The emergence of AI-powered platforms has sparked a lot of debates and polarized opinions, ranging from enthusiasm to dismissive skepticism. While some fear that AI may steal their jobs, take over the world, and even destroy humanity, others are convinced that it will not have any substantial implications for them. However, as technology continues to advance, many writers and marketing specialists are asking the same question: who is better at writing, a human or LLM?
As a copywriter, I believe that any technological advancement should be viewed objectively and with balance. In this article, I would like to take a closer look at how LLMs are transforming copywriting, explore their drawbacks and use cases in the field, and explain why I believe it is unlikely that they will replace human writers soon.
How does LLM copywriting work?
Large Language Models (LLMs) are a type of AI-powered system that can understand and generate human-like text. Trained on a great amount of text gathered from various resources, these models produce responses to user prompts based on patterns and structures they have previously identified and learned.
In simple terms, LLMs predict which words and phrases are most likely to be used with other words in a given context. Although technically, their writing capabilities are based on statistics, they often do a great job of producing coherent content, ranging from generic product descriptions to writing short stories mimicking William Shakespeare’s style in less than a minute’s time. This ability to understand linguistic nuances and the context of the conversation makes LLMs incredibly efficient and cost-effective solutions for many purposes.
Can LLMs replace human writers?
While LLMs have significant capabilities for content creation, I believe that it is far-fetched to assume that AI can fully replace human writers. As a process, writing is something more than stringing together words that sound good. It involves creativity, emotional intelligence, ethical consideration, and cultural understanding, among other things. And even though LLMs can generate coherent text based on existing patterns or create ideas, so far they struggle to produce truly original text without human help.
In addition, writing requires critical thinking, judgment, and logical reasoning. Human writers use these skills to evaluate information, identify credible sources, and present balanced arguments to create a coherent narrative. Critical thinking skills also help to adhere to ethical guidelines and moral principles, especially when it comes to navigating sensitive or controversial topics. While being proficient at analyzing data, LLMs may create biased, inappropriate content if not supervised by humans. Therefore, human intervention and oversight are crucial to ensure that the text generated by LLMs is truthful, accurate, respectful, and meets the desired standards.
The drawbacks of using LLMs in copywriting
Relying on LLMs to create content is tempting due to their speed and overall efficiency. Yet, there are several drawbacks to this approach:
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False information. LLMs are only as good as the data they were trained on. Most popular LLMs learned from the data until a specific time and are not aware of new information, statistics, and recent trends. On top of that, while these tools have been trained on vast amounts of data from various sources such as articles, reviews, product descriptions, and blog posts, the accuracy of this data has not been fully assessed. As a result, being unable to differentiate between facts and fiction, the tool often ends up dreaming up (hallucinating) false facts, references, or statistics. In my own experience, I’ve noticed that it can generate false responses even if you’re simply asking it to recommend a movie or a book on a certain topic.
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Subpar quality. At their core, LLMs are statistical models, they are developed to generate the text that statistically is most likely to be the right outcome. When it comes to content creation, it often produces text that is quite stereotypical, generic, and structurally repetitive, often lacking real human touch. For instance, if you ask the LLM to create an article on a certain topic, it is quite likely to use the same or synonymous language patterns to start the text, which is, in most cases, immediately distinguishable by a trained eye.
How can LLMs help copywriters?
Having their fair share of disadvantages, LLMs can still become your content writing assistant if used properly:
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Research. LLMs can sift through and analyze large volumes of various data. As a content writer, you can use this capability to conduct research, gather data, and extract key insights on specific topics. The platforms can also provide quick answers to specific questions, which can save you a lot of time spent scrolling the internet to find the information on your own. But remember that LLMs might hallucinate information, so I still recommend fact-checking.
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Generating ideas. LLMs can help you to kickstart the writing process and get past the blank page syndrome. You can use them to brainstorm topic ideas for future articles, titles, headings, and subheadings. They can help to plan article structure and create outlines for a long content piece. These initial outputs can become your inspiration and a starting point for your articles.
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Editing. LLMs can also be helpful for polishing your text. You can use them to proofread and edit your writing for grammar, punctuation, tone, and style errors. Using natural language processing algorithms, these AI tools can provide valuable suggestions to improve sentence structure, word choice, and overall readability of your text.
Final thoughts
AI tools are here to stay. As with any technological advancement, we can either view LLMs as a threat or embrace their spectrum of capabilities to enhance our work. I stand with the second approach. By using AI writing tools, it is possible to become more productive and reduce the time and effort spent on routine writing processes. It’s a win-win situation - humans can focus on their strengths, while the AI tools provide the necessary support to enhance their work. The future of copywriting lies not in the debate about who can write a better text – a human or computer – but in the synergy between human creativity and AI efficiency.