The Development Trends of Computer Science and Technology Driven by Artificial Intelligence

Main Article Content

Linkai Wei
Wenxi Du
Zihao Pan
Zhongyang Sun
Siqi Huang
Xiaojun Ke

Abstract

With the rapid development of artificial intelligence (AI), it has become a core driver transforming computer science and technology. This paper systematically outlines AI-driven trends in the field, analyzing key opportunities such as algorithm innovation, computing power enhancement, and application expansion, alongside critical challenges including data privacy risks, ethical dilemmas, and algorithmic bias. It further predicts future directions in technology integration, application deepening, and theoretical breakthroughs, emphasizing the structural interplay between AI advancements and the evolution of computer science.

Article Details

How to Cite
Wei, L., Du, W., Pan, Z., Sun, Z., Huang, S., & Ke, X. (2025). The Development Trends of Computer Science and Technology Driven by Artificial Intelligence. Rajapark International Journal, 2(2), 12–21. retrieved from https://so20.tci-thaijo.org/index.php/RJPIJ/article/view/633
Section
Academic Article

References

Adelaja, O., & Alkattan, H. (2023). Operating artificial intelligence to assist physicians in diagnosing medical images: A narrative review. Mesopotamian Journal of Artificial Intelligence in Healthcare, 45-51.

Adekunle, B. I., Chukwuma-Eke, E. C., Balogun, E. D., & Ogunsola, K. O. (2023). Integrating AI-driven risk assessment frameworks in financial operations: A model for enhanced corporate governance. International Journal of Scientific Research in Computer Science, Engineering and Information Technology, 9(6), 445-464.

Ayeni, O. O., Al Hamad, N. M., Chisom, O. N., Osawaru, B., & Adewusi, O. E. (2024). AI in education: A review of personalized learning and educational technology. GSC Advanced Research and Reviews, 18(2), 261-271.

Casheekar, A., Lahiri, A., Rath, K., Prabhakar, K. S., & Srinivasan, K. (2024). A contemporary review on chatbots, AI-powered virtual conversational agents, ChatGPT: Applications, open challenges and future research directions. Computer Science Review, 52, 100632.

Chen, Z. (2023). Ethics and discrimination in artificial intelligence-enabled recruitment practices. Humanities and Social Sciences Communications, 10(1), 1-12.

Chwilla, D. J. (2022). Context effects in language comprehension: The role of emotional state and attention on semantic and syntactic processing. Frontiers in human neuroscience, 16, 1014547.

Duan, S., Wang, D., Ren, J., Lyu, F., Zhang, Y., Wu, H., & Shen, X. (2022). Distributed artificial intelligence empowered by end-edge-cloud computing: A survey. IEEE Communications Surveys & Tutorials, 25(1), 591-624.

Dwivedi, Y. K., Sharma, A., Rana, N. P., Giannakis, M., Goel, P., & Dutot, V. (2023). Evolution of artificial intelligence research in Technological Forecasting and Social Change: Research topics, trends, and future directions. Technological Forecasting and Social Change, 192, 122579.

Gadhoum, Y. (2022). A proposed model of a future university in the era of the artificial intelligence transformative society: From why to how. Creative Education, 13(3), 1098-1119.

George, A. S. (2024). Artificial intelligence and the future of work: Job shifting, not job loss. Partners Universal Innovative Research Publication, 2(2), 17-37.

Guembe, B., Azeta, A., Misra, S., Osamor, V. C., Fernandez-Sanz, L., & Pospelova, V. (2022). The emerging threat of AI-driven cyber attacks: A review. Applied Artificial Intelligence, 36(1), 2037254.

Guo, Y., Zou, K., Yang, M., & Liu, C. (2022). Tripartite evolutionary game of multiparty collaborative supervision of personal information security in app: empirical evidence from China. IEEE Access, 10, 85429-85441.

Gupta, I., Singh, A. K., Lee, C. N., & Buyya, R. (2022). Secure data storage and sharing techniques for data protection in cloud environments: A systematic review, analysis, and future directions. IEEE Access, 10, 71247-71277.

Hammad, A., & Abu-Zaid, R. (2024). Applications of AI in Decentralized Computing Systems: Harnessing Artificial Intelligence for Enhanced Scalability, Efficiency, and Autonomous Decision-Making in Distributed Architectures. Applied Research in Artificial Intelligence and Cloud Computing, 7, 161-187.

Hassan, K., Thakur, A. K., Singh, G., Singh, J., Gupta, L. R., & Singh, R. (2024). Application of artificial intelligence in aerospace engineering and its future directions: a systematic quantitative literature review. Archives of Computational Methods in Engineering, 31(7), 4031-4086.

Mishra, R. K., & Agarwal, R. (2024). Impact of digital evolution on various facets of computer science and information technology. Digital Evolution: Advances in Computer Science and Information Technology, 17-57.

Lazaroiu, G., Androniceanu, A., Grecu, I., Grecu, G., & Neguriță, O. (2022). Artificial intelligence-based decision-making algorithms, Internet of Things sensing networks, and sustainable cyber-physical management systems are significant in data-driven cognitive manufacturing. Oeconomia Copernicana, 13(4), 1047-1080.

Li, B., Jiang, F., Xia, H., & Pan, J. (2022). Under the background of AI application, research on the impact of science and technology innovation and industrial structure upgrading on the sustainable and high-quality development of regional economies. Sustainability, 14(18), 11331.

Kljucaric, L., & George, A. D. (2023). Deep learning inferencing with high-performance hardware accelerators. ACM Transactions on Intelligent Systems and Technology, 14(4), 1-25.

Padmanaban, H. (2024). Quantum Computing and AI in the Cloud. Journal of Computational Intelligence and Robotics, 4(1), 14-32.

Pasham, S. D. (2022). A Review of the Literature on the Subject of Ethical and Risk Considerations in the Context of Fast AI Development. International Journal of Modern Computing, 5(1), 24-43.

Rokai, J., Ulbert, I., & Márton, G. (2023). Edge computing on TPU for brain implant signal analysis. Neural Networks, 162, 212-224.

Sarkar, C., Das, B., Rawat, V. S., Wahlang, J. B., Nongpiur, A., Tiewsoh, I., ... & Sony, H. T. (2023). Artificial intelligence and machine learning technology driven modern drug discovery and development. International Journal of Molecular Sciences, 24(3), 2026.

Singh, M., Joshi, M., Tyagi, K. D., & Tyagi, V. B. (2024). Future Professions in Agriculture, Medicine, Education, Fitness, Research and Development, Transport, and Communication. Topics in Artificial Intelligence Applied to Industry 4.0, 181-202.

Sivamayil, K., Rajasekar, E., Aljafari, B., Nikolovski, S., Vairavasundaram, S., & Vairavasundaram, I. (2023). A systematic study on reinforcement learning based applications. Energies, 16(3), 1512.

Song, H., Kim, M., Park, D., Shin, Y., & Lee, J. G. (2022). Learning from noisy labels with deep neural networks: A survey. IEEE transactions on neural networks and learning systems, 34(11), 8135-8153.

Souchleris, K., Sidiropoulos, G. K., & Papakostas, G. A. (2023). Reinforcement learning in game industry—Review, prospects and challenges. Applied Sciences, 13(4), 2443.

Tan, K., Wu, J., Zhou, H., Wang, Y., & Chen, J. (2024). Integrating advanced computer vision and AI algorithms for autonomous driving systems. Journal of Theory and Practice of Engineering Science, 4(01), 41-48.

Tiwari, P. C., Pal, R., Chaudhary, M. J., & Nath, R. (2023). Artificial intelligence revolutionizing drug development: Exploring opportunities and challenges. Drug Development Research, 84(8), 1652-1663.

Vadlakonda, G. (2023). Blockchain for AI: Enhancing Data Integrity and Security. International Journal of Unique and New Updates, 5(2), 1-8.

Vaithianathan, M. (2025). The Future of Heterogeneous Computing: Integrating CPUs, GPUs, and FPGAs for High-Performance Applications. International Journal of Emerging Trends in Computer Science and Information Technology, 6(1), 12-23.

Van Hoang, T. (2024). Impact of integrated artificial intelligence and internet of things technologies on smart city transformation. Journal of Technical Education Science, 19(Special Issue 1), 64-73.

Zahra, M. A., Al-Taher, A., Alquhaidan, M., Hussain, T., Ismail, I., Raya, I., & Kandeel, M. (2024). The synergy of artificial intelligence and personalized medicine for the enhanced diagnosis, treatment, and prevention of disease. Drug Metabolism and Personalized Therapy, 39(2), 47-58.

Zhang, W., Gu, X., Tang, L., Yin, Y., Liu, D., & Zhang, Y. (2022). Application of machine learning, deep learning and optimization algorithms in geoengineering and geoscience: Comprehensive review and future challenge. Gondwana Research, 109, 1-17.