‘Go’ is an ancient Chinese strategy game, believed to be the oldest board game still played today. But many millennia since its origin, we’re no longer playing against other people – we’re playing against artificial intelligence.
The premise of the game is simple: players move black or white stones around the board, with the goal of encircling their opponent’s stones and enclosing the largest amount of space. For years AI has bested top players, and many fear that AI superiority will be mirrored in the workplace and beyond.
However, in February 2023, amateur ‘Go’ player Kellin Pelrine discovered a weakness. While distracting the AI in the corner of the board, he was able to slowly engulf its stones in a spiral – a play that would have easily been spotted by human eyes but was left undetected by the AI.
AI, automation, machine learning, generative AI: what does it all mean?
If you use your face to unlock your phone, you’re using AI. Whenever you Google something, you’re using AI. Artificial intelligence is the “the ability of a digital computer or robot to perform tasks commonly associated with intelligent beings”. Put simply, it’s the pursuit of technology that mimics how humans think and act.
The rise of the AI boom has brought a whole new set of terminology, and with that, muddied definitions. But it’s not all semantics; inaccurate language can lead to sensationalism – or worse, false narratives.
For example, according to a study by venture capital firm MMC, 40% of companies classified as AI startups don’t actually use AI technology significantly (some might simply have a customer support chatbot on their website, and not use AI to impact their offering).
The rise of the AI boom has brought a whole new set of terminology, and with that, muddied definitions.
AI goes beyond ‘automation’, which is programming machines to carry out repetitive, predefined tasks. To think of it in human terms: when throwing a ball into a net, automation is the physical movement of your arms, while AI is your brain, responding to your arm’s movement to improve your accuracy for the next throw.
Machine learning is a specific type of AI which is about recognising patterns in data, simulating how humans think and ‘learning’. It can create rules and make predictions or recommendations for action without being programmed to do so. ‘Deep learning’ takes this further; as a subset of machine learning, it uses ‘artificial neural networks’ to more closely mimic how the human brain works.
What is Generative AI?
The AI frenzy is largely thanks to the development of Generative AI. This is a type of machine learning which uses algorithms to create new content, including:
- Text content-creation: Made by the AI research laboratory OpenAI, ChatGPT is the most popular AI chatbot which answers practically any question you give it in a text-based format.
- Image content-creation: This type of AI enables users to create new images using text-to-graphics prompts. The most popular is DALL-E, named after the Spanish surrealist artist and Pixar robot ‘Wall-E’.
- Sound content-creation: MusicLM is Google’s experimental text-to-music model that generates songs based on ideas or descriptions.
The magic of Generative AI is it puts the user in the driving seat, allowing them to use AI in a human-centred way. It has prompted individuals and businesses to question the very nature of how they work and live. It’s also been lauded for advancing the democratisation of creativity: Bernard Marr, business and technology thought leader, comments that “anyone who simply has a good idea can have AI flesh it out and bring it to life”.
User success is mostly about the questions they ask, so much so that ‘prompt engineering’ – the refinement of how we speak to AI – is its own craft.
What are the criticisms of AI?
Many of AI’s biggest criticisms fall under the umbrella of wondering where exactly intelligent machines leave humanity. There are concerns it will eclipse artists or replace workers, as Goldman Sachs reports that AI could replace 300 million jobs. In this context, the future of the human workforce suddenly looks uncertain.
Generative AI has also come under scrutiny for producing factual errors. For example, a lawyer is facing sanctions for presenting a brief riddled with fake citations that came from ChatGPT. The lawyer had even asked the language model to verify that the cases were real, to which it answered “yes”.
Artist James Bridle asks us to remember that ChatGPT has “no relation to reality whatsoever; it is dreaming sentences that sound about right.” ChatGPT will often confidently state things that are entirely wrong due to its lack of real-world understanding, biases or data limitations. In fact, artificial intelligence is so prone to making things up that it has its own creepy term: ‘hallucinating’.
“ChatGPT has no relation to reality whatsoever; it is dreaming sentences that sound about right.”James Bridle
Perhaps the most human criticism of AI is just how distinctly ‘un-human’ it all feels; the ‘uncanny valley’ of it leads people to feel distrust, confusion and perhaps even fear. It’s hard to forget a New York Times journalist’s notorious conversation with Bing’s chatbot for its persistent confessions of love – and demands that he leave his spouse.
Some argue that because AI lacks the ability to feel it removes the ‘soul’ from creative pursuits. For example, recipes generated by AI lose the human story behind cooking. “You want to know that these recipes mean something to somebody,” says Janelle Shane, an optics research scientist. “That’s something artificial intelligence may never be able to provide.”
What about regulations?
News that AI has the potential to lead to the extinction of humanity – a statement supported by OpenAI’s CEO Sam Altman – has spurred questions about the state of AI regulation. The US and UK are currently still in the discussion stages, and we don’t know exactly who is advising policymakers and whether regulation will protect worker’s jobs. But even before getting into the existential threat, Matteo Wong, Assistant Editor at the Atlantic, asks us to think about the problems AI pose in the short term, like discrimination, bias and fake news.
With no legislation or best practice to follow, the editor of the Financial Times Roula Khalaf has informed its readers that it will proceed with caution around Generative AI: “As recent history has shown, the excitement must be accompanied by caution over the risk of misinformation and the corruption of the truth.”
It’s now up to business leaders to establish where they stand on artificial intelligence in an unknown future, and more importantly, how they can use it to have a positive impact on their workers and society.
Why ‘the future of AI is the future of work’ – MIT Sloan
AI is not killing creativity; it’s enhancing it – Raconteur
New Dark Age: Technology and the End of the Future – James Bridle
What every CEO should know about generative AI – McKinsey
What can AI art teach us about the real thing? – New Yorker