A few decades ago, a computers’ power was limited due to its inability to process unstructured data in the way a human brain can. Computers could not understand natural language since their processing capabilities were limited to 1s and Os in a strictly binary structure. The advent of cognitive technology has transformed computing and therefore many aspects of business, government and organizations, offering unparalleled power to increase value in core areas. Cognitive technologies are the key outputs from the field of artificial intelligence, powering tasks that historically could only be performed by humans. They mimic some human behaviours, intelligence with one key goal in mind; l solving important and challenging problems.

Although there is no one acceptable definition of artificial intelligence, it has now been fully recognized as a collection of practices, initiatives, and activities, all extending the computers’ capability to perform more cognition, perception, decision-making based task, thereby supporting transformation in a variety of human endeavours.

The best approach to understand AI phenomena is to focus on critical areas and operationally define them within the said domain. For example, using intelligence to solve performance problems and utilizing data to improve diagnosis in health care. Although work is being done in the creation of artificial general intelligence (AGI), which can perform multiple functions in various situations, there is a movement towards specific subsets of AI to narrow focus on a peculiar problem area. For instance, we can talk about cognitive technologies which are perception based (facial recognition), or perceive things (awareness of environment based on inputs from sensors), or predict (using patterns to show what is likely to happen next, learn progressively to improve performance), plan (utilization of lessons learned to make decisions).

Although, some persons use cognitive and AI technologies interchangeably, maybe in recognition of the limited scope of AI, in real terms there is a distinction. AI can be considered to be the parent, and cognitive technologies a narrow sub-set application of this broader field of artificial intelligence.

From Abstract concept to Action

Although, there is a lot of marketing hype around AI, including over promising in terms of what it can deliver. There is a lot of evidence that points to the fact: cognitive technologies may be more useful. We can list four primary areas of the application of cognitive technology in improving operations. Firstly, it enables innovation by ensuring we can understand new patterns and discover opportunities and insights previously unattainable. It can assist with the issue of information overload, by offering personalized and adaptive experiences through tailor made products and services, delivering engaging content which meets individual needs. Furthermore, cognitive technologies provide tools for optimization, thereby ensuring more effective and efficient delivery of services. Lastly, it offers the mechanism to leverage an organization’s collective wisdom to permeate every aspect of its operations, breaking workplace silos.

For organizations wishing to leverage on cognitive technologies, a good starting point will be to define a specific problem that cognitive technologies can solve and documenting this in a business case. Once drawn, however, the business case should not be cast in stone. It should be seen as providing signposts for an iterative process.

Once the entity is clear on what problem they want to solve, it is recommended that they use the many cognitive tools available on the market, such as; Watson Virtual Agent , Watson Explorer as well as a variety from Google, Microsoft, CISCO among others. The entity can purchase or subscribe to these products, and install and integrate it with appropriate data sources without the need for coding. As the entity grows in terms of its cognitive technology capabilities, knowledge, and skills, it can build its own internally developed cognitive technology applications through coding.

In this direction, the entity can rely on a number of cognitive technologies APIs (Application Programming Interfaces) to give them a head start. The entry-level to building cognitive solutions in-house is quite steep in terms of costs and other resource requirements; therefore, organizations can collaborate with other like-minded ones to develop solutions that benefit each of the partners.

In conclusion, cognitive technologies are not a futuristic eschatology; it is a present reality; therefore, individuals, organizations, and society as a whole must recognize its limitation and risks, but work to increase its potential to help our world solve important problems.

Kwami Ahiabenu, II is a Tech Innovations Consultant

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