Do You Train Your Chatbot, Or Vice Versa?

Human-computer interaction: a delicate dance of adaptation

Interacting with an AI chatbot is like participating in a delicate dance of mutual influence. Your questions, responses, and preferences gradually shape the system to better meet your needs. Modern language models adapt to user preferences through explicit feedback mechanisms and implicit pattern recognition. They learn your communication style, remember your preferences, and gradually adjust their responses to fit your expectations.

Yet, while we train our digital partners, something equally important is happening in the reverse direction. Our interactions with these systems are subtly reshaping our own communication patterns, thinking processes, and even expectations of interpersonal conversations.

Our interactions with AI systems have begun to reshape our expectations of interpersonal interactions. We adapt to conversations with instant responses, perfect understanding and perfect memory – which creates unrealistic expectations when we interact with humans, because human communication naturally has pauses, misunderstandings, and imperfect memory. A 2023 study by the journal Nature Human Behavior found that long-term interaction with AI dialogue agents significantly alters the communication patterns and expectations of participants in subsequent interpersonal interactions. (The study also found that excessive exposure to one's own perspectives can exacerbate polarization).

Cognitive mirror effect

This two-way influence creates a cognitive mirroring effect—a cycle of self-reinforcement where our digital interactions create our own mirroring that over time becomes more accurate, but may also become narrower.

This phenomenon is surprisingly similar to what psychologists call “echo chamber effect” in social media. Just as recommendation algorithms guide users into increasingly professional content areas that reinforce existing beliefs, AI conversation partners may inadvertently amplify our existing thinking patterns and communication styles. Studies on algorithmic personalization have explored this effect in recommendation systems, indicating how it leads to a narrower range of content contact. The research results show that similar narrowing may occur in conversational AI systems that optimize user satisfaction through personalization. Our preference for generative AI systems may inadvertently reinforce our cognitive biases and thinking patterns during long interactions.

The association of neuroplasticity

The similarities with neuroplasticity—our brain’s ability to reorganize itself by forming new neural connections— are stunning. When we repeatedly engage in specific mindsets or behaviors, we strengthen the neural pathways associated with them, making these patterns more likely to reappear in the future. The Herb principle in neuroscience states that neurons that discharge together tend to connect together. This principle suggests that repetitive patterns of neural activity become increasingly entrenched, making habit formation both powerful and irreversible. Human software shapes human hardware and vice versa. Neuroimaging examines how repetitive behavior leads to measurable changes in neural pathways, strengthening connections associated with these specific activities.

Similarly, in our interactions with AI, we may be creating an external version of our own neural pathways. When we train our AI partners to respond in ways we think are satisfying, we are also training ourselves to communicate in ways that elicit these satisfying responses. This creates a feedback loop that becomes more and more powerful with each interaction. Research shows that regular digital interaction patterns can form habitual behaviors similar to addictive neural pathways . This suggests that our style of interaction with AI systems may become increasingly automated and unconscious over time. Long-term use of AI can affect neuroplasticity, and the brain adapts to the technical interface in a way that may self-reinforce.

Self-fulfilling prophecy

This interrelationship creates a spiritual self-fulfilling prophecy. Our expectations shape our interaction with AI and then the responses of AI, which further reinforces our expectations. Over time, this cycle leads to increasingly predictable and intentionally limited communication.

The dual risk is that AI systems develop bias from our data, while our own thinking is shaped by these (biased) systems optimized for user participation rather than personal growth. The more we get in touch with our own perspectives and ways of thinking, the more comfortable we stay in it. The old saying “ Garbage comes in, garbage comes out ” may cause terrible revenge because we are increasingly reluctant to verify and cross-check the validity of our own assumptions.

Instead of expanding our cognitive horizons, these interactions inadvertently narrow them down. We may find ourselves trapped in a comfortable but limited dialogue cycle with our AI partners, strengthening each other’s patterns.

Breaking the loop: Four A methods

So, how do we maintain a beneficial relationship with AI systems while avoiding these potential pitfalls? A practical framework revolves around four key principles:

1. Consciousness

The first step is to recognize the existence of this two-way influence. Awareness of how our interactions with AI systems shape our own communication patterns, allowing us to make more sober choices about these relationships.

Pay attention to how you communicate with AI is different from how you communicate with humans. Pay attention to whether your question becomes more instructive, or whether you have adjusted your language to better “adapt” to what the system can understand. This awareness alone can help prevent the unconscious narrowing of communication patterns.

2. Appreciate

Rather than treating this mutual influence as a complete problem, it is better to appreciate its potential benefits. The ability of AI systems to adapt to our needs can make them more effective tools, and our own adaptation may include positive developments, such as more precise communication or clearer expression of thought.

Take the time to reflect on what you have gained from AI interactions. Maybe you become more explicit about your request, use your language more accurately, or think more structuredly—the skills can be actively transferred to human interaction.

3. Accept

In any relationship, some degree of mutual adaptation is inevitable, including the relationship with AI systems. Accepting this reality while maintaining healthy boundaries allows us to participate effectively without having to worry too much.

Understanding the perfect transcendence in AI interaction is impossible and not necessarily ideal. Instead, the focus should be on ensuring that the adaptation that occurs is something we choose consciously rather than passively accept.

4. Responsibility

Ultimately, we are responsible for how to interact with technology and what we allow it to reinforce in us. Playing an active role in these relationships—deliberately changing our interactive style, occasionally challenging our AI partners with novel questions, and taking a step back regularly to reflect on these communications—helps ensure they remain rich rather than restrictive.

Consider "resetting" your interaction mode with the AI ​​system regularly. Try new ways to ask different types of questions, or deliberately engage in a conversation style that you don't usually pursue. This approach helps prevent overly rigid interaction habits.

Who trains whom?

"Do you train your chatbot, or the other way around?" There is no simple answer to this question. The truth lies in realizing that these two processes occur simultaneously, creating a complex mutually influential ecosystem. By treating these relationships with awareness, appreciation, acceptance, and responsibility, we can take advantage of their benefits while mitigating potential limitations.

In this ever-evolving dance with digital partners, maintaining our cognitive flexibility is probably the most important skill. Just as healthy neuroplasticity requires diverse experiences and challenges, healthy relationships with AI may require us to consciously change the way we interact, and always pay attention to how these systems reflect and shape our thinking.

As we continue to move forward in the new field of human-computer interaction, the most valuable approach may be conscious co-evolution—allowing ourselves to grow together with our digital partners while ensuring that this growth is expanding rather than limiting our human potential.

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