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Search engines, artificial intelligence and monetization in the new era
August 14, 2023
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4 minutes Read
The opening keynote at Black Hat 2023, unsurprisingly, was on the topic of artificial intelligence. Specifically, the presentation discussed the implications of AI large language models (LLMs) on the cybersecurity industry and the broader ecosystem. The presenter opened the conversation by talking about the history of investments made by Google and Microsoft, the number is large, as you would expect; Microsoft alone has invested 13 billion dollars so far.
In fact, that number led me to digress from the topic of the presentation and I began to wonder why a company would spend $13 billion and, more importantly, why they are rushing it to market when many experts, governments and Industry commentators are suggesting caution and slowing down society’s adoption of AI.
Artificial Intelligence Causes Content Demonetization
There are many uses of artificial intelligence; it could all be part of the reason. The speaker gave an example, which provides a very understandable insight, of using artificial intelligence in video conferencing by analyzing the video, audio and shared materials and then being able to summarize the meeting in more detail than simply transcribing it. Is this why you invest $13 billion or is it a play to capture the future search market? Will the word Google stop being a verb?
While the company may or may not have issues with the ethics of AI, I’m curious if the adoption of AI in search causes a problem that demonizes the internet for many content providers.
Traditional search engines, such as Bing and Google, index content and use algorithms to determine and serve what they believe to be the most relevant results on the search engine results page (SERP), and in the process place some sponsored ads at the top. If you are a content producer and have a website these days, then your monetization model probably includes advertising, or the content is protected only for subscribers or through a paywall. In either case, you’re likely relying, at least in part, on traffic generated through search, clicking on a link in the SERP, and directly navigating the content of your website.
Related: The 5 Best Search Engines for Internet-Connected Devices and Services
What happens when a large language model (LLM) is responsible for providing the answer to a search query that circumvents the need for the SERP? The model has at its disposal all the content accessible to the search engine, creating the data to train the LLM so that it can generate a human-like response to the query. Therefore, we are left with a single answer to the question that may have been formulated using many different content sites, with no attribution to what content was used to form the answer, and with no ability for the content creator to monetize the creation and hosting the content.
Was it less about a technology race and more about how to capture market share for search and monetize? Microsoft is one of the largest search engine providers; with the majority of the market share still belonging to Google. Any impact on a market valued at $225 billion annually is significant, which could explain the investment in LLM AI. Replacing the familiar list of search results with a single answer means that the person creating the query never leaves this new “SERP” page, preserving all traffic for the search engine provider to monetize directly through ads and the like .
An already urgent issue
We have already seen some similar implications: for example, news content sometimes appears directly in the SERP or on social media pages; while attribution to the source of the content is displayed, the person generating the query does not need to visit the news site and therefore no advertising or paywall traffic is generated. The Canadian government pioneered legislation, Bill C-18, to protect news content creators; it imposes a negotiation between the platform that uses the content and the creator to compensate them, to monetize the content they created.
Extend this issue to all content and remove attribution. This could cause many content providers, such as sites that have unique niche content, to stop providing good quality information due to lack of funding. Fast forward ten years and if LLM bases its responses on the content available at that time and content providers have stopped providing up-to-date relevant content, the result will become less reliable than it is today.
Is cybersecurity at risk?
Why is this important for cybersecurity? A lack of funding may cause website owners to stop updating software or paying to secure their sites, there may be a lack of trust created when query results generate incorrect information, and cyber criminals may start posting the own contents to deceive the LLM, the reasons are many. It is important to emphasize that in this transition it is necessary to consider the difficult situation of the content creator so that the Internet remains a source of income and therefore a source of factual and accurate information.
Before you go: Untrained staff and limited budgets leave 96% of companies feeling “unprepared” for cyber attacks