Summary of Ethics and Technical Aspects Of Generative Ai Models in Digital Content Creation, by Atahan Karagoz
Ethics and Technical Aspects of Generative AI Models in Digital Content Creation
by Atahan Karagoz
First submitted to arxiv on: 20 Dec 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: Computers and Society (cs.CY); Human-Computer Interaction (cs.HC); Machine Learning (cs.LG)
GrooveSquid.com Paper Summaries
GrooveSquid.com’s goal is to make artificial intelligence research accessible by summarizing AI papers in simpler terms. Each summary below covers the same AI paper, written at different levels of difficulty. The medium difficulty and low difficulty versions are original summaries written by GrooveSquid.com, while the high difficulty version is the paper’s original abstract. Feel free to learn from the version that suits you best!
| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary Medium Difficulty summary: The paper explores the capabilities and challenges of generative AI models like GPT-4o and DALL-E 3 in creative workflows. These models demonstrate impressive creativity, diversity, and technical precision, but raise significant ethical concerns. This study evaluates their performance on metrics such as creativity, diversity, accuracy, and computational efficiency, while also assessing the ethical risks they present, including bias, authenticity, and potential misuse. The findings reveal that generative models often reflect biases from their training data and carry ethical vulnerabilities that require careful oversight. To address this, the research proposes ethical guidelines for responsible AI integration into industry practices, striking a balance between innovation and ethical integrity. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Low Difficulty summary: This paper looks at special computer programs called GPT-4o and DALL-E 3 that can create new text and images on their own. These programs are very good at making things that look like they were written or drawn by humans, but they also raise important questions about fairness, honesty, and how we use them. The researchers tested these programs to see how well they do, what kind of problems they might cause, and how we can make sure they’re used in a way that’s good for everyone. |
Keywords
» Artificial intelligence » Gpt » Precision
