Cognitive systems and artificial intelligence, according to IBM

I just discovered a 2015 white paper by John E Kelly, SVP of IBM Research, called “Computing, cognition and the future of knowing.” This paper provides a great overview of artificial intelligence and machine learning.

Kelly begins by introducing us to “cognitive computing.”

“Cognitive computing refers to systems that learn at scale, reason with purpose and interact with humans naturally. Rather than being explicitly
programmed, they learn and reason from their interactions with us and from their experiences with their environment. They are made possible by
advances in a number of scientific fields over the past half-century, and are different in important ways from the information systems that preceded them.

“Those systems have been deterministic; cognitive systems are probabilistic. They generate not just answers to numerical problems, but hypotheses,
reasoned arguments and recommendations about more complex — and meaningful — bodies of data.”

In other words, we’re moving from a world of deterministic, programmable systems that perform operations to a world of probabilistic, cognitive systems that create hypotheses and make recommendations.

Kelly writes that these cognitive systems are not meant to replace human thought or actions — but rather augment them. He shares the example of Garry Kasparov, the one-time world chess champion who lost to IBM Deep Blue in 1997. After losing to Deep Blue, Kasparov participated in “freestyle” chess leagues, where players were able to compete in chess tournaments with the assistance of computers. Some players played unassisted, others relied entirely on computers, and yet others combined computer input with their own instincts and strategy. The players who were the most successful combined computer input with their own strategies.

“Teams of human plus machine dominated even the strongest computers. Human strategic guidance combined with the tactical acuity of a computer was overwhelming. We [people] could concentrate on strategic planning instead of spending so much time on calculations. Human creativity was even more paramount under these conditions.” — Garry Kasparov

As the amount of structured and unstructured data explodes, cognitive systems will be able to help us process the deluge of data to make effective decisions. According to the paper, “Gartner estimates that the
world’s information will grow by 800 percent in the next five years, and that 80 percent of that data will be unstructured.” How will cognitive systems be able to help us with this? And how do these probabilistic, cognitive systems compare to the deterministic, programmable systems of the past?

“Programmable systems are based on rules that shepherd data through a series of predetermined processes to arrive at outcomes. While they are
powerful and complex, they are deterministic — thriving on structured data, but incapable of processing qualitative or unpredictable input. This rigidity limits their usefulness in addressing many aspects of a complex, emergent world, where ambiguity and uncertainty abound.

“Cognitive systems are probabilistic, meaning they are designed to adapt and make sense of the complexity and unpredictability of unstructured information. They can ‘read’ text, ‘see’ images and ‘hear’ natural speech. And they interpret that information, organize it and offer explanations of what it means, along with the rationale for their conclusions. They do not offer definitive answers. In fact, they do not “know” the answer. Rather, they are designed to weigh information and ideas from multiple sources, to reason, and then offer hypotheses for consideration. A cognitive system assigns a confidence level to each potential insight or answer.”

So in a world where data will grow by 800% in the next 5 years, and 80% of that will be unstructured data, you need cognitive systems to be able to interpret the data and offer conclusions. You improve the performance of these cognitive systems over time by providing them with training data and feedback.

What capabilities do cognitive systems enable?

1. Deeper human engagement and personalization. Cognitive systems can take all data available to them — web interactions, transaction history, sensor data from wearable technology — to personalize interactions with a human. Cognitive systems “find what really matters in engaging a person. By continuously learning, these engagements deliver greater and greater value, and become more natural, anticipatory and emotionally appropriate.”
2. Enhanced expertise and knowledge-processing. By leveraging cognitive systems, humans will be able to keep pace with the explosion of data and knowledge that is being created. Cognitive systems become an always-on companion that professionals can use to quickly access and process all of the latest information and knowledge to help them make the best decisions. This capability can help fields as diverse as medicine, law, or customer service.
3. The ability for products and services to sense and think. “Cognition enables new classes of products and services to sense, reason and learn about their users and the world around them.” Applications will include products like self-driving cars, robotics, and home automation.
4. Improved business processes and operations. Businesses will be able to ingest and process vast amounts of data; monitor their own operations and workflow; reach effective decisions quickly; and learn from, adapt to, and even predict changes that may affect their business. Cognitive systems will enable continuous learning, better forecasting and prediction, and automation of routine tasks and tactical activities.
5. Accelerated discovery and innovation. Businesses can use cognitive systems to identify patterns and development hypotheses from vast mountains of data. This capability will help businesses accelerate R&D and innovation in fields like pharmaceuticals, materials science, and even mobile startups.

Kelly ends the white paper by discussing how IBM believes cognitive systems will assist — and not compete with — humans moving forward.

“The much-hyped drama of ‘man vs. machine’ is a distraction… and it rests on an exciting but misguided fiction. Cognitive systems are not our competitor, nor will they become so. Neither the science nor the economics support such fears. Cognitive systems, as they actually exist, are a tool to deepen the relationship that really matters — the relationship between humans and the world… It’s true that cognitive systems are machines that are inspired by the human brain. But it’s also true that these machines will inspire the human brain, increase our capacity for reason and rewire the ways in which we learn.”

After reading this white paper, I feel much more informed and inspired about the opportunities for cognitive systems, machine learning, and artificial intelligence. We are still in the early days of the cognitive computing era — and the possibilities ahead of us seem almost endless. I’m excited to continue following the trends around cognitive computing and AI over the next several years!