Role of Artificial Intelligence (AI) in Media Industry

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. 

 

Giving a whole new shape and identity to these platforms is Artificial Intelligence, a technology that is characterized by the imitation of human intelligence for its usage in machines and for programming them to think in terms of humans and to mimic their actions. 

 

 

Applications of AI in media

 

To say the applications of AI are many, would be an understatement. The use of Artificial Intelligence is constant and ever-evolving in every sector of life. Here I will be offering a brief overview of the application of AI in media. 

 

“The AI is there. You’re just not seeing it in the ways you would have expected.”  - Jason Harrison, CEO of North America for WPP’s Essence

 

As we rapidly shift towards a world characterized by digitalization, the power of AI expands and stretches till not even the media industry has been able to escape its clutches. The industry has also been undergoing a high degree of transformation with digital media paving its way towards becoming the main focus of interest across all its sub-sectors that include TV, Print, and Radio. 

 

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Below are a few central areas, residing under the umbrella of Media, that AI has impacted and transformed, for the better or worse. 

 

1. AI in Controlling Bias

 

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 its 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 its news stories. 

 

The site uses its 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.

 

 

2. 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 behavior 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 analyze 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.  
   

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AI in Social Media

 

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Twitter: 

• Tweet Recommendations - Twitter makes use of AI for recommending tweets on the user’s timeline and ensuring that the relevant tweets are catered to them first. It makes use of Natural Language Processing (NLP) to analyze thousands of tweets per second and provide insights into the inclinations of the users. 

 

• Removing Hateful Accounts - Twitter makes use of AI algorithms to flag and removes the accounts that are promoting extremist groups or hateful tweets. 

 

• Image Cropping Tools - Twitter enhances user experience through the use of neural networking and displays only the most intriguing part of an image for its thumbnail. 

 

Instagram:

• Search Suggestions - With millions of photos being shared on the platform every day, Instagram leverages AI to create its search function with its massive database to help users find images related to their own favourite activities and experiences. 

 

LinkedIn:

• Job/ Connection Recommendations -  LinkedIn makes use of AI for offering job recommendations, suggesting people for the users to connect with, and delivering specific posts on the user’s feed. 

 

 

3. AI in Automated Journalism 

 

Automated journalism, which also goes by the name of “robot journalism”, makes use of natural language generation algorithms that are powered by AI in order to automatically convert data into various news stories, images, videos, and data visualizations and then distribute it via automated journalism platforms.

 

Its power has brought it under the scrutiny of many moral debates as various experts believe its use could lead to loss of jobs and the circulation of fake content.

 

• AI’s role in writing and reporting articles - AI is being leveraged by publications to deal with the laborious and tedious tasks and remove them from the journalist’s workload. For instance, Patch a publishing network has integrated AI within its content management system for creating and distributing its repetitive articles such as weather and financial reports, on the basis of its existing framework.

 

• AI’s Role in recommending and creating multimedia - The images in publications are recommended through machine algorithms, based on the relevance of their context and past engagement criteria. For instance Getty Images, the visual communication giant launched “Panels”, a new AI tool for media publishing that recommends the best visual content to accompany a news article. Panels infer from Getty Images’s database and provide the media editors with a customizable research assistant for summarising articles and offering a selection of images for varied elements of the story. 

 

• AI’s role in generating subtitles - It is integral for media companies to ensure that their content remains appropriate for consumption from audiences of varying regions. For doing so, it is required that they offer precise multilingual subtitles in case of their video content. 

 

Drafting subtitles in a conventional manner can prove to be highly time-consuming and draining for the human translators, not to mention the struggle involved in identifying the proper human resources for translating the content in specific languages. 

 

With human translation also being largely susceptible to errors, media platforms adopt AI-based technologies such as NLP and natural language generation. For instance, YouTube’s AI permits its publishers to automatically generate closed video captions, added on the application, ensuring that their content is easily reachable.

 

• Content personalization - Popular video streaming platforms such as Spotify and Netflix are accomplished as they supply content to people from all demographics, who have varying preferences and tastes.

 

Such platforms adopt AI and machine learning algorithms for studying individual user behavior and demographics to suggest what the users can have interest in viewing or listening to after their present video and ensuring that they are constantly kept engaged. Therefore, these AI-based platforms offer users content catering to their particular preferences, facilitating them with a profoundly customized experience.

 

 

• AI’s role in creating and distributing interactive data visualizations - AI has also played a dynamic role in enabling publishers to create interactive data visualizations in a short time period. For instance, Opinary, a Berlin-based startup is an AI-powered product that goes through articles to comprehend their subject and then creates interactive data visualizations, placing them directly into the articles that allow users to share their opinion on the topic of the article, while also including the responses from other readers in real-time.

 

 

Conclusion

 

“AI has the potential to improve billions of lives, and the biggest risk may be failing to do so. By ensuring it is developed responsibly in a way that benefits everyone, we can inspire future generations to believe in the power of technology as much as I do,” - Sundar Pichai, CEO, Google & Alphabet

 

I would conclude by saying that while Artificial Intelligence holds a massive degree of power and capacity and the promise of evolution and booming of the media and all its varied sectors, its very power could also prove to be its biggest deadly weapon. Thus AI has to be effectively channeled and accurately used for it to be a positive advancement.