How Artificial Intelligence has Transformed the Professional World

Artificial intelligence promises to revolutionize the way we do just about everything. The pace of change in recent months has been fairly astounding. The launch of OpenAI’s ChatGPT software saw the service reach a million users in just five days – smashing records in the process. Microsoft has recently unveiled a version of the technology which incorporates into the much-derided Bing search engine, and Google is scrambling to follow suit with its ‘Bard’ chatbot.

But it isn’t just natural language processing that’s being revolutionized. We’ve recently seen stunning advances in image generation, robotics, and deepfakery. What the world might look like in a few years might be difficult to predict.

Current uses of AI

Of course, artificial intelligence isn’t an entirely new phenomenon. It’s all ready to be found in smartphone applications like Apple’s FaceID, which uses a neural network to determine who is attempting to unlock the phone. Then there’s the recommended content feed on your social media and streaming accounts – which will provide an endless stream of content based on your previous behavior.

Then there are digital voice assistants. You might remember that just a few years ago, digital voice recognition was so unreliable as to be virtually useless. What changed? Machine learning technology came about, along with the processing power to deliver it.

For business, it’s already completely changed how we interact with and target specific consumers. We’ve long been able to collect information on things like demographics and shopping behavior. Now, with the help of AI, we’re able to make very precise predictions about what a given user might want to see at a given time. This allows for things like highly personalized email campaigns – which provide customers with the content that’s most likely to be welcomed.

What about the future?

When it comes to the future of AI, predictions are difficult. It seems likely that just about every job in the future will depend to some extent on machine intelligence. We might have a single human worker acting as a director for a small team of specialized machines. So, a copywriter might tell a descendent of ChatGPT to outline an article, but it will be the human that ends up contributing the actual original content.

Adaptability

One of the most impressive things about ChatGPT is its ability to turn its hand to a range of tasks. It can write passable prose and code, it can explain concepts, and it can even write code in just about every language. While it does tend to make factual statements that are entirely false, it’s easy to see how it might serve a purpose in many, many workflows.

Security

With the help of sensors like light curtains, which are used to detect objects passing through a given space, a machine might be made to shut down automatically, as a safety feature.

Machines might also be used to police access certain parts of the premises. This might make it affordable even for small businesses to enforce sophisticated user access controls, without resorting to fingerprints or other biometric technologies.

Health care

Machine-learning promises to revolutionize the field of radiography, potentially detecting cancers and other problems with far greater accuracy than human beings. It might also help to ease the administrative burden since the offices of the NHS might be partially manned by machines.

Transport

Self-driving cars might seem like a distant prospect, but the fact is that they’re already with us to a certain extent. Self-parking technology, assistive braking, lane assist, adaptive cruise control: they’re all forms of artificially-intelligent driving.

Finance

According to a report from Insider Intelligence, around four-fifths of major banks are highly aware of the potential of AI in finance. In the world of personal finance, natural-language SMS assistants have long been used to help settle queries. In consumer finance, it’s used to guard against fraud and malicious cyberattacks. In corporate, it’s being used to assess the risks attached to a particular loan. According to the research, these developments stand to contribute around $447 billion to North American banks alone.

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