AI

AI-generated content doesn’t seem to have swayed recent European elections 

2 Mins read

Those fears seem to have been unwarranted, says Sam Stockwell, the researcher at the Alan Turing Institute who conducted the study. He focused on three elections over a four-month period from May to August 2024, collecting data on public reports and news articles on AI misuse. Stockwell identified 16 cases of AI-enabled falsehoods or deepfakes that went viral during the UK general election and only 11 cases in the EU and French elections combined, none of which appeared to definitively sway the results. The fake AI content was created by both domestic actors and groups linked to hostile countries such as Russia. 

These findings are in line with recent warnings from experts that the focus on election interference is distracting us from deeper and longer-lasting threats to democracy.   

AI-generated content seems to have been ineffective as a disinformation tool in most European elections this year so far. This, Stockwell says, is because most of the people who were exposed to the disinformation already believed its underlying message (for example, that levels of immigration to their country are too high). Stockwell’s analysis showed that people who were actively engaging with these deepfake messages by resharing and amplifying them had some affiliation or previously expressed views that aligned with the content. So the material was more likely to strengthen preexisting views than to influence undecided voters. 

Tried-and-tested election interference tactics, such as flooding comment sections with bots and exploiting influencers to spread falsehoods, remained far more effective. Bad actors mostly used generative AI to rewrite news articles with their own spin or to create more online content for disinformation purposes. 

“AI is not really providing much of an advantage for now, as existing, simpler methods of creating false or misleading information continue to be prevalent,” says Felix Simon, a researcher at the Reuters Institute for Journalism, who was not involved in the research. 

However, it’s hard to draw firm conclusions about AI’s impact upon elections at this stage, says Samuel Woolley, a disinformation expert at the University of Pittsburgh. That’s in part because we don’t have enough data.

“There are less obvious, less trackable, downstream impacts related to uses of these tools that alter civic engagement,” he adds.

Stockwell agrees: Early evidence from these elections suggests that AI-generated content could be more effective for harassing politicians and sowing confusion than changing people’s opinions on a large scale. 


Source link

Related posts
AI

Jina-Embeddings-v3 Released: A Multilingual Multi-Task Text Embedding Model Designed for a Variety of NLP Applications

4 Mins read
Text embedding models have become foundational in natural language processing (NLP). These models convert text into high-dimensional vectors that capture semantic relationships,…
AI

This AI Paper Introduces a Comprehensive Framework for LLM-Driven Software Engineering Tasks

3 Mins read
Software engineering integrates principles from computer science to design, develop, and maintain software applications. As technology advances, the complexity of software systems…
AI

TinyAgent: An End-to-End AI Framework for Training and Deploying Task-Specific Small Language Model Agents

3 Mins read
The significant advancements in Large Language Models (LLMs) have led to the development of agentic systems, which integrate several tools and APIs…

 

 

Leave a Reply

Your email address will not be published. Required fields are marked *