The March 2024 core algorithm update from Google targets websites created with AI-generated content. It’s indisputable that AI-generated content often needs to meet Google’s quality standards outlined in its documentation. However, there’s a method to harness AI that yields high-quality content.
Unraveling Why AI Struggles to Meet Google’s Quality Standards
Numerous ranking systems, notably Reviews and Helpful Content, embody quality standards that inherently pose challenges for AI-generated content to meet. Adding an “E” for experience in E-A-T should have been a warning sign for content creators regarding the risks associated with AI utilization.
Examples of SERP Features, Quality Signals, and Ranking Signals Incompatible with AI Content
The limitations of AI-generated content have long been evident, as highlighted in Google’s documentation. Here are several qualities emphasized by Google’s guidelines that naturally exclude purely AI-authored content:
- Experience:
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- Published reviews necessitate hands-on experience.
- Emphasis on Human Authors:
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- Google News prioritizes human authors in its SERPs.
- Google Perspectives, introduced in May 2023, highlights human authors (hidden gems) discovered in forums.
- Author Expertise:
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- Author page details (pertinent for expertise assessment).
- Author background information (relevant for expertise assessment).
- Author About page (pertinent for expertise assessment).
In essence, Google’s quality thresholds inherently challenge the viability of AI-generated content, emphasizing the indispensable role of human expertise and experience.
Understanding Quality Concepts in Content Evaluation
Google has released Self-Assessment Questions to aid publishers in evaluating whether their content aligns with Google’s quality standards. These questions don’t enumerate specific ranking factors but encompass concepts that typically characterize high-quality websites.
If AI-generated content fails to adhere to these fundamental concepts, it’s probable that the content falls short of quality standards, irrespective of publishers’ efforts to mimic indicators of quality, such as author pages.
Authorial Integrity and Expertise in Content Evaluation
The Expertise section within the Self-Assessment documentation emphasizes aspects related to authors that need to be more attainable through machine-generated content.
The excerpt underscores expertise based on the following criteria:
- Sourcing (citations, fact-checking, attribution)
- Demonstration of expertise
- Author background
These qualities represent outward signs typically associated with expertise, a realm beyond the reach of AI-generated content.
Evaluating Content Quality: Emphasis on Originality
Within the content and quality assessment framework, originality is a crucial criterion.
Google’s documentation outlines the following inquiries:
“Does the content provide original information, reporting, research, or analysis?
…Does the content provide insightful analysis or interesting information beyond the obvious?”
Unoriginality is a characteristic of generative AI, as content generated by such systems tends to lack originality and merely presents the most probable sequence of words on a given topic.
First-Hand Expertise Evaluation
In the people-first assessment section, the focus shifts to first-hand expertise:
“Does your content demonstrate first-hand expertise and a depth of knowledge?”
Machines need more capability to possess first-hand expertise, as they cannot interact with products or utilize services.
Leveraging AI for Quality Content Creation
With the rise of manual actions affecting sites featuring AI-generated content amid the March 2024 core algorithm update, it’s prudent to reassess the role of AI in web content creation. However, there still needs to be a viable approach to harnessing AI to produce high-quality, people-first content. Ultimately, what holds paramount importance in content is the depth of insight it offers, regardless of its authorship.
A potential solution lies in integrating human insight and experience into the data pool utilized by AI for content generation. This hybrid approach can create compelling content that resonates with audiences while benefiting from AI-driven efficiency.
Crafting Review Content Using AI: A Step-by-Step Guide
Creating review content with AI can be streamlined by following these steps:
1. Define Data Points:
Develop a checklist of essential data points for consumers to make informed buying decisions. This checklist should include factors specific to the product category, such as features, specifications, and performance metrics.
2. Conduct Product Assessment:
Conduct a hands-on assessment of the product, ensuring thorough testing and evaluation. The reviewer will provide scores and comments for each data point outlined in the review checklist.
3. Customize Checklists:
Tailor the checklist to suit the product being reviewed. For example, when reviewing a children’s bicycle, focus on age and size suitability, weight, sturdiness of training wheels, etc. For a television review, consider factors like black levels, off-center viewing, color settings, ease, etc.
4. Compile Final Impressions:
Conclude the review checklist with a section labeled “Final Impressions.” Here, summarize the product’s pros and cons and provide an overall sentiment. Additionally, mention the target audience, such as budget-conscious consumers or performance enthusiasts.
5. AI Content Generation:
Upload the completed checklist to your AI platform and request it to generate the review content based on the provided data points and assessments.
By following this systematic approach, you can effectively leverage AI to create comprehensive and insightful review content across various product categories.
Crafting Diverse Content Using AI: A Simple Workflow
Utilizing AI to refine raw content can be streamlined with the following workflow:
1. Dictate Content:
Start by dictating the content verbally and articulating all the necessary information without concerning yourself with paragraph structure or formatting. Pour out your thoughts into the recording, covering all relevant points.
2. Upload to AI Platform:
Once the recording is complete, upload it to an AI platform like ChatGPT. Request that AI transform the raw audio content into a polished document suitable for professional use.
3. Customize Output:
Specify any additional elements you require, such as pros and cons or an executive summary. The AI can generate these based on the provided content and instructions.
By following this straightforward process, you can leverage AI to efficiently create various types of content, from reports to articles, with ease and professionalism.
Leveraging AI to Enhance Human-Generated Content
Consider AI as a ghostwriter capable of refining rough documents into polished essays or articles suitable for various scenarios, including scaled product descriptions.
The intrinsic qualities of content humans provide, such as sourcing, evidence of expertise, and background knowledge, are indispensable elements that AI cannot replicate. Humans contribute Experience, Expertise, Authoritativeness, and Trustworthiness (E-A-T), which serve as the foundation for quality content. AI can then leverage these human inputs to produce high-quality content.
In light of the recent manual actions taken against sites featuring AI-generated content during the March 2024 core algorithm update, it’s imperative to reassess the role of AI in content creation. Despite having conceived and written this article in September 2023, the current landscape underscores the necessity of addressing concerns regarding AI-generated content.
As the SEO industry faces a paradigm shift, now is an opportune moment to explore more effective ways of integrating AI into the content generation workflow. If you find the process overwhelming, consider exploring our monthly SEO packages, where our experts can assist you.
