Canva’s text-to-image tool is the latest example of the technology hitting mainstream apps. Image: Canva
The feature is only the latest example of text-to-image AI tools reaching ever larger audiences. The launch of Stable Diffusion in particular has accelerated access to these systems, as its open-source implementation allows companies to integrate it into their own products for free. Text-to-image is quickly becoming a staple in creative platforms, and just last month, Microsoft launched its own text-to-image tool, Microsoft Designer, (powered by OpenAI’s DALL-E system) as part of its Office suite.
GitHub Copilot, which was launched in June, suggests code and functions to GitHub users in real time. Copilot is powered by Codex, an AI system that was created by OpenAI and licensed to Microsoft. According to OpenAI, Codex was trained on “millions of public repositories” and is “an instance of transformative fair use.” However, open-source programmers on GitHub disagree, claiming that Codex has violated their open-source licenses, which only allow non-commercial redistribution and modification of the code and often have restrictions including a requirement to preserve the name of the authors.
There’s a similar problem in artificial intelligence: The people who develop AI are increasingly having problems explaining how it works and determining why it has the outputs it has. Deep neural networks (DNN)—made up of layers and layers of processing systems trained on human-created data to mimic the neural networks of our brains—often seem to mirror not just human intelligence but also human inexplicability.
Shutterstock is well aware of the ethical concerns. In its announcement, the company said it plans on launching a fund to compensate artists who contributed to any AI art generation through the DALL-E 2 integration. This includes paying artists royalties when the AI-generated art they helped inspire is used.
“innovate_rye isn’t alone. Since OpenAI unveiled the latest application programming interface (API) for its widely-used language model, GPT-3, more students have begun feeding written prompts into OpenAI’s Playground and similar programs that use deep learning to generate text. The results continue the initial prompt in a natural-sounding way, and often can’t be distinguished from human-written text.”
“Assuming Dance Diffusion one day reaches the point where it can generate coherent whole songs, it seems inevitable that major ethical and legal issues will come to the fore. They already have, albeit around simpler AI systems. In 2020, Jay-Z ‘s record label filed copyright strikes against a YouTube channel, Vocal Synthesis, for using AI to create Jay-Z covers of songs like Billy Joel’s “We Didn’t Start the Fire.” After initially removing the videos, YouTube reinstated them, finding the takedown requests were “incomplete.” But deepfaked music still stands on murky legal ground.”
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