Our take: balancing AI and authenticity

[jrineakter]

Interestingly, the survey reveals a socioeconomic divide in perceptions. Those in the higher (A, B, C1) social grades are significantly more likely to see AI-generated content (70% vs. 62% of C2, D, E) and digitally-altered content (79% vs. 69% of C2DEs) as major contributors to misinformation. This could reflect a heightened awareness among higher social grades about the nuances of digital content.

The YouGov article also touches upon “labelling”, a proposed solution which sees AI-generated content marked as such. The survey says opinions are split, with half of respondents believing it buy phone number list could help reduce misinformation, while 29% are sceptical. This mirrors sentiments about digitally altered content, where 50% think labels might be useful but 29% disagree. But here’s the kicker – nearly half (48%) of those surveyed wouldn’t trust the labels on AI-generated content, compared to just 19% who would.

And how do people react when they do encounter AI-labelled content on social media? Perhaps surprisingly, 42% said they “wouldn’t take any immediate action”, which suggests a certain level of neutrality – but 27% said they would block or unfollow the account. Unsurprisingly, the survey reveals a generational divide with differing levels of acceptance, with younger users saying they’d be more likely to engage with AI-labelled posts.

We make no secret of it at Pod. We recognise the incredible potential and power of AI tools like ChatGPT and Google Gemini. We’ve always maintained that where these tools can improve our output and practices, we won’t be afraid to use them. For example, we’ve found them helpful in areas such as summarising text, suggesting options for alternative phrasing, generating ideas, and streamlining processes.