Human creativity is the elixir that’s powered civilisations down the ages. It’s brought us untold breakthroughs in all sectors of the economy, from agriculture to healthcare, energy to mobility. Our imagination continues to be our saviour as the world’s ageing population faces tough socioeconomic and environmental challenges.
Imagination entails creating mental models of things that don’t yet exist. This kind of innovation brought us the printing press, the steam engine, the light bulb, the telephone, the aeroplane, the TV and the PC. All of these required improbable acts of human invention. Yet many businesses are failing to harness their employees’ creativity, even though they say it’s a vital trait for success.
Martin Reeves, co-author of a recently published book called The Imagination Machine: how to spark new ideas and create your company’s future, is chair of the BCG Henderson Institute, a think-tank created by the Boston Consulting Group. He believes that “we need to focus on imagination because a competitive advantage doesn’t last very long anymore. If you were the leader of your industry in the 1980s, you could expect to be at the top for at least 10 years. Now that period has come down to one to two years.”
He continues: “This means that companies can’t just focus on optimising yesterday’s business model; they need to create new ones. We must generate growth through our creativity.”
Computers still struggle to emulate this uniquely human process. Even the most high-powered machines cannot imagine a product or service that’s never been seen before. They can’t conjure up the new iPhone or Tesla of tomorrow. (Neither can many humans, for that matter.) But the tide is turning.
Humans can disassemble and recombine learnt knowledge to conceive of new images – think of a red boat, visualise a blue car and then imagine a blue boat, for instance. A team of AI experts from the University of Southern California (USC) is researching how to emulate the process artificially. This involves a concept called disentanglement. Humans break down the things they learn and visualise them as colours, shapes and types. We are then able to recombine these attributes to form novel images. The researchers have replicated this using neural networks.
“The new approach truly unleashes a new sense of imagination in AI systems, bringing them closer to a human understanding of the world,” says researcher Yunhao Ge, who has been leading the project at USC.
Disentanglement isn’t a new concept. Indeed, it’s being used to create so-called deepfake content, typically by recombining separate images of well-known people. AI has also been used in this way to invent a new sport known as speedgate. Data from 400 popular sports was fed into a neural network. Out popped many suggestions, but the winner involved merging elements of football, croquet and rugby on a field with six-player teams, a ball and three gates.
The USC system takes a whole group of sample images or data, rather than one at a time, as traditional algorithms have done. The system looks at similarities between those images, which it then recombines using all the data to make something new. The process is known as controllable novel image synthesis.
What’s new is that the system can handle nearly any kind of data. It may eventually help in the discovery of novel drugs by combining learnt functions from existing medicines to form innovative treatments. The technology could disentangle race and gender bias to make fairer algorithms or create safer driverless cars by simulating countless crashes. The method may even be able to create new data sets by imagination.
“In the future, AI could be effectively boundless,” predicts Michael Conway, leader of the AI and analytics practice at IBM. “It will be able to see connections between things that humans can’t. A more advanced version will be able to look beyond the parameters we have set and offer valuable insights that humans wouldn’t have even imagined.”
If a more imaginative organisation is a clear goal for business leaders, the future is likely to involve technology, such as the system created at USC, that could in time complement more creative thinking by employees. After all, when the algorithm was trained to create speedgate, a human still had to choose the most realistic sport to select from the countless absurd options that the system suggested. Augmented imagination is therefore likely to be the next step. The term that Reeves uses to describe a business that can gain such capabilities is “a bionic organisation”.
“What will work best is AI operating alongside humans, rather than independently,” says Melissa Terras, professor of digital cultural heritage and a fellow of the Alan Turing Institute. “The obvious way forward is to have AI process vast amounts of information and propose new solutions and to have a human working in tandem, fine-tuning the results. We’ll eventually get to know the quirks of these systems and be able to play them like musical instruments, as well as choose which ideas need development. This is the ‘imagination machine’ – an act of co-creation, with computational power and intelligence complementing our own.”
Humans are relatively good at counterfactual thinking. This is the ability to imagine something that doesn’t currently exist but could in the near future. This is what sets us apart from any current form of machine learning. Yet corporations aren’t normally focused on this type of activity. Instead, they tend to be nose down in quarterly earnings reports, dealing with the here and now or facing up to the immediate past. The imaginative spirit is rarely used to help steer businesses with a firm eye on the future, but this could change.
“I am very bullish about the bionic organisation – a more effective business that taps into both human and machine cognition,” Reeves says. “The ‘imagination machine’ isn’t just the silicon; it has a human element. If you are thinking about growth right now, you are thinking about imagination.”
He continues: “In 10 years’ time, when someone says ‘organisation’, they’ll be referring to a synergistic combination of algorithmic and human thinking that gets the job done better. This raises all sorts of questions. For instance, what technology will be deployed? How do we use it? How do we match the bandwidth of machines and humans? How do you ensure that the whole organisation is serving human ends and is ethical? What do humans do and what do machines do?”
The current era of AI is all about using algorithms, neural networks and deep learning to automate lower-value, higher-volume tasks. The scale of analysis that computers can undertake puts machines in a league of their own when it comes to these kinds of jobs. One school of thought is that applying AI to more of this work could give humans the freedom to be more creative. But not everyone agrees.
“There is a concern that an AI-generated innovation sector may be repetitively iterating on the world that already exists, rather than transcending it,” says Terras, who is also a co-director of the University of Edinburgh’s R&D programme in creative informatics. “Why not let machines do what they are good at – synthesising and processing vast amounts of information – while humans deal with complexity and nuance to build products and services that will succeed for humanity?”
We still have some way to go before AI muscles in on human-led imaginative tasks and enters the mainstream in creative thinking. But, if that time comes, its potential to benefit society could mark a turning point.
There will be less talk about automation stealing people’s jobs or calls for a robot tax when the technology can create the next pandemic-beating superdrug, say, or an affordable means of capturing and storing atmospheric CO2. Then AI’s will be firmly cemented in society. It will also take human ingenuity to get us there.
“Will we be able to use organisational science, brain science, social science and digital science to do a better job? The answer is that we already can,” Reeves says. “The focus of imagination will be the reinvention of business.”