Home⇛International Journal of Multidisciplinary: Applied Business and Education Research⇛vol. 5 no. 3 (2024)

OpenAI ChatGPT, Google Bard, and Microsoft Bing: Similarity Index and Analysis of Artificial Intelligence-Based Contents

Randy Joy M. Ventayen

Discipline: Artificial Intelligence

 

Abstract:

This research compares AI language models—specifically, OpenAI's ChatGPT, Google's Bard, and Microsoft's Bing—by analyzing their originality, use of external sources, and performance. Conducted on August 5, 2023, the study evaluates how these models respond to different queries, revealing distinct characteristics. ChatGPT stands out with lower similarity scores and lesser reliance on online sources, indicating its potential for creating more unique content. In contrast, Bard and Bing show higher similarity scores, suggesting they draw more from available online content, which could be beneficial for tasks requiring context-rich information. While ChatGPT and Bard excel in grasping context, generating substantial content, and offering relevant insights, there are concerns about accuracy and consistency across queries. Notably, Bing's focus on aiding content creation rather than direct essay generation showcases diverse strengths among AI models. As AI technology progresses, refining these models and addressing inconsistencies will improve their usefulness across various applications. These findings guide users in choosing AI tools that fit their content needs and ensure the credibility of generated outputs.



References:

  1. Bautista, R. M., & Pentang, J. T. (2022). Ctrl C + Ctrl V: Plagiarism and Knowledge on Ref-erencing and Citation among Pre-service Teachers. International Journal of Multi-disciplinary: Applied Business and Educa-tion Research, 3(2), 245–257. https://doi.org/10.11594/IJMABER.03.02.10
  2. Bhardwaz, S., & Kumar, J. (2023). An Extensive Comparative Analysis of Chatbot Tech-nologies - ChatGPT, Google BARD and Mi-crosoft Bing. Proceedings of the 2nd In-ternational Conference on Applied Artifi-cial Intelligence and Computing, ICAAIC 2023, 673–679. https://doi.org/10.1109/ICAAIC56838.2023.10140214
  3. Bray, C., Bryson, C., & Zawisza, K. (2023). TIPS Lunch - Faculty Session on ChatGPT: As-sessments, Assignments, and Academic Integrity. Publications and Presentations. https://scholarworks.uark.edu/wctfscpub/55
  4. Campued, J. C., Papa, D.-M. M., Castro, A. C. de, & Malang, B. P. (2023). Exploring Chal-lenges and Opportunities: Evaluating the Awareness and Readiness of Selected Government Agencies in Adopting Artifi-cial Intelligence (AI). International Jour-nal of Multidisciplinary: Applied Business and Education Research, 4(12), 4504–4517. https://doi.org/10.11594/IJMABER.04.12.26
  5. Chen, L., Chen, P., & Lin, Z. (2020). Artificial Intelligence in Education: A Review. IEEE Access, 8, 75264–75278. https://doi.org/10.1109/ACCESS.2020.2988510
  6. Cotton, D. R. E., Cotton, P. A., & Shipway, J. R. (n.d.). Chatting and Cheating. Ensuring academic integrity in the era of ChatGPT. https://doi.org/10.35542/OSF.IO/MRZ8H
  7. Dahl, S. (2007). Turnitin®. Active Learning in Higher Education. https://doi.org/10.1177/1469787407074110
  8. Harte, P., & Khaleel, F. (2023). Keep calm and carry on: ChatGPT doesn’t change a thing for academic integrity. https://napier-reposito-ry.worktribe.com/output/3048214/keep-calm-and-carry-on-chatgpt-doesnt-change-a-thing-for-academic-integrity
  9. King, M. R. (2023). Can Bard, Google’s Experi-mental Chatbot Based on the LaMDA Large Language Model, Help to Analyze the Gender and Racial Diversity of Au-thors in Your Cited Scientific References? Cellular and Molecular Bioengineering, 16(2), 175–179. https://doi.org/10.1007/s12195-023-00761-3
  10. Lund, B. D., & Wang, T. (2023). Chatting about ChatGPT: how may AI and GPT impact academia and libraries? Library Hi Tech News, ahead-of-print(ahead-of-print). https://doi.org/10.1108/LHTN-01-2023-0009
  11. Mobo, F. D. (2021). The Role of Emerging Trends in Education. International Jour-nal of Multidisciplinary: Applied Business and Education Research, 2(10), 909–913. https://doi.org/10.11594/IJMABER.02.10.07
  12. Pavlik, J. V. (2023). Collaborating With ChatGPT: Considering the Implications of Generative Artificial Intelligence for Journalism and Media Education. https://doi.org/10.1177/10776958221149577
  13. Perkins, M. (2023). Academic Integrity consid-erations of AI Large Language Models in the post-pandemic era: ChatGPT and be-yond. Journal of University Teaching & Learning Practice, 20(2), 07. https://doi.org/10.53761/1.20.02.07
  14. Rahsepar, A. A., Tavakoli, N., Kim, G. H. J., Has-sani, C., Abtin, F., & Bedayat, A. (2023). How AI Responds to Common Lung Can-cer Questions: ChatGPT vs Google Bard. Radiology, 307(5), e230922. https://doi.org/10.1148/radiol.230922
  15. Roll, I., & Wylie, R. (2016). Evolution and Rev-olution in Artificial Intelligence in Educa-tion. International Journal of Artificial In-telligence in Education, 26(2), 582–599. https://doi.org/10.1007/S40593-016-0110-3/TABLES/8
  16. Susnjak, T. (2022). ChatGPT: The End of Online Exam Integrity? https://doi.org/10.48550/arxiv.2212.09292
  17. Tangermann, V. (2023). College Student Caught Submitting Paper Using ChatGPT. https://futurism.com/college-student-caught-writing-paper-chatgpt
  18. Ventayen, R. J. M. (2023). OpenAI ChatGPT-Generated Results: Similarity Index of
  19. Artificial Intelligence-Based Contents. Soft Computing for Security Applications, 215–226. https://doi.org/10.1007/978-981-99-3608-3_15
  20. Zhai, X. (2022). ChatGPT User Experience: Im-plications for Education. SSRN Electronic Journal. https://doi.org/10.2139/SSRN.4312418

Tools


Copyright © 2024  KITE Digital Educational Solutions |  Exclusively distributed by CE-Logic