AI: The good, the bad and the future

We've been promised for years that AI would revolutionise the world, but it now seems that we're closer than ever to this becoming a reality. So how is this technology set to change the way we live and work in the coming years? 

How AI hit the mainstream 

One of the biggest steps forward recently has been in 'generative AI', where the technology can be used to create from scratch everything from images to code. The big names here are the likes of ChatGPT for text and Stable Diffusion and Midjourney for image creation. With the right prompts, they can write essays, create recipes or even make the Pope look like a fashion icon. 

Since version 3.5 of ChatGPT was launched in November 2022, it's gained over 100 million users, making it the fastest-growing application ever. Because ChatGPT and its rivals are easy to use and publicly available, they've helped propel AI firmly into the public consciousness and showcase just how much it's capable of in a way the many more specialised, behind the scenes applications can't. 

The pros and cons of AI today 

There are already countless examples of how AI is making a positive difference across all parts of our world today, in ways both big and small.  

For example, in medicine, AI-trained models are helping to spot diseases such as cancer earlier and more accurately than ever before, as well as create better, more personalised treatment plans. Retailers are using it to optimise supply chains and make it easier for customers to find what they want. And in IT, it's being deployed for everything from software testing to data analysis. 

All this is designed to make life quicker and easier for everyone. However, the downsides of AI have also been well-documented. You may have heard the alarming warnings from tech industry names like Elon Musk and even OpenAI's own creators about the potential of AI to pose an existential threat to humanity, but even if these prove to be unfounded, there are still plenty of drawbacks that need to be considered. 

The limitations of generative AI such as ChatGPT, for example, need to be understood. Despite what some people claim, these tools don't actually think - they're just putting together words or images in response to stimulus.  

This means they can be prone to errors - even presenting completely made-up information as fact - and AI is still dependent on both the quality of information in its database and the inputs of its users. In short, the old tech maxim of 'garbage in, garbage out' still applies. 

What roles are set to be most affected? 

As is the case with any new technology, there are the usual concerns that AI is out to replace people's jobs. Indeed, one report by Goldman Sachs suggests as many as 300 million roles globally could be affected.  

According to the government, the IT and legal sectors currently have the highest rate of adoption of AI, with around 29 percent of UK firms in these fields embracing the technology.  

This will be followed by finance, accounting and media roles. 

There are still plenty of roles that require a human touch, however. For example, one of the big claims about ChatGPT a few months ago was how it was capable of passing a law exam, potentially putting the jobs of legal professionals at risk. However, when a lawyer in New York recently tried to use it in an actual case by asking the AI to prepare a court filing, it was found - far too late - that many of the legal citations offered were completely invented. 

What might an AI-driven future look like? 

This highlights how AI remains a tool that needs oversight and isn’t yet something to be relied on entirely. Although consumer-focused generative AI is currently attracting the most interest, it's through more focused, industry-specific tools that the biggest day-to-day impact will be felt by most workers. 

While AI will affect many roles, it's unlikely to eliminate the need for people entirely. Instead, employees will find themselves spending less time on data-driven tasks, freeing up their time and making them more productive overall. 

This also means there may well be a shift in the skills and requirements that employers look for. With AI taking on functions such as quality assurance and risk management due to its ability to process vast quantities of data, there's likely to be a greater focus on people with the right skills to train and manage such systems. Therefore, strong coding knowledge and data visualisation expertise will be in strong demand.  

In addition to this, softer skills such as adaptability, creative thinking and communication will also be important. In a world where the success of many activities will depend on giving AI clear, specific, and accurate instructions, these capabilities should not be overlooked. 

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