AI and Cognitive Computing

people working on computer outside

Written by Jun Wu, Freelance writer, Technology, Coding, Artificial Intelligence

Understanding the difference between AI and cognitive computing is critical for understanding the future of work.

AI and Cognitive Computing are often interchangeable terms to people who are not working in the technology industry. Both imply that computers are now responsible for performing job functions that a human used to perform.

In fact, there’s a big difference between AI and Cognitive Computing. Understanding the difference will be intrinsic in facilitating the work of a person working in the intersection of these two.

What is Artificial Intelligence?

AI is the simulation of human intelligence processes by machines. These processes include learning from constantly changing data, reasoning to make sense of data and self-correction mechanisms to make decisions.

Human intelligence is rooted in sensing the environment, learning from the environment and processing the information from the environment. Therefore, AI includes:

  • simulation of human senses: sight, hearing, smell, taste, and touch.
  • simulation of learning and processing: deep learning, machine learning.
  • simulations of human responses: robotics.

AI Applications includes problem-solving, game playing, natural language processing, speech recognition, image processing, automatic programming, and robotics.

What is Cognitive Computing?

Cognitive Computing is the individual technologies that perform specific tasks that facilitate human intelligence. These are smart decision support systems that we have been working with since the beginning of the internet boom.

With recent breakthroughs in technology, these decision support systems simply use better data, better algorithms to come up with a better analysis of vast stores of information.

Therefore, cognitive computing refers to:

  • understanding and simulating reasoning
  • understanding and simulating human behaviour
  • using cognitive computing systems, every day, we make better human decisions at work.

Cognitive Computing applications include speech recognition, sentiment analysis, face detection, risk assessment, and fraud detection.

What are the differences?

AI augments human thinking to solve complex problems. It focuses on accurately reflecting reality and providing accurate results.

Cognitive Computing focuses on mimicking human behaviour and reasoning to solve complex problems.

Cognitive Computing tries to replicate how humans would solve problems while AI seeks to create new ways to solve problems that can potentially be better than humans.

AI is not intended to mimic human thoughts and processes but to solve a problem through the best possible algorithm.

Cognitive Computing is not responsible for making the decision for humans. They simply supplement information for humans to make decisions.

AI is responsible for making decisions on their own minimizing the role of humans.

What are the similarities?

The technologies behind Cognitive Computing are similar to the technologies behind AI. These include machine learning, deep learning, NLP, neural networks, etc.

The Real World

In the real world, applications for Cognitive Computing is often different than applications for AI.

Cognitive Computing is important in analysis intensive industries such as Finance, Marketing, Government and Healthcare Data.

AI is important in service-oriented industries such as Healthcare, Manufacturing and Customer Service.

The Issue with Jobs

People do not fear Cognitive Computing since it simply supplements human decision making. The real fear is when AI Systems will displace human decision when used in conjunction with Cognitive Computing.

The middle man is now humans who are still making the decisions.

Do we need to cut out the middle man and replace him/her with AI to facilitate optimal decision making?

That’s the question that we will likely answer on a case by case basis for each job type in all of our industries in the years to come.

Originally posted here.

More thought leadership

Comments are closed.