Every month, a new tech solution is announced, promising to disrupt backward industries, revitalize stagnant business sectors, and change our lives for the better. With the building blocks of tomorrow being digital, AI is one of the most exciting emerging technologies of today.
AI is at the forefront of digital innovation—transforming fields as diverse as healthcare, retail, and finance. And it’s clear that a solid understanding of artificial intelligence gives businesses and individuals an edge when it comes to staying ahead of the competition.
But at the same time, headlines warn that the impending robot revolution will cause mass unemployment.
Can AI change the world without putting us out of work? Could an AI-human collaboration allow machines to improve our capabilities without replacing us all together?
The solution? “Augmented intelligence,” which uses AI to improve human performance. Here are a few examples of this exciting technology at work.
Healthcare
In 2019, it was discovered that a deep neural network—a type of AI—could predict which women were at future risk of breast cancer better than existing screening models. AI technology was able to extract vast amounts of information from mammograms and use it to identify those women who required additional screening.
But this use of AI doesn’t threaten the livelihood of doctors. Humans will continue to play a pivotal role as safety gates. Although AI is increasingly making accurate predictions, it’s the humans who work alongside it that allow for the best results to be achieved.
According to Harvard research, AI algorithms can read diagnostic scans with a 92% accuracy rate. On the contrary, humans score 96%. And when the two work together, that shoots up to an impressive 99%.
Robots are also being used in surgery thanks to their high levels of precision. However, these AI tools aren’t intended to replace surgeons entirely.
For example, an automatic suturing device is being developed to reduce the time it takes to perform a single stitch to one-third of a second. This tool, another example of human-machine collaboration, frees up the surgeon’s other hand for different tasks.
Retail
AI is dramatically changing retail workflows. Automation speeds up processes and makes them more efficient. For example, a task that takes employees one month to complete at Walmart can be completed in just 24 hours with drones that fly through warehouses, scanning and checking items.
But robots aren’t simply replacing humans. They’re working with them.
In manufacturing, “cobots” are an example of human-machine collaboration. A cobot arm, for example, can handle repetitive and laborious actions while humans perform those tasks requiring more judgment or dexterity. Meanwhile, Hyundai is developing robotic exoskeletons that are wearable, giving factory workers enhanced endurance and strength.
In marketing, professionals can work alongside AI to attract customers. Data mined by AI can be used to create targeted ads and offer personalized recommendations. At Starbucks, AI is being used to recognize customers’ mobile devices and ordering histories to help baristas make recommendations.
However, it remains the barista’s choice whether to act on this information. Machines provide the data, but humans make the judgment.
With this in mind, Autodesk created Dreamcatcher AI to “enhance” the imagination of designers. Dreamcatcher churns out design suggestions that might spark new ideas in designers. While the machine does the boring work, making sure each design meets the necessary criteria, the designer can focus on aesthetic judgment.
Financial Services
In cybersecurity, intelligent technologies are powerful fraud-detection tools. By comparing millions of transactions and discerning which are legitimate and which aren’t, machines can spot things in security screenings that humans don’t pick up on.
Machine learning sees patterns in data from which we can draw insights and solve complex problems. This means financial institutions can also react better to market trends, predict risks, and manage client satisfaction.
Just as with healthcare and retail, however, this is about human-machine collaboration. Technology provides the data and insights. Humans make the decisions.
And, insecurity, data analysts and IT professionals will still be needed to ensure that the software that detects financial fraud is constantly kept up-to-date.
Working together
Many fear a dystopian future with humans swept to the side in favor of robots who can do their job faster and better.
But the future is likely to look far more collaborative. Augmented intelligence means using AI technology to complement and improve our own abilities in a symbiotic relationship between humans and machines.
Machines are accurate, precise, have a limitless memory, and a capacity for consistency that we will never attain. They work fast and efficiently and can handle vast quantities of information with ease.
But our critical way of thinking has not yet been replicated in robots. We also have superior leadership and teamwork skills, and our capacity for creativity and understanding social nuances has so far proven impossible to reproduce.
By working with machines, we can profit from their skills to ensure the best possible outcomes. Machines can automate physical, repetitive, and time-consuming tasks, freeing us up for more creative, sociable, and intuitive roles. We can take on the jobs of overseeing, guiding, and making judgments and decisions.
Or perhaps we can focus on training artificially intelligent machines or re-calibrating software to keep it up-to-date. Or we might collaborate with machines in a very literal sense—as seen with cobots.
Whatever form augmented intelligence takes, automation of low-level tasks allows humans to take on roles that are more focused on creativity, innovation, and empathy. In this sense, AI has the potential to make the workplace far more fulfilling for everyone.
A new future
Productive partnerships between AI and humans could transform this world for the better. The leaders of tomorrow will be “those that embrace collaborative intelligence.” Employees of the future will need to be able to work with the human-machine interface, and a knowledge of the complexities of AI will be essential