Chapter 1: The Rise of AI in Writing

In recent times, the emergence of generative text AI has sparked significant concern among writers. Even before tools like ChatGPT gained prominence, I experienced firsthand the impact of this technology when a long-term client decided to transition to an AI writing system.

This client, although not the highest payer, had been a reliable source of income, providing me with stability in the unpredictable landscape of freelancing. I vividly recall the conversation where he suggested I shift from writing to editing. He then revealed, “I hope this doesn’t offend you, but we are moving to an AI writer.” My role was reduced to merely editing the AI-generated content, accompanied by a substantial pay reduction.

Initially, I felt despondent, fearing this marked the end of my freelance writing career. However, I soon recognized that the jobs taken over by AI were primarily low-level, SEO-focused writing tasks. Creative writing roles, on the other hand, remained largely unaffected.

Despite the introduction of more advanced technologies like ChatGPT, the core principle stays the same: these large language models are built on extensive datasets of human language. Since they rely on existing words, they inherently lack true innovation and creativity.

Here is an insightful video on the topic:

Chapter 2: The Mechanics of AI Writing

These AI models operate by identifying statistical patterns in language rather than genuinely understanding the text. For instance, transformer models, like those underpinning ChatGPT, analyze the context of words based on their placement in sentences.

To illustrate this, consider a scenario described by philosopher John Searle in his Chinese Room Argument. He imagined a person who, despite being locked in a room filled with Chinese symbols and instructions, could produce correct responses without truly comprehending the language. Similarly, AI models generate responses based on learned patterns without any real understanding of meaning or intention.

To delve deeper into why AI isn't the end of creativity, watch this video:

Chapter 3: The Limitations of AI Creativity

Moreover, AI's design limits its creative potential. These models are optimized to produce grammatically correct responses, often at the expense of originality. Unconventional word combinations—like ‘minty flames’ or ‘bright black’—are unlikely to emerge from an AI, as they typically avoid phrases that fall outside the norm.

On a bell curve, AI developers aim for results that are statistically typical (the median), minimizing the chances of generating nonsensical output. However, this approach simultaneously restricts the model's ability to produce innovative language that reflects human creativity, such as compelling marketing taglines.

Additionally, AI lacks the personal experiences and insights that enrich human writing. It cannot draw from life stories or unique perspectives that lend depth to creative expression. Instead, it regurgitates content already available on the internet.

Chapter 4: Finding Purpose Beyond AI

While the rapid advancement of AI technology does raise concerns, it's crucial to recognize that a large language model, constrained by its normative framework, will never capture the essence of human experience, cultural knowledge, or the creativity necessary for impactful writing.

In my case, AI has ultimately enhanced my writing journey. I no longer focus on producing content solely for SEO purposes. Instead, I can channel my energy into writing about subjects that resonate with me personally, utilizing my creativity to craft original works.

Regardless of how sophisticated AI becomes, the unique perspective and creativity of the human writer will always prevail.