Can Google Algorithm Detect AI-Generated Content?

Amid increasing digitalization, Artificial Intelligence (AI) has gained a significant traction among wide businesses and consumer base. It has often proven a broader acceptance in the field of content creation, especially due to spike in demand from digital marketing applications. On the other hand, such brand-new technology gradually evolves, and hence, plays a crucial role in personalized content marketing. This eventually causes personalization to move to greater heights.

Even marketers today have left behind generalized email marketing campaigns with the support of AI-powered tools that can create personalized marketing content. For instance, Jasper, Grammarly, and CopyAI, to name a few, are the most commonly used AI tools that can assist with idea generation during content creation and personalized writing. Also, Persado, a Motivation AI platform, uses machine learning technologies to analyze audience management data and relevant topics. Similarly, in November 2022, OpenAI has unveiled ChatGPT, an incredibly AI-powered tool, capable of generating ideas for stories and articles depending on a set of user-defined parameters. Conclusively, these tools can be further used for keyword research, in turn, speeding up the content creation process and produce SEO-friendly results. Therefore, AI-generated content is considered to be imperative and brings engagement together with better lead generation.

Furthermore, due to the incessant rise in marketing content through various enterprises alongside the sizeable business transition from conventional to online dimensions, there is more demand for content nowadays. As per the Hosting Tribunal, roughly 600 million blogs were valued as of 2021. In addition, there are almost 6 million blog posts on a daily basis. This implies that marketers have considerable pressure to make content SEO friendly. Also, creating such content requires more resources and precise algorithms. In this way, AI finds meaningful application to generate content with limited resources and costs. The below figure depicts the application of AI for content generation:

Figure 01: Contribution of AI in different applications

Source: AMR Analysis

According to several research studies, it is found that nearly 61% of marketers use AI tools for email marketing, followed by advertising (56%), and data analysis (54%). Interestingly, there are almost one-third of marketers using AI for content generation. Therefore, the application of AI has increased in the field of content creation. As a result, several companies around the world have realized the immense potential of generative AI and thus are planning to enter into the market by means of strategic developments and initiatives to diversify their product offerings in the market. For instance,

• In January 2023, Chinese search giant Baidu has proclaimed that generative AI will be a prime focus of its hyperscale cloud and remains a key interest in the near future. The firm also plans to launch its AI chatbot this year, immediately after the successful completion of internal testing. The chatbot is named Enhanced Representation through Knowledge Integration (ERNIE) Bot and can perform tasks ranging from language generation and comprehension to text-to-image generation.
• Likewise, in February 2023, Microsoft unveiled its new version of Bing Search and Microsoft Edge, both powered by ChatGPT. These newer developments are expected to incorporate meeting notes & recommended tasks and assists in creating meeting templates for users. The company has also revealed that it will integrate ChatGPT into all its diversified products.

Such tactical developments by key players are expected to increase market competitiveness, which eventually is likely to revolutionize the landscape of AI-generated content industry.

Google’s contribution to the field of AI-generated content

Following the resounding success of OpenAI’s ChatGPT, Google is making significant efforts into the trajectory to integrate new technologies, such as machine learning and natural language processing techniques, as well as harnessing the possibilities of generative AI. For instance, in February 2023, Google unveiled its own interactive AI chatbot Bard to compete with ChatGPT. Bard typically applies natural language processing (NLP) and machine learning algorithms that can help it generate human-like responses. This new chatbot is typically centered on Google’s Language Model for Dialogue Application (LaMDA). However, the company has currently rolled it out on a testing basis for merely a few users and will be available for public use in a short span of time. In addition, the company pumps up millions of funds into application and research on generative AI, as a result of rising popularity among the technology fraternity and increasing interest of venture capitalists. Like, in February 2023, Google marked the investment of about US$300 million in AI-tech startup Anthropic. This deal made the company one of the greatest names to robustly invest in companies fostering generative AI.

Enabling role of Google’s algorithms to detect AI content

Since AI continues to improve, it may become more difficult for algorithms to distinguish between AI-generated and human-generated content. This might be the same consequence in Google’s algorithm, as it can efficiently execute editing, until it is not revised by an individual prior to publishing. However, Google can function better while AI content is poorly written and revised by a real human. Thus, it’s more of an issue that Google can better detect high-quality vs low-quality content, instead of ‘real’ vs ‘fake’ content. Also, Google’s algorithms are not much capable to detect content generated by few language models, such as GPT-3. In case, if Google detects such automatically generated content, the web spam team could take stringent action.

In contrast, Google is now putting great efforts to develop and tweak innovative algorithms to deal with the matter of AI-generated content. This will make Google’s algorithms potent enough to detect certain patterns and characteristics that are common in AI-generated content, such as repetition or unnatural language usage. In this context, machine learning algorithms are playing a progressive role in identifying AI-generated texts by looking at the indications, such as text structure, grammar, and syntax in the text. Few instances of Google’s algorithm to detect content through AI-powered tools:

• Google has capability to detect AI-generated content by JasperAI tool, however, in terms of theory only.
• Another example, ChatGPT is an extremely advanced AI tool, which Google’s algorithm can detect, but it generally penalizes for its usage.

Such AI-powered tools are demonstrating that Google can detect AI-generated content; however, it has challenges like penalizing and messing with SEO and site ranking.

Conclusion

In view of technological breakthrough across AI-generated content, several companies are empowering themselves to advance algorithmic techniques for the purpose of content planning and eliminating grammar and spelling issues. It is also worth noting that regardless of whether content is AI-generated or human-generated, companies, including Google, are developing their emphasis on ethically appropriate AI tools. Hence, Google’s focus is now more on providing relevant content of improved quality to users. The matter of AI-generated content is fairly new, but as Google has always done; it will remain in same trajectory to innovate and find more precise ways to identify AI-generated content. 

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