THE RISE OF DEEP FAKES: WHAT YOU NEED TO KNOW?

Deep fake technology refers to the use of artificial intelligence (AI) and machine learning techniques to manipulate or generate video or audio content in a way that it appears to be real or authentic. With deep fake technology it is possible to create videos that show people saying or doing things that they never actually said or did.

This technology has the potential to be used for malicious purpose, such as creating fake news or spreading misinformation . It can also be used to create harmful or offensive content , such as non consensual pornography.

There are also positive uses also, such as in entertainment industry for creating special effects or in the education sector for creating instructional videos . However  , it is important to ensure that the use of deepfake technology is transparent and ethically responsible.

There are several ways in which deep fake technology are created . One of them is using machine learning technique called generative adversarial networks (GANs) . GANs consist of two networks ;

1. A generator
2. A discriminator

The generator creates fake content , while the discriminator tries to distinguish between real and fake content. As the two net works are trained together , the generator becomes more skilled at content that is difficult for the discriminator to distinguish from real content.

Another approach is to use a technique called autoencoding , which involves training a neural network to compress and reconstruct an input image or video. The network learns to identify and encode the important features of the input , and can be used to generate new, realistic images or videos.

INDIA AND DEEP FAKE TECHNOLOGY

There has been some research and development in deep fake technology in India, but it is not clear to what extent deep fake technology is being used in the country.

In 2019 , researchers at IIT in Kanpur published a paper on deep fake detection method using combination of visual and  audio features. The researchers trained a machine learning model on a data set of real and deep fake videos and found that the model was able to accurately distinguish between the two with an accuracy of over 95%.

Over all , deep fake technology is a powerful and rapidly evolving field that has the potential to be used for both good and bad purposes. It is important for individuals and society as a whole to be aware of the potential risk associated with deep fake technology , and develop safeguards and regulations to ensure its responsible use.