Artificial Intelligence in the Creative Industries: A Review
Nantheera Anantrasirichai, David Bull

TL;DR
This review explores AI's current applications and limitations in creative industries, emphasizing its role as a collaborative tool to augment human creativity rather than replace it.
Contribution
It categorizes AI applications in creative fields, critically examines their successes and limitations, and discusses future prospects for AI as a creative assistant.
Findings
AI is widely adopted as a collaborative creative tool.
Success of AI as an autonomous creator remains limited.
Human-centric AI enhances creativity more effectively.
Abstract
This paper reviews the current state of the art in Artificial Intelligence (AI) technologies and applications in the context of the creative industries. A brief background of AI, and specifically Machine Learning (ML) algorithms, is provided including Convolutional Neural Network (CNNs), Generative Adversarial Networks (GANs), Recurrent Neural Networks (RNNs) and Deep Reinforcement Learning (DRL). We categorise creative applications into five groups related to how AI technologies are used: i) content creation, ii) information analysis, iii) content enhancement and post production workflows, iv) information extraction and enhancement, and v) data compression. We critically examine the successes and limitations of this rapidly advancing technology in each of these areas. We further differentiate between the use of AI as a creative tool and its potential as a creator in its own right. We…
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