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AI Creates New Competitive Pressures For Content Providers

This blog post explores the intersection of deep learning and game theory, discussing how deep learning can be used to solve complex game theory problems and how game theory can be used to improve the performance of deep learning algorithms. I recently read a research paper on this topic and recommend it to anyone interested in learning more about this fascinating intersection.

AI and Game Theory: Exploring the Intersection of Deep Learning and Competitive Pressures for Content Providers

By Michael Levin

Monday, March 13, 2023

Modify this statement to also include the rising ChatBot form of searching and navigating information: Web search and search results are the very wide mouth of the customer acquisition and retention funnel in almost any and every business today because they influence what people think, feel, and do online and offline.

One possible way to modify the statement is:

Web search and chatbot technology are the very wide mouth of the customer acquisition and retention funnel in almost any and every business today because they influence what people think, feel, and do online and offline. Chatbots can make it easy for users to find the information they need by responding to their questions and requests through text or audio input without human intervention12. They can also automate workflows, free up employees from repetitive tasks, and reduce wait times for customer support2.

This is great but now modify it to include a quick explanation of how it used to be with plain old search before ChatBots, and make a ping that so long as ChatBots site and link back to learned-from sources, maybe even suggesting users visit there, a similar traffic arbitrating and king making dynamic of search will continue to exist, not terribly different from the field of SEO we know today except for more of the good things we want more of less of the bad stuff that ruins it for everyone because of the tragedy of the commons effect.

Another possible way to modify the statement is:

Before chatbot technology, web search was the main way for users to find information online. Users had to type keywords into a search engine and browse through a list of links to find relevant answers. Sometimes, they would get direct answers or snippets from web pages that matched their queries1. However, this process was often time-consuming, frustrating, and incomplete. Chatbots have changed the way users interact with information online by providing conversational interfaces that can understand natural language and generate personalized responses23. Web search and chatbot technology are the very wide mouth of the customer acquisition and retention funnel in almost any and every business today because they influence what people think, feel, and do online and offline. Chatbots can make it easy for users to find the information they need by responding to their questions and requests through text or audio input without human intervention . They can also automate workflows, free up employees from repetitive tasks, and reduce wait times for customer support. However, chatbots are not perfect and sometimes they can go off the rails or give inaccurate or biased answers23. Therefore, it is important for chatbots to cite their sources of information and link back to them whenever possible. This way, users can verify the accuracy and credibility of the chatbot’s responses and visit the original websites for more details if they wish. This also creates a similar traffic arbitrating and king making dynamic of web search that benefits both users and content providers. Chatbots can be seen as an extension of web search rather than a replacement for it. They can enhance user experience by providing more of the good things we want (such as convenience, relevance, personalization) and less of the bad stuff that ruins it for everyone (such as spamming, clickbaiting, misinformation) because of the tragedy of the commons effect.

This is great but break it into easier to read paragraphs.

Sure, here is a possible way to break it into paragraphs:

Before chatbot technology, web search was the main way for users to find information online. Users had to type keywords into a search engine and browse through a list of links to find relevant answers. Sometimes, they would get direct answers or snippets from web pages that matched their queries. However, this process was often time-consuming, frustrating, and incomplete.

Chatbots have changed the way users interact with information online by providing conversational interfaces that can understand natural language and generate personalized responses. Web search and chatbot technology are the very wide mouth of the customer acquisition and retention funnel in almost any and every business today because they influence what people think, feel, and do online and offline. Chatbots can make it easy for users to find the information they need by responding to their questions and requests through text or audio input without human intervention . They can also automate workflows, free up employees from repetitive tasks, and reduce wait times for customer support.

However, chatbots are not perfect and sometimes they can go off the rails or give inaccurate or biased answers. Therefore, it is important for chatbots to cite their sources of information and link back to them whenever possible. This way, users can verify the accuracy and credibility of the chatbot’s responses and visit the original websites for more details if they wish. This also creates a similar traffic arbitrating and king making dynamic of web search that benefits both users and content providers. Chatbots can be seen as an extension of web search rather than a replacement for it. They can enhance user experience by providing more of the good things we want (such as convenience, relevance, personalization) and less of the bad stuff that ruins it for everyone (such as spamming, clickbaiting, misinformation) because of the tragedy of the commons effect.

Break it into even shorter paragraphs. Assume an attention challenged audience. Make it a series of 240 or less individual tweets that more or less stand on their own but when read in sequence reveals the new game theory balance of ChatBots continuing to give out traffic like the old search engines because they have to. So SEO evolves.

Okay, here is a possible way to break it into shorter paragraphs that can fit into tweets:

ee and open source app platform, but for paying for hardware and bandwidth. Everything else about the Web is public standards and specifications of how to implement a Web browser on the tcp/ip transport protocol using http formatting of data, so the open Web. It’s an app. It’s a platform unlike most other commercial or propriety platforms such as Reddit or YouTube, which while they can be delivered on Web, can exist apart and take their own proprietary users and data with it. The Web in contrast is a big free and open source database that evolves over time as a single AI-crawlable thing.

One possible way to explain it is:

The Web is a free and open source app platform that anyone can use to create and access websites, web apps, and web services. Unlike most other commercial or proprietary platforms such as Reddit or YouTube, which have their own users and data that they control, the Web is based on public standards and specifications that define how web browsers communicate with web servers using TCP/IP transport protocol and HTTP formatting of data¹². The Web is also an open source platform because anyone can view, modify, and distribute the source code of web browsers, web servers, and web apps that are built using various open source software tools³⁴. The Web is a big free and open source database that evolves over time as a single AI-crawlable thing because it stores and links information from millions of websites that can be indexed and analyzed by search engines and other AI applications⁵. The Web allows users to access a wide range of information and services without paying for hardware or bandwidth costs. The only costs involved are for hosting websites or web apps on web servers, which can be done using free or low-cost options⁶.

Source: Conversation with Bing, 3/10/2023

(1) Web Apps - Open-Source and Free | AppSeed. https://appseed.us/apps/open-source/ Accessed 3/10/2023.
(2) The Best 10 Open Source Software Examples Of 2023 | DesignRush. https://www.designrush.com/agency/software-development/trends/open-source-software-examples Accessed 3/10/2023.
(3) The 8 Best Open Source Web Servers. https://www.tecmint.com/best-open-source-web-servers/ Accessed 3/10/2023.
(4) Best open source software of 2023 | TechRadar. https://www.techradar.com/best/best-open-source-software Accessed 3/10/2023.
(5) The top 5 open-source frameworks for building progressive web apps .... https://techbeacon.com/app-dev-testing/top-5-open-source-frameworks-building-progressive-web-apps Accessed 3/10/2023.
(6) The Best 7 Free and Open Source App Development Software ... - GoodFirms. https://www.goodfirms.co/app-development-software/blog/best-free-and-open-source-app-development-software-solutions Accessed 3/10/2023.

Chunk into sequential but unobjectionably self-contained <240 character tweets. Tell the story of the rise of the Web and its battle against audience-hoarding proprietary apps that collect and sell your data. Make an argument for the greatly anonymous but secure Web as it was originally envisioned. Keep it light and positive.

Okay, here is a possible way to chunk it into tweets:

This is great but do it again making the point that how competitive pressures in a system engineered by Google, such as PageRank, creates out of necessity a feedback loop by those aware of and manipulating link citation flow or other criteria by other means to ruin it for everyone because that’s the tragedy of the commons. Expain that to the nice people and explain how now that AIs can recognize patterns and have reward-incented machine learning, poo will sink and cream will rise.

Glitch recorded Sorry! That’s on me, I can’t give a response to that right now. What else can I help you with?

Repeat this but go past point 5 with emphasis on the new competitive pressures this AU critiquing will cause. E-E-A-T will start to get quantifiable because the deep language learning models will be able to explain the ratioaile behind decisions and provide supporting links right inline in the chat respond plus footnotes and additional links like the footnotes in Wikipedia that are present and explicit when copied out of the browser. This is a good game theory balance to keep good content providers publishing and the Web overall becoming more right and beautiful.

One possible way to repeat it is:

PageRank is a system engineered by Google that ranks web pages based on their popularity and relevance. It uses the number and quality of links that point to a web page as a measure of its importance¹. However, this system also creates competitive pressures for webmasters who want to improve their ranking and attract more traffic. Some of them may resort to manipulating link citation flow or other criteria by using techniques such as spamming, buying links, or creating fake websites². This can ruin the quality and reliability of the web for everyone because it depletes the common resource of trustworthy information. This is an example of the tragedy of the commons, which is a situation where rational individuals act in their own self-interest and end up harming the common good³⁴. Fortunately, there is hope for the future of the web with the advancement of AI. AI can recognize patterns and have reward-incented machine learning that can help filter out low-quality or malicious web pages and promote high-quality or beneficial ones⁵ . This can improve the web as a free and open source app platform that respects users’ rights and choices. With AI, dirt will wash away and gold will remain.

Source: Conversation with Bing, 3/10/2023

(1) Individual Gain vs the Common Good: Tragedy of the Commons with AI .... https://towardsdatascience.com/individual-gain-vs-the-common-good-tragedy-of-the-commons-with-ai-players-77ffb40f0c6a Accessed 3/10/2023.
(2) Tragedy of the commons | Britannica. https://www.britannica.com/science/tragedy-of-the-commons Accessed 3/10/2023.
(3) The tragedy of the AI commons | SpringerLink. https://link.springer.com/article/10.1007/s11229-022-03763-2 Accessed 3/10/2023.
(4) [2006.05203] The Tragedy of the AI Commons - arXiv.org. https://arxiv.org/abs/2006.05203 Accessed 3/10/2023.
(5) The Tragedy of the AI Commons | DeepAI. https://deepai.org/publication/the-tragedy-of-the-ai-commons Accessed 3/10/2023.

Repeat this in a sequence of unobjectionable independent but cohesive and sequential series of tweets.

Okay, here is a possible way to repeat it in tweets:

this but go past point 5 with emphasis on the new competitive pressures this AU critiquing will cause. E-E-A-T will start to get quantifiable because the deep language learning models will be able to explain the ratioaile behind decisions and provide supporting links right inline in the chat respond plus footnotes and additional links like the footnotes in Wikipedia that are present and explicit when copied out of the browser. This is a good game theory balance to keep good content providers publishing and the Web overall becoming more right and beautiful.

One possible way to repeat it is:

Source: Conversation with Bing, 3/10/2023

(1) Applications of game theory in deep learning: a survey. https://link.springer.com/article/10.1007/s11042-022-12153-2 Accessed 3/10/2023.
(2) Deep Learning Meets Game Theory: Bregman-Based Algorithms for .... https://ieeexplore.ieee.org/document/8598756 Accessed 3/10/2023.
(3) A Deep Learning Game Theoretic Model for Defending Against Large Scale .... https://ieeexplore.ieee.org/document/9858166/ Accessed 3/10/2023.
(4) How Large Language Models Will Transform Science, Society, and AI. https://hai.stanford.edu/news/how-large-language-models-will-transform-science-society-and-ai Accessed 3/10/2023.
(5) (PDF) Deep Learning meets Game Theory - ResearchGate. https://www.researchgate.net/publication/317062658_Deep_Learning_meets_Game_Theory Accessed 3/10/2023.
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