MLNoIndex: A Simple yet Pragmatic solution to Web Data scraping in AI
Published: 2023-07-10 12:26:11

As an analyst working with big data and AI, I've recently stumbled upon an interesting project hosted on [MLNoIndex.org](https://mlnoindex.org). My discovery was not entirely coincidental - given the EU AI Act currently being a hot topic, I was researching technicalities applicable to projects I'm currently working on. 

This initiative, while intriguing, raises several questions about the future of web data usage in AI in terms of providing training data for machine learning and LLMs. In this post, I'll provide a more technical, realistic perspective on MLNoIndex.org, discussing its potential implications on AI data sources and copyright issues.

## The Concept

MLNoIndex.org proposes a simple mechanism for website owners to signal to AI models (or their web scraping parts) that they should not use the data from their site for training. This is achieved through a "MLNoIndex" tag, akin to the "noindex" tag used by search engines. The tag is intended to instruct AI models not to use the data from the page for training purposes.

## Implementation

The implementation of the MLNoIndex tag is relatively straightforward. Web developers add a meta tag to the head section of their HTML code:

```html
<meta name="MLNoIndex" content="true" />
```

The expectation is that AI models / crawlers, when encountering this tag during web scraping, will respect it and exclude the data from that page in their training set. The project also defines a simple attribute to address data nested deeper into website structures.

## Implications on AI Data Sources

While the idea behind MLNoIndex.org is commendable, it does raise some significant questions about the future of AI data sources. AI models, particularly those based on machine learning, rely heavily on vast amounts of data for training. Web scraping provides a rich, diverse, and easily accessible source of such data.

If the MLNoIndex tag becomes widely adopted, it could potentially limit the amount of data available for training AI models. This could, in turn, impact the performance and effectiveness of these models. However, it's important to note that the success of this initiative largely depends on AI developers and companies programming their models to respect the MLNoIndex tag.

## Copyright Issues

The MLNoIndex tag also brings to light the ongoing debate about copyright issues in web scraping and AI. While web scraping is generally legal, the use of scraped data in AI models can potentially infringe on copyright laws, particularly when the data is used to create derivative works.

The MLNoIndex tag provides a mechanism for website owners to assert their rights over their data, potentially helping to prevent copyright infringement. However, the enforcement of this tag is a complex issue. It would require a consensus in the AI community to honor these tags, and there may also be legal challenges in enforcing the tag across different jurisdictions.

## Future Outlook

The future of MLNoIndex.org is uncertain. While it has the potential to spark interest, its success depends on widespread adoption by both website owners and AI developers. Moreover, it raises complex questions about data privacy, copyright, and the future of AI development.

In conclusion, MLNoIndex.org represents an interesting attempt to address some of the challenges at the intersection of AI, data privacy, and copyright. Given the premise, this initiative might look amateurish, it might however start something.