Artificial Intelligence
& Content

Search Engine Journal discusses a study by researchers from Princeton University, Georgia Tech, Allen Institute for AI, and IIT Delhi on optimizing websites for AI search engines. The researches tested nine strategies and found that citing sources, adding quotations, and including statistics significantly improved visibility, especially for smaller websites. These techniques, which enhance content credibility and richness, proved effective across various knowledge domains. However, using authoritative tones and keyword optimization did not improve rankings. The findings suggest a new approach to SEO tailored for AI search engines, potentially leveling the playing field for smaller content creators.

This week, we talk about how fake, doctored, and false media is so easily spread, how the social platforms are dealing with it, and how generative AI is making things worse.

To create content with strong E.E.A.T, publishers should focus on meeting the user's search intent and providing well-researched, relevant information. The article also suggests including diverse expert voices for high-stakes topics and encouraging authors to promote their content on social media.

The blog post discusses a phenomenon known as 'model collapse,' which occurs as AI-generated content proliferates on the internet and starts to be used as training data for AI models. This model collapse results in these models degrading over time, producing more errors and less varied responses. The phenomenon was investigated by a group of researchers from the UK and Canada, who found that as AI models are trained on data produced by other AI models, they quickly forget the original data they were initially trained on. This 'pollution' of the training data leads to the AI gaining a distorted perception of reality and may result in discrimination based on factors like gender, ethnicity, etc. These models tend to overfit popular data and misrepresent less popular data, leading to the loss of minority data characteristics over time. This problem is likened to the degradation in quality observed when a JPEG image is repeatedly copied or when a clone creates a clone of itself, leading to exponentially decreasing levels of intelligence.

Ensuring that chatbots aren’t serving false information to users has become one of the most important and tricky tasks in the tech industry.

Unpacking the legal, practical and strategic risks of using AI-generated content in your marketing.

Everyone should be empowered with the tools they need to find information they can trust.

Tristan Harris and Aza Raskin discuss how existing A.I. capabilities already pose catastrophic risks to a functional society, how A.I. companies are caught in a race to deploy as quickly as possible without adequate safety measures, and what it would mean to upgrade our institutions to a post-A.I. world.

Bing's AI-powered search engine made up information about a pet vacuum and reported incorrect financial data in its responses in its public demo.

Researchers used ChatGPT to produce clean, convincing text that repeated conspiracy theories and misleading narratives.

Is AI-generated content in line with Google’s guidelines, or a violation of them? Learn how to navigate generative AI within your SEO content strategy.

A Textio analysis of job posts written in ChatGPT.

The best content that ChatGPT writes is also the most biased.

Researchers predict that generative technology could make disinformation cheaper and easier to produce.

Plus: A Roomba recorded a woman on the toilet. How did screenshots end up on Facebook?