From the digital data revolution to digital health and digital economy toward a digital society: Pervasiveness of Artificial Intelligence
Frank Emmert-Streib

TL;DR
This paper discusses how artificial intelligence, especially deep learning and natural language processing, is transforming digital data analysis, management, and interpretation across various sectors, shaping a digital society with new opportunities and challenges.
Contribution
It provides a comprehensive perspective on AI's role in digital data revolution, highlighting recent technological advances and potential societal issues.
Findings
Deep learning enhances data analysis efficiency.
Natural language processing enables large-scale text data processing.
AI's integration presents new societal challenges.
Abstract
Technological progress has led to powerful computers and communication technologies that penetrate nowadays all areas of science, industry and our private lives. As a consequence, all these areas are generating digital traces of data amounting to big data resources. This opens unprecedented opportunities but also challenges toward the analysis, management, interpretation and utilization of these data. Fortunately, recent breakthroughs in deep learning algorithms complement now machine learning and statistics methods for an efficient analysis of such data. Furthermore, advances in text mining and natural language processing, e.g., word-embedding methods, enable also the processing of large amounts of text data from diverse sources as governmental reports, blog entries in social media or clinical health records of patients. In this paper, we present a perspective on the role of artificial…
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Taxonomy
TopicsData Quality and Management · Artificial Intelligence in Healthcare · Topic Modeling
