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Humans Will Set The Context And Machines Will Execute

The need of the hour is to harness the complementing strengths of both the forms of intelligence for best results.

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Machines and technologies are magical because of the way they function. Look at the ‘Demo: The magic of AI (artificial intelligence), neural TTS (text-to-speech), and holograms at Microsoft Inspire 2019’ video. It shows a machine that not only looks like a human but is also equipped with advanced skills that allow it to communicate in the local language anywhere in the world. Or picture the awe-inspiring machines that convincingly master human languages. There is a spoiler, though, about one of those machines losing in a debate competition to a human champion.

Machines are very close to mimicking human capabilities. As artificial intelligence (AI) continues to grow and solve incredibly complex problems, there is an opportunity for the human mind to augment its intelligence exponentially by harnessing technology. The biggest win would be to leverage the strengths of man and the AI-powered machine for achieving a common goal.

The technological landscape is dynamic. Concepts such as social media or peer-to-peer sharing were alien to us a couple of years ago. For instance, a website like TripAdvisor, with the myriad reviews it gathers from its customers worldwide, leaves an indelible impression on a traveler's choice of hotel. Machines have streamlined the process of gathering feedback from customers and freed staff at hotels from this mundane task. As a result, the process of gathering reviews and pricing is now automated, and it was never this efficient.

Let’s consider an automated pricing system for a movie multiplex to maximize its revenue every month. While many variables have an impact on revenue performance, we can determine key factors, such as the popularity of the lead cast, director, storyline, music, etc., which influence the buying behaviors of customers. Machines can take all the relevant information about the variables and co-relate them without any human intervention to arrive at the right price for each seat for each time slot.

The variables will not be constant as the context keeps changing. Machines will need humans to tell them about any new data, which cannot be predicted by them. For a movie multiplex, the emergence of new platforms such as Netflix, Jio DTH, or sporting events like IPL (Indian Premier League) can bring in significant changes in buying behavior. The platforms will generate new data that needs to be factored in by the machines. The human mind can observe and analyze such new patterns and improve the machine's ability to predict future outcomes more accurately.

While humans set the context, machines are far better designed to execute complex analytical processes. They can compute more efficiently and work without fatigue and emotions, given the right variables and their interdependencies. Going back to our analogy, the relative value of the variables will keep changing, which the machines are capable of processing. Also, you can set them in self-learning mode wherein they learn and correct themselves with each additional data point.

We, as humans, should take the responsibility to reduce complexity, set the right context, and strategy so that machines can do the execution. If you consider the Pareto principle, also known as the 80/20 rule, machines will do 80 percent of execution while the human brain will do the remaining 20 percent— that of context-setting. However, the 20 percent is crucial and should be managed by people with both an in-depth understanding of the business as well as analytical and data management skills.

While artificial intelligence is imperative for scaling and execution, it cannot function beyond the programs encoded in it. Human intelligence carries with it the ability to identify new data and their impact on trends.  The need of the hour is to harness the complementing strengths of both the forms of intelligence for best results.

Disclaimer: The views expressed in the article above are those of the authors' and do not necessarily represent or reflect the views of this publishing house. Unless otherwise noted, the author is writing in his/her personal capacity. They are not intended and should not be thought to represent official ideas, attitudes, or policies of any agency or institution.


Tags assigned to this article:
artificial intelligence

Abhijit Joshi

The author is Director, Service Delivery, IDeaS Revenue Solutions (a SAS company).

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