LLMs

‘Not healthy’ LLM use is more common than you think

Publicado porRedacao AIDaily
4 min de leitura
Autor na fonte original: Robert Hart

Hank Green, a popular YouTuber and science communicator, said he is stepping back from production amid intense criticism over his use of AI. Green described his AI usage as "not healthy," but stressed that he used it for finding research sources and not to write scripts. Much of the ensuing firestorm in this corner of […]

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Hank Green, a popular YouTuber and science communicator, said he is stepping back from production amid intense criticism over his use of AI. Green described his AI usage as “not healthy,” but stressed that he used it for finding research sources and not to write scripts.

Much of the ensuing firestorm in this corner of the internet has centered on how a creator can square a brand built on authenticity and credibility with a technology trained on the (often uncompensated) works of others, and which has a well-known tendency to generate plausible-sounding falsehoods. Some attention has fallen on Green’s description of what appears to be an unhealthy reliance on the technology.

But his case points to a much larger gap in our understanding of AI’s psychological impact. Here, most public discussion is clustered around two poles: apparently benign use on one end, and self-evidently problematic cases involving psychiatric care, delusions, and psychosis on the other. Between them is a vast, murkier space in which use may become compulsive, dependent, or otherwise unhealthy without tipping into an obvious crisis. Green appears to see himself somewhere in that space. Many others likely do too.

Considering how LLMs are designed, that shouldn’t come as much of a surprise. AI chatbots are, by their nature, built to keep chatting. Much like social media platforms, they are explicitly built to engage users. Experts have identified this as one of the key drivers of AI psychosis, a catchall term in cases where highly agreeable chatbots reinforce delusional beliefs. Claims that companies prioritize engagement over user well-being have also begun to appear in lawsuits . Providers, meanwhile, have also introduced warnings prompting people to take breaks after lengthy sessions.

But the same qualities can become harmful well before they contribute to psychiatric crises. There are growing reports of people instinctively turning to chatbots to think through problems, make decisions, or seek reassurance, while others forge emotional bonds that seem strong enough to lead to grief when broken. It will likely take years before enough evidence can be gathered to properly understand the technology’s impact, but these early reports feel eerily familiar to the early years of another engagement-maximizing technology: social media. Over time, concern has grown over social media’s impact on our well-being, attention, and sometimes compulsive use, and governments around the world are now responding with measures to restrict its use, such as banning children and teens.

Green’s case illustrates a different kind of reliance. He said he used it as a research aid, helping him locate papers and other material on a given topic. There is little to suggest his use of chatbots in this way was inherently problematic, despite the furious responses it provoked or Green’s apology.

That doesn’t necessarily mean the technology isn’t having an effect on the person using it. Though the research is still in its infancy, early research suggests that repeated AI tool use can weaken the skills we’d use to do the task it replaces. Other work suggests that chatbot users showed notably less brain activity when measuring a particular task, while additional studies have linked chatbot use to reduced critical thinking skills. None of this is conclusive, but the underlying idea is not new. Cognitive offloading — shifting mental work like memory, mental math, or directions from our brains to external tools — is a well-documented phenomenon.

Even if only a fraction of chatbot use is considered unhealthy, the sheer scale of AI adoption means millions of people could still be affected. Comprehensive data covering all available tools is hard to come by, but OpenAI alone this year said it has more than 900 million weekly active users.

It took years to fully understand how search engines changed the ways we remember information, or how social media affects attention and well-being. AI is unlikely to be any different. Green may simply be one of the first high-profile people to publicly articulate a feeling that many others have already had, long before science has the evidence to explain how AI is changing our consciousness.

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Pontos-chave

  • A dependência de LLMs pode afetar a credibilidade de criadores de conteúdo no Brasil.
  • Questões de saúde mental relacionadas ao uso de IA precisam de maior atenção e regulamentação.
  • A transparência e a ética no uso de IA se tornarão cada vez mais exigidas por criadores e usuários.

Análise editorial

A situação de Hank Green levanta questões cruciais sobre o uso de LLMs (Modelos de Linguagem de Grande Escala) e suas implicações psicológicas, especialmente em um contexto onde a autenticidade é um valor central para criadores de conteúdo. No Brasil, onde a produção de conteúdo digital cresce rapidamente, é essencial que os criadores reflitam sobre como a dependência dessas tecnologias pode afetar sua credibilidade e a relação com seus seguidores. A percepção de que a utilização de IA pode ser "não saudável" sugere que muitos criadores podem estar enfrentando dilemas semelhantes, o que pode impactar a forma como o público percebe a autenticidade e a originalidade do conteúdo.

Além disso, a discussão sobre a saúde mental e o uso de IA é particularmente relevante em um país onde questões de saúde mental ainda são estigmatizadas. A crescente dependência de chatbots para tomada de decisões e busca de apoio emocional pode levar a um aumento de problemas psicológicos, refletindo uma necessidade urgente de regulamentação e conscientização sobre o uso responsável dessas tecnologias. O Brasil, por sua vez, deve observar como outros países estão lidando com essas questões e considerar a implementação de diretrizes que protejam os usuários.

Por fim, o caso de Green pode ser um indicativo do que está por vir: um aumento na demanda por transparência e ética no uso de IA, tanto por parte de criadores quanto de plataformas. À medida que mais pessoas se tornam conscientes dos riscos associados ao uso excessivo de LLMs, pode haver um movimento em direção a práticas mais saudáveis e equilibradas. As empresas de tecnologia no Brasil devem estar atentas a essa tendência e se preparar para adaptar suas abordagens, promovendo um uso mais consciente e responsável da IA em suas plataformas.

O que esta cobertura entrega

  • Atribuicao clara de fonte com link para a publicacao original.
  • Enquadramento editorial sobre relevancia, impacto e proximos desdobramentos.
  • Revisao de legibilidade, contexto e duplicacao antes da publicacao.

Fonte original:

The Verge AI

Sobre este artigo

Este artigo foi curado e publicado pelo AIDaily como parte da nossa cobertura editorial sobre desenvolvimentos em inteligência artificial. O conteúdo é baseado na fonte original citada abaixo, enriquecido com contexto e análise editorial. Ferramentas automatizadas podem auxiliar tradução e estruturação inicial, mas a decisão de publicar, a revisão factual e o enquadramento de contexto seguem responsabilidade editorial.

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