Allow me to get to know you, mistakes and all
The author passionately argues against using LLMs to "clean up" personal messages, contending it strips away the unique human element and hinders genuine connection. This resonated deeply with some HN readers who value authenticity, but many others highlight the practical benefits of LLMs for efficiency, overcoming writing challenges, or managing corporate communication. The debate centers on where the line should be drawn between human imperfection and AI-assisted clarity, especially when the stakes are high.
The Lowdown
This post critically examines the growing trend of using Large Language Models (LLMs) to refine or generate personal and internal communications. The author argues that while seemingly innocuous, this practice fundamentally undermines authentic human connection by obscuring the sender's true voice and intent.
- LLM processing invariably removes the subtle nuances, unique phrasing, and even "mistakes" that allow recipients to build an implicit understanding of the sender's communication style and personality.
- This "genericizing" effect disrupts the vital social handshake component of communication, making it harder to interpret emotional undercurrents or the speaker's true meaning.
- The author laments that by filtering messages through an LLM, individuals rob their conversation partners of the opportunity to truly "get to know" them.
- The piece concludes with a plea for genuine, unpolished communication, advocating for the value of individual expression, even if imperfect, over AI-generated perfection.
Ultimately, the author champions the messy, human aspect of communication as essential for building rapport and understanding, urging readers to embrace their natural voice.
The Gossip
Clarity & Cognitive Catalysts
Many commenters, particularly non-native English speakers or those with conditions like ADHD, praise LLMs as invaluable tools for overcoming writing blocks, translating, or refining grammar. They argue that AI allows them to express their thoughts more effectively and clearly, bridging linguistic or cognitive gaps that might otherwise hinder their communication, proving LLMs can enhance rather than detract from their ability to convey a message.
Corporate Communication Conundrum
The discussion frequently shifts to the workplace, debating whether authenticity truly matters in corporate communication. Some argue that efficiency and professionalism often outweigh personal expression, especially in mass communications or high-volume environments, suggesting that corporate speak was already prevalent long before AI. Others highlight the potential for an 'inflate-deflate' cycle where AI inflates messages only for other AIs to deflate them, questioning the overall value.
Entitlement to Empathy
A significant counter-current challenges the author's premise that recipients are 'entitled' to discern the sender's true self through unpolished communication. These commenters assert that individuals have a right to control their self-presentation and maintain boundaries, particularly in professional contexts, and that prioritizing clarity or efficiency over raw authenticity is a legitimate personal or professional choice. This sparked a spirited debate on what constitutes reasonable expectations in communication.
Erosion of Expressive Uniqueness
Many commenters align with the author, voicing concerns about the diminishing individuality and rise of generic, 'too perfect' communication. They emphasize that LLM-generated text often strips away the subtle cues, personality, and even imperfections that imbue human interaction with richness and meaning. This genericization, they argue, can lead to a sense of alienation and a loss of personal identity in written exchanges, exemplified by observations of AI-generated performance reviews.