When OpenAI unchained the “beast” that is ChatGPT back in November 2022, the pace of market competition between tech companies involved in AI increased exponentially.
Market competition determines the price of goods and services, their quality and the speed of innovation – which has been remarkable in the AI industry. However, some experts believe we are deploying the most powerful technology in the world far too quickly.
This could hamper our ability to detect serious problems before they’ve caused damage, resulting in profound implications for society, particularly when we can’t anticipate the capabilities of something that may end up having the ability to train itself.
But AI is nothing new – and while ChatGPT may have taken many people by surprise, the seeds of the current commotion over this technology were laid years ago.
Is AI new?
The origins of modern AI can be traced back to developments in the 1950s when Alan Turing worked to solve complex mathematical problems to test machine intelligence.
Limited resources and computational power available at the time hindered growth and adoption. But breakthroughs in machine learning, neural networks, and data availability fuelled a resurgence of AI around the early 2000s. That prompted many industries to embrace AI. The finance and telecommunications sectors used it for fraud detection and data analytics.
An explosion of data, the development of cloud computing and the availability of huge computing resources all later facilitated the development of AI algorithms. This significantly shaped what could be done with – for example, image and video recognition and targeted advertising.
Why is AI getting so much attention now? AI has long been used in social media, to recommend relevant posts, articles, videos, and ads. The technology ethicist Tristan Harris says social media is broadly humanity’s “first contact” with AI.
And humanity has learned that AI-driven algorithms on social media platforms can spread disinformation and misinformation – polarising public opinion and fostering online echo chambers. Campaigns spent money on targeting voters online in both the 2016 US presidential election and the UK Brexit vote.
Both events led to public awareness about AI and how technology could be used to manipulate political outcomes. These high-profile incidents set in motion concerns about the capabilities of evolving technologies.
However, in 2017, a new class of AI emerged. This technology is known as a transformer. It’s a machine learning model which processes language and then uses that to produce its own text and have conversations.
This breakthrough facilitated the creation of large language models such as ChatGPT, which can understand and generate text which resembles that written by humans. Transformer-based models such as OpenAI’s GPT (Generative Pre-trained Transformer) have demonstrated impressive capabilities in generating coherent and relevant text.
The difference with transformers is that, as they absorb new information, they learn from it. This potentially allows them to gain new capabilities that engineers did not programme into them.