Ethical and Legal Challenges With Text-To-Image AI Software

Text-to-image AI software has rapidly progressed in recent years, allowing the generation of high-quality images from textual descriptions. While this technology has numerous practical applications, including in fields such as e-commerce, design, and gaming, it also raises a range of ethical and legal challenges.

One of the key ethical concerns with text-to-image AI software is the potential for misuse. For instance, the technology could be used to generate fake images for propaganda purposes or to manipulate public opinion. With the increasing sophistication of text-to-image AI software, it is becoming harder to differentiate between real and fake images, to the point where experts can not always tell the difference. This could lead to a loss of trust in visual media and ultimately undermine the credibility of news and other sources of information.

Another ethical challenge is the potential for text-to-image AI software to perpetuate biases and stereotypes. The quality of the generated images is heavily influenced by the training data used to train the algorithm, which often contains biases and prejudices. For instance, if the algorithm is trained on images of predominantly white, male faces, it may struggle to accurately generate images of people from other racial or gender groups. This could lead to the perpetuation of harmful stereotypes and discrimination.

At Eight Buffalo, we have discussed internally how all model checkpoints are biased in some way, depending on the data used to train them. In some cases, the bias is disturbing, such as a few model checkpoints that had no understanding of skin color other than white.

There are also several legal challenges associated with text-to-image AI software. One of the key issues is copyright infringement. If the generated image is based on copyrighted material, such as a photograph, the creator of the image may be liable for infringement. This could become particularly problematic if the generated image is used for commercial purposes, such as in advertising.

For creators, licensing will continue to be a problem. Applying, tracking, and enforcing licenses on datasets and model checkpoints is a huge challenge that needs to be addressed. Just like with open-source software, everyone borrows and learns from everyone else. As model checkpoints are used, merged, trained, and merged again, how will we track what licenses the original creator applied to it?

In addition, there are concerns around privacy and data protection. Text-to-image AI software typically requires large amounts of data to be trained effectively. If this data contains personal information, there is a risk that the generated images may reveal sensitive information about individuals. This could lead to violations of privacy and data protection laws.

At Eight Buffalo Media Group, we take these ethical and legal concerns seriously. We have set up our own ethical guidelines as AI software continues to mature:

1. Give credit where credit is due - If you use software, datasets, or model checkpoints, give credit and links to those projects/creators/individuals.
2. Do not use images without permission - Do NOT scrape the web and train models on images or people's faces without permission.
3. Do not knowingly violate licenses and copyrights - This is difficult with models and datasets, but taking a little time to check and read licenses when they are available is important. No one wants their work stolen.
4. Share creative works in appropriate forums - We all have different cultural and moral lines, and those should be respected. If we don't moderate ourselves, others will try to censor us, and no one wants that.
5. Respect individuals' privacy - Many of us at Eight Buffalo have experienced online trolls and attacks because they disagreed with our art, didn't like a comment, or disagreed with our politics. I started Eight Buffalo so we can have a safe place to share our creativity. Maintaining a level of professionalism and privacy makes us a stronger group.

In conclusion, while text-to-image AI software has enormous potential to revolutionize various fields, it also poses significant ethical and legal challenges. It is essential that developers and users of this technology carefully consider these issues and take appropriate measures to ensure that it is used responsibly and ethically. This may include developing ethical guidelines, conducting regular audits to ensure that the technology is not being misused, and seeking legal advice where necessary. By taking these steps, we can ensure that text-to-image AI software is used to benefit society in a responsible and ethical manner.