The Publisher Lab Ep. 26: Will AI Replace Search Engines? Exploring the Future of Online Search

Welcome back to another podcast episode recap!

In a recent podcast episode, Tyler Bishop had the pleasure of discussing some of the most pressing issues in the digital advertising and AI industry with my producer, Manny. We delved into the challenges advertisers face on YouTube, Elon Musk’s new AI start-up focused on transparency, and the future of search engine optimization. Here’s a recap of our insightful conversation.

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YouTube’s Brand Safety Dilemma

Our discussion kicked off with the recent controversy surrounding YouTube’s alleged violation of standards, which has led to advertisers rethinking their strategies on the platform. The concern is about brand safety and reputation, as ads can sometimes appear alongside harmful or inappropriate content. This isn’t a new issue, but it’s one that’s gaining more attention.

Advertisers are now demanding more transparency and stricter content moderation measures from YouTube. They’re exploring options such as whitelisting trusted channels or using third-party verification tools to mitigate risks. YouTube is responding by reevaluating its targeting and content guidelines, updating policies, and increasing manual content reviews.

As for the underlying motivation, we believe that advertisers are using brand safety as a negotiation tactic to establish new mechanisms or back channels for better value and flexibility in revenue share. We suggested that publishers should consider hosting their videos on their own platforms to have more control over monetization and audience connections. We also predicted that YouTube may start to lose its dominance as other ad platforms emerge.

Elon Musk’s New AI startup, xAI, Focused on Transparency

Elon Musk’s new AI startup, xAI aims to create AI that is more explainable and transparent, allowing for better understanding and scrutiny of its reasoning. He warns against blindly accepting AI outputs without proper oversight.

Tyler shares his thoughts on the complexity of AI decision-making and its similarities to human decision-making. AI models, like humans, consider various factors when making decisions, and it’s challenging to pinpoint one specific reason for a decision. AI models rely on deep learning and large language models, which collect and analyze vast amounts of data over time. However, unlike targeted and specific AI models, it is difficult for machines to explain why they made a particular decision.

The issue of credibility in decision-making is also a concern. Tyler compared the credibility of a random person giving medical advice to that of a trained doctor and emphasized the importance of objective evaluation in determining the quality of AI models for decision-making. We acknowledged that there are buzzwords and marketing slogans surrounding AI accountability and bias, but it remains to be seen how these issues will be addressed.

Google’s Search Ranking Algorithm & The Relationship Between SERPs and User Attention

We concluded with Google’s search ranking algorithm and the recent volatility observed in search rankings and organic traffic. Tyler shared his perspective on algorithm updates and emphasized the consistency that Google strives for in its search results.

It’s important to look at the relationship between search engine results pages (SERPs) and user attention. While maintaining a high-ranking position is ideal, the other content on the SERP can also impact the attention of the searcher. Google measures the user’s interaction with the search results page to determine if they are finding what they need. If the user quickly leaves after finding a knowledge graph answer, it may not be beneficial. Tyler advises publishers to monitor their own search console data for fluctuations outside of seasonality. If there are changes in ranking positions, it’s worth examining the other content ranking for the query.

Adapting to Changing Environments

Publishers tend to be heavily reliant on Google search for website traffic but we encourage them to adapt quickly to changing environments. We believe that advertisers may diversify their spending, and Google may not dominate traffic distribution in the future. Publishers should explore other platforms and outlets to reach their target audience. We can’t emphasize the importance of making content unique and not treating it as a commodity enough.

In conclusion, the digital advertising and AI industry is rapidly evolving, and it’s crucial for digital publishers to stay ahead of the curve. By understanding the challenges and opportunities in these areas, we can navigate this changing landscape more effectively.

Leave us a some feedback!

Please feel free to share your feedback, questions, or suggestions by visiting PublisherLab.org. We value your input and would love to hear from you regarding topics you would like us to cover in future discussions.

You can listen to this podcast anywhere you can find podcasts or watch it on YouTube.