Artificial intelligence: Difference between revisions

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'''Artificial intelligence''' (AI) is a field of computer science that produces systems designed to solve problems that humans typically solve using intelligence. In the consumer and industry space, it is commonly referred to as chatbots or [[wikipedia:Large language model|large language models]] (LLMs), which have been a main focus of industry

'''Artificial intelligence''' (AI) is a field of computer science that produces systems designed to solve problems that humans typically solve using intelligence. In the consumer and industry space, it is commonly referred to as chatbots or [[wikipedia:Large language model|large language models]] (LLMs), which have been a main focus of industry since the November 2022 launch of [[OpenAI]]'s [[ChatGPT]], with tens of billions of dollars in funding allocated to producing more popular LLMs. This is also a significant focus on [[wikipedia:Text-to-image model|text-to-image models]], which "draw" an image using a written prompt, and less commonly, [[wikipedia:Text-to-video model|text-to-video models]], which extend the text-to-image concept across several smooth video frames.

since the November 2022 launch of [[ChatGPT]], with tens of billions of dollars in funding allocated to producing more popular LLMs. ~~Also,~~ a significant focus is on [[wikipedia:Text-to-image model|text-to-image models]], which "draw" an image using a written prompt, and less commonly, [[wikipedia:Text-to-video model|text-to-video models]], which extend the text-to-image concept across several smooth video frames.

~~So far, no AI solutions are intelligent.~~ AI is not a new concept; it has been of interest since the 1950s. AI is a catch-all term~~; it encompasses~~ many areas and techniques~~, so merely stating that something uses AI tells us little about it~~.

AI is not a new concept; it has been of interest since the 1950s. AI is a catch-all term, encompassing many areas and techniques.

[[wikipedia:Generative artificial intelligence|Generative artificial intelligence]] models are trained through vast amounts of existing human-generated content. ~~Using the example of an LLM, by gathering~~ statistics on patterns ~~of words that people use~~, the model ~~can~~ generate sequences of words that seem similar to what a person might have written. LLM does not understand anything; they cannot reason. ~~Everything they~~ generate ~~is just a~~ randomly modulated pattern of tokens. ~~People reading sequences of tokens sometimes perceive things~~ they ~~think are true. Sequences that do not make sense~~ to ~~the reader, or that are false, are called [[wikipedia:Hallucination (artificial intelligence)|hallucinations]]~~. LLMs are typically trained to produce output that is pleasing to people, exhibiting [[dark patterns]]. For example, they often produce output which seems confidently written, use patterns which praise the user (sycophancy), and employ emotionally manipulative language.

[[wikipedia:Generative artificial intelligence|Generative artificial intelligence]] models are trained through vast amounts of existing human-generated content. LLMs gather statistics on word patterns, which allows the model to generate sequences of words that seem similar to what a person might have written. However, an LLM does not understand anything; they cannot reason. They generate randomly modulated pattern of tokens. In this way, they function similarly to autocomplete.

~~LLMs~~ are ~~a glorified autocomplete~~. ~~People~~ are ~~accustomed~~ to ~~interacting with others, and many overestimate the abilities of things~~ that ~~exhibit complex~~, ~~person-like~~ patterns. ~~Promoters of “AI” systems take advantage of this tendency~~, ~~using suggestive names~~ (~~like “reasoning” and “learning”~~) and ~~grand claims (“PHD level”), which make it harder for people to understand these systems~~.

People reading sequences of tokens sometimes perceive things they think are true. Sequences that do not make sense to the reader, or that are false, are called [[wikipedia:Hallucination (artificial intelligence)|hallucinations]]. LLMs are typically trained to produce output that is pleasing to people, exhibiting [[Dark pattern|dark patterns]]. For example, they produce output which seems confidently written, use patterns which praise the user (sycophancy), and employ emotionally manipulative language.

~~From November 2022~~ to ~~2025~~, ~~venture capitalists~~ and ~~companies invested hundreds~~ of ~~billions of dollars into AI but received minimal returns. When companies seek returns, consumers can expect~~ that ~~products may be orphaned~~, ~~services may be reduced, customer data may be sold or repurposed, costs may rise, and companies may reduce staff or fail~~. ~~Historically, AI has had brief periods~~ of ~~intense hype~~, ~~followed by disillusionment~~, ~~and “AI winters~~.”

People are accustomed to interacting with others, and many overestimate the abilities of things that exhibit complex, person-like patterns. Promoters of “AI” systems take advantage of this tendency, using suggestive names (like “reasoning” and “learning”) and grand claims (“PhD level”), which make it harder for people to understand these systems.

The current well-funded industry of artificial intelligence tools has led to the rampant and unethical use of content. Startups aiming to develop AI services have been rapidly scraping the internet for content to train future models, and members of the field are concerned that they are approaching the limit of publicly available content to train from.<ref>{{Cite web |last=Tremayne-Pengelly |first=Alexandra |date=16 Dec 2024 |title=Ilya Sutskever Warns A.I. Is Running Out of Data—Here’s What Will Happen Next |url=https://observer.com/2024/12/openai-cofounder-ilya-sutskever-ai-data-peak/ |website=Observer}}</ref>

From November 2022 to 2025, venture capitalists and companies invested hundreds of billions of dollars into AI but received minimal returns. When companies seek returns, consumers can expect that products may be orphaned, services may be reduced, customer data may be sold or repurposed, costs may rise, and companies may reduce staff or fail. Historically, AI has had brief periods of intense hype, followed by disillusionment, and “AI winters.”[<nowiki/>[[Consumer Rights Wiki:Verifiability|citation needed]]]

The current well-funded industry of artificial intelligence tools has led to the rampant and unethical use of content. Startups aiming to develop AI services have been rapidly scraping the internet for content to train future models, and members of the field are concerned that they are approaching the limit of publicly available content to train from.<ref>{{Cite web |last=Tremayne-Pengelly |first=Alexandra |date=16 Dec 2024 |title=Ilya Sutskever Warns A.I. Is Running Out of Data—Here’s What Will Happen Next |url=https://observer.com/2024/12/openai-cofounder-ilya-sutskever-ai-data-peak/ |website=Observer |url-status=live |archive-url=http://web.archive.org/web/20251126053705/https://observer.com/2024/12/openai-cofounder-ilya-sutskever-ai-data-peak/ |archive-date=26 Nov 2025}}</ref>

==Why is it a problem==

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:Further reading: [[Artificial intelligence/training]]

Users' work is sometimes silently ~~trained~~ without their explicit consent, as was the case for [[Adobe's AI policy]].

Users' work is sometimes silently used in training without their explicit consent, as was the case for [[Adobe's AI policy]].

===Privacy concerns of AI===

AI can be and has been used to generate deepfakes of people with and without their consent. Deepfakes are media generated with the likeness of an individual. Deepfake media can range from harmless to harmful. The latter includes child pornography, revenge porn, blackmail, etc. Since the rampant rise of consumer AI, deepfakes have become even more prevalent, with some websites explicitly specializing in them.[<nowiki/>[[Consumer Rights Wiki:Verifiability|citation needed]]]

===Privacy concerns of online AI models===

There are several concerns with using online AI models like [[ChatGPT]] ~~([[OpenAI]])~~, not only because they are proprietary, but also because there is no guarantee of where your data will be stored or used. Recent developments in local AI models offer an alternative to online AI models, ~~as they~~ can be ~~used offline once~~ downloaded from platforms like [https://huggingface.co/ HuggingFace]. Common models to run include Llama ([[Meta]]), DeepSeek ([[DeepSeek]]), Phi ([[Microsoft]]), Mistral ([[Mistral AI]]), Gemma ([[Google]]).

There are several concerns with using online AI models like [[ChatGPT]], not only because they are proprietary, but also because there is no guarantee of where your data will be stored or used. Recent developments in local AI models offer an alternative to online AI models, which can be downloaded from platforms like [https://huggingface.co/ HuggingFace] and used offline. Common models to run include Llama ([[Meta]]), DeepSeek ([[DeepSeek]]), Phi ([[Microsoft]]), Mistral ([[Mistral AI]]), Gemma ([[Google]]).

In some cases, AI models can be hijacked for malicious purposes. Demonstrated with Comet ([[Perplexity]]), users can run arbitrary prompts to the browser's built-in AI assistant by hiding text in the HTML comments, non-visible webpage text, or simple comments on a webpage.<ref name=":0">{{Cite web |date=Aug 20, 2025 |title=Tweet from Brave |url=https://nitter.us.catsarch.com/brave/status/1958152314914508893 |url-status=live |archive-url=https://web.archive.org/web/20260321120531/https://nitter.us.catsarch.com/brave/status/1958152314914508893 |archive-date=21 Mar 2026 |access-date=Aug 24, 2025 |website=X (formerly [[Twitter]])}}</ref> These arbitrary prompts can then be exploited to obtain sensitive information or gain unauthorized access to high-value accounts, such as those for banking or gaming libraries.<ref>{{Cite web |date=Aug 23, 2025 |title=Tweet from zack (in SF) |url=https://nitter.us.catsarch.com/zack_overflow/status/1959308058200551721 |url-status=live |archive-url=https://web.archive.org/web/20260321120841/https://nitter.us.catsarch.com/zack_overflow/status/1959308058200551721 |archive-date=21 Mar 2026 |access-date=Aug 24, 2025 |website=X (formerly [[Twitter]])}}</ref> See [[wikipedia:Prompt_injection|Prompt injection]].

===Unethical maintenance of data centers===

Due to heavy investments into and increased use of generative AI and LLMs, many data centers have been constructed to host LLMs. These data centers consume large amounts of power and water, in order to power and cool the computer systems running the models. Residents that live in cities where AI data centers have been constructed have complained of an increase in their electricity bills despite no change in their personal usage.[<nowiki/>[[Consumer Rights Wiki:Verifiability|citation needed]]] According to a research video by Benn Jordan, these data centers (as well as fracking operations and natural occurrences) cause a high amount of sound pollution, which can cause various symptoms.<ref> https://www.youtube.com/watch?v=_bP80DEAbuo ([https://preservetube.com/watch?v=_bP80DEAbuo Archived])</ref>

~~In some cases, these~~ AI ~~models can also be hijacked for malicious purposes. Demonstrated from the usage of Comet ([[Perplexity]]), users can run arbitrary prompts~~ to the ~~browser's built-in~~ AI ~~assistant via hiding text in~~ the ~~HTML comments, non-visible webpage text, or simple comments on a webpage~~.~~<ref>{{Cite web |date=Aug 20~~, ~~2025 |title=Tweet from Brave |url=https://xcancel~~.~~com/brave/status/1958152314914508893#m |access-date=Aug 24, 2025 |website=X (formerly [[Twitter]])}}</ref> These arbitrary prompts can then be exploited~~ to ~~hijack sensitive information, or worse, gain unauthorized access~~ to ~~high-value accounts~~, ~~such as those for banking or gaming libraries~~.<ref>~~{{Cite web |date=Aug 23, 2025 |title=Tweet from zack (in SF) |url=~~https://~~xcancel~~.com/~~zack_overflow~~/~~status/1959308058200551721 |access-date=Aug 24, 2025 |website=X (formerly [[Twitter]])}}~~</ref>

=== Hidden directives ===

Most AI apps include an initial "root"/"system" prompt given to the AI, which is hidden from the user. Some corporations go to great lengths to keep those prompts hidden, and to avoid leaking it to the user. Some projects attempt to bring back transparency to these tools, in spite of the restrictions.<ref>https://github.com/elder-plinius/CL4R1T4S</ref>

==Further reading==

*[[Dark pattern]]

*[[Automatic content recognition]]

*[[Palantir]]

*[[Meta]]

==External links==

*[[Yandex]]

*[[TikTok and AI-powered ad tracking]]

*[https://aisafety.dance/ Nicky Case, ''“AI Safety for Fleshy Humans”'', Hack Club (2024)]

*[[Flock license plate readers]]

*[[Ring]]

*[[Waymo]]

*[~~[Google]~~]

==References==

[[Category:Artificial intelligence]]

@@ Line 1: / Line 1: @@
 {{Irrelevant}}{{ToneWarning}}
-'''Artificial intelligence''' (AI) is a field of computer science that produces systems designed to solve problems that humans typically solve using intelligence. In the consumer and industry space, it is commonly referred to as chatbots or [[wikipedia:Large language model|large language models]] (LLMs), which have been a main focus of industry
+'''Artificial intelligence''' (AI) is a field of computer science that produces systems designed to solve problems that humans typically solve using intelligence. In the consumer and industry space, it is commonly referred to as chatbots or [[wikipedia:Large language model|large language models]] (LLMs), which have been a main focus of industry since the November 2022 launch of [[OpenAI]]'s [[ChatGPT]], with tens of billions of dollars in funding allocated to producing more popular LLMs. This is also a significant focus on [[wikipedia:Text-to-image model|text-to-image models]], which "draw" an image using a written prompt, and less commonly, [[wikipedia:Text-to-video model|text-to-video models]], which extend the text-to-image concept across several smooth video frames.
-since the November 2022 launch of [[ChatGPT]], with tens of billions of dollars in funding allocated to producing more popular LLMs. Also, a significant focus is on [[wikipedia:Text-to-image model|text-to-image models]], which "draw" an image using a written prompt, and less commonly, [[wikipedia:Text-to-video model|text-to-video models]], which extend the text-to-image concept across several smooth video frames.
-So far, no AI solutions are intelligent.  AI is not a new concept; it has been of interest since the 1950s. AI is a catch-all term; it encompasses many areas and techniques, so merely stating that something uses AI tells us little about it.
+AI is not a new concept; it has been of interest since the 1950s. AI is a catch-all term, encompassing many areas and techniques.
-[[wikipedia:Generative artificial intelligence|Generative artificial intelligence]] models are trained through vast amounts of existing human-generated content. Using the example of an LLM, by gathering statistics on patterns of words that people use, the model can generate sequences of words that seem similar to what a person might have written.  LLM does not understand anything; they cannot reason.  Everything they generate is just a randomly modulated pattern of tokens.  People reading sequences of tokens sometimes perceive things they think are true.  Sequences that do not make sense to the reader, or that are false, are called [[wikipedia:Hallucination (artificial intelligence)|hallucinations]].   LLMs are typically trained to produce output that is pleasing to people, exhibiting [[dark patterns]]. For example, they often produce output which seems confidently written, use patterns which praise the user (sycophancy), and employ emotionally manipulative language.
+[[wikipedia:Generative artificial intelligence|Generative artificial intelligence]] models are trained through vast amounts of existing human-generated content. LLMs gather statistics on word patterns, which allows the model to generate sequences of words that seem similar to what a person might have written. However, an LLM does not understand anything; they cannot reason.  They generate randomly modulated pattern of tokens. In this way, they function similarly to autocomplete.
-LLMs are a glorified autocomplete.  People are accustomed to interacting with others, and many overestimate the abilities of things that exhibit complex, person-like patterns.  Promoters of “AI” systems take advantage of this tendency, using suggestive names (like “reasoning” and “learning”) and grand claims (“PHD level”), which make it harder for people to understand these systems.
+People reading sequences of tokens sometimes perceive things they think are true.  Sequences that do not make sense to the reader, or that are false, are called [[wikipedia:Hallucination (artificial intelligence)|hallucinations]].  LLMs are typically trained to produce output that is pleasing to people, exhibiting [[Dark pattern|dark patterns]]. For example, they produce output which seems confidently written, use patterns which praise the user (sycophancy), and employ emotionally manipulative language.
-From November 2022 to 2025, venture capitalists and companies invested hundreds of billions of dollars into AI but received minimal returns.  When companies seek returns, consumers can expect that products may be orphaned, services may be reduced, customer data may be sold or repurposed, costs may rise, and companies may reduce staff or fail.  Historically, AI has had brief periods of intense hype, followed by disillusionment, and “AI winters.”
+People are accustomed to interacting with others, and many overestimate the abilities of things that exhibit complex, person-like patterns. Promoters of “AI” systems take advantage of this tendency, using suggestive names (like “reasoning” and “learning”) and grand claims (“PhD level”), which make it harder for people to understand these systems.
-The current well-funded industry of artificial intelligence tools has led to the rampant and unethical use of content. Startups aiming to develop AI services have been rapidly scraping the internet for content to train future models, and members of the field are concerned that they are approaching the limit of publicly available content to train from.<ref>{{Cite web |last=Tremayne-Pengelly |first=Alexandra |date=16 Dec 2024 |title=Ilya Sutskever Warns A.I. Is Running Out of Data—Here’s What Will Happen Next |url=https://observer.com/2024/12/openai-cofounder-ilya-sutskever-ai-data-peak/ |website=Observer}}</ref>
+From November 2022 to 2025, venture capitalists and companies invested hundreds of billions of dollars into AI but received minimal returns. When companies seek returns, consumers can expect that products may be orphaned, services may be reduced, customer data may be sold or repurposed, costs may rise, and companies may reduce staff or fail. Historically, AI has had brief periods of intense hype, followed by disillusionment, and “AI winters.”<sup>[<nowiki/>[[Consumer Rights Wiki:Verifiability|citation needed]]]</sup>
+The current well-funded industry of artificial intelligence tools has led to the rampant and unethical use of content. Startups aiming to develop AI services have been rapidly scraping the internet for content to train future models, and members of the field are concerned that they are approaching the limit of publicly available content to train from.<ref>{{Cite web |last=Tremayne-Pengelly |first=Alexandra |date=16 Dec 2024 |title=Ilya Sutskever Warns A.I. Is Running Out of Data—Here’s What Will Happen Next |url=https://observer.com/2024/12/openai-cofounder-ilya-sutskever-ai-data-peak/ |website=Observer |url-status=live |archive-url=http://web.archive.org/web/20251126053705/https://observer.com/2024/12/openai-cofounder-ilya-sutskever-ai-data-peak/ |archive-date=26 Nov 2025}}</ref>
 ==Why is it a problem==
@@ Line 18: / Line 19: @@
 :Further reading: [[Artificial intelligence/training]]
-Users' work is sometimes silently trained without their explicit consent, as was the case for [[Adobe's AI policy]].
+Users' work is sometimes silently used in training without their explicit consent, as was the case for [[Adobe's AI policy]].
+===Privacy concerns of AI===
+AI can be and has been used to generate deepfakes of people with and without their consent. Deepfakes are media generated with the likeness of an individual. Deepfake media can range from harmless to harmful. The latter includes child pornography, revenge porn, blackmail, etc. Since the rampant rise of consumer AI, deepfakes have become even more prevalent, with some websites explicitly specializing in them.<sup>[<nowiki/>[[Consumer Rights Wiki:Verifiability|citation needed]]]</sup><!-- In this case, I would recommend including a reliable news source on the topic, not citing the harmful website themselves.  -->
 ===Privacy concerns of online AI models===
-There are several concerns with using online AI models like [[ChatGPT]] ([[OpenAI]]), not only because they are proprietary, but also because there is no guarantee of where your data will be stored or used. Recent developments in local AI models offer an alternative to online AI models, as they can be used offline once downloaded from platforms like [https://huggingface.co/ HuggingFace]. Common models to run include Llama ([[Meta]]), DeepSeek ([[DeepSeek]]), Phi ([[Microsoft]]), Mistral ([[Mistral AI]]), Gemma ([[Google]]).
+There are several concerns with using online AI models like [[ChatGPT]], not only because they are proprietary, but also because there is no guarantee of where your data will be stored or used. Recent developments in local AI models offer an alternative to online AI models, which can be downloaded from platforms like [https://huggingface.co/ HuggingFace] and used offline. Common models to run include Llama ([[Meta]]), DeepSeek ([[DeepSeek]]), Phi ([[Microsoft]]), Mistral ([[Mistral AI]]), Gemma ([[Google]]).
+In some cases, AI models can be hijacked for malicious purposes. Demonstrated with Comet ([[Perplexity]]), users can run arbitrary prompts to the browser's built-in AI assistant by hiding text in the HTML comments, non-visible webpage text, or simple comments on a webpage.<ref name=":0">{{Cite web |date=Aug 20, 2025 |title=Tweet from Brave |url=https://nitter.us.catsarch.com/brave/status/1958152314914508893 |url-status=live |archive-url=https://web.archive.org/web/20260321120531/https://nitter.us.catsarch.com/brave/status/1958152314914508893 |archive-date=21 Mar 2026 |access-date=Aug 24, 2025 |website=X (formerly [[Twitter]])}}</ref> These arbitrary prompts can then be exploited to obtain sensitive information or gain unauthorized access to high-value accounts, such as those for banking or gaming libraries.<ref>{{Cite web |date=Aug 23, 2025 |title=Tweet from zack (in SF) |url=https://nitter.us.catsarch.com/zack_overflow/status/1959308058200551721 |url-status=live |archive-url=https://web.archive.org/web/20260321120841/https://nitter.us.catsarch.com/zack_overflow/status/1959308058200551721 |archive-date=21 Mar 2026 |access-date=Aug 24, 2025 |website=X (formerly [[Twitter]])}}</ref> See [[wikipedia:Prompt_injection|Prompt injection]].
+===Unethical maintenance of data centers===
+Due to heavy investments into and increased use of generative AI and LLMs, many data centers have been constructed to host LLMs. These data centers consume large amounts of power and water, in order to power and cool the computer systems running the models. Residents that live in cities where AI data centers have been constructed have complained of an increase in their electricity bills despite no change in their personal usage.<sup>[<nowiki/>[[Consumer Rights Wiki:Verifiability|citation needed]]]</sup> According to a research video by Benn Jordan, these data centers (as well as fracking operations and natural occurrences) cause a high amount of sound pollution, which can cause various symptoms.<ref> https://www.youtube.com/watch?v=_bP80DEAbuo ([https://preservetube.com/watch?v=_bP80DEAbuo Archived])</ref>
-In some cases, these AI models can also be hijacked for malicious purposes. Demonstrated from the usage of Comet ([[Perplexity]]), users can run arbitrary prompts to the browser's built-in AI assistant via hiding text in the HTML comments, non-visible webpage text, or simple comments on a webpage.<ref>{{Cite web |date=Aug 20, 2025 |title=Tweet from Brave |url=https://xcancel.com/brave/status/1958152314914508893#m |access-date=Aug 24, 2025 |website=X (formerly [[Twitter]])}}</ref> These arbitrary prompts can then be exploited to hijack sensitive information, or worse, gain unauthorized access to high-value accounts, such as those for banking or gaming libraries.<ref>{{Cite web |date=Aug 23, 2025 |title=Tweet from zack (in SF) |url=https://xcancel.com/zack_overflow/status/1959308058200551721 |access-date=Aug 24, 2025 |website=X (formerly [[Twitter]])}}</ref>
+=== Hidden directives ===
+Most AI apps include an initial "root"/"system" prompt given to the AI, which is hidden from the user. Some corporations go to great lengths to keep those prompts hidden, and to avoid leaking it to the user. Some projects attempt to bring back transparency to these tools, in spite of the restrictions.<ref>https://github.com/elder-plinius/CL4R1T4S</ref>
 ==Further reading==
-*[[Dark pattern]]
 *[[Automatic content recognition]]
-*[[Palantir]]
-*[[Meta]]
+==External links==
-*[[Yandex]]
-*[[TikTok and AI-powered ad tracking]]
+*[https://aisafety.dance/ Nicky Case, ''“AI Safety for Fleshy Humans”'', Hack Club (2024)]
-*[[Flock license plate readers]]
-*[[Ring]]
-*[[Waymo]]
-*[[Google]]
 ==References==
 {{Reflist}}
 [[Category:Artificial intelligence]]