At Beck Digital, we spend a considerable amount of time and resources researching and engaging with new technology. AI is no exception. AI, in all of its forms, is becoming pervasive throughout nearly every industry, so we want to ensure if we’re engaging with it, that we know how to leverage its strengths while avoiding its pitfalls. If you’re interested in using large language models within your brand, we will work with you every step of the way to ensure your content is consistent with your own brand standards.
Since the advent of the AI large language models in mainstream America, the who, what, when, where, and why of content creation has changed exponentially. AI has revolutionized the world of content, design, and development, among others, and transformed how we create and consume information. When used as the tool it is intended to be, AI models allow content strategists, copywriters, academic writers, and others to generate articles, blog posts, and books – lickety-split. Which on its face seems like an amazing leap of technological application that can benefit the world. But is it? There’s more to consider than content creation as it relates to AI. There are also the many global implications, both positive and negative, that are currently being felt all over both the digital and print world. Let’s explore the benefits and limitations of using AI to understand a few of the ramifications of using large language models in content creation.
The Pros of AI
1. Efficient and Time-Saving
Large Language Models, including ChatGPT, Google Bard, GPT4, Grammarly, and many others, are changing the game when it comes to creating content. So, what do they do? They generate text at lightning speed, providing research, thought-starters, and brainstorming ideas for every kind of writer. With their enormous knowledge base, any of these models can retrieve and aggregate information at hyper speeds, saving hours and days of time-consuming research time. Many AI models also improve writing speeds by offering grammar suggestions, correcting spelling, and improving overall readability. These speedy fixes allow content creators to streamline workflows, save time, and produce even more content.
2. Productive and Scalable
Sometimes in the world of content creation, there’s more work than time to do it. AI can help. With a quick prompt like “Write me a five-sentence paragraph on making lemonade,” AI can generate coherent and relevant text much faster than traditional methods. AI can produce vast content by automating content generation tasks and thought starters and allowing content creators to focus on higher-level strategic work. Over time, you can train large language models to align with specific brand voices and styles, ensuring brand continuity and consistency.
3. Enhanced Personalization
Understanding user preferences and the behaviors that drive those preferences is critical for effective brand personalization. This tailored content can resonate with individuals on a deeper level, allowing greater engagement. How does an AI model do this? By analyzing user data through a natural language process and delivering more personalized recommendations, offers, or suggestions that are relevant to the user. Although they’re not doing it very well just yet, AI large language models can mimic the tone, style, and language to match audience preferences, allowing a greater understanding of user behavior. This personalization will provide a more immersive and interactive content experience for user engagement.
4. Language Translation and Localization
One of the biggest challenges in content creation is translating complex text into other languages. Large language models can accurately translate text from one language to another, allowing greater reach to other audiences. Because the knowledge database is so vast, it can handle the nuances of other languages during translation by calling on its enormous multilingual capabilities. The result? A more natural and authentic translation.
5. Data-Driven Insights
One of the significant advantages of using AI tools to analyze content performance is their ability to help optimize strategy, messaging, user engagement, and conversions, allowing content strategists to make informed decisions based on measurable outcomes. How do they do it? They start by collecting relevant data from various sources such as website analytics, social media platforms, or email marketing tools, giving you access to all the data you need for analysis. Another advantage of using AI for data analysis is that large language models can “clean” the data to ensure it’s compatible with the information you’re trying to disseminate or convert. It also removes unnecessary data “noise” for the most relevant information. However, this piece of the AI tool still needs to be perfected, so be sure to go back and validate your data before using it.
The Cons of AI
1. Lack of Human Creativity and Originality
As of today, AI tools like Bard, GPT4, and ChatGPT can’t write the way humans do. Why? Because large language models can’t achieve the depth, creativity, and emotional nuances a human can. So, as a result, pieces can feel generic and potentially won’t resonate with readers.
There are multiple ways in which AI tools lack the human touch, including:
• No personal perspective
Large language models can’t generate human experience, emotions, wisdom, or perspectives because they have none. They don’t have real-world interactions and are thus limited in their capacity to provide content that is rich with human experience.
• Inability to generate original ideas
You can train AI models to create content based on provided patterns and examples, but these models can’t achieve the same creativity or originality that a human can. There won’t be any cutting-edge or groundbreaking ideas springing forth naturally from the machine. It can only generate what it’s been exposed to.
• AI can’t be creative on the fly
To be creative – copywriters, content producers, and authors – all pull on knowledge and experience to produce original ideas. AI models can’t do the same thing. They can imitate or mimic creative expression but can’t have “A-HA” moments or land on an idea out of nowhere. It just can’t produce original content.
2. Overdependence on Existing Data
The content that an AI tool generates comes from patterns and information that it’s consumed in its training data. Large language models rely on existing text to generate text, meaning it can’t generate what it doesn’t know. AI tools can only “stay the course”. They cannot color outside the lines or deviate from their already available data.
3. Limited Contextual Understanding
Because AI Models can’t interpret what they’re generating, it can often lead to inaccuracies, misunderstandings, and inappropriate content. And sometimes, AI-generated content can sound robotic – as if written by a middle-schooler learning how to write an essay. Without deep knowledge of the subject, AI can produce information that is not entirely accurate, leading to a lack of credibility overall. This inability to “think” could accidentally offend or harm the intended audience.
4. Ethical Concerns
A growing concern about the rise of AI in the world is the ethical questions using AI in everyday life raises. When you use AI to generate content and then run a plagiarism checker, the content returns as original. But it’s not. Large language models pull content from a database that scours the internet for information and then generates responses based on that aggregation. Because AI models don’t know if something is true or false, they can also produce “truthy” or inaccurate content.
Additionally, there’s the whole matter of whether using AI in content generation is responsible. AI models don’t have a conscience and thus can be used to manipulate or deceive audiences, ultimately undermining trust in individuals or society. Privacy is also a huge concern since AI models can be used intentionally or inadvertently to share sensitive and personal information. If large language models aren’t used responsibly, they could easily violate ethical and legal guidelines. Transparency is essential in all things AI-related.
Using AI models in content creation is revolutionizing content creation for all of the reasons stated above. However, there is a slew of limitations and pitfalls depending on AI models for generating new content without proper oversight. As with everything in technology, using large language models correctly is all about striking the right balance between human and machine.
To learn more about how we can effectively integrate large language model learning into your content, design, development, and more, get in touch to get started!
About Beck Digital
Over the last 20 years, Beck Digital has crafted more than 3,000 custom digital solutions for leading Fortune 100 and 500 companies across multiple industries, including healthcare, nonprofit, technology, luxury real estate, and financial industries. Our recommendations stem from our profound expertise and experience across multiple channels in numerous industries. We work seamlessly within your team to ensure the solutions we develop speak to the essence of your brand and drive customer engagement every step of the way.