By Girish Linganna

Feb 1: Artificial intelligence (AI) has taken global industries by storm, and the media world is no different! Over the years, AI has transformed the way news is created, distributed and consumed. This article explores the recent advancements in AI technology and its impact on media usage. 

The Content Creation Game

For years, the media was dependent on expert, age-wisened journalists—with long years of training and experience—for writing, and editing, news articles. But now, automated content creation tools powered by AI can produce articles, blog posts—and even news stories. Uninitiated journalists have even been trying their hand at using AI support to produce news analyses and opinion pieces. 

These systems use natural language processing (NLP) algorithms to analyse vast amounts of data and generate coherent and relevant content. AI-generated content has found applications in such areas as sports reporting, financial news and weather updates, enabling media outlets to provide timely and accurate information to their audiences.

Although AI has become increasingly proficient in generating media content, the media world still depends on journalists to come up with unique stories. The field of journalism often involves writing mundane and repetitive news reports on a regular basis. And this is precisely where AI has immense potential to contribute because such news items can be written using AI-powered programmes, so that journalists can focus more on fleshing out in-depth articles that need more expertise and acumen. 

Personalized Recommendations

AI algorithms have revolutionized the way media is recommended to consumers. AI has the ability to find patterns in reader and viewer behaviour and using this can help media houses serve them stories they are more likely to read. AI also has the capacity to create content for boilerplates for the likes of Press releases, newsletters and company news so that flesh-and-bones writers can work on their basic drafts. 

Streaming platforms, social media sites and news aggregators leverage AI to analyse user preferences and behaviour to offer personalized recommendations. By employing machine learning (ML) techniques, these platforms can even help suggest relevant movies, TV shows, articles and news stories to individual users according to their preferred areas of interest, enhancing their overall media consumption experience. 

Real-Time Analytics

AI-powered analytics tools enable media organizations to gain real-time insights into audience behaviour, content performance and market trends. By processing large volumes of data, AI algorithms can extract valuable insights, allowing media outlets to make data-driven decisions. This information can be used to optimize content creation, distribution strategies and advertising campaigns—ultimately improving audience engagement and revenue generation. 

Enhanced Advertising

AI-driven advertising has witnessed significant advancements. Remember all those times that you searched for a holiday location on Google, and then were flooded by a battery of ads on search engines and social media platforms like Facebook suggesting the cheapest flights, hotels and destinations you might like to try out? 

Advertisers leverage AI algorithms to identify target audiences more accurately and tailor advertisements according to individual consumer preferences and choices. By analysing user data and behaviour patterns, AI-powered systems can deliver such personalized ads that not only resonate with individual preferences, but also suit their budgets. This targeted approach enhances the effectiveness of advertising campaigns, leading to improved conversion rates and return on investment (RoI). 

Automated Content Moderation

Moderating user-generated content is a time-consuming and challenging task. However, AI-powered content moderation systems have made the process more efficient and effective. These systems employ computer vision and NLP algorithms to automatically flag—and filter out—inappropriate or harmful content, such as hate speech, spam, or graphic images. AI-driven content moderation helps media platforms maintain a safe and inclusive environment for their users. 

Deepfake Detection

With the rise of deepfake technology, where AI and ML are used to create realistic, but fake, videos or images, the need for effective detection systems has become crucial. ML is a part of AI, which trains computers to recognize patterns and make decisions without specific programming for each task through algorithms that get better with time as they analyse and interpret data. 

So, AI algorithms are now being developed and improved to identify and flag deepfake content, helping media platforms combat the spread of misinformation. These detection systems analyse visual cues, inconsistencies and artifacts to differentiate between real and manipulated media, ensuring the integrity of information presented to the audience. 

Automated Translation

Language barriers have always posed a challenge in media consumption. However, AI-based translation tools have made significant strides in breaking down these barriers. Advanced machine translation algorithms can translate text, audio and video content in real time, allowing media organizations to reach a global audience. These tools facilitate cross-cultural communication and enable media content to be accessible to a wider range of viewers. 

A recent article in NiemanReports says that, in May 2022, tens of thousands of war-displaced Ukrainians who had moved to Finland had trouble understanding local public broadcasts in the Finnish language. The broadcaster, Yle, served up news in Finnish, Swedish, Russian and English, but had no journalist who could speak the Ukrainian language. It solved the problem by taking the help of AI to translate news items for its new audience in one of the more significant instances of AI storming the Newsroom. 

Ethical Considerations

As AI continues to play a vital role in media usage, ethical considerations have become increasingly important. Concerns regarding data privacy, algorithmic bias and the impact of AI on employee displacement need to be addressed. Media organizations must ensure transparency, accountability and fairness when implementing AI systems to mitigate potential risks and build trust with their audience. 

Conclusion

AI integration in media usage has transformed the industry, improving content creation, personalized recommendations, advertising, content moderation, deepfake detection, analytics, translation, and more. With further advancements in AI technology, the media landscape is poised to undergo even more significant changes in future. 

However, it is not only possible, but also very likely as of now, to have hilarious errors—even plagiarism—in content created by AI-powered tools. Thus, human intervention is needed at every step of the way, so that media houses do not run into legal tangles—especially copyright issues—over the content they distribute. 

So, it is crucial to navigate these developments responsibly, considering the ethical implications and ensuring that AI turns into an ‘enabler' of enhanced media experience and not a substitute for Newsroom warriors putting their nose to the grindstone.

(The author of this article is a Defence, Aerospace & Political Analyst based in Bengaluru. He is also Director of ADD Engineering Components, India, Pvt. Ltd, a subsidiary of ADD Engineering GmbH, Germany. You can reach out to him at: girishlinganna@gmail.com)