Will automation and AI really kill the majority of the world’s jobs? While some believe that any job that doesn’t require creativity can be digitised, an alternative view is that artificial intelligence and automation systems don’t have to entirely replace human workers, but can help people do their jobs more efficiently. Whatever happens in the future, there’s no question that we’re now at the point where these kinds of questions need to be examined closely. AI, robots, and other forms of automation are already in use, and will only become more widespread over time.
I’ve written about how artificial intelligence has been used to analyze online opinions to determine most popular ecommerce sites and how it’s been used in cognitive computing. This time I am looking at examples in the workplace.
Information Technology’s use of Artificial Intelligence at Work
As of now, by far the most widespread use of AI is in IT departments, where it’s employed in service to data security. In one global survey, 44% of companies surveyed said they were using AI in this way. AI is used most often in detecting and thwarting attempts to breach security defences, and it plays a role that for the most part couldn’t be done by humans. In fact, in IT, artificial intelligence is helping people do their jobs more effectively, rather than replacing them.
Customer Service and Artificial Intelligence at Work
AI may in some instances be able to replace human employees, but in customer service, it’s being employed to help people deal with customer queries more effectively. For instance, DigitalGenius provides what it calls “Human+AI Customer Service” by using deep learning and artificial intelligence to analyse incoming customer service messages and provide CS agents with suggested responses to new customer queries.
Another example of how AI can be useful in improving the way people deliver customer service is that of Cogito, a company that has combined machine learning and behavioural science to help CS representatives improve the service they provide.
Cogito is particularly powerful because it provides this guidance in real time, as a customer service rep is interacting with callers. Cogito performs ongoing voice analysis and provides recommendations to CS reps as they work—for instance by notifying a rep when they’re speaking too quickly, or if they interrupt the caller. This helps improve the level of service that CS reps provide, and ensures that customer service calls are more successful and more satisfying for the customer.
Other examples are in my earlier article about AI in customer service.
For the most part, AI is used in one of two ways: to improve how workers do their jobs, and to improve the level of service a company provides to its customers. Predictive technology is a great example of the latter, where AI is used to recommend new products to customers based on what they’ve already indicated a preference for.
This is employed to lucrative effect by Amazon, Netflix, and the music streaming service Pandora. Each of these services uses a predictive algorithm to suggest new products or entertainment to its users, and to do so, it uses an AI that analyses a vast amount of data to improve the accuracy of its recommendations. Netflix, in fact, was so serious about developing the best possible predictive algorithm, that in 2006 it offered a $1 million prize to the first team who could improve its existing algorithm by 10%. The prize was eventually awarded in 2009, but ironically, the company decided not to use the code that was developed by the winning team.
Automation and Artificial Intelligence in Healthcare
In some spheres, it’s automation rather than AI that is starting to take over certain tasks previously performed only by people. Healthcare is fast exploring Artificial Intelligence, for instance, a system developed by Johnson & Johnson, called Sedasys, can deliver anaesthesia for a fraction of the cost of a trained anaesthesiologist. Currently the system is under development only for delivering light anaesthesia to people undergoing a colonoscopy, but there’s no doubt that the potential applications will increase greatly as the technology is refined and improved.
Another example is that of the IBM computer Watson, which has been trained to diagnose certain kinds of cancer, with an accuracy rate that in some cases almost doubles that of human doctors. And surprisingly, it’s not Watson’s supreme level of intelligence that is the key; it’s simply the computer’s ability to rapidly absorb new information. It’s literally impossible for a doctor to keep pace with the rate at which new medical information is discovered—it’s why medical specialisations exist, after all—but for Watson it’s an easy task. Watson is also being trained to analyse tumours of individual patients and recommend the most effective treatments from amongst an array of options.
Whether we’re ready for it or not, and whether we like it or not, automation and AI are becoming more prevalent in a wide range of industries. There likelihood of a certain amount of job loss is a virtual certainty, but there’s definitely a lot to be gained from these developments too.