Cognitive disruption: Where man and machine become one!

In 2017, digital disruption is history. If you are not thinking about cognitive disruption, your business is way behind in the technology curve.

In the recent IBM annual survey of global CEOs, about 73 percent say cognitive computing will play an important role in the near future of their organizations, with the same sentiment echoed by other c-suite executives as well. While almost three-fourths of CEOs agree that their businesses, and their industries, will be disrupted by cognitive computing in the near future, surprisingly only about half of these CEOs are planning to adopt cognitive computing by 2020.

While that may seem stunning, the primary reason is pretty clear: infusing cognition into an existing infrastructure is extremely difficult, very time-consuming and will be very expensive.

As an example, the cognitive brain known as IBM Watson took years to build, cost a ton of money, and involved thousands of super-bright engineers. Given the substantial investment required to build cognitive apps, the average enterprise may not have the tolerance or the capital to expend resources at that level. Therefore, it’s critical to look for a cloud platform that not only brings a robust, scalable, and secure environment, but also comes with cognitive capabilities already infused at the core of the platform.

What is cognitive computing? 

It is an effort to mimic the human brain’s learning process, thought process, reasoning, analysis, and decision-making. A major difference between existing systems and cognitive systems is that cognitive systems can understand what’s called “dark data.” Dark data – images, video, audio, medical scans, sensor data, telematics, etc. – cannot be analyzed by most of the existing systems to get insights that can help with the decision-making. Dark data is growing exponentially – it is estimated to be about 80 percent of world’s current data collection, and is expected to grow to about 90 percent by 2020.

The other difference is that cognitive systems can help users move away from the “programmable era” and into the “cognitive era.” Historically, computers needed to be programmed, explicitly, on what to recognize and how to react to different scenarios. However, these traditional, non-cognitive systems hit a brick wall when they encounter a scenario that they are not programmed for. In contrast, cognitive systems have critical thinking capability, much like a human brain. When presented with a new scenario, they can learn, understand, analyze the situation and act without the need for additional programming to make authoritative decisions.

Cognitive computing is not about mankind against the machines, as Terminator movie series would suggest. It is about machines collaborating with mankind, augmenting the human brain, man and the machine turning into one, with specific goals in mind.

A real-life example

When a patient (TJ Richard from FL) went to get his physical required for his CDL license, he was asked by his doctors to go for a chest x-ray as they suspected something. They detected early stage lung cancer. After the successful initial operation, they wanted a second opinion, so they engaged a famous Oncology Dr named Watson (Watson for Oncology, same Watson you saw on Jeopardy, with a slightly different flavor) in the clinical decision-making process. Two specialists and Dr. Watson came up with the same conclusion for further treatment of TJ.

While the two specialists came up with the treatment based on their experience, Watson for Oncology, on the other hand, came up with recommendation based on the training it received from Memorial Sloan Kettering Cancer Center to understand the cancer type and provide different treatment options. In other words, it is as if those two specialists were going to MSK cancer center for a second opinion. Watson was not only able to read and understand the specific medical history of TJ, and the fact that he was producing excessive PD-L1 that was making him vulnerable for future recurrence, but it also came up with evidence based medicine based on oncology guidelines, medical literature, clinical trials information, and more. Both the specialists and Watson recommended the same primary option – Keytruda treatment, an immunotherapy that TJ is on today and well on his way to a complete cure.

While TJ was lucky enough to have two experts, who helped him with his battle against cancer, the majority of the global population do not have access to proper healthcare, or specialists, to make such knowledgeable decisions. This is where cognitive systems can step in by allowing a local physician, with limited resources, have access to experts in the medical field that they’ve never had before. Imagine, a rural physician in Africa feeding the exact same documents he is seeing to Watson, and have Watson come up with a treatment recommendation, using collective medical brains, to save lives – machines helping Mankind.

You can see the full case study about TJ here – https://www.youtube.com/watch?v=W8DOi11_F78

Essentially, cognitive systems, such as Watson, can not only read x-rays, MRI images, CT scan, etc., understand and analyze it just as a specialist would, but they can also learn the medical history and recommend treatment options such as a human brain would to augment our decision-making abilities.

You can browse through the list of Watson APIs & SDKs here to see how Watson can help you build a cognitive enabled smarter solution for you.

Ultimately, it will be the ability to speak to, and understand a user, in their native tongue, when they need it the most, in a form that is most consumable (e.g. mobile app, speech, text, chatbot, virtual agent), understand the urgency, needs and emotions at that time, and make critical decisions based on the “human” context in conjunction with the existing data, will add the powerful differentiator for your business in the marketplace. 

Cognitive solutions are ready to help us. It’s about time we embrace them!