The survey first aims to acquire the profile of the artist, such as the medium they work in and their online presence or lack thereof. It then asks whether or not artists use any currently available protection on their art and why or why not. The survey was run over the period of a month, and received 39 responses.

Figure 1. shows the percentage of people who used available protective resources, 25.6%, compared to the percentage who did not, 69.2%. Alongside this, there were two AI users, accounting for the remaining 5.1%.

Figure 2. represents the protection methods chosen by artists who answered “Yes” on the previous figure. Some artists used multiple methods, however there were a total of 11 respondents. The majority of respondents used Glaze. Despite this, only 3 people utilized Nightshade, created by the same group as Glaze. Two artists rely on Cara, which is a portfolio sharing platform for artists that prohibits the sharing of AI-generated images. Similar to Artstation, Cara uses the “NoAI” tag that notifies AI scrapers to not scrape tagged images, but this system is built on the honor code, meaning that AI scrapers are able to use tagged images regardless. At last, a number of artists also chose to not upload their work, preventing any AI scrapers from reaching it in the first place.

Figure 3. represents the reasons listed for not using protective resources by artists who selected “No” in figure one. Some artists listed multiple reasons, however there were a total of 26 respondents. First of all, some artists do not know where to find protective resources. Others do not have the available income to afford protection. Some stated that they tried to use resources, but they caused technical difficulties: “I tried to use a protecting tool twice (I don't remember the name), but it crashed my computer and the artworks they put as examples didn't [have] noticeable changes, so I thought it didn't work well.” Other artists also saw a worsened image quality and differences within artworks. Another inconvenience is that it is another process in the step, with one respondent saying they would use these resources “if it was automatic on export from [Adobe] Lightroom.” 

Lastly, most answered in an indifferent fashion, whether that be apathy towards their works being used in AI or a pessimistic outlook on trying to defend themselves from AI, leading to non-action. Survey responses include “It is a futile effort. All information can and is accessed by someone with [the] ability to do so,” and “...there's a plethora of content they can scrape already, mine literally won't make a difference.” These indicate an idea of helplessness throughout artists dealing with generative AI, that their work is a drop in an ocean of other content. Contrasting this, another says  “I don't care if my art is used in training datasets.”

A few weeks ago, our school welcomed guest speaker Eric Hudson to give a presentation to the student body, regarding generative AI and education. Hudson detailed uses of AI that could be helpful, not harmful to students, and made sure people were "in the know" about how AI can be used as a tool. One of the ways he did that was by talking about what AI can and can't do. Hudson said that AI has flaws and that it should not be trusted above all else. Adding on, he gave sample scenarios where students can determine whether the use of AI was acceptable or not, such as a student using ChatGPT to grade their essay for them to see where they can improve versus a student using AI to create ideas for a project. After the presentation, Hudson had an open Q&A session, where I then asked a few questions about AI and artists.

Q: Do you think AI-generated art is ethical?

A: AI art is very iffy, as what it does is scraping the internet for art, which the artists don't usually give permission for it to be used. 

Q: Where would you draw the line for usage of AI art?

A: Again, it's a tough subject, because when you use AI, it's hard to say how much of the original idea still comes through. Art is always a tricky subject because artists develop their own style and method, and AI skips that process.

Q: What is the most ideal scenario for AI in the future?

A: In the most idyllic world, AI does tedious tasks for humans, while humans have the freedom to be creative instead of doing tedious jobs.

Recently, the US government put out an executive order, stating that the purpose is to regulate and manage the risks of AI while furthering research and development. This executive order lists many goals and standards for AI, for protecting security, privacy and equity. One other goal is being able to recognize when material is AI generated, using watermarks and labels. In the current era, AI generated images in particular are easily discernable to the human eye, due to a common style of art and errors that human artists wouldn't make. The same cannot be said completely for AI writings, as their only fallacy is being too advanced for the actual writer to write. In other words, AI writing is only detected because it is "too good".  Although methods of detecting AI exist prior to this, they are easily fooled and prone to falsely labeling material as AI generated. This acknowledgement of the dangers of AI demonstrates that they are taking action to protect citizens. However, while it lists many safeguards, many of them seem to be in development and quite vague when it comes down to the specifics of what they are doing. As an example, one statement is to "protect Americans from AI-enabled fraud and deception," by using "tools" developed by AI companies. The issue is that there are no specifics beyond that they will watermark AI content, with no information on how they will do this. This executive order mainly only answers what the government will do in response, not how they will do it.

This article, "How is Artificial Intelligence Changing Art History?" by Verity Babbs, covers the DALL-E 2 AI which generates images based off of a text prompt. This AI is fed many samples and can generate images in the styles of famous artists. However, one of the issues that comes with it is the dataset fed. This dataset consists of many biases, as the majority of famous artists in history have been white males, as well as an overabundance of very similar art styles like impressionism and surrealism. While some do not accept DALL-E 2's images as part of art history, others think it should be incorporated into the arts education curriculum. I feel that DALL-E 2 should be a part of art history, as a paradigm shift in how art is considered. A major debate in the arts world is whether or not AI is creating new art or merely trying to replicate art that has already been created. While the subjects may be different, AI only generates based off of other artists. 

This article, "Can machines do art history?", details both the aspects where machines succeed, and where they fail in analyzing art. This type of AI uses image processing software, and in particular, a CNN (convolutional neural network). This type of software isolates specific groups of pixels in the image together. When trained, the algorithm can then recognize patterns and brushstrokes, then attribute paintings and styles to artists. However, it has been said that these algorithms should not be used for attribution. Whether they should never be used or are only currently inadequate is left to be seen. Algorithms can also only analyze objectively and visually, without any other background knowledge. There is also the subject that much of the algorithm's process is unknown; we do not know how it is able to reach conclusions. I think that while AI will inevitably grow stronger at attribution and visual analysis, there is no way for it to perform analysis on the meaning of a painting. AI relies on the visual aspects of a painting, and analysis requires other context and knowledge that the visuals do not cover. There will be aspects it excels in, however, ultimately there will also be tasks it can't do.