Trans-AI/DS: transformative, transdisciplinary and translational artificial intelligence and data science
Longbing Cao
Abstract
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.