{"id":71381,"date":"2025-04-15T23:23:54","date_gmt":"2025-04-15T23:23:54","guid":{"rendered":"https:\/\/wellvyl.com\/media\/?p=71381"},"modified":"2025-04-15T23:34:22","modified_gmt":"2025-04-15T23:34:22","slug":"the-hidden-cost-of-letting-ai-do-the-talking","status":"publish","type":"post","link":"https:\/\/wellvyl.com\/media\/the-hidden-cost-of-letting-ai-do-the-talking\/","title":{"rendered":"The Hidden Cost of Letting AI Do the Talking"},"content":{"rendered":"\n
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I feel them\u2026 don\u2019t you? The expectations\u2026 to respond instantly, to make that message perfect, to stay on top of my mountain of emails and other messages. And so I\u2019m grateful\u2014I really am\u2014for predictive text and AI tools that write for me, edit my hurried attempts, and take the edge off of messages that came out a little sharp. The rapid adoption of these tools around the world is creating no less than a revolution in the history of human communication.<\/p>\n\n\n\n

But just as cars made us lazier about walking and texting has made us lazier about calling, I also wonder how this shift is going to worsen our dependency on machines and, consequently, our social isolation (for more on that, see my article, \u201cHej! Howdy! and Other Small Steps in the Right Direction\u201d<\/a>).<\/p>\n\n\n\n

The 2013 movie, Her<\/em>, opens with a scene of Joaquin Phoenix writing love letters and greeting cards for his employer\u2019s customers because he can write better ones than those who know their loved ones intimately (or do they?). Twelve years later, Large Language Models (LLMs) can write these love letters for us for free, or even better ones for a fee. They can also write emails to our boss, our colleagues, the leads we\u2019d like to convert to clients, or the people we\u2019d like to convert to our way of seeing the world.<\/p>\n\n\n\n

In Her<\/em>, Joaquin\u2019s use of technology comes at a price\u2014which I won\u2019t spoil for you in case you still need to see it. In real life, what will be the cost we pay for outsourcing our communication to AI? How will reliance on LLMs reshape our ability to connect authentically, communicate effectively, and understand one another?<\/p>\n\n\n\n

AI’s Impressively Imperfect Mimicry<\/strong><\/h2>\n\n\n\n

LLMs have a remarkable capacity for generating coherent, correctly-spelled and punctuated responses, undoubtedly improving the clarity of written communication. <\/sup>They can bridge language barriers through real-time translation and tailor messages to specific audiences and contexts. Trained on immense datasets of human text, LLMs are learning to emulate human communication patterns with increasing sophistication.<\/p>\n\n\n\n

Perhaps most impressively, research indicates that LLMs can exhibit elements of cognitive empathy<\/em>\u2014the ability to recognize emotions in written communication and provide contextually appropriate, supportive responses. Studies evaluating models like ChatGPT-3.5 and GPT-4 have found they can perform well on empathy-related tasks, sometimes even being preferred over human responses<\/strong> in specific scenarios. <\/p>\n\n\n\n

There is an important difference, however, between cognitive empathy<\/em> (understanding feelings) and affective empathy<\/em> (genuinely experiencing or sharing those feelings). LLMs, lacking the ability to have genuine emotional experiences, excel at the former but are incapable of the latter. Their sympathetic responses are sophisticated pattern matching, not felt understanding. LLMs do not “understand” text in the human sense of that word; their responses are based on statistical patterns in data, not true comprehension.<\/p>\n\n\n\n

The Costs of Outsourcing Communication<\/strong><\/h2>\n\n\n\n

Note:<\/em> what follows is not a call to abandon the use of LLMs or other AI tools. That horse has left the barn. It is a note of caution about the unintended, negative consequences of this revolution that we are only just beginning to see.<\/p>\n\n\n\n

So, let\u2019s say that LLMs can mimic empathic human communication perfectly, or will soon be able to; a dependency on AI to write for me also has a dark side: the loss of authenticity and the uniqueness of my voice. If you\u2019ve used LLMs at all, you\u2019ve likely noticed that the outputs generated or influenced by LLMs often feel robotic, impersonal, and generic. <\/sup>AI tools are prone to clich\u00e9s, formulaic language, and hackneyed phrases (“In today\u2019s rapidly changing world\u2026”, “Harnessing the power of\u2026”) that signal machine learning rather than original thought. Unique elements like personal anecdotes, contextual understanding, timing, vulnerability, and emotional nuance\u2014qualities that build connection and convey sincerity\u2014are lost on AI (at least for now).<\/p>\n\n\n\n

The result is an authenticity deficit. Communication that feels overly polished, automated, or otherwise inauthentic erodes trust and the writer\u2019s reputation. People connect with perceived effort, personality, and sincerity\u2014attributes that AI cannot (yet) replicate convincingly. When communication feels robotic, it creates distance, making the sender seem disconnected, predictable, and even tone-deaf.<\/p>\n\n\n\n

Research reveals an intriguing authenticity paradox. While using AI-generated “smart replies” can increase communication speed and emotional positivity, the knowledge<\/em> or suspicion<\/em> that AI is involved triggers significantly negative perceptions in the reader. People evaluate communication partners they suspect are using AI as less cooperative, less affiliative (less interested in connection), and more dominant, even if the AI objectively improved certain metrics of communication (e.g., positivity). In other words, the upside of AI-assisted writing may be outweighed by distrust and other downsides. The perceived lack of genuine thought or intention behind AI-generated messages negates the efficiency gains. <\/sup>The process and perceived source of the communication appear to matter as much, if not more, than the polished output itself.<\/p>\n\n\n\n

More importantly, human communication does much more than just convey information. Kindness, constructive feedback, empathy, social nuances, active listening, and expressing oneself honestly are not innate talents but abilities developed over time through interaction, effort, and practice. These skills are vital for building strong relationships, fostering understanding, and maintaining personal well-being, and must be skills that humans can perform in-person<\/em> and verbally, not merely in writing. <\/p>\n\n\n\n

Reliance on LLMs (as opposed to the use <\/em>of them) carries the risk of dependency and downskilling<\/em>. The concern here is that AI-dependency in our digital communication can spill over into our face-to-face interactions as well, limiting our capacity for unassisted, real-world conversations. Consistently outsourcing communication to AI limits our own opportunities for practice in the same way that my son delegating his subtraction problems to Alexa limits his opportunity to learn. Outsourcing our communication to LLMs becomes a crutch that limits our personal capabilities, diminishing our capacity to communicate independently and our adaptability when faced with novel situations.<\/p>\n\n\n\n

Several skills seem particularly vulnerable to downskilling:<\/p>\n\n\n\n