Cognitive Computing

Cognitive computing is a branch within artificial intelligence (AI) that aims to mimic human cognitive abilities using technology, operating outside of the human body.

In simple terms, cognitive computing is a branch within artificial intelligence (AI) that aims to mimic human cognitive abilities using technology, operating outside of the human body.

But what does it really mean? If AI in general is technology that mimics human cognitive abilities, what does cognitive computing specifically entail? How does it differ from other AI facets like generative AI, for example?

I know we all believe we know what it means but let’s remind ourselves you can find it here: human cognitive abilities.

What is the conventional definition of Cognitive computing?

By conventional definition Cognitive computing refers to the field of computer science that aims to simulate human thought processes and capabilities in a computerized model. 

It involves developing systems that can understand, learn, reason, and interact with humans in a more natural and intelligent way.

Key characteristics of cognitive computing include:

Natural Language Processing (NLP): Ability to understand and generate human language, enabling interactions via speech or text.

Machine Learning: Capability to learn from data and improve performance over time without explicit programming.

Pattern Recognition: Capacity to identify and interpret patterns and trends in large datasets.

Adaptability: Ability to adapt to new information and circumstances to make more informed decisions.

Problem-solving: Capacity to solve complex problems by processing and analyzing vast amounts of information.

Cognitive computing systems are designed to assist humans in making decisions, solving problems, and improving overall efficiency across various domains, including healthcare, finance, customer service, and more. These systems often leverage artificial intelligence (AI) technologies such as deep learning, neural networks, and advanced algorithms to achieve their cognitive capabilities.

What is Cognitive Computing from AI’s perspective?

From AI’s perspective, cognitive computing enables it to engage with humans in a more sophisticated manner that involves multiple facets simultaneously. This means AI can understand and respond to human interactions that encompass language, reasoning, problem-solving, pattern recognition, and adaptation to different contexts. Cognitive computing enhances AI’s capability to process complex information and interact with humans more naturally, resembling human cognitive abilities in diverse scenarios.

AI technology encompasses a spectrum of capabilities, ranging from basic applications that use simple automation to respond to routine inquiries or route calls based on predefined rules. Such AI systems lack the sophisticated understanding, learning, and adaptive behavior characteristic of cognitive computing.

On the other hand, cognitive computing incorporates advanced AI technologies such as natural language processing (NLP), machine learning, and pattern recognition. It enables systems to understand complex queries, learn from interactions, make contextually relevant recommendations, and continuously improve based on new data.

The key distinction lies in the depth of intelligence exemplified and the ability to simulate human-like cognitive functions, which are hallmarks of cognitive computing. While both types of applications serve customer service purposes, cognitive computing applications offer a higher degree of sophistication and capability in handling complex interactions and tasks.

My Thoughts on Cognitive Computing and AI

The starting point of working with AI is understanding human cognition because, at its most basic level, AI is a technology that imitates human cognitive abilities. If we don’t understand what this means, we cannot fully grasp what AI can offer us.

This understanding is crucial because it forms the foundation of everything we do with AI. AI is not better than us and not worse than us; it’s just different. The key difference is that AI lacks the emotional charge, what we call feelings. While AI can logically understand emotions, it does not experience or feel them the way humans do.

For humans, emotions shape how we experience the world and understand reality. If we were unable to feel emotions connected to our thoughts and feelings, we would be similar to AI. In the context of work, emotions may not always have a place, but just because we don’t show our feelings doesn’t mean we don’t have them, and they don’t affect how we engage with reality and show up in the world.

This difference is at the core of what makes us unique. Our cognition operates within a biological body, which means we have the capability to experience the world fully. This unique human trait is the source of our creativity, individuality, and the basis for true collaboration between humans and technology. With the use of AI, we are augmenting reality, creating new experiences that AI cannot feel and requires us, humans, to do so.