Shifting Boundary: Human and Artificial Intelligence
One of the most significant boundary shifts in recent years has been the blurring line between human and artificial intelligence, particularly in the realm of content creation and conversation.
What has changed:
In the past five years, there have been remarkable advancements in AI language models and generative AI. These technologies have begun to produce content – including text, images, and even code – that is increasingly difficult to distinguish from human-created work. An example of this is the development and public release of large language models like GPT-3 and the ones that have come after it. These AI’s can engage in human-like conversations, write coherent articles, create art, and even assist in coding tasks.
In 2022, an AI-generated artwork won a fine arts competition at the Colorado State Fair, sparking debates about the nature of creativity and authorship. This event highlighted how the boundary between human and AI-generated content is becoming increasingly blurred. You can read more about this specific incident in this article from The New York Times: “An A.I.-Generated Picture Won an Art Prize. Artists Aren’t Happy.” Another example is the use of AI in film and television production. In 2023, the film “The Creator” utilized AI to generate entire scenes and characters, pushing the boundaries of what’s possible in visual effects and storytelling. This represents a significant shift from traditional CGI and practical effects, again blurring the line between human and AI-generated content in cinema.
What has prompted this change?
There are several factors have contributed to this shift:
1. Advancements in machine learning algorithms: The development of more sophisticated neural networks and training techniques has allowed AI to process and generate more complex and nuanced content.
2. Increased computing power: The availability of more powerful hardware has enabled the training of larger, more capable AI models.
3. Investment from tech companies: Major corporations and startups have poured significant resources into AI research and development.
4. Public interest and engagement: As these technologies have become more accessible, there’s been increased public participation in using and testing them, leading to further refinement and development.
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