Will Artificial Intelligence surpass Human Intelligence in future? If yes, in how much time?

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To answer these questions, let us first understand:

What is Human Intelligence?

Human intelligence refers to the abilities and skills possessed by human beings. 

It encompasses a wide range of mental processes, including 

  • perception, 
  • learning, 
  • reasoning, 
  • problem-solving, 
  • creativity,
  • emotional understanding, etc.

Human intelligence is highly flexible and adaptive

It enables humans to understand complex concepts and make decisions based on intuition & experience.

Human intelligence is not limited to specific domains and can be applied to various multiple tasks and situations.

Ok, so far so good.

Now, let’s try to understand Machine intelligence

What is Machine Intelligence?

Machine intelligence, also known as artificial intelligence (AI), refers to the ability of machines or computer systems to mimic (or replicate) human-like intelligence. 

Basically, some smart people thought can we build such machines that can acquire human-level intelligence?

So, they wrote algorithms, used previous data, and computational power to achieve this.

Now, we have machines that can do certain tasks that humans are capable of.

But machines might do it faster and more accurately.

Can Machines match human intelligence?

So, the question is – can we improve machines so much that they acquire intelligence like humans.

Currently, Machine intelligence can be categorized into 

  1. narrow AI and 
  2. general AI:

1. Narrow AI: 

Narrow AI refers to AI systems designed for specific tasks or domains. 

These systems are focused on performing well-defined tasks, such as face recognition, music generation, translation, etc. 

They excel in their specific area but lack the general cognitive abilities of humans.

This is the stage the machine intelligence has reached.

2. General AI: 

General AI, often referred to as artificial general intelligence (AGI), aims to replicate the broad spectrum of human intelligence. 

AGI systems would possess the ability to understand, learn, and apply knowledge across various domains, similar to humans. 

Basically, if Machines can achieve AGI, then they can match human intelligence. 

So, this is more of a philosophical concept as of 2023 than a reality and remains a subject of ongoing research.

So, in future, is it a possibility that Machine intelligence can surpass human intelligence?

The question of whether machine intelligence can surpass human intelligence is a topic of ongoing debate and speculation. 

While it is difficult to predict the future with certainty, there are differing viewpoints on this matter:

Viewpoint 1 – Machines can

Some proponents of artificial intelligence believe in the concept of technological singularity, which suggests that at some point, machine intelligence could surpass human intelligence. 

They argue that as AI technology continues to advance and improve, it may reach a level of sophistication and capability that surpasses human abilities. 

This hypothetical scenario suggests that AI systems could rapidly improve themselves and outperform humans in various domains.

Viewpoint 2 – Machines can’t

On the other hand, many experts argue that achieving human-level general intelligence in machines remains a complex and challenging task. 

Human intelligence is multifaceted, encompassing not only cognitive abilities but also 

  • creativity, 
  • empathy, 
  • intuition, 
  • Common sense,
  • Moral reasoning
  • subjective experiences, etc.

Replicating all these aspects in machines is a formidable scientific and technical challenge. 

Viewpoint 3 – Collaboration

A third perspective is that machine intelligence has the potential to enhance human intelligence rather than surpass it. 

As AI technology advances, it can assist humans in various domains, complementing their cognitive abilities. 

This perspective sees a future where humans and machines work together synergistically, leveraging the unique strengths of each to achieve higher levels of performance and problem-solving.

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Nikhilesh Tayal
Nikhilesh Tayal
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