Recently, talk of generative AI is everywhere. Whether it’s marvelling over AI filters that can make you look like a Renaissance painting or scrutinising videos of celebrity deep fakes, generative AI is hard to ignore. And in today’s highly accessible media landscape, the power of generative AI is both real and concerning – especially when considering the potential of a drastically changing information environment.

Generative AI technologies like GPT-4 and Dall-E make it increasingly difficult to tell what is genuine and what is manufactured. Perhaps more concerning is that with Generative Adversarial Networks (GANs) and open-source platforms, practically anyone can produce synthetic media with relative ease – and that means practically anyone can influence our perception of reality. Because of this, we’re in a new era of misinformation and disinformation that is often made up of computational propaganda, creating an entirely new set of dangers for us to consider as we navigate this ever-changing digital world.

With this in mind, brands, companies, and governments need to take steps to prevent malicious actors from exploiting this new medium that can easily warp our perception of reality. To this end, it’s crucial that technology and security companies act with vigilance and invest in research around these new technologies that can help ensure businesses are able to mitigate the risk of generative AI.

The Pros and Cons of Generative AI

Though it’s easy to focus on the dangers of generative AI – and for good reason – there are positive business uses. These technologies assist with accurate translation services, financial forecasting, data analysis, and are revolutionising automated processes that can go a long way in optimising productivity as well as cost efficiency.

But, it’s clear that the same technology in the hands of bad actors poses enormous threats. Generative AI works by tapping into machine learning models of data sets such as images and videos, analysing them using deep neural networks that are trained to recognise patterns, and then generating new content based on what the model has “learned” from the existing data.

Because this new AI-generated content appears realistic, but is completely fabricated, this technology can drive synthetic media that seems real – so much so that it routinely tricks humans into believe it is real – on an unprecedented scale. With generative AI, there is no more need for out-of-context imagery as the technology can generate instant, affordable, accessible, and realistic visual content, offering endless possibilities to its users and poses a significant threat to the information landscape. This can include not just images, but voice simulation and videos, known as deep fakes, that can fuel disinformation and misinformation.

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