & O’Donnell, D. P. (2025). “Scarlet Cloak and the Forest Adventure”: a preliminary study of the impact of AI on commonly used writing tools. International Journal of Educational Technology in Higher Education, 22(1), 6.

Borovick, H. (2024). AI and Academia. In AI and the Law: A Practical Guide to Using Artificial Intelligence Safely (pp. 19-49). Berkeley, CA: Apress.

Chanpradit, T. (2025). Generative artificial intelligence in academic writing in higher education: A systematic review. Edelweiss Applied Science and Technology, 9(4), 889-906.

Cheng, A., Calhoun, A., & Reedy, G. (2025). Artificial intelligence-assisted academic writing: recommendations for ethical use. Advances in Simulation, 10(1), 22.

COPE Council (2023). COPE position - Authorship and AI - English. https://doi.org/10.24318/cCVRZBms

Debnath, R., Tkachenko, N., & Bhattacharyya, M. (2025). Enabling people-centric climate action using human-in-the-loop artificial intelligence: a review. Current Opinion in Behavioral Sciences, 61, 101482.

Delgado-Quirós, L., & Ortega, J. L. (2025). Citation counts and inclusion of references in seven free-access scholarly databases: A comparative analysis. Journal of Informetrics, 19(1), 101618.

Dong, D., & Leow, B. (2024). Try it Together-Qualitative coding with Atlas. ti.

Eswaran, U., & Eswaran, V. (2025). AI-Driven Cross-Platform Design: Enhancing Usability and User Experience. In Navigating Usability and User Experience in a Multi-Platform World (pp. 19-48). IGI Global.

Faix, A. (2025). Consensus: Using AI to Analyze Scientific Literature. Library Trends, 73(3), 344-354.

Floridi, L. (2014). The Fourth Revolution: How the infosphere is reshaping human reality. Oxford University Press.

Foley, K., McLean, C., De Zylva, R., Asa, G., Maio, J., Batchelor, S., ... & Dimassi, A. (2025). Developing a Critical Imagination for How Researchers can use Artificially Intelligent Tools Reflexively and Responsibly During Qualitative Literature Reviews. International Journal of Qualitative Methods, 24, 16094069251316249.

Fricker, M. (2007). Epistemic injustice: Power and the ethics of knowing. Oxford University Press.

Ganjavi, C., Eppler, M. B., Pekcan, A., Biedermann, B., Abreu, A., Collins, G. S., ... & Cacciamani, G. E. (2024). Publishers’ and journals’ instructions to authors on use of generative artificial intelligence in academic and scientific publishing: bibliometric analysis. BMJ, 384:e077192

Ghosh, S., Venkit, P. N., Gautam, S., Wilson, S., & Caliskan, A. (2024). Do Generative AI Models Output Harm while Representing Non-Western Cultures: Evidence from A Community-Centered Approach. In Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society (Vol. 7, pp. 476-489).

Gil, Y., Greaves, M., Hendler, J., & Hirsh, H. (2014). Amplify scientific discovery with artificial intelligence. Science, 346(6206), 171-172.https://doi.org/10.1126/science.1259439

Goddard, K., Roudsari, A., & Wyatt, J. C. (2012). Automation bias: a systematic review of frequency, effect mediators, and mitigators. Journal of the American Medical Informatics Association, 19(1), 121-127.https://doi.org/10.1136/amiajnl-2011-000089

Gross, N. (2023). What ChatGPT tells us about gender: a cautionary tale about performativity and gender biases in AI. Social Sciences, 12(8), 435.

Helczman, M., & Kovacik, A. (2025). Comparıson of AI Tools For Creation of Scıentıfıc Texts In Biology: Balancing Innovation with Integrity and Transparency. Journal of Microbiology, Biotechnology and Food sciences, e12509.

Herrera, F. (2025). Reflections and attentiveness on eXplainable Artificial Intelligence (XAI). The journey ahead from criticisms to human–AI collaboration. Information Fusion, 121, 103133.

Holmes, W., & Porayska-Pomsta, K. (2023). The ethics of artificial intelligence in education. Lontoo: Routledge. http://dx.doi.org/10.1136/

Huang, H., Ravi, S., Warrington, T., Cui, H., Wang, C., McCreary, M., ... & Lu, C. (2025). A comparison of data visualization tools: A case study in health-related research. Information Visualization, 24(1), 62-78.Krishnan, A. R. (2025). Research trends in criteria importance through intercriteria correlation (CRITIC) method: a visual analysis of bibliographic data using the Tableau software. Information Discovery and Delivery, 53(2), 233-247.

Izuchukwu, C. C. (2025). Application of Machine Learning and Large Language Models in Healthcare for Data Prediction and Summarization.

Kabir, N. (2025). Adapting Open-Source LLMs for Finnish Digital Scribe Systems: A Performance Evaluation.

Kay, J., Kasirzadeh, A., & Mohamed, S. (2024). Epistemic injustice in generative AI. In Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society (Vol. 7, pp. 684-697).

Khan, H., Alzabut, J., Almutairi, D. K., & Alqurashi, W. K. (2025). The Use of Artificial Intelligence in Data Analysis with Error Recognitions in Liver Transplantation in HIV-AIDS Patients Using Modified ABC Fractional Order Operators. Fractal & Fractional, 9(1).

Knox, J. (2023). Artificial intelligence and the ethics of academic knowledge. AI & Society, 38, 195–206. https://doi.org/10.1007/s00146-022-01414-1

Kostenko, I. S., & Andreieva, K. S. (2025). Analysis and Visualizatıon of Exchange Rate Dynamics Using Power BI to Improve Decision-Making Efficiency. Publishing House “Baltija Publishing”.

Kotek, H., Dockum, R., & Sun, D. (2023, November). Gender bias and stereotypes in large language models. In Proceedings of the ACM collective intelligence conference (pp. 12-24).

Kumar, S., Datta, S., Singh, V., Datta, D., Singh, S. K., & Sharma, R. (2024). Applications, challenges, and future directions of human-in-the-loop learning. IEEE Access.

Larionov, D., Takeshita, S., Zhang, R., Chen, Y., Leiter, C., Wang, Z., ... & Eger, S. (2025). DeepSeek vs. o3-mini: How Well can Reasoning LLMs Evaluate MT and Summarization?. arXiv preprint arXiv:2504.08120.

Liebling, D. J., Kane, M., Grunde-Mclaughlin, M., Lang, I. J., Venugopalan, S., & Brenner, M. P. (2025). Towards AI-assisted Academic Writing. arXiv preprint arXiv:2503.13771.

Lim, B., Seth, I., Maxwell, M., Cuomo, R., Ross, R. J., & Rozen, W. M. (2025). Evaluating the efficacy of large language models in generating medical documentation: A comparative study of chatgpt-4, chatgpt-4o, and claude. Aesthetic Plastic Surgery, 1-12.

Lipton, Z. C. (2018). The mythos of model interpretability: In machine learning, the concept of interpretability is both important and slippery. Queue, 16(3), 31-57.

Liu, S., Yang, W., Wang, J., & Yuan, J. (2025). Visualization for Artificial Intelligence. Springer International Publishing AG.

Liu, Y., Kong, W., & Merve, K. (2025). ChatGPT applications in academic writing: a review of potential, limitations, and ethical challenges. Arquivos Brasileiros de Oftalmologia, 88(3), e2024-0269.

Lixandru, D. (2024). The Use of Artificial Intelligence for Qualitative Data Analysis: ChatGPT. Informatica Economica, 28(1).

Magesh, V., Surani, F., Dahl, M., Suzgun, M., Manning, C. D., & Ho, D. E. (2025). Hallucination‐Free? Assessing the Reliability of Leading AI Legal Research Tools. Journal of Empirical Legal Studies, 22(2), 216-242.

Mahmood, S., Hasan, R., Hussain, S., & Adhikari, R. (2025). An Interpretable and Generalizable Machine Learning Model for Predicting Asthma Outcomes: Integrating AutoML and Explainable AI Techniques. World, 6(1), 15.

Messeri, L., & Crockett, M. J. (2024). Artificial intelligence and illusions of understanding in scientific research. Nature, 627(8002), 49-58.

Miao, F. ve Holmes, W. (2023). Guidance for generative AI in education and research. United Nations Educational, Scientific and Cultural Organization (UNESCO). https://unesdoc.unesco.org/ark:/48223/pf0000386097

Michael, M. ve Lupton, D. (2016). Toward a manifesto for the ‘public understanding of big data’. Public Understanding of Science, 25(1), 104-116.https://doi.org/10.1177/0963662515609005

Mickel, J., De-Arteaga, M., Liu, L., & Tian, K. (2025). More of the Same: Persistent Representational Harms Under Increased Representation. arXiv preprint arXiv:2503.00333.

Minglani, D., Pal, M., Shanker, U., & Kumar, A. (2025). Ethical Considerations and Challenges in Human-AI Collaboration. In Humans and Generative AI Tools for Collaborative Intelligence (pp. 53-86). IGI Global Scientific Publishing.

Mo, Z., & Crosthwaite, P. (2025). Exploring the affordances of generative AI large language models for stance and engagement in academic writing. Journal of English for Academic Purposes, 75, 101499.

Morgan, D. L. (2025). Query-based analysis: A strategy for analyzing qualitative data using ChatGPT. Qualitative Health Research, 10497323251321712.

Mortelmans, D. (2024). NVivo and AI:(Semi)-Automatic Coding. In Doing Qualitative Data Analysis with NVivo (pp. 229-250). Cham: Springer Nature Switzerland.

Nature Editorial. (2023). Tools such as ChatGPT threaten transparent science; Here are our ground rules for their use. Nature, 613(7945), Article 612. https://doi.org/10.1038/d41586-023-00191-1

Nesterov, V. (2024). Optimization of big data processing and analysis processes in the field of data analytics through the integration of data engineering and artificial intelligence. Computer-integrated technologies: education, science, production, (54), 160-164.

OpenAI Achiam, J., Adler, S., Agarwal, S., Ahmad, L., Akkaya, I., Aleman, F. L., ... & Anadkat, S. (2023). GPT-4 technical report. arXiv. arXiv preprint arXiv:2303.08774.

Park, S. G. (2025). AI and Systematic Reviews: Can AI Tools Replace Librarians in the Systematic Search Process?. Science & Technology Libraries, 1-22.

Paulus, T. M., & Marone, V. (2025). “In minutes instead of weeks”: discursive constructions of generative ai and qualitative data analysis. Qualitative Inquiry, 31(5), 395-402.

Perkins, M., & Roe, J. (2024). The use of Generative AI in qualitative analysis: Inductive thematic analysis with ChatGPT. Journal of Applied Learning and Teaching, 7(1).

Peters, U., & Chin-Yee, B. (2025). Generalization bias in large language model summarization of scientific research. Royal Society Open Science, 12(4), 241776.

Prillaman, M. (2024). Is ChatGPT making scientists hyper-productive? The highs and lows of using AI. Nature, 627(8002), 16-17.

Qiao, S., Fang, X., Garrett, C., Zhang, R., Li, X., & Kang, Y. (2024). Generative AI for Qualitative Analysis in a Maternal Health Study: Coding In-depth Interviews using Large Language Models (LLMs). medRxiv, 2024-09.

Rajit, D., McDonald, S., Tay, C. T., Du, L., Enticott, J., & Teede, H. (2025). Assessing the Coverage of PubMed, Embase, OpenAlex and Semantic Scholar for Automated Single Database Searches in Living Guideline Evidence Surveillance: A Case Study of the International PCOS Guidelines 2023. Journal of Clinical Epidemiology, 111789.

Ratmelia, B., Leow, B., & Dong, D. (2024). Streamlined workflow for qualitative data analysis with Whisper and ATLAS. ti.

Seele, P. (2024). AI ethics inflation, Delphi and the restart of theory: Why Big Data, Delphi, GPT3 and AI in general does not mean the “end of theory”, but a boost for a restart. AI & SOCIETY, 39(1), 403-405.

Shin, S., Hong, S., & Elmqvist, N. (2025). Visualizationary: Automating design feedback for visualization designers using llms. IEEE Transactions on Visualization and Computer Graphics.

Silva, N., & Wickramaarachchi, D. (2025, February). Enhancing Systematic Literature Reviews: Evaluating the Performance of LLM-Based Tools Across Key Systematic Literature Review Stages. In 2025 5th International Conference on Advanced Research in Computing (ICARC) (pp. 1-6). IEEE.

Song, L., Ding, X., Zhang, J., Shi, T., Shimizu, R., Gupta, R., ... & Zhao, J. (2025). Discovering knowledge deficiencies of language models on massive knowledge base. arXiv preprint arXiv:2503.23361.

Sontake, P. (2025). A Review on Artificial Intelligence (AI) Tools in Research Writing. International Journal of Scientific Research and Technology.

Talukdar, R., Ajayan, R., Gupta, S., Biswas, S., Parveen, M., Sadhukhan, D., ... & Parameswaran, S. (2025). Chronic Kidney Disease Prevalence in India: A Systematic Review and Meta‐Analysis From Community‐Based Representative Evidence Between 2011 to 2023. Nephrology, 30(1), e14420.

Thurzo, A., & Varga, I. (2025). Revisiting the role of review articles in the age of AI-agents: integrating AI-reasoning and AI-synthesis reshaping the future of scientific publishing. Bratislava Medical Journal, 1-13.

Valdez, J. P. M., Datu, J. A. D., ve Chu, S. K. W. (2022). Gratitude intervention optimizes effective learning outcomes in Filipino high school students: A mixed-methods study. Computers & Education, 176, 104268.

Valerdi Zárate, J. C. (2025). Evaluative language in undergraduate academic writing: expressions of attitude as sources of text effectiveness in English as a Foreign Language. International Review of Applied Linguistics in Language Teaching, 63(2), 1139-1168.

Villarroel Ordenes, F., Packard, G., Hartmann, J., & Proserpio, D. (2025). Using Traditional Text Analysis and Large Language Models in Service Failure and Recovery. Journal of Service Research, 10946705241307678.

Walters, W. H., & Wilder, E. I. (2023). Fabrication and errors in the bibliographic citations generated by ChatGPT. Nature Scientific Reports, 13, 14045.

Watermeyer, R., Lanclos, D., & Phipps, L. (2024). Does generative AI help academics to do more or less?. Nature, 625(7995), 450.

Whitfield, S., & Hofmann, M. A. (2023). Elicit: AI literature review research assistant. Public Services Quarterly, 19(3), 201-207.

Windarsari, W. R., Ridha, A., Mangga, A. R., & Haruna, H. (2025). Systematic Literature Mapping and Bibliometric Synthesis: Study of The Impact of Artifıcial Intelligence on Marketing Performance. Jurnal Maneksi (Management Ekonomi Dan Akuntansi), 14(2), 529-546.

Xu, Y., Liu, X., Cao, X., Huang, C., Liu, E., Qian, S., ... & Zhang, J. (2021). Artificial intelligence: A powerful paradigm for scientific research. The Innovation, 2(4).

Yan, L., Echeverria, V., Fernandez-Nieto, G. M., Jin, Y., Swiecki, Z., Zhao, L., ... & Martinez-Maldonado, R. (2024, May). Human-AI collaboration in thematic analysis using ChatGPT: A user study and design recommendations. In Extended Abstracts of the CHI Conference on Human Factors in Computing Systems (pp. 1-7).

Yuan, D., Liu, B., & Liang, G. A (2025). Framework for Comparing Reasoning between Chatgpt and Deepseek During Code Generation Tasks. Available at SSRN 5206623.

Yusuf, M. (2025). Using AI-Powered Tools to Enhance Article Retrieval Processes: Locating Quality Resources Quickly.