[Paper Review] AI and the creative realm: A short review of current and future applications

Fabio Crimaldi, Manuele Leonelli|arXiv (Cornell University)|Jun 1, 2023

Aesthetic Perception and Analysis8 citations

TL;DR

The paper surveys how AI is entering the creative domain, offering classifications of AI types, arts applications, programming tools, and algorithms, while addressing philosophical and ethical considerations.

ABSTRACT

This study explores the concept of creativity and artificial intelligence (AI) and their recent integration. While AI has traditionally been perceived as incapable of generating new ideas or creating art, the development of more sophisticated AI models and the proliferation of human-computer interaction tools have opened up new possibilities for AI in artistic creation. This study investigates the various applications of AI in a creative context, differentiating between the type of art, language, and algorithms used. It also considers the philosophical implications of AI and creativity, questioning whether consciousness can be researched in machines and AI's potential interests and decision-making capabilities. Overall, we aim to stimulate a reflection on AI's use and ethical implications in creative contexts.

Motivation & Objective

• Motivate exploration of AI involvement in creative contexts and its ethical implications.
• Differentiate AI categories (weak vs. strong) and discuss their relevance to art.
• Identify current artistic domains where AI is impactful and outline future directions and gaps.
• Examine programming languages and algorithms commonly used in AI-assisted arts.

Proposed method

• Provide novel categorizations of current AI uses in the arts.
• Review the two AI paradigms (weak vs. strong) and their implications for creativity.
• Summarize major art forms (images, text, music, sculpture, video) and table-like achievements/futures.
• Present programming languages and their pros/cons for creative AI projects.
• Outline algorithms with strengths/weaknesses in creative contexts.
• Discuss philosophical questions about AI consciousness, artistic sensibility, and autonomy.

Experimental results

Research questions

• RQ1 What are the current and potential future applications of AI in various art forms?
• RQ2 How do weak and strong AI differ in their capacity to participate in artistic creation, and what are the implications for creativity and authorship?
• RQ3 What programming languages and algorithms dominate AI-driven art, and what are their trade-offs?
• RQ4 What philosophical and ethical considerations arise regarding AI, creativity, consciousness, and autonomy?

Key findings

• AI tools enable generative capabilities across images, text, music, sculpture, and video.
• Weak AI dominates current creative AI applications, while strong AI remains theoretical.
• Programming languages like Python are prevalent for creative AI, with Java, C++, and Lisp also used.
• Common algorithms include neural networks, genetic algorithms, and decision trees, each with distinct pros and cons for art tasks.
• There is evidence of audience engagement with AI-generated art, but debates persist about originality, intentionality, and authorship.
• Future AI in creativity is expected to grow rapidly, with concerns about bias, autonomy, and the boundaries of machine-based creativity.