COMPARING HUMAN INTELLIGENCE AND ARTIFICIAL INTELLIGENCE: A COGNITIVE PERSPECTIVE

Authors

  • Dr. Ayesha Shahid Senior Researcher, Cognitive Computing Institute, Lahore, Pakistan.
  • Dr. Daniel Greenfield Professor, Department of Computer Science, University of Oxford, UK.

Keywords:

Human Intelligence, Artificial Intelligence, Cognitive Science, Learning, Problem-Solving, Machine Learning, Neural Networks, Cognitive Processes, AI Ethics, Human-AI Collaboration

Abstract

Human intelligence has long been a subject of fascination, with researchers striving to understand its mechanisms and capabilities. In recent decades, the field of Artificial Intelligence (AI) has emerged, aiming to replicate human cognitive functions in machines. This paper compares human intelligence with AI from a cognitive perspective, highlighting the similarities and differences in how both process information, learn, and make decisions. We explore key cognitive abilities such as perception, reasoning, problem-solving, and learning, and examine how these are implemented in both human and artificial systems. By analyzing these cognitive processes, we shed light on the current capabilities of AI and its limitations, while also considering the ethical, philosophical, and societal implications of AI development. Ultimately, we aim to provide insights into the potential for AI to complement and enhance human intelligence in various domains.

References

Russell, S., & Norvig, P. (2020). Artificial Intelligence: A Modern Approach (4th ed.). Pearson.

Goleman, D. (1995). Emotional Intelligence: Why It Can Matter More Than IQ. Bantam Books.

Goertzel, B., & Pennachin, C. (2007). Artificial General Intelligence. Springer.

Bostrom, N. (2014). Superintelligence: Paths, Dangers, Strategies. Oxford University Press.

Tegmark, M. (2017). Life 3.0: Being Human in the Age of Artificial Intelligence. Penguin Press.

Yudkowsky, E. (2008). Artificial Intelligence as a Positive and Negative Factor in Global Risk.

Salovey, P., & Mayer, J. D. (1990). Emotional intelligence. Imagination, Cognition, and Personality, 9(3), 185-211.

Mayer, J. D., & Salovey, P. (1997). What is emotional intelligence? In P. Salovey & D. J. Sluyter (Eds.), Emotional Development and Emotional Intelligence: Implications for Educators (pp. 3-31). Basic Books.

Schutte, N. S., & Malouff, J. M. (2002). Emotional intelligence and interpersonal relations. Journal of Social Behavior and Personality, 30(1), 91-98.

Petrides, K. V., & Furnham, A. (2001). Emotional intelligence: Some evidence for its personality-based theory. Personality and Individual Differences, 30(6), 413-420.

Cherniss, C., & Goleman, D. (2001). The Emotionally Intelligent Workplace: How to Select for, Measure, and Improve Emotional Intelligence in Individuals, Groups, and Organizations. Jossey-Bass.

Matthews, G., Zeidner, M., & Roberts, R. D. (2002). Emotional Intelligence: Science and Myth. MIT Press.

Johnson, S. (2014). How We Got to Now: Six Innovations That Made the Modern World. Riverhead Books.

Clarke, N. (2006). Emotional intelligence and its impact on performance. International Journal of Selection and Assessment, 14(1), 81-92.

Goldenberg, I., & Matheson, K. (2004). The emotional intelligence of groups. Journal of Applied Social Psychology, 34(4), 716-738.

Wong, C. S., & Law, K. S. (2002). The effects of leader and follower emotional intelligence on performance and attitude: An exploratory study. The Leadership Quarterly, 13(3), 243-274.

Goleman, D. (2006). Social Intelligence: The New Science of Human Relationships. Bantam.

Mayer, J. D., Salovey, P., & Caruso, D. R. (2004). Emotional intelligence: Theory, findings, and implications. Psychological Science in the Public Interest, 5(2), 1-25.

Damasio, A. R. (1994). Descartes' Error: Emotion, Reason, and the Human Brain. Grosset/Putnam.

Tannenbaum, R. J., & Salovey, P. (2003). The role of emotional intelligence in the workplace. In A. H. Normand & J. D. Stokols (Eds.), Handbook of Environmental Psychology (pp. 417-439). Wiley.

Hussain, T. (2025). Market thinking in public service: Designing statutory authorities for governance and efficiency. Contemporary Journal of Social Science Review, 3(4), 81-93. https://doi.org/10.63878/cjssr.v3i4.1346

Ahmad, N. R. (2025). Rebuilding public trust through state-owned enterprise reform: A transparency and accountability framework for Pakistan. International Journal of Business and Economic Affairs, 10(3), 45–68. https://doi.org/10.24088/IJBEA-2025-103004

Ahmad, N. R. (2025). Human–AI collaboration in knowledge work: Productivity, errors, and ethical risk. https://doi.org/10.52152/6q2p9250

Ahmad, N. R. (2024). AI-enabled public governance in developing states: Service delivery gains, accountability risks, and a practical risk-based regulatory model. https://doi.org/10.52152/wja5db40

Irk, E. (2025). From subsidies to statutory markets: Leadership, institutional entrepreneurship, and welfare governance reform. https://doi.org/10.52152/s59sjh53

Ahmad, N. R. (2025). Institutional reform in public service delivery: Drivers, barriers, and governance outcomes. Journal of Human and Social Research. https://doi.org/10.52152/jhs8rn12

Ahmad, N. R. (2025). Urban water service delivery in emerging economies: Fiscal sustainability, cost recovery, and governance performance. International Journal of Business Economics and Administration. https://doi.org/10.24088/IJBEA-2025-103005

Porter, M. E. (1985). Competitive advantage: Creating and sustaining superior performance. Free Press.

Wirtz, B. W., Weyerer, J. C., & Geyer, C. (2019). Artificial intelligence and the public sector—Applications and challenges. International Journal of Public Administration, 42(7), 596–615. https://doi.org/10.1080/01900692.2018.1498103

Doz, Y., & Kosonen, M. (2010). Embedding strategic agility: A leadership agenda for accelerating business model renewal. Long Range Planning, 43(2–3), 370–382. https://doi.org/10.1016/j.lrp.2009.07.006

Lee, I., & Shin, Y. J. (2018). Fintech: Ecosystem, business models, investment decisions, and challenges. Business Horizons, 61(1), 35–46. https://doi.org/10.1016/j.bushor.2017.09.003

Hart, S. L., & Dowell, G. (2011). A natural-resource-based view of the firm: Fifteen years after. Journal of Management, 37(5), 1464–1479. https://doi.org/10.1177/0149206310390219

Downloads

Published

2025-08-31

Issue

Vol. 1 No. 02 (2025): Algorithms and Intelligence

Section

Articles

License

Copyright (c) 2025 Algorithms and Intelligence

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.