Artificial intelligence is huge news at the moment, with scientists calling for international controls on its spread and even the Times indulging in apocalyptic headlines – “Two years to save the world says AI adviser”

We’re surrounded by examples of AI, many of which we take for granted.  The technology fuels virtual assistants, like Apple’s Siri, helps doctors to spot cancer in MRIs and allows your phone to recognize your face

Tools that generate content have widened the field. Chatbots, like ChatGPT and Bard, write software code and chapter books. Voice tools can manipulate celebrities’ speech. Image generators can make hyper-realistic photos given just a bit of text

This groundbreaking technology has the potential to revolutionise entire industries, but even experts have trouble explaining how some tools work. And tech leaders disagree on whether these advances will bring a utopian future or a dangerous new reality, where truth is indecipherable from fiction

NMTBP navigates the minefield.

What is artificial intelligence?

 Artificial intelligence is an umbrella term for a vast array of technology. There’s no single definition, and even researchers disagree. Generally, AI is a field of computer science that focuses on creating and training machines to perform intelligent tasks, “something that, if a person was doing it, we would call it intelligence,” said Larry Birnbaum, Professor of computer science at Northwestern University

For decades, AI has operated largely within academia and the scientific establishment, being used for analysis, allowing people to spot patterns and make predictions by assessing huge sets of data

But advancements in the field have led to a boom in generative AI, a form of artificial intelligence that can make things. The technology can create words, sounds, images and video, sometimes at a level of sophistication that mimics human creativity. It backs chatbots like ChatGPT and image generators like DALL-E

Although this technology can’t ‘think’ like humans do, it can sometimes create work of a similar quality. AI-powered image generators have made photos that tricked art judges into thinking they were human-made, and voice generating software has preserved voices of people suffering from degenerative diseases such as ALS

Chatbots backed by generative AI have dazzled users by carrying on eerily lifelike conversations – an early dream of the field as envisioned by Alan Turing. In 1950, he developed the ‘Turing test,’ which judged the success of an AI machine by how well it could fool users into believing it was human.

Turing never gave much credence to the idea that a computer could really ‘think’ – calling that question “too meaningless to deserve discussion”

How do we interact with AI?

The most common way people experience artificial intelligence is throughchatbots, which work like an advanced form of instant messenger, answering questions and formulating tasks from prompts

These bots are trained on troves of internet data, including Reddit conversations and digital books. Chatbots are incredibly adept at finding patterns and imitating speech, but they don’t interpret meanings, experts say. “It’s a super, super high-fidelity version of autocomplete,” Birnbaum says

Since it debuted in November 2022, ChatGPT has stunned users with its ability to produce fluid language – generate complete novels, computer code, TV episodes and songs. GPT stands for ‘generative pre-trained transformer.’ ‘Generative’ means that it uses AI to create things. ‘Pre-trained’ means that it has already been trained on a large amount of data. And ‘transformer’ is a powerful type of neural network that can process language

Created by the San Francisco start-upOpenAI, ChatGPT has led to a rush of companies releasing their own chatbots. Microsoft’s chatbot, Bing, uses the same underlying technology as ChatGPT. And Google released a chatbot, Bard, based on the company’s LaMDA model

Some people think chatbots will alter how people find and consume information on the internet. Instead of entering a term into a search engine, like Google, and sifting through various links, people may end up asking a chatbot a question and getting a confident answer back. (Though sometimes these answers are false – stay tuned!)

Taming AI: Deepfakes, hallucination and misinformation

The boom in generative artificial intelligence brings exciting possibilities – but also concerns that the cutting-edge technology might cause harm

Chatbots can sometimes make up sources or confidently spread misinformation. In one instance, ChatGPT invented a sexual harassment scandal against a college law professor. It can also churn out conspiracy theories and racist answers. Sometimes it expresses biases in its work: In one experiment, robots identified black men when asked to find a ‘criminal’ and marked all ‘homemakers’ as women

AI ethicists and researchers have long been concerned that, because chatbots draw on massive amounts of human speech – using data from Twitter to Wikipedia — they absorb our problems and biases. Companies have tried to put semantic guardrails in place to limit what chatbots can say, but that doesn’t always work

Sometimes artificial intelligence produces information that sounds plausible but is irrelevant, nonsensical or entirely false. These odd detours are called hallucinations. Other people have become so immersed in chatbots they falsely believe the software issentient, meaning it can think, feel, and act outside of human control. Experts say it can’t – at least not yet – but it can speak in a fluid way so that it mimics something alive

Another worry is deepfakes: synthetically generated photos, audio or video that are fake but look real. The same technology that can produce awesome images could be deputized to fake wars, make celebrities say things they didn’t actually say or cause mass confusion or harm

Companies test their artificial intelligence models for vulnerabilities, rooting out biases and weaknesses by simulating flaws in a process called red teaming

Despite attempts to tame the technology, the innovation and sophistication of generative AI causes some to worry

“When things talk to us like humans, we pick up a little suspension of disbelief,” said Mark Riedl, Professor of Computing at Georgia Tech and an expert on machine learning. “We kind of assume that these things are trying to be faithful to us, and when they come across as authoritative, we can find it hard to be sceptical.”

You have been warned!