Computing and Cognition1

Cognitive Computing



Cognitive computing refers to systems that learn at scale, maintain processes with purpose and interact with humans naturally. Rather than being explicitly programmed for specific functionality, they learn and adjust processes from their interactions with users and from their experiences with their environment. These systems are made possible by advances in a number of scientific fields over the past decades, and are different in important ways from the information systems that preceded them.

Traditional functional systems have been deterministic; cognitive systems are probabilistic. They generate not just specific answers to problems, but hypotheses, reasoned arguments and recommendations about more complex and meaningful objects of data. This way, cognitive systems can make sense of most of the world’s data commonly known as “unstructured data”. This way are able to keep pace with the volume, complexity and unpredictability of information and systems in the modern world.

None of this involves either sentience or autonomy on the part of machines. Rather, it consists of augmenting the human ability to understand -and act upon, the complex systems of our society. This augmented intelligence or rather say the extra dimension of understanding the flow of things, is the necessary next step in our ability to harness technology in the pursuit of knowledge, to further our expertise and to improve the human condition. That is why it represents not just a new technology, but the dawn of a new era of technology, business and society: the Cognitive Era.

What are Cognitive Systems

Cognitive systems are probabilistic, meaning they are designed to adapt themselves making sense of the complexity and unpredictability of unstructured information. The system shall interpret information from several unstructured sources like printed and spoken words, images, and sound and organize it and offering explanations of what it means, along with the rationale for their conclusions. The system don't need to offer definitive answers or even understand 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.

However the most important fact is that cognitive systems can learn from their mistakes. Large-scale machine learning is the process by which cognitive systems improve with training and use. The system “knowledge” is enhanced as humans interact with the system and provide feedback on the accuracy of the system’s responses, multiplying the process ad-infinitum.

The Future

For cognitive computing to fulfill its true promise, the underlying platform must be broad and flexible enough to be applied by any company in any industry, and able to be applied across industries, requiring a holistic approach to research and development.

This platform must encompass many complex computing disciplines. Many of these capabilities require infrastructure that leverages high-performance computing, specialized hardware architectures and even new computing paradigms. Each growing from its own scientific or academic field. But these technologies must be developed in concert, with hardware, software, cloud platforms and applications that are built expressly to work together in support of cognitive solutions. for the power of this new model to be applied to any domain.

What implies the advance of cognitive science

The Cognitive era is the next step in the application of science to understand nature and improve the human condition. In that sense, it is a new chapter of a familiar story, and the controversy surrounding AI is merely the latest example of the age-old debate between those who believe in progress and those who fear it. Within the scientific community there is broad agreement on the importance of pursuing a cognitive future, along with recognition of the need to develop the technology responsibly.

Specifically, we must continue to shape the effect of cognitive computing on work and employment. Like all technology, cognitive computing will change the nature of work done by people. It will help us perform some tasks faster and more accurately, with many processes done cheaper and more efficient. What has always happened is that higher value is found in new skills, and humans and our institutions adapt and evolve. There is no reason to believe it will be different this time. Indeed, given the exponential growth in knowledge, discovery and opportunity opened up by a Cognitive era, there is every reason to believe that the work of humans will become ever-more interesting, challenging and valuable.

Equally important is the need for societal controls and safeguards. However, such concerns are not unique to intelligent systems. Questions about security -both individual and institutional, attach themselves to every transformational technology. These issues are already urgent, and will remain so as cognitive technologies develop, fueled especially by today’s radical democratization of technology, driven by the rapid spread of networks and the cloud, and the accompanying reduction in costs.


1. Excerpts from IBM: "Computing, cognition and the future of knowing".