How does AI help media?
Defeating the rising bias is one excruciating stigma which the media has been facing in today’s modern world. The information being catered to the audience may often be layered with degrees of bias leading to misleading content instead of factual, balanced news.
While Artificial Intelligence certainly holds the threat of being an apprentice in the indulgence of these very biased tastes at the same time it could also be a part of its resolution. In various cases, AI assists in reducing the subjective interpretation of the data of the human as it’s machine learning algorithms are trained to only consider the variables which improve their predictive accuracy, based on the data used for training. AI decisions unlike decisions made by humans can be explored, overseen and interrogated.
As quoted by Andrew McAfee of MIT, “If you want the bias out, get the algorithms in.”
Let’s take the example of Knowhere, a startup news company that is widely known for its impartiality. The company uses a combination of machine learning technologies as well as human journalists for creating it’s news stories.
The site uses it’s AI to select a story, taking into account the latest trends. Once a topic is selected, it explores thousands of news sources for gathering content, irrespective of the opinions the sources propagate, while also looking into the reliability of the source. Then on the basis of its research, the AI writes its own non - biased version of the story.
Yet at the same time, the company also has a pair of human editors reviewing each of its stories and then feeding the edits back to the AI, which could end up being a major defect for the tech seeing how AI’s tend to adopt the biases of their creators.
AI in Social Media
As the use of Social Media expands and booms at an increasing rate over the years, so does the hold Artificial Intelligence enjoys over it.
Facebook: The entire backbone of Facebook is based on understanding and gaining knowledge of the behaviour of its users, yet with its massive user base it makes use of several techniques to do the same.
Deep Learning - This technique doesn’t need any definite data from an image and has the ability to comprehend the context of an image as well as to analyze its contents using meta and text. For instance, if there is an abundance of tiger images and videos being shared across Facebook this technique can produce insights to understand the frequency of appearance of products with these images and videos in order to place ads for the people who might like to watch tiger videos.
DeepText - This technique uses neural networking to analyse the words in user posts in order to understand their context and comprehend their meaning, with its own algorithm.
Face Recognition - This technology is used to recognize human faces in two or more different images. The technology’s accuracy has also made it the target of much controversy.
Looking back at the days when “conversing” was characterized by painting on caves and sending news and information via pigeons to the present when Facebook-ing, Snapchatting, or tweeting our thoughts and ideas to the world has become the norm, we’ve traveled a long complicated way.
In today’s world which is ruled and impacted by digitalization, technology is the powerful magic tool giving wings to our pigeons, the pigeons which are now multiple mass media platforms that include TV, newspapers or news media.