Trends in AI from Red and Blue Team Perspectives: Synthetic Data in a Data-Driven Society vs Sentiment Analysis
Trends in AI from Red and Blue Team Perspectives: Synthetic Data in a Data-Driven Society vs Sentiment Analysis

Author(s): Gundars Bergmanis-Korats, Alec Winshel, James Ostrowski, Kevin Zerussen, Omar Ali, Anastasija Cuikina, Alexander Gegov, Djamila Ouelhadj
Subject(s): Media studies, Security and defense, Social Informatics, ICT Information and Communications Technologies
Published by: NATO Strategic Communications Centre of Excellence
Keywords: AI; Data-driven society; synthetic data; deepfakes; malicious and harmful data; NATO; Toxic language; microaggression; dependency parsing;
Summary/Abstract: In today’s world, much of what we do, from exercising to texting, is measured and tracked. This data is constantly harvested by data brokers and social media to create behavioural profiles, later used by artificial intelligence (AI) powered services. The overwhelming abundance of data has ushered in an age of analytics, and the rise of AI has enabled big-data decision making. However, the training of AI models is often challenging due to a supervised training strategy that requires a large amount of labelled data. Synthetic data is a possible solution to various challenges, including data labelling and, more importantly, data privacy problems. Synthetic data can be generated by using advances in rendering pipelines, generative adversarial models, and fusion models. It is predicted that most online-generated content will be AI created.

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