AI Literacy

What is AI Art?

AI art refers to any artistic work created with the assistance of artificial intelligence algorithms. These algorithms, often based on machine learning and neural networks, can generate, manipulate, or enhance images in ways that were previously impossible or highly labor-intensive.

AI art is typically created using generative AI. Here's an overview of the process:

1. Training: The AI model is trained on large datasets of existing artwork and images.
2. Prompting: A human provides a text description or prompt of the desired image.
3. Generation: The AI analyzes the prompt and uses its training to generate a new image that matches the description.
4. Refinement: The image can be iteratively refined through additional prompts or adjustments.

Use of Artificial intelligence generates questions about the future of art by PBS Newshour:

"Artificial intelligence is everywhere and part of our conversations about education, politics and social media. It's also a hot topic in the arts world as programs that generate art using AI are widely available to the public. But what goes into these programs, and the work that comes out, are heavily debated. Jeffrey Brown explores the influence of AI for our arts and culture series, CANVAS."

The controversy surrounding the training of AI art models centers on several key issues:

• Copyright and intellectual property: Many AI models are trained on vast datasets of existing artwork without explicit permission from the original artists. This raises questions about whether using these images for training constitutes copyright infringement.
• Lack of compensation: Artists whose work is used to train AI models generally don't receive compensation, even though their art contributes to the AI's capabilities.
• Consent and control: Artists often have no say in whether their work is included in training datasets, and no way to opt out if they object.
• Attribution and credit: When AI generates art inspired by or mimicking an artist's style, there's no clear mechanism for attributing or crediting the original artist's influence.
• Data scraping ethics: Many training datasets are created by scraping images from the internet, which raises questions about privacy and the ethics of using publicly available data for commercial purposes.
• Impact on the art market: There are concerns about how AI-generated art might affect the livelihoods of human artists and the overall art market.
• Bias and representation: The datasets used for training can perpetuate or amplify existing biases in art representation, potentially marginalizing certain groups or styles.

Who owns AI Art? By the Verge.

Attribution: Tulsa Community College Library

“AI Inputs and Outputs” by Creative Commons was made from details from two images generated by the DALL-E 2 AI platform with the text prompts “A Hieronymus Bosch triptych showing inputs to artificial intelligence as a Rube Goldberg machine; oil painting” and “a robot painting its own self portrait in the style of Artemisia Gentileschi.” CC dedicates any rights it holds to the image to the public domain via CC0.

Craiyon.com AI Prompt

Generative AI are artificial intelligence applications that generate content such as text or images. Text bots use natural language processing to generate responses to prompts. They are not search engines, but instead pull on a set of training data to create output. ChatGPT, DALL-E, and other Generative AI applications present higher education with new considerations for teaching and learning.

Generated AI art with the prompt "San Bernardino Valley College": 

Ponder:

• How accurate are these images? 
• Why are they so different? Why is one of a human and one image is blank?
• The text generated through AI text generators make the same inaccuracies AI image generators make, meaning users should be cautious of trusting outputs without fact-checking.

Attribution: Tulsa Community College Library