Artificial Intelligence is the most talked-about topic, ensuing massive speculation on whether robots will rule the roost. A contemplation on the present scheme of things and of the days to come as this stream of science goes about redefining the relationship between humans and technology...
Artificial Intelligence (AI) is an unavoidable topic today triggering an ongoing media frenzy of coverage and the ensuing public concern that current jobs will be overtaken by robots. Taking a step back, it is useful to identify the AI becoming widespread today versus the AI of tomorrow and recognize the practical business and societal problems it solves.
Artificial Narrow Intelligence (also known as ANI or Weak AI) refers to systems programmed to do a single task, whether it’s playing chess, identifying early stages of a disease on an MRI scan or autonomously driving through an environment. While these tasks differ significantly in complexity and in advancements of AI techniques, they still fall under specific operational domains.
Artificial General Intelligence (AGI or Strong AI) is the machine equivalent of human intelligence where the AI is conscious, sentient and has emotions; this is typically the popular sci-fi representation of AI such as is in Ex-Machina, Her, iRobot and Westworld. There are more speculative levels of AI such as Artificial Super Intelligence, where the robot could outperform human intelligence in multiple domains and tasks, such as autonomously driving to a hospital to detect a patient’s disease and later defeat a human in chess.
Although AI research has progressed immensely in the last few years, there will likely be some time before there is an AGI breakthrough; AI researchers speculate it could happen in 10 years or take over 100 years.
AI Replaces Tasks, not Work
There is substantial misconception about automation and AI replacing a job’s task versus the job itself. As we know with ANI, a single task can be automated but people underestimate how many different and constantly changing tasks a typical worker experiences. McKinsey estimates that less then 5 percent of jobs consist of activities that are 100 percent automatable. The recurring theme is that increasing productivity through automating certain monotonous tasks creates net new jobs. For example, IDC forecasts that by 2023, 25 percent of leading retailers will have explored or deployed in-store robots to relieve human workers from repetitive tasks, thus increasing worker productivity by 40 percent. There will likely be some job displacement, but this can be solved by reskilling and upskilling programs improved by using innovative training tools such as augmented reality.
AI in Practice is Saving Lives Today
Advancements in complementary technologies such as cloud computing, sensors and processors is propelling AI research across industries unlocking use cases and solving problems once thought unsurmountable. Like most pieces of emerging technologies, the goal of AI is to solve actual challenges plaguing industries such as healthcare.
In the healthcare industry, there is a global shortage of medical personnel and, even in developed countries such as the US, there is estimated to be a shortage of up to 120,000 physicians by 2030.
Through emerging deep learning techniques based on artificial neural networks, AI can scale doctors’ expertise to mitigate this skills gap as well as be a complementary tool to time-constrained medical professionals.
A deep-learning computer vision model called DeepGestalt was able to identify more than 215 genetic syndromes at 91 percent accuracy through its facial analysis framework. UC San Diego researchers used AI to analyze structured (health records, test results) and unstructured (hand-written notes) paediatric patient data to diagnose sinus infections at 95 percent accuracy, acute asthma with 97 percent accuracy, and mononucleosis at 90 percent accuracy.
AI saving lives does not take medical professionals out of the picture; Microsoft’s Healthcare Bot service is designed to streamline more straightforward customer service questions while only the complex issues reach a human counterpart, which optimizes time and improves interactions with patients.
There are several other AI applications across industries not directly saving lives, but still improving our safety. Striving to save lives in a different sense (94 percent of crashes are due to human error according to the National Highway Traffic Safety Administration (NHTSA), ANSYS is using simulation to train autonomous vehicles through virtual driving scenarios, which improves its self-driving AI algorithms without jeopardizing human safety. Rockwell Automation’s Project Sherlock is creating a safer environment and enabling operational efficiencies through an AI module reducing false-positive alarms for boiler, pumps and chillers in industrial settings.