Engineering and Technology
| Open Access |
DOI: The Autonomous Knowledge Frontier: AI Systems Redefining Human Learning and Infinite Knowledge Flow
Subhasis Kundu , Solution Architecture & Design Roswell, GA, USAAbstract
This paper investigates the transformative effects of autonomous AI systems on human learning and the dissemination of knowledge. It presents a framework for developing self-evolving knowledge solutions that integrate autonomous individuals with adaptive AI networks. By employing continuous feedback loops and dynamic interactions, these systems facilitate a perpetual flow of knowledge, thereby enhancing both individual and collective intelligence. The study highlights the key mechanisms through which AI supports personalized learning experiences and accelerates the evolution of knowledge. It also addresses challenges related to autonomy, scalability, and ethical considerations. The proposed model aims to bridge the gap between human cognition and machine intelligence, fostering a collaborative ecosystem for lifelong learning. This work contributes to the emerging field of AI-driven knowledge management and educational innovation.
Keywords
Autonomous AI, Human Learning, Knowledge Flow, Self-Evolving Systems, Adaptive Networks, Lifelong Learning, AI Knowledge Solutions
References
D. Zhu, Z. Zhu, Y. Zhang, Q. Bu, and Z. Wang, “Advancing autonomy through lifelong learning: a survey of autonomous intelligent systems.,” Front. Neurorobot., vol. 18, Apr. 2024, doi: 10.3389/fnbot.2024.1385778.
N. A. Megahed, H. Y. Soliman, and R. F. Abdel-Kader, “Post-pandemic Education Strategy: Framework for Artificial Intelligence-Empowered Education in Engineering (AIEd-Eng) for Lifelong Learning,” Springer, 2022, pp. 544–556. doi: 10.1007/978-3-031-03918-8_45.
S. Singha and R. Singha, “Revolutionizing Content Creation and Curriculum Development Through Generative AI,” Igi Global, 2024, pp. 261–280. doi: 10.4018/979-8-3693-1351-0.ch013.
A. Madison et al., “Scalable Interactive Machine Learning for Future Command and Control,” Institute Of Electrical Electronics Engineers, Apr. 2024, pp. 1–10. doi: 10.1109/icmcis61231.2024.10540933.
J. Shuford, “Deep Reinforcement Learning Unleashing the Power of AI in Decision-Making,” JAIGS, vol. 1, no. 1, Feb. 2024, doi: 10.60087/jaigs.v1i1.36.
G. Sandini, A. Sciutti, and P. Morasso, “Artificial cognition vs. artificial intelligence for next-generation autonomous robotic agents.,” Front. Comput. Neurosci., vol. 18, Mar. 2024, doi: 10.3389/fncom.2024.1349408.
L. Yan et al., “Human-AI Collaboration in Thematic Analysis using ChatGPT: A User Study and Design Recommendations,” Association for Computing Machinery, May 2024, pp. 1–7. doi: 10.1145/3613905.3650732.
M. Alavi, R. Mousavi, and D. E. Leidner, “Knowledge Management Perspective of Generative Artificial Intelligence,” JAIS, vol. 25, no. 1, pp. 1–12, Jan. 2024, doi: 10.17705/1jais.00859.
K. H. D. Tang, “Implications of Artificial Intelligence for Teaching and Learning,” Acta Pedagogia Asia, vol. 3, no. 2, pp. 65–79, Feb. 2024, doi: 10.53623/apga.v3i2.404.
M. N. Masrek, F. Mutia, H. P. Yuwinanto, R. T. Atmi, and T. Susantari, “Enabling Education Everywhere: How artificial intelligence empowers ubiquitous and lifelong learning,” E-BPJ, vol. 9, no. SI18, pp. 57–63, Jan. 2024, doi: 10.21834/e-bpj.v9isi18.5462.
W.-L. Cheung and C.-Y. Luk, “Implementing Automated Error Correction and Feedback Loops in Kimi, A Chinese Large Language Model,” Apr. 24, 2024, Center for Open Science. doi: 10.31219/osf.io/7vpxr.
Q. Sun, Z. Song, and Y. Xue, “Adaptive User Interface Generation Through Reinforcement Learning: A Data-Driven Approach to Personalization and Optimization,” Institute Of Electrical Electronics Engineers, Dec. 2024, pp. 1386–1391. doi: 10.1109/icftic64248.2024.10913228.
A. I. Jony and S. A. Hamim, “Empowering virtual collaboration: harnessing AI for enhanced teamwork in higher education,” Educ. Technol. Q., vol. 2024, no. 3, pp. 337–359, Sept. 2024, doi: 10.55056/etq.746.
M. R. Faraji, F. Shikder, M. H. Hasan, M. M. Islam, and U. K. Akter, “Examining the Role of Artificial Intelligence in Cyber Security (CS): A Systematic Review for Preventing Prospective Solutions in Financial Transactions,” Intl. J. Rel., vol. 5, no. 10, pp. 4766–4782, July 2024, doi: 10.61707/7rfyma13.
N. V. Naveen Vemuri, “Enhancing Human-Robot Collaboration in Industry 4.0 with AI-driven HRI,” pst, vol. 47, no. 4, pp. 341–358, Dec. 2023, doi: 10.52783/pst.196.
D. Aggarwal, D. Sharma, and A. B. Saxena, “Adoption of Artificial Intelligence (AI) For Development of Smart Education as the Future of a Sustainable Education System,” JAIMLNN, no. 36, pp. 23–28, Oct. 2023, doi: 10.55529/jaimlnn.36.23.28.
M. Guettala, S. Harous, O. Kazar, and S. Bourekkache, “Generative Artificial Intelligence in Education: Advancing Adaptive and Personalized Learning,” AIP, vol. 13, no. 3, pp. 460–489, Aug. 2024, doi: 10.18267/j.aip.235.
V. B. Alexsius Pardosi, S. Xu, U. Umurohmi, N. Nurdiana, and F. Sabur, “Implementation of an Artificial Intelligence Based Learning Management System for Adaptive Learning,” JAF, vol. 12, no. 1, p. 149, June 2024, doi: 10.31958/jaf.v12i1.12548.
H. U. Rehman, F. Mo, J. C. Chaplin, L. Zarzycki, M. Jones, and S. Ratchev, “A modular artificial intelligence and asset administration shell approach to streamline testing processes in manufacturing services,” Journal of Manufacturing Systems, vol. 72, pp. 424–436, Dec. 2023, doi: 10.1016/j.jmsy.2023.12.004.
J. Chukwunweike, J. Arogundade, O. Lawal, and B. E, “Navigating ethical challenges of explainable ai in autonomous systems,” Int. J. Sci. Res. Arch., vol. 13, no. 1, pp. 1807–1819, Oct. 2024, doi: 10.30574/ijsra.2024.13.1.1872.
S. Singhal, “Data Privacy, Compliance, and Security Including AI ML,” Igi Global, 2024, pp. 111–126. doi: 10.4018/979-8-3693-2909-2.ch009.
O. S. Owolabi, P. C. Uche, R. B. Islam, C. Ihejirika, N. T. Adeniken, and B. J. T. Chhetri, “Ethical Implication of Artificial Intelligence (AI) Adoption in Financial Decision Making,” CIS, vol. 17, no. 1, p. 49, Apr. 2024, doi: 10.5539/cis.v17n1p49.
M. S. Farahani and G. Ghasmi, “Artificial Intelligence in education: A comprehensive study,” Forum Edu. Stud., vol. 2, no. 3, p. 1379, July 2024, doi: 10.59400/fes.v2i3.1379.
A. Jedličková, “Ethical approaches in designing autonomous and intelligent systems: a comprehensive survey towards responsible development,” AI & Soc, vol. 40, no. 4, pp. 2703–2716, Aug. 2024, doi: 10.1007/s00146-024-02040-9.
M. M. Karim, Q. Qu, D. H. Van, S. Khan, and Y. Kholodov, “AI Agents Meet Blockchain: A Survey on Secure and Scalable Collaboration for Multi-Agents,” Future Internet, vol. 17, no. 2, p. 57, Feb. 2025, doi: 10.3390/fi17020057.
Article Statistics
Copyright License
This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors retain the copyright of their manuscripts, and all Open Access articles are disseminated under the terms of the Creative Commons Attribution License 4.0 (CC-BY), which licenses unrestricted use, distribution, and reproduction in any medium, provided that the original work is appropriately cited. The use of general descriptive names, trade names, trademarks, and so forth in this publication, even if not specifically identified, does not imply that these names are not protected by the relevant laws and regulations.