THE EFFECT OF COGNITIVE OFFLOADING THROUGH GENERATIVE AI USE ON ORGANIZATIONAL COMMUNICATION EFFECTIVENESS
Keywords:
cognitive offloading, generative artificial intelligence, human oversight, organizational communication, technology reliance.Abstract
Delegating cognitive tasks to external systems may reduce immediate processing demands while changing how individuals understand and communicate information. This conceptual article examines the potential effects of cognitive offloading through generative artificial intelligence on organizational communication effectiveness, using literature available through 2017. A narrative literature review connects cognitive offloading, early neural text generation, automation reliance, and organizational communication theory. Generative AI is discussed in relation to research systems available within the period rather than contemporary general-purpose assistants. The synthesis proposes that external support may assist selected information-processing activities, but communication benefits depend on system capability, user verification, contextual interpretation, and opportunities for clarification. Reduced production effort should not be equated with accurate messages or shared understanding. Possible risks include inappropriate reliance, inconsistent output, and the transfer of unresolved interpretation to recipients. The article develops propositions concerning task suitability, verification, and human responsibility. It concludes that effects on organizational communication are conditional and require empirical evaluation. No causal effect, organizational adoption rate, or observed communication outcome is established by this review.
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References
Bainbridge, L. (1983). Ironies of automation. Automatica, 19(6), 775–779. https://doi.org/10.1016/0005-1098(83)90046-8ScienceDirect
Baumeister, R. F., & Leary, M. R. (1997). Writing narrative literature reviews. Review of General Psychology, 1(3), 311–320. https://doi.org/10.1037/1089-2680.1.3.311
Clark, A., & Chalmers, D. (1998). The extended mind. Analysis, 58(1), 7–19. https://doi.org/10.1093/analys/58.1.7
Daft, R. L., & Lengel, R. H. (1986). Organizational information requirements, media richness and structural design. Management Science, 32(5), 554–571. https://doi.org/10.1287/mnsc.32.5.554
Dennis, A. R., Fuller, R. M., & Valacich, J. S. (2008). Media, tasks, and communication processes: A theory of media synchronicity. MIS Quarterly, 32(3), 575–600. https://doi.org/10.2307/25148857
Dunn, T. L., & Risko, E. F. (2016). Toward a metacognitive account of cognitive offloading. Cognitive Science, 40(5), 1080–1127. https://doi.org/10.1111/cogs.12273 Wiley Online Library
Fisher, M., Goddu, M. K., & Keil, F. C. (2015). Searching for explanations: How the Internet inflates estimates of internal knowledge. Journal of Experimental Psychology: General, 144(3), 674–687. https://doi.org/10.1037/xge0000070 apa.org
Gilbert, S. J. (2015). Strategic offloading of delayed intentions into the external environment. The Quarterly Journal of Experimental Psychology, 68(5), 971–992. https://doi.org/10.1080/17470218.2014.972963 Sam J. Gilbert, 2015
Goodfellow, I., Pouget-Abadie, J., Mirza, M., Xu, B., Warde-Farley, D., Ozair, S., Courville, A., & Bengio, Y. (2014). Generative adversarial nets. Advances in Neural Information Processing Systems, 27. https://papers.neurips.cc/paper_files/paper/2014/hash/f033ed80deb0234979a61f95710dbe25-Abstract.html
Lee, J. D., & See, K. A. (2004). Trust in automation: Designing for appropriate reliance. Human Factors, 46(1), 50–80. https://doi.org/10.1518/hfes.46.1.50_30392
Parasuraman, R., & Riley, V. (1997). Humans and automation: Use, misuse, disuse, abuse. Human Factors, 39(2), 230–253. https://doi.org/10.1518/001872097778543886
Risko, E. F., & Dunn, T. L. (2015). Storing information in-the-world: Metacognition and cognitive offloading in a short-term memory task. Consciousness and Cognition, 36, 61–74. https://doi.org/10.1016/j.concog.2015.05.014
Risko, E. F., & Gilbert, S. J. (2016). Cognitive offloading. Trends in Cognitive Sciences, 20(9), 676–688. https://doi.org/10.1016/j.tics.2016.07.002
Sparrow, B., Liu, J., & Wegner, D. M. (2011). Google effects on memory: Cognitive consequences of having information at our fingertips. Science, 333(6043), 776–778. https://doi.org/10.1126/science.1207745
Storm, B. C., & Stone, S. M. (2015). Saving-enhanced memory: The benefits of saving on the learning and remembering of new information. Psychological Science, 26(2), 182–188. https://doi.org/10.1177/0956797614559285
Sutskever, I., Vinyals, O., & Le, Q. V. (2014). Sequence to sequence learning with neural networks. Advances in Neural Information Processing Systems, 27, 3104–3112. https://papers.nips.cc/paper_files/paper/2014/hash/5a18e133cbf9f257297f410bb7eca942-Abstract.html
Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A. N., Kaiser, Ł., & Polosukhin, I. (2017). Attention is all you need. Advances in Neural Information Processing Systems, 30. https://papers.nips.cc/paper_files/paper/2017/hash/3f5ee243547dee91fbd053c1c4a845aa-Abstract.html
Vinyals, O., & Le, Q. (2015). A neural conversational model [Preprint]. arXiv. https://doi.org/10.48550/arXiv.1506.05869
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Copyright (c) 2019 Farida Hanum Siregar
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