![]() For example, when photography was invented, some painters said it was “the end of art.” But instead it ended up being its own medium and eventually liberated painting from realism, giving rise to Impressionism and the modern art movement. With aesthetics and culture, we’re considering how past art technologies can inform how we think about AI. For each of those we highlight the big open questions. How do we talk about AI and how do these narratives cut along lines of power? As we outline in the article, there are these themes around AI’s impact that are important to consider: aesthetics and culture legal aspects of ownership and credit labor and the impacts to the media ecosystem. We need to understand how perceptions of the generative process affect attitudes toward outputs and authors, and also design the interfaces and systems in a way that is really transparent about the generative process and avoids some of these misleading interpretations. Q: What do you see as the gaps in research around generative AI and art today?Ī: The way we talk about AI is broken in many ways. We’re trying to build coalitions across academia and beyond to help think about the interdisciplinary connections and research areas necessary to grapple with the immediate dangers to humans coming from the deployment of these tools, such as disinformation, job displacement, and changes to legal structures and culture. Even the term “artificial intelligence” reinforces these beliefs: ChatGPT uses first-person pronouns, and we say AIs “hallucinate.” These agentic roles we give AIs can undermine the credit to creators whose labor underlies the system’s outputs, and can deflect responsibility from the developers and decision makers when the systems cause harm. Many discussions about AI anthropomorphize the technology, implicitly suggesting these systems exhibit human-like intent, agency, or self-awareness. The complexity of black-box AI systems can make it hard for researchers and the broader public to understand what’s happening under the hood, and what the impacts of these tools on society will be. Are we going to get automated out of jobs? How are we going to preserve the human aspect of creativity with all of these new technologies? This raises a lot of fundamental questions about the creative process and the human’s role in creative production. MIT News spoke with Epstein, the lead author of the paper.Ī: Generative AI tools are doing things that even a few years ago we never thought would be possible. The paper’s MIT-affiliated co-authors include Media Lab postdoc Ziv Epstein SM ’19, PhD ’23 Matt Groh SM ’19, PhD ’23 PhD students Rob Mahari ’17 and Hope Schroeder and Professor Alex "Sandy" Pentland. Today a group of 14 researchers from a number of organizations including MIT published a commentary article in Science that helps set the stage for discussions about generative AI’s immediate impact on creative work and society more broadly. Popular generative AIs like the chatbot ChatGPT generate conversational text based on training data taken from the internet. One such technology is generative AI, which can create content including text, images, audio, and video. ![]() ![]() But speculation about where AI technology is going, while important, can also drown out important conversations about how we should be handling the AI technologies available today. The rapid advance of artificial intelligence has generated a lot of buzz, with some predicting it will lead to an idyllic utopia and others warning it will bring the end of humanity.
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