AI: Difference between revisions
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[[AI]] art is a subject of ongoing debate, particularly regarding its capacity for originality. Critics argue that [[AI]]-generated content is inherently derivative, as it relies on pre-existing data to produce output. This perspective is rooted in the notion that [[AI]] systems cannot generate truly original ideas without being "seeded" with prior information. However, this view is contested by some, who claim that human creativity is similarly constrained, asserting that many individuals struggle to produce novel concepts without prior exposure to ideas or training. |
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Art created by AI is derivative. It cannot produce original content. If it could then it could produce content without being seeded, but it can't. |
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This argument, however, has been criticized as a non sequitur. By definition, human artists capable of producing original art *can* generate new ideas, even if such creativity is rare. Similarly, the claim that humans require learning to create art is challenged by the existence of blind individuals who have produced visual artwork without ever having seen visual art. This underscores a key distinction: while [[AI]] systems depend on external data to generate output, humans may draw on innate abilities or alternative forms of learning. |
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Some people counter that most humans, they assert, can't come up with original ideas. |
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[[https://en.wikipedia.org/wiki/E%C5%9Fref_Arma%C4%9Fan]] |
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This argument is non-sequitar. By definition, the humans producing original art *can* come up with new ideas |
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The term "[[AI]]" encompasses a wide range of meanings and applications, reflecting its evolving role in society. Discussions about [[AI]]'s impact on employment often intersect with broader debates about automation and economic transformation. For instance, some studies suggest that [[AI]] and automation may disproportionately affect jobs held by women, though the extent of this impact remains contested. |
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Some may argue that humans can't produce original content without learning language or how to use their hands but this argue is specious. The learning involved is different. AIs must be fed with content before they can produce output. Humans can produce visual artwork without ever having seen visual artwork. We know this because blind people have produced visual artwork. |
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[[https://www.bloomberg.com/news/articles/2023-05-26/[[AI]]-threatened-jobs-are-mostly-held-by-women-study-shows]] |
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Wide range of meanings of AI. |
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A recurring argument is that if [[AI]] were to replace a significant portion of jobs, this would manifest in reduced working hours rather than increased labor demands. However, historical trends show that unemployment rates have fluctuated while overtime hours have generally increased over recent decades. This complicates predictions about [[AI]]'s role in labor markets, as the relationship between technological advancement and employment is far from straightforward. |
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{{AI}} |
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{{Draft}} |
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[[https://www.abc.net.au/news/2025-05-28/productivity-commission-growth-report/105336036]] |
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Proponents of [[AI]] often emphasize its potential to enhance productivity, but skeptics caution that intelligence—whether artificial or human—is not devoid of challenges. Issues such as procrastination, mental health struggles, and even anxiety may be inherent to advanced intelligence. This raises questions about whether truly "superintelligent" systems can be developed without encountering significant limitations. |
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[[https://www.news.com.au/finance/work/youre-a-peasant-exgoogle-executive-exposes-grim-[[AI]]-reality/news-story/c861d146b38e26dcd96be505c082e2cb]] |
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The discourse surrounding [[AI]]'s economic impact often involves tensions between technical experts and economists. While engineers may focus on [[AI]]'s capabilities, economists are better positioned to assess its broader social and economic consequences. Claims about [[AI]]-driven mass unemployment are frequently criticized as misapplications of expertise, diverging from established economic theories such as the Luddite fallacy. |
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[[https://boards.straightdope.com/t/is-artificial-intelligence-[[AI]]-plagiarizing/994299/21]] |
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[[https://metr.org/blog/2025-07-10-early-2025-[[AI]]-experienced-os-dev-study/]] |
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[[https://dianne.skoll.ca/writings/[[AI]]-is-bad/]] |
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{{Bias}} |
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[[https://www.sciencedirect.com/science/article/pii/S2451958824001660]] |
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[[https://archive.is/wip/JcqZI]] |
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{{Ollama}} |
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{{Pending Human Review}} |
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Latest revision as of 04:27, 21 October 2026
AI art is a subject of ongoing debate, particularly regarding its capacity for originality. Critics argue that AI-generated content is inherently derivative, as it relies on pre-existing data to produce output. This perspective is rooted in the notion that AI systems cannot generate truly original ideas without being "seeded" with prior information. However, this view is contested by some, who claim that human creativity is similarly constrained, asserting that many individuals struggle to produce novel concepts without prior exposure to ideas or training.
This argument, however, has been criticized as a non sequitur. By definition, human artists capable of producing original art *can* generate new ideas, even if such creativity is rare. Similarly, the claim that humans require learning to create art is challenged by the existence of blind individuals who have produced visual artwork without ever having seen visual art. This underscores a key distinction: while AI systems depend on external data to generate output, humans may draw on innate abilities or alternative forms of learning.
[[1]]
The term "AI" encompasses a wide range of meanings and applications, reflecting its evolving role in society. Discussions about AI's impact on employment often intersect with broader debates about automation and economic transformation. For instance, some studies suggest that AI and automation may disproportionately affect jobs held by women, though the extent of this impact remains contested.
[AI-threatened-jobs-are-mostly-held-by-women-study-shows]
A recurring argument is that if AI were to replace a significant portion of jobs, this would manifest in reduced working hours rather than increased labor demands. However, historical trends show that unemployment rates have fluctuated while overtime hours have generally increased over recent decades. This complicates predictions about AI's role in labor markets, as the relationship between technological advancement and employment is far from straightforward.
[[2]]
Proponents of AI often emphasize its potential to enhance productivity, but skeptics caution that intelligence—whether artificial or human—is not devoid of challenges. Issues such as procrastination, mental health struggles, and even anxiety may be inherent to advanced intelligence. This raises questions about whether truly "superintelligent" systems can be developed without encountering significant limitations.
[AI-reality/news-story/c861d146b38e26dcd96be505c082e2cb]
The discourse surrounding AI's economic impact often involves tensions between technical experts and economists. While engineers may focus on AI's capabilities, economists are better positioned to assess its broader social and economic consequences. Claims about AI-driven mass unemployment are frequently criticized as misapplications of expertise, diverging from established economic theories such as the Luddite fallacy.
[AI-plagiarizing/994299/21]
[AI-experienced-os-dev-study/]
[AI-is-bad/]
[[3]]
[[4]]
This page contains information generated by Ollama. The information was reviewed, and may have been altered, by a human editor before being added to the Featured category. As of July 2026 information generated by AI is not subject to copyright and is thus in the public domain. This page is pending human review.