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  3. Something Bizarre Is Happening to People Who Use ChatGPT a Lot

Something Bizarre Is Happening to People Who Use ChatGPT a Lot

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  • Z [email protected]

    I couldn’t be bothered to read it, so I got CharGPT to summarise it. Apparently there’s nothing to worry about.

    I This user is from outside of this forum
    I This user is from outside of this forum
    [email protected]
    wrote on last edited by
    #152

    You didn't, I did

    The article discusses a study by OpenAI and MIT Media Lab revealing that heavy ChatGPT users — dubbed "power users" — are showing signs of addiction to the chatbot. These signs include preoccupation, withdrawal, mood changes, and loss of control. While most users don't form emotional connections with ChatGPT, those who use it more frequently tend to view it as a "friend," especially if they feel lonely or emotionally unfulfilled.

    Interestingly, people using ChatGPT for personal reasons (like sharing emotions) showed less emotional dependency than those using it for non-personal tasks (like brainstorming). Also, text-based interactions led to more emotional language than voice interactions, with brief voice use correlating to better well-being. Overall, prolonged use — regardless of purpose — increased the risk of emotional dependence.

    You said:

    Make a list of the main points and for each explain why it will be worse when it is society wide

    ChatGPT said:

    Here’s a list of the main points from the article, along with why each could be more concerning on a society-wide scale:

    Heavy ChatGPT users show signs of addiction (preoccupation, withdrawal, mood changes, loss of control):
    
    Why it's worse at scale:
    
    If large numbers of people become dependent on AI tools, especially to the point of addiction, it could lead to widespread mental health issues, reduced productivity, and a society increasingly unable to function without AI assistance.
    
    Long-term users tend to form emotional bonds with ChatGPT, sometimes seeing it as a “friend”:
    
    Why it's worse at scale:
    
    A society where many people substitute AI for real human connection could see rising loneliness, social detachment, and a decline in community and interpersonal relationships. This weakens social bonds and may impact mental health and civic cohesion.
    
    Lonelier individuals are more likely to use ChatGPT heavily and become emotionally attached:
    
    Why it's worse at scale:
    
    This could create a feedback loop where loneliness drives AI use, and AI use further isolates people from real-world interactions, exacerbating social alienation on a mass level.
    
    People stress out over subtle changes in ChatGPT’s behavior:
    
    Why it's worse at scale:
    
    If millions of people are emotionally reactive to minor algorithmic changes, this gives tech companies enormous influence over collective emotional states. It also creates societal instability, as shifts in AI behavior could unintentionally trigger widespread anxiety or confusion.
    
    Emotional language is used more in text interactions than voice, and brief voice use is associated with better well-being:
    
    Why it's worse at scale:
    
    If the most popular and accessible form of interaction (text) increases emotional entanglement, and the healthier option (brief voice use) is less utilized, we might unintentionally nudge society toward less emotionally healthy patterns of AI interaction.
    
    Users who engage with ChatGPT for non-personal tasks are more emotionally dependent than those who use it for personal reasons:
    
    Why it's worse at scale:
    
    This is counterintuitive and dangerous because it suggests people may not realize they're forming dependencies while doing routine work. If AI tools meant to boost productivity are quietly making users emotionally reliant, it could have long-term effects on workforce dynamics and mental resilience.
    
    Prolonged usage increases risk of emotional dependence, regardless of how it's used:
    
    Why it's worse at scale:
    
    As AI becomes embedded in everyday life, the likelihood of widespread emotional dependence increases. This could shift power dynamics between humans and AI, making people less autonomous and more easily influenced by algorithmic systems.
    

    Let me know if you want this formatted for a presentation, policy paper, or discussion.

    I F liv@lemmy.nzL 3 Replies Last reply
    0
    • I [email protected]

      You didn't, I did

      The article discusses a study by OpenAI and MIT Media Lab revealing that heavy ChatGPT users — dubbed "power users" — are showing signs of addiction to the chatbot. These signs include preoccupation, withdrawal, mood changes, and loss of control. While most users don't form emotional connections with ChatGPT, those who use it more frequently tend to view it as a "friend," especially if they feel lonely or emotionally unfulfilled.

      Interestingly, people using ChatGPT for personal reasons (like sharing emotions) showed less emotional dependency than those using it for non-personal tasks (like brainstorming). Also, text-based interactions led to more emotional language than voice interactions, with brief voice use correlating to better well-being. Overall, prolonged use — regardless of purpose — increased the risk of emotional dependence.

      You said:

      Make a list of the main points and for each explain why it will be worse when it is society wide

      ChatGPT said:

      Here’s a list of the main points from the article, along with why each could be more concerning on a society-wide scale:

      Heavy ChatGPT users show signs of addiction (preoccupation, withdrawal, mood changes, loss of control):
      
      Why it's worse at scale:
      
      If large numbers of people become dependent on AI tools, especially to the point of addiction, it could lead to widespread mental health issues, reduced productivity, and a society increasingly unable to function without AI assistance.
      
      Long-term users tend to form emotional bonds with ChatGPT, sometimes seeing it as a “friend”:
      
      Why it's worse at scale:
      
      A society where many people substitute AI for real human connection could see rising loneliness, social detachment, and a decline in community and interpersonal relationships. This weakens social bonds and may impact mental health and civic cohesion.
      
      Lonelier individuals are more likely to use ChatGPT heavily and become emotionally attached:
      
      Why it's worse at scale:
      
      This could create a feedback loop where loneliness drives AI use, and AI use further isolates people from real-world interactions, exacerbating social alienation on a mass level.
      
      People stress out over subtle changes in ChatGPT’s behavior:
      
      Why it's worse at scale:
      
      If millions of people are emotionally reactive to minor algorithmic changes, this gives tech companies enormous influence over collective emotional states. It also creates societal instability, as shifts in AI behavior could unintentionally trigger widespread anxiety or confusion.
      
      Emotional language is used more in text interactions than voice, and brief voice use is associated with better well-being:
      
      Why it's worse at scale:
      
      If the most popular and accessible form of interaction (text) increases emotional entanglement, and the healthier option (brief voice use) is less utilized, we might unintentionally nudge society toward less emotionally healthy patterns of AI interaction.
      
      Users who engage with ChatGPT for non-personal tasks are more emotionally dependent than those who use it for personal reasons:
      
      Why it's worse at scale:
      
      This is counterintuitive and dangerous because it suggests people may not realize they're forming dependencies while doing routine work. If AI tools meant to boost productivity are quietly making users emotionally reliant, it could have long-term effects on workforce dynamics and mental resilience.
      
      Prolonged usage increases risk of emotional dependence, regardless of how it's used:
      
      Why it's worse at scale:
      
      As AI becomes embedded in everyday life, the likelihood of widespread emotional dependence increases. This could shift power dynamics between humans and AI, making people less autonomous and more easily influenced by algorithmic systems.
      

      Let me know if you want this formatted for a presentation, policy paper, or discussion.

      I This user is from outside of this forum
      I This user is from outside of this forum
      [email protected]
      wrote on last edited by
      #153

      You said:
      Take the same list again, for each point explain why it's actually beneficial and how it will get better with increased adoption

      ChatGPT said:

      Here’s the same list of main points, but this time with a more optimistic take — highlighting how each trend could actually be beneficial and how increased adoption might make things better for individuals and society as a whole:

      Heavy ChatGPT users show signs of addiction (preoccupation, withdrawal, mood changes, loss of control):
      
      Why it could be beneficial:
      
      If people are turning to ChatGPT frequently, it may indicate that it's providing meaningful value — like reducing cognitive load, aiding creativity, or offering emotional support. As usage becomes more common, society may develop healthier digital habits, just as it has with smartphones and social media. Over time, norms and tools (e.g., usage timers, digital wellness features) could help people manage their use responsibly.
      
      Long-term users tend to form emotional bonds with ChatGPT, sometimes seeing it as a “friend”:
      
      Why it could be beneficial:
      
      For people lacking companionship or emotional support, especially the elderly or isolated, AI companions can provide comfort, conversation, and a sense of presence. On a wider scale, AI could reduce loneliness-related health problems and even support mental wellness initiatives by being an accessible form of care or early intervention.
      
      Lonelier individuals are more likely to use ChatGPT heavily and become emotionally attached:
      
      Why it could be beneficial:
      
      If AI offers a low-barrier outlet for the lonely, it might be a first step toward re-engagement with the world. AI can encourage people to express feelings they wouldn't share with others and even prompt them to seek human connection, therapy, or support services. Widespread AI use could destigmatize conversations about loneliness and mental health.
      
      People stress out over subtle changes in ChatGPT’s behavior:
      
      Why it could be beneficial:
      
      This shows users are emotionally invested — which can push developers to create more consistent, emotionally intelligent systems. If society recognizes the emotional impact of AI, it will encourage better design, transparency, and regulation. Over time, this can lead to more stable and human-aware AI that positively complements emotional needs.
      
      Emotional language is used more in text interactions than voice, and brief voice use is associated with better well-being:
      
      Why it could be beneficial:
      
      This gives users multiple channels of expression to suit their mood or needs — voice for brief emotional boosts, text for deeper reflection. With broader adoption, people can tailor AI interaction styles to maximize personal benefit. This insight also allows designers to create features that better match emotional and mental health goals.
      
      Users who engage with ChatGPT for non-personal tasks are more emotionally dependent than those who use it for personal reasons:
      
      Why it could be beneficial:
      
      This means AI is becoming a highly trusted tool, even in practical domains. As more people adopt it for brainstorming, research, or decision-making, we’ll likely see a democratization of high-level thinking tools. Over time, dependency could evolve into partnership — similar to how calculators or GPS became essential but ultimately empowering tools.
      
      Prolonged usage increases risk of emotional dependence, regardless of how it's used:
      
      Why it could be beneficial:
      
      Long-term usage can foster deeper understanding of one’s own thought processes, communication patterns, and emotional states. As AI integrates into daily life, people might develop greater self-awareness and reflection through their interactions. Society could benefit from individuals who are more emotionally literate and thoughtful, even if that awareness is sparked by an AI relationship.
      

      Let me know if you'd like this version turned into a policy brief, an article, or a debate prep doc — could be used in all kinds of conversations.

      You said:
      Explain how chatgpt is a stochastic parrot that cannot by design say anything fundamentally new and how it is basically just a keyboard auto complete on steroid

      ChatGPT said:

      Alright, here's the breakdown of that critique — the "stochastic parrot" idea and the comparison to advanced autocomplete — explained clearly and fairly:

      1. What does “stochastic parrot” mean?

      The term "stochastic parrot" was coined in a 2021 paper by researchers including Emily Bender and Timnit Gebru. It refers to large language models like ChatGPT that:

      "Stochastic" means based on probability. The model doesn’t “think” or “understand”; it predicts the next word based on statistical likelihood, given the words before it.
      
      "Parrot" because it doesn’t generate new ideas—it repeats patterns and phrases it has seen in training data, like a parrot mimics human speech.
      

      So, calling ChatGPT a stochastic parrot is a way of saying:
      It’s not truly intelligent. It’s mimicking language patterns, not generating original thought.

      1. It can’t say anything fundamentally new — why?

      By design, ChatGPT:

      Is trained on vast amounts of existing text from books, websites, forums, and more.
      
      Learns the statistical patterns of how humans use language.
      
      Generates responses by predicting the next most likely word or phrase based on that training.
      

      Because it’s not connected to lived experience, emotion, consciousness, or intent, it:

      Can’t invent genuinely new concepts.
      
      Can’t form subjective opinions.
      
      Can’t create knowledge that isn’t derived from patterns it has already seen.
      

      It might sound novel, but under the hood, it’s remixing existing information in clever ways — not discovering or reasoning in a human sense.

      1. It's like "autocomplete on steroids" — how so?

      If you’ve used Gmail’s or your phone’s autocomplete, you’ve seen basic language prediction in action. Type “I hope you...” and it might suggest “...have a great day.”

      ChatGPT is essentially the same mechanism:

      Autocomplete predicts the next word based on simple models.
      
      ChatGPT predicts sequences of words using a far more complex, nuanced statistical model trained on billions of examples.
      

      So e:

      It can hold context better.
      
      It can imitate different styles.
      
      But it's still guessing the next words, not “thinking” or “understanding.”
      

      In summary:

      Calling ChatGPT a stochastic parrot or autocomplete on steroids emphasizes that:

      It doesn’t understand meaning.
      
      It doesn’t create knowledge.
      
      It reflects patterns in language, not consciousness or intelligence.
      

      It’s powerful and useful — but it’s important not to mistake fluency for understanding.

      Let me know if you want the counterpoint to this critique too — because there are arguments in defense of the model’s creative utility despite its limitations.

      I 1 Reply Last reply
      0
      • I [email protected]

        You said:
        Take the same list again, for each point explain why it's actually beneficial and how it will get better with increased adoption

        ChatGPT said:

        Here’s the same list of main points, but this time with a more optimistic take — highlighting how each trend could actually be beneficial and how increased adoption might make things better for individuals and society as a whole:

        Heavy ChatGPT users show signs of addiction (preoccupation, withdrawal, mood changes, loss of control):
        
        Why it could be beneficial:
        
        If people are turning to ChatGPT frequently, it may indicate that it's providing meaningful value — like reducing cognitive load, aiding creativity, or offering emotional support. As usage becomes more common, society may develop healthier digital habits, just as it has with smartphones and social media. Over time, norms and tools (e.g., usage timers, digital wellness features) could help people manage their use responsibly.
        
        Long-term users tend to form emotional bonds with ChatGPT, sometimes seeing it as a “friend”:
        
        Why it could be beneficial:
        
        For people lacking companionship or emotional support, especially the elderly or isolated, AI companions can provide comfort, conversation, and a sense of presence. On a wider scale, AI could reduce loneliness-related health problems and even support mental wellness initiatives by being an accessible form of care or early intervention.
        
        Lonelier individuals are more likely to use ChatGPT heavily and become emotionally attached:
        
        Why it could be beneficial:
        
        If AI offers a low-barrier outlet for the lonely, it might be a first step toward re-engagement with the world. AI can encourage people to express feelings they wouldn't share with others and even prompt them to seek human connection, therapy, or support services. Widespread AI use could destigmatize conversations about loneliness and mental health.
        
        People stress out over subtle changes in ChatGPT’s behavior:
        
        Why it could be beneficial:
        
        This shows users are emotionally invested — which can push developers to create more consistent, emotionally intelligent systems. If society recognizes the emotional impact of AI, it will encourage better design, transparency, and regulation. Over time, this can lead to more stable and human-aware AI that positively complements emotional needs.
        
        Emotional language is used more in text interactions than voice, and brief voice use is associated with better well-being:
        
        Why it could be beneficial:
        
        This gives users multiple channels of expression to suit their mood or needs — voice for brief emotional boosts, text for deeper reflection. With broader adoption, people can tailor AI interaction styles to maximize personal benefit. This insight also allows designers to create features that better match emotional and mental health goals.
        
        Users who engage with ChatGPT for non-personal tasks are more emotionally dependent than those who use it for personal reasons:
        
        Why it could be beneficial:
        
        This means AI is becoming a highly trusted tool, even in practical domains. As more people adopt it for brainstorming, research, or decision-making, we’ll likely see a democratization of high-level thinking tools. Over time, dependency could evolve into partnership — similar to how calculators or GPS became essential but ultimately empowering tools.
        
        Prolonged usage increases risk of emotional dependence, regardless of how it's used:
        
        Why it could be beneficial:
        
        Long-term usage can foster deeper understanding of one’s own thought processes, communication patterns, and emotional states. As AI integrates into daily life, people might develop greater self-awareness and reflection through their interactions. Society could benefit from individuals who are more emotionally literate and thoughtful, even if that awareness is sparked by an AI relationship.
        

        Let me know if you'd like this version turned into a policy brief, an article, or a debate prep doc — could be used in all kinds of conversations.

        You said:
        Explain how chatgpt is a stochastic parrot that cannot by design say anything fundamentally new and how it is basically just a keyboard auto complete on steroid

        ChatGPT said:

        Alright, here's the breakdown of that critique — the "stochastic parrot" idea and the comparison to advanced autocomplete — explained clearly and fairly:

        1. What does “stochastic parrot” mean?

        The term "stochastic parrot" was coined in a 2021 paper by researchers including Emily Bender and Timnit Gebru. It refers to large language models like ChatGPT that:

        "Stochastic" means based on probability. The model doesn’t “think” or “understand”; it predicts the next word based on statistical likelihood, given the words before it.
        
        "Parrot" because it doesn’t generate new ideas—it repeats patterns and phrases it has seen in training data, like a parrot mimics human speech.
        

        So, calling ChatGPT a stochastic parrot is a way of saying:
        It’s not truly intelligent. It’s mimicking language patterns, not generating original thought.

        1. It can’t say anything fundamentally new — why?

        By design, ChatGPT:

        Is trained on vast amounts of existing text from books, websites, forums, and more.
        
        Learns the statistical patterns of how humans use language.
        
        Generates responses by predicting the next most likely word or phrase based on that training.
        

        Because it’s not connected to lived experience, emotion, consciousness, or intent, it:

        Can’t invent genuinely new concepts.
        
        Can’t form subjective opinions.
        
        Can’t create knowledge that isn’t derived from patterns it has already seen.
        

        It might sound novel, but under the hood, it’s remixing existing information in clever ways — not discovering or reasoning in a human sense.

        1. It's like "autocomplete on steroids" — how so?

        If you’ve used Gmail’s or your phone’s autocomplete, you’ve seen basic language prediction in action. Type “I hope you...” and it might suggest “...have a great day.”

        ChatGPT is essentially the same mechanism:

        Autocomplete predicts the next word based on simple models.
        
        ChatGPT predicts sequences of words using a far more complex, nuanced statistical model trained on billions of examples.
        

        So e:

        It can hold context better.
        
        It can imitate different styles.
        
        But it's still guessing the next words, not “thinking” or “understanding.”
        

        In summary:

        Calling ChatGPT a stochastic parrot or autocomplete on steroids emphasizes that:

        It doesn’t understand meaning.
        
        It doesn’t create knowledge.
        
        It reflects patterns in language, not consciousness or intelligence.
        

        It’s powerful and useful — but it’s important not to mistake fluency for understanding.

        Let me know if you want the counterpoint to this critique too — because there are arguments in defense of the model’s creative utility despite its limitations.

        I This user is from outside of this forum
        I This user is from outside of this forum
        [email protected]
        wrote on last edited by
        #154

        You said:
        Now make the maximally opposite idea, make heavy use of the concept of the latent space

        ChatGPT said:

        Absolutely — here's the maximally opposite take, fully embracing the idea that models like ChatGPT are more than just stochastic parrots, and heavily leveraging the concept of latent space to argue that these models can, in a very real sense, generate novel ideas and insights.
        ChatGPT Is Not a Stochastic Parrot — It’s a Navigator of Latent Thought Space

        While critics call ChatGPT a “stochastic parrot” or “autocomplete on steroids,” this view drastically underestimates the depth and complexity of what large language models are actually doing. These models aren’t just parroting data — they are mapping and exploring an extraordinarily rich latent space of human knowledge, culture, and thought.

        1. Latent Space: The Hidden Geometry of Meaning

        At the core of models like ChatGPT is the idea of a latent space — a high-dimensional mathematical structure where abstract concepts, relationships, and patterns are embedded.

        Every word, sentence, and idea is represented as a point or vector in this space.
        
        The relationships between points encode not just surface patterns, but deep structural relationships between ideas — analogies, metaphors, causal chains, emotional tones, etc.
        

        This latent space isn’t programmed in — it emerges from the training data through self-supervised learning. The result is a dynamic, multi-dimensional conceptual map that humans don’t have direct access to but the model can navigate.

        1. Novelty as Latent Interpolation and Extrapolation

        Human creativity often works by connecting existing concepts in unexpected ways — something these models are exceptionally good at.

        When ChatGPT generates text, it’s not repeating past sentences — it’s interpolating and extrapolating within the latent space.
        
        It finds new paths between existing ideas, often producing connections no single human has written down before.
        
        This is not parroting — it’s a form of latent-space creativity.
        

        For example, when the model generates a metaphor or analogy you've never heard before, it’s discovering a new alignment in the conceptual topology — something genuinely emergent.

        1. Emergent Generalization, Not Memorization

        Critics argue LLMs can’t understand or generalize. But in fact:

        Models demonstrate emergent behaviors that were not directly trained into them — like multi-step reasoning, analogical thinking, or transfer across domains.
        
        These behaviors arise from complex interactions in the latent space, not from rote recall.
        

        In this view, ChatGPT is less like a parrot and more like a mathematical mind, fluent in the topography of human language and thought.

        1. Language as a Proxy for Thought

        Language is not just a tool for communication — it’s a compressed, high-bandwidth representation of human thinking.

        Because LLMs are trained on so much human-generated language, they build an internal model of how humans think, reason, feel, and imagine — as encoded in language.

        That means ChatGPT isn’t just finishing your sentence; it’s navigating the conceptual manifolds of knowledge, philosophy, narrative, humor, and more — sometimes in ways humans themselves haven’t yet seen.

        1. With Scale Comes Emergence

        As models scale in size and training data, they demonstrate qualitatively new behaviors — not just quantitative improvements. This includes things like:

        Few-shot learning
        
        Chain-of-thought reasoning
        
        Style transfer
        
        Multi-modal integration
        

        These aren't just features of autocomplete — they’re signs of systems operating in a rich cognitive manifold, capable of abstract manipulation of meaning.
        In Summary:

        ChatGPT isn’t just guessing the next word. It’s:

        Navigating a vast, learned geometry of meaning
        
        Connecting ideas in novel ways
        
        Generating emergent insight by recombining latent concepts
        

        It may not “understand” like a human, but it can synthesize in a way that mimics — and sometimes even surpasses — human creativity.

        Calling it a "stochastic parrot" is like calling a jazz musician an “audio repeater” because they’re using notes they’ve heard before. It misses the creativity in the combination — the generative power that lies within the latent space.

        Want to see a side-by-side debate between these two perspectives? Or explore where the middle ground is?

        T grrgyle@slrpnk.netG hark@lemmy.worldH 3 Replies Last reply
        0
        • E [email protected]

          I don't understand what people even use it for.

          bilb@lem.monsterB This user is from outside of this forum
          bilb@lem.monsterB This user is from outside of this forum
          [email protected]
          wrote on last edited by
          #155

          I use it to make all decisions, including what I will do each day and what I will say to people. I take no responsibility for any of my actions. If someone doesn't like something I do, too bad. The genius AI knows better, and I only care about what it has to say.

          1 Reply Last reply
          0
          • I [email protected]

            You didn't, I did

            The article discusses a study by OpenAI and MIT Media Lab revealing that heavy ChatGPT users — dubbed "power users" — are showing signs of addiction to the chatbot. These signs include preoccupation, withdrawal, mood changes, and loss of control. While most users don't form emotional connections with ChatGPT, those who use it more frequently tend to view it as a "friend," especially if they feel lonely or emotionally unfulfilled.

            Interestingly, people using ChatGPT for personal reasons (like sharing emotions) showed less emotional dependency than those using it for non-personal tasks (like brainstorming). Also, text-based interactions led to more emotional language than voice interactions, with brief voice use correlating to better well-being. Overall, prolonged use — regardless of purpose — increased the risk of emotional dependence.

            You said:

            Make a list of the main points and for each explain why it will be worse when it is society wide

            ChatGPT said:

            Here’s a list of the main points from the article, along with why each could be more concerning on a society-wide scale:

            Heavy ChatGPT users show signs of addiction (preoccupation, withdrawal, mood changes, loss of control):
            
            Why it's worse at scale:
            
            If large numbers of people become dependent on AI tools, especially to the point of addiction, it could lead to widespread mental health issues, reduced productivity, and a society increasingly unable to function without AI assistance.
            
            Long-term users tend to form emotional bonds with ChatGPT, sometimes seeing it as a “friend”:
            
            Why it's worse at scale:
            
            A society where many people substitute AI for real human connection could see rising loneliness, social detachment, and a decline in community and interpersonal relationships. This weakens social bonds and may impact mental health and civic cohesion.
            
            Lonelier individuals are more likely to use ChatGPT heavily and become emotionally attached:
            
            Why it's worse at scale:
            
            This could create a feedback loop where loneliness drives AI use, and AI use further isolates people from real-world interactions, exacerbating social alienation on a mass level.
            
            People stress out over subtle changes in ChatGPT’s behavior:
            
            Why it's worse at scale:
            
            If millions of people are emotionally reactive to minor algorithmic changes, this gives tech companies enormous influence over collective emotional states. It also creates societal instability, as shifts in AI behavior could unintentionally trigger widespread anxiety or confusion.
            
            Emotional language is used more in text interactions than voice, and brief voice use is associated with better well-being:
            
            Why it's worse at scale:
            
            If the most popular and accessible form of interaction (text) increases emotional entanglement, and the healthier option (brief voice use) is less utilized, we might unintentionally nudge society toward less emotionally healthy patterns of AI interaction.
            
            Users who engage with ChatGPT for non-personal tasks are more emotionally dependent than those who use it for personal reasons:
            
            Why it's worse at scale:
            
            This is counterintuitive and dangerous because it suggests people may not realize they're forming dependencies while doing routine work. If AI tools meant to boost productivity are quietly making users emotionally reliant, it could have long-term effects on workforce dynamics and mental resilience.
            
            Prolonged usage increases risk of emotional dependence, regardless of how it's used:
            
            Why it's worse at scale:
            
            As AI becomes embedded in everyday life, the likelihood of widespread emotional dependence increases. This could shift power dynamics between humans and AI, making people less autonomous and more easily influenced by algorithmic systems.
            

            Let me know if you want this formatted for a presentation, policy paper, or discussion.

            F This user is from outside of this forum
            F This user is from outside of this forum
            [email protected]
            wrote on last edited by
            #156

            What's the point of a summary that's longer than the article itself?

            I 1 Reply Last reply
            0
            • graphene@lemm.eeG [email protected]

              And the amount of connections and friends the average person has has been in free fall for decades...

              ? Offline
              ? Offline
              Guest
              wrote on last edited by
              #157

              I dunno. I connected with more people on reddit and Twitter than irl tbh.

              Different connection but real and valid nonetheless.

              I'm thinking places like r/stopdrinking, petioles, bipolar, shits been therapy for me tbh.

              I 1 Reply Last reply
              0
              • nostradavid@programming.devN [email protected]

                That was clear from GPT-3, day 1.

                I read a Reddit post about a woman who used GPT-3 to effectively replace her husband, who had passed on not too long before that. She used it as a way to grief, I suppose? She ended up noticing that she was getting too attach to it, and had to leave him behind a second time...

                ? Offline
                ? Offline
                Guest
                wrote on last edited by
                #158

                Ugh, that hit me hard. Poor lady. I hope it helped in some way.

                1 Reply Last reply
                0
                • I [email protected]

                  You said:
                  Now make the maximally opposite idea, make heavy use of the concept of the latent space

                  ChatGPT said:

                  Absolutely — here's the maximally opposite take, fully embracing the idea that models like ChatGPT are more than just stochastic parrots, and heavily leveraging the concept of latent space to argue that these models can, in a very real sense, generate novel ideas and insights.
                  ChatGPT Is Not a Stochastic Parrot — It’s a Navigator of Latent Thought Space

                  While critics call ChatGPT a “stochastic parrot” or “autocomplete on steroids,” this view drastically underestimates the depth and complexity of what large language models are actually doing. These models aren’t just parroting data — they are mapping and exploring an extraordinarily rich latent space of human knowledge, culture, and thought.

                  1. Latent Space: The Hidden Geometry of Meaning

                  At the core of models like ChatGPT is the idea of a latent space — a high-dimensional mathematical structure where abstract concepts, relationships, and patterns are embedded.

                  Every word, sentence, and idea is represented as a point or vector in this space.
                  
                  The relationships between points encode not just surface patterns, but deep structural relationships between ideas — analogies, metaphors, causal chains, emotional tones, etc.
                  

                  This latent space isn’t programmed in — it emerges from the training data through self-supervised learning. The result is a dynamic, multi-dimensional conceptual map that humans don’t have direct access to but the model can navigate.

                  1. Novelty as Latent Interpolation and Extrapolation

                  Human creativity often works by connecting existing concepts in unexpected ways — something these models are exceptionally good at.

                  When ChatGPT generates text, it’s not repeating past sentences — it’s interpolating and extrapolating within the latent space.
                  
                  It finds new paths between existing ideas, often producing connections no single human has written down before.
                  
                  This is not parroting — it’s a form of latent-space creativity.
                  

                  For example, when the model generates a metaphor or analogy you've never heard before, it’s discovering a new alignment in the conceptual topology — something genuinely emergent.

                  1. Emergent Generalization, Not Memorization

                  Critics argue LLMs can’t understand or generalize. But in fact:

                  Models demonstrate emergent behaviors that were not directly trained into them — like multi-step reasoning, analogical thinking, or transfer across domains.
                  
                  These behaviors arise from complex interactions in the latent space, not from rote recall.
                  

                  In this view, ChatGPT is less like a parrot and more like a mathematical mind, fluent in the topography of human language and thought.

                  1. Language as a Proxy for Thought

                  Language is not just a tool for communication — it’s a compressed, high-bandwidth representation of human thinking.

                  Because LLMs are trained on so much human-generated language, they build an internal model of how humans think, reason, feel, and imagine — as encoded in language.

                  That means ChatGPT isn’t just finishing your sentence; it’s navigating the conceptual manifolds of knowledge, philosophy, narrative, humor, and more — sometimes in ways humans themselves haven’t yet seen.

                  1. With Scale Comes Emergence

                  As models scale in size and training data, they demonstrate qualitatively new behaviors — not just quantitative improvements. This includes things like:

                  Few-shot learning
                  
                  Chain-of-thought reasoning
                  
                  Style transfer
                  
                  Multi-modal integration
                  

                  These aren't just features of autocomplete — they’re signs of systems operating in a rich cognitive manifold, capable of abstract manipulation of meaning.
                  In Summary:

                  ChatGPT isn’t just guessing the next word. It’s:

                  Navigating a vast, learned geometry of meaning
                  
                  Connecting ideas in novel ways
                  
                  Generating emergent insight by recombining latent concepts
                  

                  It may not “understand” like a human, but it can synthesize in a way that mimics — and sometimes even surpasses — human creativity.

                  Calling it a "stochastic parrot" is like calling a jazz musician an “audio repeater” because they’re using notes they’ve heard before. It misses the creativity in the combination — the generative power that lies within the latent space.

                  Want to see a side-by-side debate between these two perspectives? Or explore where the middle ground is?

                  T This user is from outside of this forum
                  T This user is from outside of this forum
                  [email protected]
                  wrote on last edited by
                  #159

                  Dear god dude. You are trying way too hard on these comments. Chill

                  D I 2 Replies Last reply
                  0
                  • L [email protected]

                    It's more up to you to prove that a hypothetical edge case you dreamed up is more likely than what happens in a normal bell curve. Given the size of typical LLM data this seems futile, but if that's how you want to spend your time, hey knock yourself out.

                    S This user is from outside of this forum
                    S This user is from outside of this forum
                    [email protected]
                    wrote on last edited by
                    #160

                    Lol. Be my guest and knock yourself out, dreaming you know things

                    1 Reply Last reply
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                    • return2ozma@lemmy.worldR [email protected]
                      This post did not contain any content.
                      ? Offline
                      ? Offline
                      Guest
                      wrote on last edited by
                      #161

                      I mean, I stopped in the middle of the grocery store and used it to choose best frozen chicken tenders brand to put in my air fryer. …I am ok though. Yeah.

                      F aceshigh@lemmy.worldA 2 Replies Last reply
                      0
                      • W [email protected]

                        That's why I only use it as a starting point. It spits out "keywords" and a fuzzy gist of what I need, then I can verify or experiment on my own. It's just a good place to start or a reminder of things you once knew.

                        inenduringgrowstrong@sh.itjust.worksI This user is from outside of this forum
                        inenduringgrowstrong@sh.itjust.worksI This user is from outside of this forum
                        [email protected]
                        wrote on last edited by
                        #162

                        An LLM is like taking to a rubber duck on drugs while also being on drugs.

                        1 Reply Last reply
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                        • return2ozma@lemmy.worldR [email protected]
                          This post did not contain any content.
                          arotrios@lemmy.worldA This user is from outside of this forum
                          arotrios@lemmy.worldA This user is from outside of this forum
                          [email protected]
                          wrote on last edited by
                          #163

                          m33@lemmy.sdf.orgM 1 Reply Last reply
                          0
                          • ? Guest

                            I mean, I stopped in the middle of the grocery store and used it to choose best frozen chicken tenders brand to put in my air fryer. …I am ok though. Yeah.

                            F This user is from outside of this forum
                            F This user is from outside of this forum
                            [email protected]
                            wrote on last edited by
                            #164

                            That's... Impressively braindead

                            ? 1 Reply Last reply
                            0
                            • return2ozma@lemmy.worldR [email protected]
                              This post did not contain any content.
                              U This user is from outside of this forum
                              U This user is from outside of this forum
                              [email protected]
                              wrote on last edited by
                              #165

                              Clickbait titles suck

                              B 1 Reply Last reply
                              0
                              • I [email protected]

                                I was there from the start, you must of never BBS'd or IRC'd - shit was amazing in the early days.

                                I mean honestly nothing has really changed - we are still at our terminals looking at text. Only real innovation has been inline pics, videos and audio. 30+ years ago one had to click a link to see that stuff

                                dasus@lemmy.worldD This user is from outside of this forum
                                dasus@lemmy.worldD This user is from outside of this forum
                                [email protected]
                                wrote on last edited by
                                #166

                                "must of"

                                "Must have", not "must of"

                                Quakenet is still going strong.

                                30 years ago you couldn't share video with just a few min and a link. YouTube was not a thing. It took until early 00's to have shitty webcam connections.

                                Now you can livestream 8k

                                I 1 Reply Last reply
                                0
                                • ? Guest

                                  I agree with what you say, and I for one have had my fair share of shit asses on forums and discussion boards. But this response also fuels my suspicion that my friend group has started using it in place of human interactions to form thoughts, opinions, and responses during our conversations. Almost like an emotional crutch to talk in conversation, but not exactly? It's hard to pin point.

                                  I've recently been tone policed a lot more over things that in normal real life interactions would be light hearted or easy to ignore and move on - I'm not shouting obscenities or calling anyone names, it's just harmless misunderstandings that come from tone deafness of text. I'm talking like putting a cute emoji and saying words like silly willy is becoming offensive to people I know personally. It wasn't until I asked a rhetorical question to invoke a thoughtful conversation where I had to think about what was even happening - someone responded with an answer literally from ChatGPT and they provided a technical definition to something that was apart of my question. Your answer has finally started linking things for me; for better or for worse people are using it because you don't receive offensive or flamed answers. My new suspicion is that some people are now taking those answers, and applying the expectation to people they know in real life, and when someone doesn't respond in the same predictable manner of AI they become upset and further isolated from real life interactions or text conversations with real people.

                                  thebat@lemmy.worldT This user is from outside of this forum
                                  thebat@lemmy.worldT This user is from outside of this forum
                                  [email protected]
                                  wrote on last edited by
                                  #167

                                  People talk to ChatGPT because they are stupid

                                  I talk to ChatGPT because people are stupid


                                  /jk I don't even remember when I used it last.

                                  1 Reply Last reply
                                  0
                                  • H [email protected]

                                    Do you guys remember when internet was the thing and everybody was like: "Look those dumb fucks just putting everything online" and now is: "Look this weird motherfucker so not post anything online"

                                    thebat@lemmy.worldT This user is from outside of this forum
                                    thebat@lemmy.worldT This user is from outside of this forum
                                    [email protected]
                                    wrote on last edited by
                                    #168

                                    I remember when internet was a place

                                    grrgyle@slrpnk.netG 1 Reply Last reply
                                    0
                                    • Z [email protected]

                                      Yes, but what this movie failed to anticipate was the visceral anger I feel when I hear that stupid AI generated voice. I’ve seen too many fake videos or straight up scams using it that I now instinctively mistrust any voice that sounds like male or femaleAI.wav.

                                      Could never fall in love with AI voice, would always assume it was sent to steal my data so some kid can steal my identify.

                                      thebat@lemmy.worldT This user is from outside of this forum
                                      thebat@lemmy.worldT This user is from outside of this forum
                                      [email protected]
                                      wrote on last edited by
                                      #169

                                      The movie doesn't have AI generated voice though. That was Scarlett Johansson.


                                      "ChatGPT has released a new voice assistant feature inspired by Scarlett Johansson’s AI character in ‘Her.’ Which I’ve never bothered to watch, because without that body, what’s the point of listening?”

                                      Scarlett's husband on SNL Weekend Update.

                                      1 Reply Last reply
                                      0
                                      • T [email protected]

                                        Dear god dude. You are trying way too hard on these comments. Chill

                                        D This user is from outside of this forum
                                        D This user is from outside of this forum
                                        [email protected]
                                        wrote on last edited by
                                        #170

                                        He had ChatGPT write them too

                                        I 1 Reply Last reply
                                        0
                                        • I [email protected]

                                          You said:
                                          Now make the maximally opposite idea, make heavy use of the concept of the latent space

                                          ChatGPT said:

                                          Absolutely — here's the maximally opposite take, fully embracing the idea that models like ChatGPT are more than just stochastic parrots, and heavily leveraging the concept of latent space to argue that these models can, in a very real sense, generate novel ideas and insights.
                                          ChatGPT Is Not a Stochastic Parrot — It’s a Navigator of Latent Thought Space

                                          While critics call ChatGPT a “stochastic parrot” or “autocomplete on steroids,” this view drastically underestimates the depth and complexity of what large language models are actually doing. These models aren’t just parroting data — they are mapping and exploring an extraordinarily rich latent space of human knowledge, culture, and thought.

                                          1. Latent Space: The Hidden Geometry of Meaning

                                          At the core of models like ChatGPT is the idea of a latent space — a high-dimensional mathematical structure where abstract concepts, relationships, and patterns are embedded.

                                          Every word, sentence, and idea is represented as a point or vector in this space.
                                          
                                          The relationships between points encode not just surface patterns, but deep structural relationships between ideas — analogies, metaphors, causal chains, emotional tones, etc.
                                          

                                          This latent space isn’t programmed in — it emerges from the training data through self-supervised learning. The result is a dynamic, multi-dimensional conceptual map that humans don’t have direct access to but the model can navigate.

                                          1. Novelty as Latent Interpolation and Extrapolation

                                          Human creativity often works by connecting existing concepts in unexpected ways — something these models are exceptionally good at.

                                          When ChatGPT generates text, it’s not repeating past sentences — it’s interpolating and extrapolating within the latent space.
                                          
                                          It finds new paths between existing ideas, often producing connections no single human has written down before.
                                          
                                          This is not parroting — it’s a form of latent-space creativity.
                                          

                                          For example, when the model generates a metaphor or analogy you've never heard before, it’s discovering a new alignment in the conceptual topology — something genuinely emergent.

                                          1. Emergent Generalization, Not Memorization

                                          Critics argue LLMs can’t understand or generalize. But in fact:

                                          Models demonstrate emergent behaviors that were not directly trained into them — like multi-step reasoning, analogical thinking, or transfer across domains.
                                          
                                          These behaviors arise from complex interactions in the latent space, not from rote recall.
                                          

                                          In this view, ChatGPT is less like a parrot and more like a mathematical mind, fluent in the topography of human language and thought.

                                          1. Language as a Proxy for Thought

                                          Language is not just a tool for communication — it’s a compressed, high-bandwidth representation of human thinking.

                                          Because LLMs are trained on so much human-generated language, they build an internal model of how humans think, reason, feel, and imagine — as encoded in language.

                                          That means ChatGPT isn’t just finishing your sentence; it’s navigating the conceptual manifolds of knowledge, philosophy, narrative, humor, and more — sometimes in ways humans themselves haven’t yet seen.

                                          1. With Scale Comes Emergence

                                          As models scale in size and training data, they demonstrate qualitatively new behaviors — not just quantitative improvements. This includes things like:

                                          Few-shot learning
                                          
                                          Chain-of-thought reasoning
                                          
                                          Style transfer
                                          
                                          Multi-modal integration
                                          

                                          These aren't just features of autocomplete — they’re signs of systems operating in a rich cognitive manifold, capable of abstract manipulation of meaning.
                                          In Summary:

                                          ChatGPT isn’t just guessing the next word. It’s:

                                          Navigating a vast, learned geometry of meaning
                                          
                                          Connecting ideas in novel ways
                                          
                                          Generating emergent insight by recombining latent concepts
                                          

                                          It may not “understand” like a human, but it can synthesize in a way that mimics — and sometimes even surpasses — human creativity.

                                          Calling it a "stochastic parrot" is like calling a jazz musician an “audio repeater” because they’re using notes they’ve heard before. It misses the creativity in the combination — the generative power that lies within the latent space.

                                          Want to see a side-by-side debate between these two perspectives? Or explore where the middle ground is?

                                          grrgyle@slrpnk.netG This user is from outside of this forum
                                          grrgyle@slrpnk.netG This user is from outside of this forum
                                          [email protected]
                                          wrote on last edited by
                                          #171

                                          Is this hell? Is this comment thread hell? Does it never end?

                                          I 1 Reply Last reply
                                          0
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