Ghosts in the Machine<\/strong><\/h2>\n\n\n\nThe apprehension isn\u2019t misplaced as artists find their work devalued<\/a> and we address the ethical questions of adding machine learning to our lives. To be clear there are many AI-related questions and shortcomings. <\/p>\n\n\n\nFor one, I don\u2019t dare to call AI art generation very accessible yet. While mobile image morphing apps are widespread, a full AI art generator takes more computing heft. Midjourney\u2019s cheapest unlimited plan is $30 per month and running Stable Diffusion at home<\/a> still requires a beefy computer. It\u2019s not accessible the way a pencil and paper are accessible\u2014yet. <\/p>\n\n\n\nThere are also more complex reasons to be concerned about participating in AI art. For one, AI is trained on vast sums of online data, which creates issues of consent. Creators have lamented the ability of AI to use their work without permission<\/a> to create new content. The risk to artists is palpably real. <\/p>\n\n\n\nAI is also susceptible to bias. Although it cannot act with intentionality and personal agency, it can reflect the biases of its creators. This is often seen when flawed training data<\/a> leads to biased creations. Shortcomings like these can complicate efforts to generate gender-affirming artwork from data that reflects cisnormative biases. Although frustrating, the user-driven and iterative learning sides of AI art makes it easier to rectify this imbalance over time.<\/p>\n\n\n\n![\"A](\"https:\/\/translash.org\/wp-content\/uploads\/2024\/04\/3-4tw5guw-1.jpg\")
A gender-affirming portrait created by Summer Tao with AI.<\/figcaption><\/figure>\n\n\n\nWhile I was learning to use these programs, there were hundreds of duds, sure. It made dogs with too many eyes or eyes in worrisome places. Trees blended into mountains in beautiful but unsettling ways. Don\u2019t get me started on what it did to human fingers. Despite these errors, there was magic in participating in artistic creation. I felt unburdened by scrutiny and failure when asking the AI box for pictures. <\/p>\n\n\n\n
However, one branch of AI artistry remains relatively unexplored: the potential for queer-affirming portraiture and visual art. <\/p>\n\n\n \n\n \n
For one, I don\u2019t dare to call AI art generation very accessible yet. While mobile image morphing apps are widespread, a full AI art generator takes more computing heft. Midjourney\u2019s cheapest unlimited plan is $30 per month and running Stable Diffusion at home<\/a> still requires a beefy computer. It\u2019s not accessible the way a pencil and paper are accessible\u2014yet. <\/p>\n\n\n\n There are also more complex reasons to be concerned about participating in AI art. For one, AI is trained on vast sums of online data, which creates issues of consent. Creators have lamented the ability of AI to use their work without permission<\/a> to create new content. The risk to artists is palpably real. <\/p>\n\n\n\n AI is also susceptible to bias. Although it cannot act with intentionality and personal agency, it can reflect the biases of its creators. This is often seen when flawed training data<\/a> leads to biased creations. Shortcomings like these can complicate efforts to generate gender-affirming artwork from data that reflects cisnormative biases. Although frustrating, the user-driven and iterative learning sides of AI art makes it easier to rectify this imbalance over time.<\/p>\n\n\n\n While I was learning to use these programs, there were hundreds of duds, sure. It made dogs with too many eyes or eyes in worrisome places. Trees blended into mountains in beautiful but unsettling ways. Don\u2019t get me started on what it did to human fingers. Despite these errors, there was magic in participating in artistic creation. I felt unburdened by scrutiny and failure when asking the AI box for pictures. <\/p>\n\n\n\n However, one branch of AI artistry remains relatively unexplored: the potential for queer-affirming portraiture and visual art. <\/p>\n\n\n