Speaking to the BBC, Lindy Cameron, the chief executive of the National Cyber Security Centre (NCSC), highlighted the potential dangers of overlooking security in the early stages of AI development.

Without adequate security, malicious attacks could have devastating consequences, said Robert Hannigan, a former intelligence chief.

As AI becomes increasingly integrated into our daily lives, from autonomous vehicles to utilities and beyond, attacks on these systems could have severe consequences.

"As we become dependent on AI for all sorts of things, attacks on those systems could be devastating," Hannigan said.

Cameron agreed, emphasizing the importance of applying basic security principles in the early stages of AI development to avoid the risk of misuse.

One of the key challenges with AI is that the systems themselves can be subverted by those seeking to do harm.

A small group of experts has been studying the field of "adversarial machine learning" for many years, looking at how AI and machine learning systems can be tricked into giving bad results.

For example, researchers were able to change how self-driving cars see signs by placing stickers on a stop sign, making the AI think it was a speed limit sign.

Similarly, poisoning the data that AI is learning from can also lead to biased results, potentially with serious consequences.

The problem with AI is that it can be hard to understand, making it difficult to trust.

Even if someone suspects that their AI model may have been poisoned by bad data, it becomes harder to trust it.

"It is a fundamental challenge for AI right across the board as to how far we can trust it," Hannigan said.

The use of AI in national security is also a major concern.

If AI was used to analyze satellite imagery looking for military build-up, for instance, a malicious attacker could manipulate the results to miss the real tanks or see an array of fake tanks.

In conclusion, as the use of AI continues to expand and become more integrated into our daily lives, it is crucial that security is built into the early stages of development to prevent devastating consequences from potential attacks.

The NC The use of artificial intelligence (AI) in cyber security is becoming increasingly prevalent, as companies utilize the technology to detect and prevent cyber attacks.

However, adversaries are also seeking ways to bypass these systems, allowing their malicious software to move undetected.

As AI continues to advance, it is important to consider the potential risks and challenges it may pose.

A recent article co-authored by the chief data scientist at GCHQ highlights the potential security risks associated with large language models (LLMs), such as ChatGPT.

These models have the ability to process and generate human-like language, but they also pose serious concerns about individuals providing sensitive information when they input questions into the models, as well as the risk of "prompt hacking," in which models are tricked into providing inaccurate or harmful results.

With the rapid development of AI, it is crucial to learn from the early days of internet security and ensure that those building these systems are taking responsibility for security.

"I don't want consumers to have to worry," says Lindy Cameron of the National Cyber Security Centre (NCSC), "but I do want the producers of these systems to be thinking about it." As the use of AI in cyber security continues to grow, it is important to remain vigilant and proactive in addressing potential risks and threats.