Technology is the powerful magic weapon that gives wings to our pigeons, the pigeons that are now many mass media platforms such as TV, newspapers, or news media, in today’s society, which is dominated and influenced by digitalization.
Artificial Intelligence, a technology characterized by the replication of human intelligence for use in machines and training them to think in terms of humans and copy their activities, is giving these platforms a whole new shape and personality.
Artificial Intelligence, or AI, is becoming more widely used at an unprecedented rate. According to ReportLinker, the AI market is expected to reach $312.4 billion dollars by 2027.
It’s vital for businesses to stay on top of the current developments in order to figure out how they can use technology to not only boost productivity but also stay ahead of the competition.
Artificial intelligence (AI) has been a game-changer, rapidly infiltrating practically every aspect of our lives and providing organizations with increased efficiency. The Internet of Things (IoT) and the growing number of linked devices are the primary drivers of market growth.
The way businesses operate has changed. Business executives may gain a more detailed understanding of their customers through better data collecting and predictive models.
Personalization is now anticipated, and the switch to facial recognition technology is improving security standards. Nearly every industry is using AI tools, including banking, healthcare, and e-commerce, but the media and entertainment industry is a notable early adopter.
Let’s dive into the growth, trend and application of AI in media.
The growing trend of AI in media
In the music industry, AI has already made an appearance through the development of musical compositions. Now, AI is on its way to revolutionizing the way people watch television.
The US media sector is expected to reach $759 billion dollars by 2021, according to PwC’s Entertainment & Media Outlook. COVID-19 has accelerated adoption by encouraging more individuals to stay at home and turn on their streaming services. AI is being applied in a variety of ways in the media and entertainment industries.
The adoption of AI in media and entertainment
The ‘hype’ of AI has unexpectedly caught on with media professionals, and it’s now progressively showing up in the sector to solve problems. Warner Bros., a multinational media and entertainment company, is just one example of a media conglomerate that is utilizing technology to manage its films and expenditures.
Artificial intelligence is used to automate monotonous operations, streamline captioning, filter and distribute news, and much more, freeing up time for producers to focus on their work.
AI in the media is filtering fake news
The internet is awash in “false news,” making it more difficult for consumers to distinguish fact from fiction. The future, on the other hand, looks promising. To identify ‘fake news,’ deep learning AI techniques can now be used to source and fact verify a narrative.
Google’s 2017 Search Algorithm change, for example, was aimed to combat the spread of fake news and hate speech. In addition, the University of Michigan created an AI technique that correctly detects fake news items 76% of the time.
Websites are fed into a sophisticated algorithm that scans the sources and predicts the most accurate and reliable versions of news. The more websites that are ‘fed’ into the algorithm, the more accurate it becomes as it continuously ‘learns’ over time. While this technology isn’t 100% accurate (yet), it’s certainly a step in the right direction.
Applications of AI in media
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 get closer to a world dominated by digitalization, AI’s power grows and grows, and not even the media sector has been able to escape its grasp. The industry has also been undergoing significant change, with digital media opening the way for it to become the primary center of attention across all of its sub-sectors, including television, print, and radio.
Below are a few key domains that AI has influenced and modified, for better or worse, under the umbrella of Media.
1. AI in Controlling Bias
Defeating the increasing prejudice is one unpleasant stigma which the media has been experiencing in today’s modern environment. The information being customized to the audience may often be stacked with degrees of bias leading to deceptive content instead of factual, balanced news.
While Artificial Intelligence has the risk of becoming an apprentice in the gratification of these highly prejudiced tastes, it also has the potential to be a part of the solution. AI can help humans perceive data more objectively in a variety of ways since its machine learning algorithms are trained to only examine variables that increase predicted accuracy based on the data used for training. Unlike human decisions, AI decisions can be investigated and monitored.
As quoted by Andrew McAfee of MIT, “If you want the bias out, get the algorithms in.”
Let’s look at the case of Knowhere, a news startup that is well-known for its objectivity. For the creation of its news stories, the firm uses a combination of machine learning tools and human journalists.
The site’s artificial intelligence selects an article based on current events. Once a topic is chosen, it searches through thousands of news sources for material, regardless of the sources’ points of view, while simultaneously assessing the source’s dependability. The AI then develops its own non-biased version of the story based on its findings.
See Also: 10 Practical Uses of AI in Everyday Life
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’s entire foundation is built on studying and learning from its users’ behavior, but with such a large user base, it employs a variety of strategies to do so.
- Deep Learning – This technique does not require any specific data from an image and is capable of understanding the context of an image as well as analyzing its contents utilizing meta and text. For example, if there are many tiger photographs and videos being shared on Facebook, this technique can provide insights into the frequency with which products appear in these images and videos, allowing advertisers to target people who might be interested in watching tiger films.
- 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.
- 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.
- 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.
- 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, sometimes known as “robot journalism,” uses AI-powered natural language generation algorithms to automatically turn data into news stories, photos, videos, and data visualizations, which are then distributed through automated media platforms.
Its potency has sparked a slew of moral issues, with experts claiming that its use could result in job losses and the spread of fraudulent 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 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.