Trans-AI/DS: transformative, transdisciplinary and translational artificial intelligence and data science

Longbing Cao

doi:10.1007/s41060-023-00383-y

Trans-AI/DS: transformative, transdisciplinary and translational artificial intelligence and data science

Longbing Cao^*

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

13 Citations (Scopus)

89 Downloads (Pure)

Abstract

After the many ups and downs over the past 70 years of AI and 50 years of data science (DS), AI/DS have migrated into their new age. This new-generation AI/DS build on the consilience and universology of science, technology and engineering. In particular, it synergizes AI and data science, inspiring Trans-AI/DS (i.e., Trans-AI, Trans-DS and their hybridization) thinking, vision, paradigms, approaches and practices. Trans-AI/DS feature their transformative (or transformational), transdisciplinary, and translational AI/DS in terms of thinking, paradigms, methodologies, technologies, engineering, and practices. Here, we discuss these important paradigm shifts and directions. Trans-AI/DS encourage big and outside-the-box thinking beyond the classic AI, data-driven, model-based, statistical, shallow and deep learning hypotheses, methodologies and developments. They pursue foundational and original AI/DS thinking, theories and practices from the essence of intelligences and complexities inherent in humans, nature, society, and their creations.

Original language	English
Pages (from-to)	119-132
Number of pages	14
Journal	International Journal of Data Science and Analytics
Volume	15
Issue number	2
DOIs	https://doi.org/10.1007/s41060-023-00383-y
Publication status	Published - Mar 2023
Externally published	Yes

Bibliographical note

Copyright the Author(s) 2023. Version archived for private and non-commercial use with the permission of the author/s and according to publisher conditions. For further rights please contact the publisher.

Keywords

Trans-AI
Trans-DS
Trans-AI/DS
Transformative AI
Transformative data science
Transdisciplinary AI
Transdisciplinary data science
Translational AI
Translational data science

Access to Document

10.1007/s41060-023-00383-yLicence: CC BY

Publisher version (open access)Final published version, 753 KBLicence: CC BY

Cite this

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title = "Trans-AI/DS: transformative, transdisciplinary and translational artificial intelligence and data science",

abstract = "After the many ups and downs over the past 70 years of AI and 50 years of data science (DS), AI/DS have migrated into their new age. This new-generation AI/DS build on the consilience and universology of science, technology and engineering. In particular, it synergizes AI and data science, inspiring Trans-AI/DS (i.e., Trans-AI, Trans-DS and their hybridization) thinking, vision, paradigms, approaches and practices. Trans-AI/DS feature their transformative (or transformational), transdisciplinary, and translational AI/DS in terms of thinking, paradigms, methodologies, technologies, engineering, and practices. Here, we discuss these important paradigm shifts and directions. Trans-AI/DS encourage big and outside-the-box thinking beyond the classic AI, data-driven, model-based, statistical, shallow and deep learning hypotheses, methodologies and developments. They pursue foundational and original AI/DS thinking, theories and practices from the essence of intelligences and complexities inherent in humans, nature, society, and their creations.",

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author = "Longbing Cao",

note = "Copyright the Author(s) 2023. Version archived for private and non-commercial use with the permission of the author/s and according to publisher conditions. For further rights please contact the publisher.",

year = "2023",

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doi = "10.1007/s41060-023-00383-y",

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N2 - After the many ups and downs over the past 70 years of AI and 50 years of data science (DS), AI/DS have migrated into their new age. This new-generation AI/DS build on the consilience and universology of science, technology and engineering. In particular, it synergizes AI and data science, inspiring Trans-AI/DS (i.e., Trans-AI, Trans-DS and their hybridization) thinking, vision, paradigms, approaches and practices. Trans-AI/DS feature their transformative (or transformational), transdisciplinary, and translational AI/DS in terms of thinking, paradigms, methodologies, technologies, engineering, and practices. Here, we discuss these important paradigm shifts and directions. Trans-AI/DS encourage big and outside-the-box thinking beyond the classic AI, data-driven, model-based, statistical, shallow and deep learning hypotheses, methodologies and developments. They pursue foundational and original AI/DS thinking, theories and practices from the essence of intelligences and complexities inherent in humans, nature, society, and their creations.

AB - After the many ups and downs over the past 70 years of AI and 50 years of data science (DS), AI/DS have migrated into their new age. This new-generation AI/DS build on the consilience and universology of science, technology and engineering. In particular, it synergizes AI and data science, inspiring Trans-AI/DS (i.e., Trans-AI, Trans-DS and their hybridization) thinking, vision, paradigms, approaches and practices. Trans-AI/DS feature their transformative (or transformational), transdisciplinary, and translational AI/DS in terms of thinking, paradigms, methodologies, technologies, engineering, and practices. Here, we discuss these important paradigm shifts and directions. Trans-AI/DS encourage big and outside-the-box thinking beyond the classic AI, data-driven, model-based, statistical, shallow and deep learning hypotheses, methodologies and developments. They pursue foundational and original AI/DS thinking, theories and practices from the essence of intelligences and complexities inherent in humans, nature, society, and their creations.

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KW - Translational AI

KW - Translational data science

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Trans-AI/DS: transformative, transdisciplinary and translational artificial intelligence and data science

Abstract

Bibliographical note

Keywords

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Other files and links

Fingerprint

Deep Interaction Learning in Unlabelled Big Data and Complex Systems (FT190100734)

Deep analytics of non-occurring but important behaviours (DP190101079)

Cite this

Trans-AI/DS: transformative, transdisciplinary and translational artificial intelligence and data science

Abstract

Bibliographical note

Keywords

Access to Document

Other files and links

Fingerprint

Projects

Deep Interaction Learning in Unlabelled Big Data and Complex Systems (FT190100734)

Deep analytics of non-occurring but important behaviours (DP190101079)

Cite this