
At Search Central Live Tokyo, Google addressed a crucial question: how to deal with AI-generated content. During the event, Gary Illyes, a research analyst at Google, shared new insights. Other company representatives also gave recommendations on this topic.
Kenich Suzuki, renowned specialist in Japanese search marketing, had the opportunity to present some of these developments during the event in Tokyo. In his blog, he shared a summary of the most relevant insights discussed.
The information provided by Suzuki reinforces what we already know about Google's vision for quality and usefulness of AI content are the key points. However, it's important to better understand how these types of content rank within search results.
Google's evaluation of AI content is primarily based on its quality and relevance to users. The company aims to provide accurate and useful research results, regardless of whether they are generated by humans or by AI systems.
Additionally, Google emphasizes the need for transparency in using AI to create content. It is important that content producers make it clear when they are using AI to generate their materials. This allows users to better understand the origin of the content and to make their own assessments.
To determine the quality of the content generated by Artificial Intelligence, a combination of manual assessment and Google machine learning algorithms. Human reviewers play a crucial role in this process, reviewing content and providing valuable feedback to improve Google's algorithms.
What is "Search Central Live Tokyo"
The event focused on online optimization for marketers, developers, content producers and anyone interested in better understanding How to optimize your online presence and get better results in Google search results.
Strategies, recommendations and practices were presented to improve website visibility in search results. The conference addresses content optimization, user experience, SEO and other factors that influence online presence.
The importance of labeling AI-generated content
- Identification and transparency: Label the AI-generated content helps users understand the origin of content, which can affect how they interpret and use it. Transparency in content contributes to user trust.
- Accuracy of information: AI may not guarantee 100% accuracy. Thus, labeling allows human verification to ensure the correctness of the information.
- Human review before publication: Labeling AI-generated content reinforces the need for human review before publication, ensuring that content meets quality and relevance standards.
- Applicability in content translations: The principle of AI-generated content labeling is equally applicable in machine translation contexts, to ensure that the translated content is accurate and of quality.
- AI-generated image labeling: The Google recommends using IPTC metadata to label AI-generated images, which could become standard practice in the future.
- Confidentiality and integrity of information: AI-generated content labeling helps preserve the confidentiality and integrity of information, which is critical to ensuring user trust and the quality of online content.
The Power of Natural Content in Google Search
Google algorithms are powered by advanced machine learning techniques that are constantly learning from the environment. content written by real people. This enables Google to understand the context, intent, and relevance of natural content. The idea behind this is to deliver authentic, accurate and engaging information to users.
Understanding this preference for natural content can also help companies optimize their digital marketing strategies. By creating authentic and original content, brands can increase your visibility and authority in search results. It's important to remember that Google is constantly updating its algorithms to improve user experience, and valuing natural content is an increasingly strong trend.
What if Artificial Intelligence (AI) could simulate EEAT?
However, currently, an AI does not have the ability to claim expertise on a particular topic or product. This means that it is seemingly impossible for an AI to reach the level of quality necessary for certain types of content that require expertise.
Once a policy is established, Google will officially communicate it to users. It is important to wait for these updates to better understand how AI-generated content could simulate EEAT in the future and how this will impact the evaluation of online content.
The Evolving AI Policies: Addressing Trustworthiness Challenges
Google, a leader in this field, is striving to regulate and adapt AI in an ethical and practical way. It highlights that, despite advances, AI is subject to errors and highlights the importance of raising awareness about this.
Google emphasizes that Publishers must maintain content quality to ensure reliability and relevance. With the continued development of AI, publishers must strive to offer high quality content, generating trust in users.
Addressing the challenges of AI trustworthiness requires collaboration between developers, companies, and regulators. Transparency in the creation and use of algorithms and accountability in the use of AI are key. AI trustworthiness is a shared responsibility for everyone in the digital ecosystem.