Artificial Intelligence (AI) is transforming the nature of almost everything which is connected to human life e.g. employment, economy, communication, warfare, privacy, security, ethics, healthcare etc. However, we are yet to see its evolution in long-term, whether it’s leading humanity towards making this planet a better place to live or a place which is full of disaster. Every technology has its advantages and disadvantages but advantages always outweigh disadvantages for the technology to survive in the market. Nonetheless, for Artificial Intelligence we are not yet sure whether in the long-term positive effects will always keep outweighing the negative effects and if that is not the case then we are in serious trouble. If we look around us, on one hand, we seem to embrace the change being brought by technology, be it smart home, smart healthcare, Industry 4.0 or autonomous cars. On the other hand, we often find ourselves protesting against the government in the context of unemployment, taxes, privacy etc. As AI development is speeding up, more robots or autonomous systems are being born and replacing the human labor. This is the current situation; however, in long-term, results seem to get more interesting.

Now talking about whether it’s a boon or bane, it totally depends on the way you use your system and build the model (mathematical model built to create AI systems). There are two different kinds of data in an AI system, one is known as the training data and other is the testing data. The training data is the one which is used initially in order to build the system and this data is fed into the knowledge base initially before testing. While on the other hand, the testing data is the data which is used in order to test any new data or an unknown data which might not be present in the knowledge base. So to make your artificial intelligence system accurate and reliable, it is very important to train the system efficiently with a good set of data and knowledge. Based on the training data, your output of the system matters a lot. The impact of the output or the end result depends on a lot of the training data that is fed to the model during the development of the AI system.

artificial intelligence

Let’s consider an example :

You have 1000 images and out of those images you need to identify which are cancerous and which are not and further you need to predict an unknown image which comes as an input in the system. For performing such kind of tasks, you need an expert in the field of radiology, cancer treatment and likewise. Only with such high expertise, the knowledge base in the model will be good and the system will be reliable. If this is the case then here AI is a BOON.

But consider another scenario for the same example. Instead of domain experts, you have general surgeon specialist (the ones who are not specifically into cancer treatment), in this case, the result will be unreliable and would not be highly efficient for the end user. In such a case AI is a BANE.

artificial intelligence

Thus to sum it up, whether AI is a Boon or a Bane, depends on the following factors:

  • The knowledge-based fed initially in the system.
  • The way an AI model (the math model) is trained to perform AI tasks.
  • The knowledge that is fetched from domain experts.
  • The way AI system is trained to learn new things and update its own knowledge base.

Also with the growing field of AI researchers are continuously working and trying to integrate human cognition and brain with the AI. With such an advancement and growing use of AI, there might also be a possibility where AI becomes destructive to the world. But as mentioned earlier, it completely depends on the way you build the system and then uses it further for more productive purposes.

Based on such main factors, AI can be either a boon or a bane.

-Shreesha Balan

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1 Comment

Rifat · October 8, 2020 at 10:19 am

I have learned huge knowledge from here. I am waiting for your updates

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