Ethics and risks for e-commerce brands

By Ryan Turner, Founder of

A big part of effective e-commerce marketing is writing search engine optimized content, a job that can be quite tedious. It’s no wonder some authors are trying to make it easier by using artificial intelligence (AI) generated content. However, this raises the question whether AI writing tools can actually develop useful content that solves the consumer’s problem by providing the right answer to their search intent. Is their contribution to the web a net positive or a net negative?

AI content generators rely on identifying patterns by sifting through billions of phrases online. The tools then use a transformer model to generate predictive text based on the training samples; therein lies the main concern of critics of AI writing tools. This article will look at the ethics and risks of using AI-generated content in e-commerce marketing and how it could potentially harm your brand in the future.

How do AI content writers work?

AI content generators rely on a set of inputs such as keywords or topic titles to predict entirely “new” content word-by-word. At the very heart of the generator is a collection of machine learning algorithms that identify patterns in human language. Language models rely on mathematical functions designed as neural networks similar to how neurons in the brain are wired. Prediction is made by calculating the strength of neural connections to reduce prediction error through parallel learning. These models are pre-trained on billions of pages with all kinds of content on the internet.

Many AI content generators rely on the GPT-3 language model, which uses deep learning to create human-like text. The key phrase here being “human-like”. When it comes to predicting text, the model uses generative pre-training, which means that its predictions are based on the patterns it has learned from the training data. Although the model may come up with some weird and sometimes almost genius phrases, it’s still based on statistics and not real human intelligence.

Ethical concerns and risks associated with AI-generated content marketing

Toxic content

Since AI content generators learn from both supervised and unsupervised sources, there is an inherent risk that the model will be exposed to biased and toxic content. Keep in mind that models cannot fully understand what the content they are trained on actually means. Think of it as a great word association game. Sooner or later, the algorithm will learn to associate certain words with similar words because they appear more often in similar contexts in the training data.

Although Ai writing tools can create well-structured content, it is still likely to spit out hate speech in the middle of a normal sentence. The researchers attribute this to the presence of hate speech-related words in the training data, which leads the algorithm to form statistical relationships between the sentences it is trained on. Yet he doesn’t fully understand the context or meaning behind them.

It goes without saying that if this type of content is published without being carefully checked and edited by a human, it could have a real negative impact on any e-commerce brand using AI to generate web content to promote its Mark.

Absurd statements

While most large language models train on billions of parameters in what is best described as a brute force scale, there are still scenarios where their predictions don’t make sense. Professor Emily M Bender, a computational linguist from the University of Washington, has called these models “stochastic parrots” because of their echo chamber-like abilities to make ridiculous but understandable statements. In effect, the algorithms simply introduce randomness into the existing content in their predictions, so that they retain the biases in the training data.

When you invite a writing tool to generate text on a topic that isn’t very common on the internet, chances are the model will have even less data to learn from. This affects the variable quality of the results, and often the generated text will contain placeholder text that has nothing to do with the subject matter. Predictions can also contain statements that aren’t flowing and paragraphs lack the flow of ideas.

Potential for AI content to see poor search engine performance

In a recent blog post, Google said its next update will focus on helpful content in a bid to fix loopholes that websites use to gamify the ranking system. The fix involves changes to search engine ranking signals to rank content value. The update is expected to change how algorithms evaluate content on a website and how useful it is to satisfy searcher intent.

With this update, Google will give top priority to people-oriented content so that quality evaluation is paramount. This is bound to have a negative impact on websites whose AI-generated content does not clearly demonstrate the depth of knowledge and expertise of the topics covered. Although the new signal is automated based on machine learning models, it will not mark content as spam or issue a manual action. Instead, Google’s ranking algorithm will take the signal into account when ranking websites in search engine results pages (SERPs). If you’re looking to rank higher, it’s high time to get rid of unnecessary content, especially if you’re using heavy automation to write your content on a lot of topics.

Ryan Turner, Founder of Ecommerce Marketing Agency, said the following when asked about the trend of e-commerce companies using AI to make content marketing production faster and cheaper: “This is something we’re definitely wary of. Many of the brands we speak with have lofty content publishing goals that are potentially too focused on quantity over quality. We don’t We’ve yet to see search engines take definitive action against AI content, but it’s something that many in the industry believe will happen at some point in the near future.

Misinformation and disinformation in AI-generated content

Ai writing tools are bound to repeat inaccurate information that already exists in the training data. In this case, the tools generate inaccurate information with no harmful intent in what is commonly referred to as disinformation. However, as AI tools grow in complexity, there are fears that they will begin to deliberately generate false information, a common misinformation tactic. This is often the case with AI tools that write news articles that can fool human readers.

In an effort to stay competitive with the big brands in their market, some e-commerce marketers are publishing AI-generated articles without much human proofreading and editing of the content. This mass publication of AI-generated content is more likely to spread disinformation by repeating existing malicious information in an endless cycle. Some researchers have estimated that 99% of the internet will be based on AI-generated content by 2025 if we continue at the current rate of adoption, raising concerns about the accuracy of all this information.

Summary for eCommerce Marketers

There is no denying that artificial intelligence is here to stay. While AI writing tools have seen drastic improvement over the past two years, there are still serious ethical and operational risks associated with publishing AI-generated content – ​​especially if it is in line representing a premium brand. AI writing tools can be used to help generate ideas and titles for articles and blogs, as well as the overall structure of the article. However, it may be a good idea to rely on real humans to do most of the actual writing.