Part 1 of the Future of Intelligence series
Artificial intelligence (AI); we’ve all heard of it. The universally disruptive technology, coming to change the working landscape forever. Every industry is clutching for it and every occupation is holding its breath in anticipation of its threatened effects. It is tipped to be one of the biggest innovations of our lifetime.
Replicating human intelligence is enticing for businesses. The ability to replace expensive labor costs with software alternatives immediately reduces operating costs, speeds up delivery and, ultimately, improves business efficiency. But does it have the ability to improve effectiveness or quality?
Steve Jobs famously said, “The key to Apple’s success has been a marriage of technology and the liberal arts.” AI definitely has the technology side of the analogy – but can it offer the liberal arts? Can AI compete with a human’s capacity for creativity and critical thinking?
Perhaps then, to artifice human intelligence is not the correct solution. Instead, we need to be focusing on augmenting human capabilities by reducing the work easily managed through technology and supporting what humans are good at – creativity.
What are the differences between Artificial and Augmented Intelligence?
Artificial intelligence, by its very definition, seeks to replace human intelligence. The term is often used to describe machines with the capacity to mimic cognitive functions such as learning or problem-solving. Intelligence augmentation (IA), on the other hand, isn’t about recreating human intelligence but enhancing it. It demonstrates an understanding that there is an inherent human capability not recreatable by technology; thus it is important that there remains a human aspect of intelligent decision-making. Although not as widely recognized or revered as its artificial counterpart, there are still great expectations in the immediate future of IA with Gartner predicting that by 2021 it will be creating up to $2.9 trillion of business value and 6.2 billion hours of worker productivity globally.
The technologies that enable both aren’t too dissimilar; in fact, in most cases they’re identical. Machine learning, Natural Language Processing and General Intelligence all form the basis for this automated learning. It is the intention or outcome of the technologies that differ. One aims to create systems that run without humans, whereas the other aims to create systems that make humans better.
When to replace and when to augment?
To fully understand this argument, we first need to understand the differences in machine processing and human cognition. Where does human intelligence trump that of computers and where does AI have us beat? Below we look at the pros and cons of AI:
Memory recall: Humans have limited memory and can make mistakes in their memory recall. Computers don’t.
Processing speed: Although the human brain is a complex and substantial processing unit, and quantifying its processing speed isn’t an exact science, it is obvious that the latest in supercomputer processing is much more capable – at least when it comes to controlled and logical decision-making.
Emotions: Humans are subject to emotion and there’s very little that can be done about. Even the most objective and rational human decision are biased by emotions. This isn’t necessarily a bad thing, but in some situations can reduce rational decision-making.
Environmental factors: Humans are easily affected by environmental pressures. Whether a person is too hot, stressed or tired, for example, can substantially affect the outcome.
Critical thinking: What a computer offers in logical and controlled decision-making, it is much less capable of in complex and multifaceted decision-making. The necessary agility to think critically is still very much a human ability.
Creativity: While a computer can think logically and systematically, it is unable to pursue creativity. Art, literature and music are just a few examples of where their creative capacity is lacking.
Unstructured decision-making: AI works best in a closed environment, with known factors, known consequences and clear goals. Outside of these controls, it is much less effective and mobile. A human, however, is uniquely skilled at weighing knowns, unknowns and, in some cases, guessing, to make decisions of significant complexity.
What can be drawn from these comparisons?
AI shines in process-based and logical decision-making. The human brain is outpaced and outsized in comparison to a computer’s processing ability. Humans, by definition, are human and subject to the flaws of humanity. Machines, meanwhile, aren’t influenced by their surroundings or moods, faithfully following their programming to the letter (or code).
Nevertheless, the human brain is still the most advanced processor when it comes to complex and unstructured decision-making. While it may not be able to keep up with the processing capabilities of technology, it is still the best critical and creative tool we know.
Essentially, to develop the best intelligence tool you need some form of AI-human hybrid. The machine, to handle the processing, the mundane and mass; the human, to handle the creativity, complexity and quality. Otherwise known as augmented intelligence.
AI is most likely the future of intelligence, yet it is clear that it is a long way from truly replacing the complexity of human cognition. In the interim, doesn’t it make more sense to utilize the power and capacity of machine ability to supplement that of human intelligence?