Euroviews. Is generative AI truly making disinformation worse?

In recent years, AI has dominated discussions across various sectors. 

Its swift integration and growth outpace the general public's ability to keep up with the developments. 

This has forced journalists, researchers, and civil society organisations to continuously highlight the drawbacks of these emerging technologies, and they are right in doing so.

The discussion was sparked by the latest release of Sora, a text-to-video AI model, with many debating whether tools like these have any beneficial applications or an inherently negative impact on the world. 

Some opted for a more measured approach and sought to investigate the dataset utilized in training models like Sora. They decided to run the prompts demoed by OpenAI via Midjourney, a contemporary of Sora, and discovered striking similarities between the outputs of both models. 

A tech columnist uncovered that a hyperrealistic clip generated by Sora, which gained significant traction on social media, was trained using footage from Shutterstock, a company partnered with OpenAI. This highlights the limited availability of high-quality datasets for training such models.

One of the significant concerns that repeatedly arise in the public discourse is the harmful impacts of AI-assisted disinformation campaigns, particularly given the widespread availability of tools for creating deceptive content such as images, text, deep fakes, and voice cloning. 

The overarching concern is that these tools enable the production of misleading content at scale, potentially skewing public perceptions and even influencing behaviours. 

However, excessively highlighting the potential of AI-assisted disinformation shifts attention away from two important realities. 

Firstly, traditional disinformation