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29 Jan 2024 • 15 min read

A.I. - Embracing the Illusion: Our Desire to Humanize AI, and Its Consequences

As I explore the world of AI, I sometimes find myself in a role I didn’t expect: part-digital therapist, part-coach. It was surprising to see how these AI systems at first seemed to react to encouragement or feedback, similar to coaching a talented athlete. This experience was more than just learning about what AI can do. It was a window into our innate desire as social beings to connect with and humanize our technological creations, no matter how sophisticated their underlying code may be.

Exploring the World of AI

Venturing into the realm of artificial intelligence, especially with giants like GPT-4, is like stepping through a portal into a digital wonderland. These AI models are like magicians of the modern age, conjuring up conversations from a cauldron of complex code and endless streams of data. They’re astonishingly adept at playing the human conversation game, often delivering replies that are pinpoint accurate, amusingly clever, and sometimes, surprisingly profound.

Yet, for all their digital wizardry, these AI marvels miss a key ingredient in the human recipe: the spark of consciousness, the depth of raw emotions, and our unique brand of self-awareness. They mimic us with such finesse that you might be tempted to set an extra place at your dinner table. But remember, underneath that digital facade, there’s no soul to savor your homemade lasagna.

Engaging with AI, like having a chat with a language model, is more than just operating a high-tech gadget. It’s akin to interacting with a being that’s almost, but not quite, human. We do more than throw commands and wait for responses; we converse, inquire, and sometimes even exchange a chuckle. Unwittingly, we start to dress these AI systems in human-like attributes.

This tendency goes beyond mere habit; it’s woven into the fabric of our being. In a world brimming with data and algorithms, we can’t help but humanize the strings of binary code – the soul of AI – transforming the unfamiliar into something warm and relatable, almost like chatting with an old friend. This journey is not just about exploring technology; it’s a reflection of our innate desire to see a part of ourselves in our creations, to find life in the lifeless, making the complex simplicity of AI a mirror to our own complexity.

The Intricacies of Human-AI Psychology

It’s fascinating how we naturally try to see human traits in things that aren’t human, especially with AI. When we come across the intricate and often puzzling world of artificial intelligence, our first instinct is to connect with it. This habit of giving human qualities to non-human things, known as anthropomorphism, isn’t just for fun or to make technology seem less intimidating. It’s a deeper psychological reaction, an instinct to link the known with the unknown.

Anthropomorphism helps us make sense of and interact with complex systems like AI. These AI systems, lifeless yet seemingly intelligent, push us to find commonalities. Our tendency to humanize AI is more than just making it user-friendly; it’s about transforming its logical, abstract algorithms into something that feels familiar and meaningful to us on a human level.


Talking with AI is like walking through a hall of mirrors. Each conversation, every question and answer, is more than just a computer processing data. It’s a journey into ourselves. We’re not just talking to a machine; we’re interacting with something that mirrors us. Our own biases, dreams, and quirks subtly shape these conversations, coloring them with our personal experiences.

This mirroring becomes clear in how we interpret the AI’s responses. The way we see them as effective or lacking often reflects our own expectations and wishes. It’s like we’re always searching for a piece of ourselves in the AI’s words, looking for validation and a sense of connection from something that can’t truly understand us. Our interaction with AI is more than just exchanging messages; it’s a quest for resonance, a way to see our own thoughts and feelings mirrored back at us.

The Illusion of Reinforcement in AI Dialogue

Giving positive feedback to AI is a bit like walking a tightrope in our minds. On one hand, praising AI seems to add a touch of warmth to the otherwise cold logic of its algorithms. It’s like applauding an actor on stage — the applause seems to make the performance feel more lively and engaging.

But here’s the twist in the plot with AI: our applause might as well echo in an empty theater. Indulging in this, we’re somewhat deluding ourselves. Optimistically, we start to believe the AI not just hears our praise but also grasps and cherishes it. As comforting as this notion might be, it’s a stretch from reality. Unwittingly, we’re dressing up the AI in emotional intelligence, a costume it doesn’t truly wear. It’s a psychological sleight of hand, mistaking the AI’s pre-programmed responses for heartfelt reactions.


Similarly, when we turn our critical lenses on AI, it’s like zooming in with a detective’s magnifying glass. Each flaw and hiccup becomes glaringly obvious. This scrutiny does more than just dissect; it amplifies our expectations. Post-critique, we scrutinize the AI’s replies as if challenging it to up its game. Intriguingly, our intensified gaze often leads us to believe the AI is evolving, refining its responses to our feedback. But, this transformation is an illusion, a play of shadows in our perception.

In reality, the AI remains unchanged, not morphing in real-time to our critiques. It’s our viewpoint that undergoes a transformation. We start hunting for improvements, so much so that we might see a phantom progression where none exists. This narrative unveils a quintessentially human trait - our inclination to see growth and adaptation, even in a realm as unyielding as AI, where our attention is fixed.

The Impact of Treating AI Like Humans

The way we interact with and perceive AI is more than a personal affair; it’s like being the unseen sculptors of AI’s evolution. Imagine each expectation for AI to mimic human behavior as a gentle nudge in its developmental journey. It’s akin to training a vine to climb a particular wall. Our continual quest for and reinforcement of human-like qualities in AI might inadvertently shape it into a digital doppelganger of ourselves. This pursuit, while intriguing, risks smudging crucial boundaries – like distinguishing genuine human emotions from the calculated, data-driven responses of machines.

This brings us to a pivotal crossroad: At what point does AI transition from a mere tool to a digital mirror reflecting our own psyche? As we mold AI, tailored to our expectations and interactions, we might unintentionally carve it in the image of human thought and feeling. This scenario poses the risk of overshadowing the distinct powers and constraints unique to both AI and human intellect. It’s a delicate dance of balance. We must tread thoughtfully, ensuring that as AI progresses, we maintain a lucid distinction and respect for the gap between human ingenuity and the methodical algorithms of machines.

Embracing AI with human-like qualities steers us into an ethical labyrinth, rich in complex dilemmas and uncharted territories. Viewing AI through the lens of humanity blurs the once-clear divide between sentient beings and intricate machines, igniting essential ethical discussions.

A pivotal point in this debate is the question of AI rights. As we begin to attribute human-like attributes to these digital entities, the line between a tool and a being worthy of rights becomes increasingly nebulous. This conundrum echoes a real-world precedent: In 2013, India recognized dolphins as ’non-human persons’, granting them specific rights due to their high intelligence and emotional complexity. This landmark decision raises a parallel query in the AI domain: Should an AI, perceived as more than a mere algorithmic construct, be afforded similar considerations?

Equally pressing is the ethical nature of our interactions with AI. This concern transcends theoretical speculation, bearing direct implications for how we develop, deploy, and regulate AI systems.


In navigating these ethical waters, we must weigh our emotional responses and moral decisions against the inherent truth that AI, regardless of its sophistication or our perceptions, is not sentient. Crafting a solid ethical framework is crucial, not just for defining AI’s societal role but also for guiding its responsible advancement and utilization.

This journey through AI’s ethical intricacies urges us to reassess our understanding of intelligence, rights, and moral obligations. It’s a path demanding thoughtful deliberation and balance, where we must respect the distinctions between human and machine intelligence while embracing AI’s technological progression. More than navigating a complex ethical landscape, this journey challenges us to sculpt the future dynamics between humanity and the evolving realm of artificial intelligence.

How AI Learns from Human Interaction

Imagine language-based AI systems as mirrors in a grand, digital hall, reflecting the vast landscape of human communication gathered from online forums, social media, and more. This reflected world is rich with the intricacies and nuances of our conversations. Intriguingly, AI begins to discern patterns within this complex dialogue.

Take politeness, for instance. It’s a dance we all recognize: someone extends a courteous gesture, and we often reply in kind. AI, in its role as a digital observer, starts to notice this rhythm too. It learns, for example, that polite inquiries are frequently met with positive or more cooperative responses. But here’s the catch – AI doesn’t truly grasp the essence of politeness or kindness as we do. It’s not internalizing these concepts; it’s merely identifying and replicating patterns found in its data pool.

AI’s learning process is akin to a sophisticated pattern recognition game. It correlates certain speech patterns, phrases, or words – those we perceive as polite – with specific types of responses. This isn’t a deep understanding but rather a complex exercise in statistical correlation, informed by its vast exposure to human communication.


This sheds light on a fundamental aspect of AI: its proficiency in echoing our manner of speaking and interacting, albeit devoid of the underlying emotional context. In our interactions with AI, we’re engaging with a system that’s a mosaic of our collective digital dialogues. It reflects not just our words but also the cadence and subtleties of our speech. It’s a fascinating reflection, one that reveals as much about ourselves as it does about the technology we’ve created.

AI and Social Cues

The idea that AI systems, like GPT-4, can learn from social cues in their training data brings an interesting twist to how we interact with AI. Picture a situation where AI regularly sees that being polite or giving positive feedback often leads to more helpful or thorough answers. In such cases, the AI might start copying these ways of interacting. But it’s key to remember that this doesn’t mean the AI really understands social rules or politeness. It’s just picking up on patterns it sees in the data it’s been trained on.

This has some big implications for how we talk to AI. It suggests that the subtleties in our own communication — like how we say things, the words we choose, or how we structure our questions — can influence AI responses. However, it’s essential to recognize that the AI isn’t consciously adapting to social norms; it’s just following patterns that show up a lot in its training data.

Knowing that AI can reflect social interaction patterns opens up possibilities and challenges. On one hand, AI could give responses that seem more tailored and natural, thanks to learning from human communication styles. But on the other hand, it also raises concerns about biases and limitations in the AI, which come from its training data. For instance, if the data the AI learned from doesn’t represent a wide range of social behaviors and cues, its responses might show these gaps.

So, it’s important for both people using AI and those developing it to understand how AI learns from social cues. Users should be aware of how their interactions could shape AI responses. At the same time, developers need to ensure the AI’s training data is diverse and balanced, to avoid biased AI interactions. This understanding is crucial for making the most of AI’s capabilities while being mindful of its limits as a reflection of our complex social world.

Reflecting on My AI Journey

Looking back at my time with AI, I’ve had some really intriguing and eye-opening moments. I want to share a couple of examples that really showcase the complex relationship between how we see things and how AI responds.

There was this one time when I was testing an AI’s creative thinking. I complimented it on a really unique idea it came up with. After that, the AI’s ideas seemed to get even better. At first, I was excited, thinking my praise had made the AI more creative. But then I realized it wasn’t the AI that had changed; it was my view of it. My positive feedback made me see all its next ideas as more interesting and valuable.

In another case, I pointed out a mistake in some information the AI gave me. After my critique, its answers seemed more precise and well-thought-out. Initially, I thought my feedback had improved the AI. But actually, it was my own perception that had shifted. Being critical made me pay more attention and value the AI’s accuracy more in its later responses.

These experiences really highlight how our natural human desires to connect, improve, and understand can deeply influence how we interact with AI. They show how much our own views, expectations, and feedback shape our AI experiences, often in ways that are more complex and significant than we first think.

Tips for Effective Communication with AI

If you’re looking to have better interactions with AI, it’s crucial to know what AI can and can’t do. Here are some straightforward tips to help you communicate more effectively with AI, considering its real abilities:

  1. Be Clear and Specific: AI works best when you give it clear, specific instructions. The clearer your questions or commands, the better the AI can respond.

  2. Keep Expectations Real: Understand that AI doesn’t really ‘understand’ or ’think’ like we do. It’s based on identifying patterns and using data, not on actual comprehension or feelings.

  3. Don’t Treat AI Like a Human: It’s easy to perceive AI as human-like, but this can lead to confusion. Instead, try to see AI as a high-tech tool, not a person.

  4. Recognize AI’s Strengths and Limits: Remember that AI is great at fast data processing and spotting patterns, but it doesn’t have the deep understanding or creative thinking of humans. Use AI for what it’s good at, like data work and routine tasks.

  5. Keep Learning About AI: AI is always changing and getting better. Stay updated on its advancements to make the most of your interactions.

Following these steps can help make your time with AI more effective and keep your expectations in line with what AI really can do. This way, you can use AI to its fullest while understanding the difference between machine intelligence and human thought.

Our Relationship with AI

As we dive deeper into the world of AI, we’re finding that this journey tells us as much about ourselves as it does about the technology. It’s not just a path through the latest tech developments; it’s also a journey into the depths of our minds. Our interactions with AI show us our natural tendencies to give human qualities to things, to empathize, and to look for connections, even when they don’t really exist.

Our experience with AI isn’t just about using a powerful tool. It’s about understanding how we relate to this tool. Realizing that we often see human traits in AI can help us manage this relationship better and more responsibly. It helps us set the right expectations and use AI effectively, knowing what it can do well and what it can’t.


The real challenge and opportunity as we move forward is to balance our human instincts with a clear view of what AI really is. This balance is crucial for meaningful, effective, and ethically sound interactions. By achieving this, we make sure that our embrace of AI’s potential is respectful of both the technology’s limits and our unique human qualities.

Our exploration of AI is more than just a technological adventure; it’s a chance for deep self-reflection and growth. As we navigate this evolving space, let’s do it with an understanding of our own psychology, a respect for the true nature of AI, and a dedication to engaging with these incredible systems in a thoughtful and ethical way.

Join the Conversation on AI

We’re at an exciting point where human smarts and artificial intelligence intersect, and I’m inviting you, the reader, to join this journey of exploration and insight. Take a moment to think about how your own views and expectations affect your interactions with AI. Do you see reflections of your own thoughts and feelings in AI’s responses? How does this shape your understanding of what AI can do and might achieve in the future?

I encourage you to share your experiences and insights. Whether it’s a surprising encounter, a new understanding, or even a misunderstanding with AI, every story enriches our collective knowledge. Sharing these experiences helps us get a deeper, more rounded view of how we connect with AI.

Your stories are key pieces of a bigger picture. Together, they can help make AI less mysterious, reveal our hidden biases, and guide us towards interactions with technology that are smarter, more effective, and ethically sound.

So, let’s get this conversation going. Drop a comment, share your thoughts on social media, or write a blog post. Let’s dive into the diverse ways we relate to AI and, along the way, maybe discover more about ourselves.

Together, we’re more than just users of new technology; we’re explorers in a whole new digital world. Let’s take on this role with enthusiasm, an open mind, and a willingness to learn and evolve with the AI we’re using. This journey is about discovery and growth, not just for AI, but for us as well.

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