Redefining the digital age: the AI renaissance in human-computer interaction and decision-making
DOI:
https://doi.org/10.37497/rev.artif.intell.educ.v4i00.12Keywords:
AI Renaissance, artificial intelligence, information overload, human-computer interaction, decision-makingAbstract
Objective: This paper aims to explore the concept of AI as a modern-day Renaissance movement, triggered by the proliferation of the internet and advancements in artificial intelligence technologies. It delves into the transformative impact of AI on human-computer interactions and decision-making processes.
Results: O’Leary's (1997) early notion of a Renaissance movement sparked by the internet's ubiquity finds resonance in the emergence of the AI renaissance. AI technologies such as natural language processing, machine learning, heuristic language processing, and neural networks have integrated into intricate networked computing environments. These technologies facilitate the handling, retrieval, and analysis of vast amounts of data available on the World Wide Web. Given the overwhelming volume of data, direct human analysis has become impractical, necessitating AI-driven support for efficient data utilization. In today's competitive and tech-driven landscape, the time available for decision-making has diminished, prompting reliance on intelligent agents and delegating decision-making tasks to these digital surrogates.
Conclusions: The contemporary AI renaissance signifies a paradigm shift in human-computer dynamics. The convergence of AI technologies with the internet's vast information landscape has created a symbiotic relationship, redefining traditional computer roles. AI-enabled tools not only manage the deluge of data but also extend decision-making capabilities, optimizing efficiency in an increasingly fast-paced world. This transformative movement transcends conventional computing boundaries and has paved the way for a new era of human-machine interaction.
References
Kiayias, A., Russell, A., David, B., & Oliynykov, R. (2017). Ouroboros: A provably secure proof-of-stake blockchain protocol. In Proceedings of the 37th Annual International Cryptology Conference (CRYPTO '17) (pp. 357-388).
Bursell, S. E., Cavallerano, J. D., Cavallerano, A. A., Clermont, A. C., Birkmire-Peters, D., Aiello, L. P., ... & Aiello, L. M. (2001). Stereo nonmydriatic digital-video color retinal imaging compared with Early Treatment Diabetic Retinopathy Study seven standard field 35-mm stereo color photos for determining level of diabetic retinopathy. Ophthalmology, 108(8), 572-585. https://doi.org/10.1016/S0161-6420(01)00570-7
Chen, J., & Micali, S. (2016). Algorand: Scaling Byzantine agreements for cryptocurrencies. arXiv preprint arXiv:1607.01341. https://arxiv.org/abs/1607.01341
Chopra, R., Mulholland, P. J., Dubis, A. M., Anderson, R. S., & Keane, P. A. (2017). Human factor and usability testing of a binocular optical coherence tomography system. Translational Vision Science & Technology, 6(3), 16-20. https://doi.org/10.1167/tvst.6.3.16
O'Leary, D. E. (1997). The Internet, intranets, and the AI renaissance. Computer, 30(1), 71-78. https://doi.org/10.1109/2.562929
Kortuem, K., Fasler, K., Charnley, A., Khambati, H., Fasolo, S., & Katz, M. (2018). Implementation of medical retina virtual clinics in a tertiary eye care referral centre. British Journal of Ophthalmology, 102(7), 141-151. https://doi.org/10.1136/bjophthalmol-2017-310778
Kotecha, A., Brookes, J., & Foster, P. J. (2017). A technician-delivered ‘virtual clinic’ for triaging low-risk glaucoma referrals. Eye, 31(6), 899–905. https://doi.org/10.1038/eye.2016.306
Kozak, I., Payne, J. F., Schatz, P., Al-Kahtani, E., Winkler, M., & Bartsch, D.-U. (2017). Teleophthalmology image-based navigated retinal laser therapy for diabetic macular edema: a concept of retinal telephotocoagulation. Graefe's Archive for Clinical and Experimental Ophthalmology, 255(8), 1509–1513. https://doi.org/10.1007/s00417-017-3695-1
Joy, B. (2000, April). Why the future doesn’t need us. Wired. https://www.wired.com/2000/04/joy-2/
Lucignani, G., & Neri, E. (2019). Integration of imaging biomarkers into systems biomedicine: a renaissance for medical imaging. Clinical and Translational Imaging, 7(3), 149–153. https://doi.org/10.1007/s40336-019-00320-9
Luginbuhl, C. (2019). Future Renaissance [Master's thesis, OCAD University]. OCAD University Digital Repository.
Markoff, J. (2016). Machines of loving grace: The quest for common grounds between humans and robots. Harper Collins.
Parloff, R. (2016, September 28). Why deep learning is suddenly changing your life. Fortune. https://fortune.com/2016/09/28/ai-deep-machine-learning/
Peckham, M. (2016, April 7). What 7 of the world’s smartest people think about artificial intelligence. Time. https://time.com/4278790/smart-people-ai/
Pesapane, F., Codari, M., & Sardanelli, F. (2018). Artificial intelligence in medical imaging: threat or opportunity? Radiologists again at the forefront of innovation in medicine. European Radiology Experimental, 2(1), 35. https://doi.org/10.1186/s41747-018-0061-6
Petro, G. (2016, August 25). Amazon vs. Walmart: Clash of the Titans. Forbes. https://www.forbes.com/sites/gregpetro/2016/08/25/amazon-vs-walmart-clash-of-the-titans/
Rifkin, J. (2015, November 4). How developing nations can leapfrog developed countries with the sharing economy. The Huffington Post. https://www.huffpost.com/entry/developing-nations-sharing-economy_b_8419960
Nakamoto, S. (2008). Bitcoin: A peer-to-peer electronic cash system. https://bitcoin.org/bitcoin.pdf
Silva, P. S., Cavallerano, J. D., Tolls, D., Omar, A., Thakore, K., Patel, B., ... & Aiello, L. M. (2014). Potential efficiency benefits of nonmydriatic ultrawide field retinal imaging in an ocular telehealth diabetic retinopathy program. Diabetes Care, 37(1), 50–55. https://doi.org/10.2337/dc13-2030
Silver, D., Huang, A., Maddison, C. J., Guez, A., Sifre, L., Van Den Driessche, G., ... & Hassabis, D. (2016). Mastering the game of Go with deep neural networks and tree search. Nature, 529(7587), 484–489. https://doi.org/10.1038/nature16961
Tesauro, G. (1995). Temporal difference learning and TD-Gammon. Communications of the ACM, 38(3), 58–68. https://doi.org/10.1145/203330.203343
Van der Heijden, A. A., Abramoff, M. D., Verbraak, F., van Hecke, M. V., Liem, A., & Nijpels, G. (2018). Validation of automated screening for referable diabetic retinopathy with the IDx-DR device in the Hoorn Diabetes Care System. Acta Ophthalmologica, 96(1), 63–68. https://doi.org/10.1111/aos.13587
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