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Practice paper

Emanating confluence: The symbiotic relationship between artificial intelligence and data

Ted W. Gross
Applied Marketing Analytics: The Peer-Reviewed Journal, 7 (2), 169-195 (2021)
https://doi.org/10.69554/AITR7051

Abstract

This paper seeks to explain significant constructs within artificial intelligence (AI), including but not limited to: the impact of ‘information theory’; entropy, especially in terms of ‘information entropy’; and language theory (linguistics), dealing with all communication methods and the ‘meaning’ in that communication. The paper discusses the progression from ‘chaos theory’ to ‘complexity theory’ to ‘emergence’ and finally the ‘technological singularity’. It examines such questions as: How do chaos and complexity lead to emergent systems which will inevitably lead to a technological singularity? How does the endless loop of AI progress as it emanates outward, comes to confluence, and emanates yet again? What does each phase entail? How does our advance towards exponential growth in data affect the progression of AI? What are the dangers of ‘bias’? What are the risks as we move towards emergence? Finally, why must we exercise extreme caution as we come closer to the technological singularity?

Keywords: artificial intelligence; entropy; chaos; complexity; emergence; singularity; superintelligence

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Author's Biography

Ted W. Gross is a futurist and theorist who has worked in the high-tech industry for many years as a chief technology officer and vice president of research and development. Ted believes there is a hidden order within chaos, and that complexity arises from simple models and concepts. His work on technology theory and application has been published in various professional technology journals.

Citation

Gross, Ted W. (2021, September 1). Emanating confluence: The symbiotic relationship between artificial intelligence and data. In the Applied Marketing Analytics: The Peer-Reviewed Journal, Volume 7, Issue 2. https://doi.org/10.69554/AITR7051.

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cover image, Applied Marketing Analytics: The Peer-Reviewed Journal
Applied Marketing Analytics: The Peer-Reviewed Journal
Volume 7 / Issue 2
© Henry Stewart
Publications LLP

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