The world of content creation is undergoing a seismic shift thanks to the rise of artificial intelligence (AI). A new wave of automated writing software, powered by advanced natural language processing models, is making it possible to generate articulate, persuasive text with just a few clicks. From social media captions to SEO-optimized blog posts, AI is automating the writing process like never before.
As an AI researcher and content strategist, I‘ve had a front-row seat to the development of these tools and the impact they‘re having on the industry. There‘s no doubt that automated writing software has the potential to be tremendously beneficial for businesses and content teams. But there are also valid concerns and risks to consider. In this article, I‘ll share an insider‘s perspective on the pros, cons and future of AI-powered writing.
The Evolution of Language AI
To understand the capabilities of today‘s automated writing software, we first need to look at the cutting-edge AI that powers it. The key enabler has been the development of massive deep learning language models over the past few years.
Back in 2018, Google released a model called BERT (Bidirectional Encoder Representations from Transformers) that made waves in the natural language processing world. By learning from huge troves of online data in a more generalized way, BERT was able to establish new benchmarks for tasks like question answering, text classification and sentiment analysis.
Not to be outdone, OpenAI upped the ante in 2019 with the release of GPT-2 (Generative Pre-trained Transformer 2). With 1.5 billion parameters, it was 10X larger than previous language models and capable of generating impressively fluid text. OpenAI actually deemed it too dangerous to release in full at first due to concerns over how it could be misused for disinformation.
But the real game changer came in 2020 with GPT-3. Trained on nearly 500 billion tokens from across the internet, it boasted an astonishing 175 billion parameters. For the first time, a single AI model was able to perform at human-level or better across a wide range of language tasks, from translation to question-answering to creative writing. And it did it all without any task-specific fine-tuning, using few-shot learning to adapt to new prompts.
GPT-3‘s ability to generate cohesive articles, stories and scripts with just a small amount of input text was unprecedented. It quickly became the foundation for a new generation of AI writing tools like Copy.ai and Jasper.ai that aimed to put this technology in the hands of businesses and content creators.
Rapid Adoption of AI Writing Tools
It didn‘t take long for automated writing software to start catching on. The lure of being able to generate high volumes of fairly high-quality content quickly and cheaply was strong for teams struggling to scale production. And the tools were rapidly evolving to support an expanding range of formats, tones and styles.
According to a survey by Content Marketing Institute, the percentage of marketers using AI for content creation nearly doubled from 13% in 2020 to 25% in 2021. And that number is expected to keep climbing as the tools mature and awareness grows.
Another study by Semrush found that 46% of businesses were planning to invest in AI writing software in 2022, with 42% specifically looking to use it for SEO and content marketing purposes.
Early adopters are reporting impressive results and ROI. Jasper.ai, one of the leading AI writing platforms, touts that its users are able to increase content production by up to 5X while cutting costs by 50% or more. And case studies show companies generating anywhere from a few dozen to over a thousand machine-written articles per month.
Benefits of Automated Writing for Content Teams
Having tested many of these tools myself, I can attest to their potential for content creation. The best AI writers are able to achieve some astounding feats and confer a number of powerful benefits:
1. Accelerating Idea Generation
One of the most common challenges content teams face is coming up with a steady stream of new topics to write about. It can be a constant struggle to ideate angles that are both novel and relevant to target audiences.
AI writing tools excel at rapidly generating content ideas from small amounts of input. Just enter a focus keyword and some context, and you can get back dozens of thought-starters in seconds that actually make sense (for the most part). This is a huge time-saver in the brainstorming phase.
2. Enabling Impressive Output Speeds
With a human writer, crafting a 1,000-word blog post might take anywhere from a few hours to a few days depending on complexity. An AI like GPT-3 can spit one out in a matter of seconds. Even if significant editing is still required, that‘s an order of magnitude faster. scale across an entire content calendar, and the efficiency gains are game-changing for keeping up with demanding publishing schedules.
3. Unlocking Cost Efficiencies
All of that speed also translates into meaningful cost savings when compared to human labor. A full-time content writer might cost $50K+ per year, whereas many of the AI writing tools top out at a few hundred dollars per month for unlimited generation. The cost per article or post can easily drop into the low single digits, making high-volume production vastly more economical.
4. Enhancing Writer Productivity
Staring at a blank page is the bane of many writers‘ existence. There‘s evidence that AI writing tools can help bust through that writer‘s block by providing a launching off point. Instead of agonizing over how to get started, writers can lean on the machines for that first 80% and then take it the last mile with their own polish and flair. I‘ve found my own writing output increasing since I started using the tools this way.
5. Assisting with SEO Research
While human intuition is still invaluable for SEO, some of the leading AI writing tools are getting quite adept at baking best practices into their outputs. Frase and CopySmith are two that come to mind for their ability to analyze top-ranking content and provide automated optimization suggestions on elements like keyword usage, heading structure, sentiment and reading level.
Having this extra algorithmic guidance can help content stay in line with the latest search ranking factors.
Hazards and Hurdles of AI-Generated Content
For all the potential upside, we can‘t ignore the pitfalls and limitations of automated writing software in its current form.
1. Lack of Fact-Checking and Accuracy
One of the biggest weaknesses of AI writing tools is that they can confidently generate false or inconsistent information. They have no inherent sense of what‘s factual – they simply predict the next most plausible sounding words based on patterns they‘ve ingested. While some of the tools are starting to add features like citations and data integrations, the burden is still on human editors to verify every claim. Publishing mistakes can damage reputations.
2. Risk of Repetitive, Shallow Output
Although language models like GPT-3 can string words together in impressively fluid ways, they still struggle with long-term coherence and originality. They have a tendency to get stuck in ruts, repeating variations of the same phrases and ideas. And while the writing may seem plausible at a surface level, it often lacks the deeper insights that come from real subject matter expertise. Raw AI output usually feels generic and lacks a strong point of view.
3. Potential for Plagiarism and Content Spam
The worst case scenario is that businesses abuse AI writing tools to mass produce low-quality, auto-generated content at a rate that pollutes the web. While truly egregious cases might get flagged as spam by Google and other search engines, there‘s valid concern that a flood of mediocre machine-written content could degrade the overall search experience. Even if the plagiarism is unintentional, too much AI output without human oversight could trigger algorithmic penalties.
4. Uncertainty Over SEO Policies and Enforcement
Google has never outright said that automatically generated content is against its guidelines. But it has consistently espoused the importance of unique, high-quality, user-focused content as an SEO best practice. As the capabilities of AI writing tools grow, it‘s still a bit of a gray area as to where the search giant will draw the line and how it might enforce those standards at scale. Content teams should be cautious about going all-in on AI without clear policies in place.
5. Anxiety Over Writer Displacement
Perhaps the biggest concern is how the rise of automated writing software could impact the livelihood of professional writers and content creators. Many fear being replaced by machines that can work faster and cheaper. While I believe the most likely outcome is that AI will be a net positive in augmenting rather than eliminating writing roles, the transition could be bumpy. Writers who can‘t adapt their skills to work alongside AI may struggle to stay relevant unfortunately.
Responsible Best Practices for AI-Assisted Writing
Having weighed both the benefits and risks, I firmly believe that automated writing software is here to stay and will only keep improving. The key is to develop frameworks for using it effectively and ethically to unlock its potential while mitigating the hazards.
Some best practices I‘d recommend:
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Position AI as an assistive tool, not a human replacement. Use it to accelerate parts of the workflow (research, outlining, drafting), but keep people in the loop for oversight and refinement.
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Implement clear content quality control processes. Have guidelines in place for fact-checking claims, catching inconsistencies, adding original insight and massaging pieces to align with brand voice.
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Don‘t over-optimize for algorithms at the expense of readability. Focus first on creating authentic value for target audiences vs. gaming search rankings through volume.
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Be transparent about the use of AI in the content production process. Disclose when and how it was used to maintain trust.
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Continuously monitor search engine policies around AI content. Stay apprised of the latest guidance from Google and others to avoid running afoul of spam flags or demotion.
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Prioritize upskilling writers to work alongside AI vs. wholesale role elimination. Focus on developing their subject matter expertise, analytical abilities and knack for compelling narratives.
The Future of AI-Powered Content Creation
Looking ahead, I believe we‘ll see automated writing software continue to evolve in sophistication at a rapid clip. With companies like Google, Meta and DeepMind all making big investments in foundational language AI research, even more massive and capable models are surely on the horizon.
I wouldn‘t be surprised if GPT-4 makes an appearance within the next year or two, potentially adding multimedia capabilities for generating images, audio and video in addition to text. We‘ll likely see an explosion of more specialized AI writing tools purpose-built for different industries, content types and platforms.
Content itself will become more dynamic and intelligent, with the ability to adapt to individual users‘ personalized contexts and queries in real-time. The lines may start to blur between content that is explicitly written by humans vs. AI vs. a combination of both.
As a result, I expect the primary role of content teams to shift more heavily toward prompt engineering, quality assurance and AI management vs. raw content generation. But there will still be a vital place for talented writers and subject matter experts who can interpret data, shape narratives and connect with audiences on an emotional level. The machines are nowhere close to replicating those higher-order skills.
Ultimately, I predict that we‘ll reach a point in the not-too-distant future where most published content on the web has been touched by AI in some way. The key will be developing scalable standards and systems to ensure that this content is genuinely valuable and trustworthy vs. spammy or misleading.
Embracing Augmented Creativity
No matter how you slice it, AI is poised to profoundly reshape the way we create and consume content. Automated writing software is one of the most tangible manifestations of this shift. And while it‘s still early days, the impact is already reverberating across the industry.
As someone who has built a career around content, I‘ll admit that the idea of machines writing articles was a bit unnerving at first. But the more I‘ve experimented with the tools, the more excited I am for their potential to streamline and democratize the creative process.
To me, AI at its best is about augmenting and enhancing human capabilities, not replacing them outright. It‘s a powerful source of leverage and inspiration when used intentionally. Far from stifling creativity, I‘ve found these tools to be an incredible sandbox for exploring ideas and sparking new ways of thinking about old topics.
So while I have immense respect for the art and craft of writing, I don‘t believe AI is here to disrupt it so much as evolve it. The goal should be to embrace the algorithms as partners in the process, using our uniquely human editorial judgment as the differentiating factor.
Automated writing software is a tool like any other – its impact ultimately depends on how we choose to wield it. We can use it exploitatively and deceptively for a quick buck, or we can use it to democratize knowledge-sharing and storytelling at a scale never before possible.
My hope is that the content community will rally around the latter path – seizing the opportunity to reach more people with resonant ideas while preserving the integrity and value exchange that makes great writing so essential in the first place. There‘s room for both bits and neurons in the prose of tomorrow.
