Artificial intelligence in the media is penetrating deeper and deeper into the structures of editorial teams, production studios, and streaming platforms. AI is changing how content is created, distributed, and personalized, adapting materials and their presentation to individual audience preferences. This technology facilitates editorial work and revolutionizes interactions with viewers and listeners, providing them with unique experiences. From content generation to data analysis, artificial intelligence in the media is gaining importance as a tool that supports both small and large media companies in delivering rich, engaging, and credible content. Let’s take a closer look at how industry giants are leveraging AI.
In 2023, Spotify introduced many solutions based on artificial intelligence. One of them is DJ AI, which provides personalized music recommendations for users. DJ AI utilizes:
DJ AI can provide users with a personalized list of songs along with comments about artists and tracks they might like. DJ AI constantly learns and updates its recommendations based on user feedback.
Another AI-based solution is hyper-personalized recommendations, where audio content is recommended to users based on their music preferences. Spotify uses AI models to recommend music and podcasts to improve user satisfaction.
Source: Spotify (https://engineering.atspotify.com/2023/06/experimenting-with-machine-learning-to-target-in-app-messaging/)
Spotify is also testing machine learning models to decide which users to show messages to in the mobile app. According to the results of an A/B experiment described on the Spotify Engineering Blog, such personalized targeting significantly improved the retention rate, or how long users stayed with the streaming service.
However, Spotify emphasizes that it must be very careful and selective in choosing the recipients of such messages so as not to interfere with the listening experience of their favorite music, while its machine learning algorithms are constantly being improved to best understand listeners’ intentions and preferences.
Netflix is inextricably intertwined with advanced artificial intelligence systems used to personalize offerings and improve streaming quality. Special algorithms recommend movies and shows that best match users’ tastes, based on their past activity.
Netflix uses machine learning algorithms to optimize video quality. These algorithms analyze a user’s Internet connection, device, and video settings, and then adjust video quality to provide the best viewing experience. Netflix also uses machine learning models to predict future traffic demands. This allows the company to optimize server performance, even during peak times. AI also enables the rendering of personalized trailers and graphics to encourage viewing of specific productions.
Source: Netflix (https://about.netflix.com/en/news/netflix-2023-upfront-building-a-forever-business)
Artificial intelligence in the media is also utilized by Netflix for:
AI is also used in the production of video and audio content, assisting with editing and post-production. Netflix uses AI to select clips for the so-called Mega Asset, which is then used to create personalized Dynamic Sizzles. This helps to efficiently generate multiple personalized video combinations, saving up to 70% in time and cost (according to Netflix TechBlog).
Interestingly, James Earl Jones has granted Netflix the rights to his voice recordings, allowing AI to replicate his voice as Darth Vader.
Artificial intelligence in the media is also utilized by Netflix for:
An influential daily newspaper, The New York Times, is testing the use of machine learning algorithms to personalize content. For example, the NYT Cooking platform offers users personalized recipe recommendations based on their past choices and activity on the site.
However, according to the survey, only 22% of American adults rate the quality and credibility of articles automatically generated by artificial intelligence as good. The New York Times must therefore implement such solutions very carefully and ethically, so as not to lose the trust of its readers at the expense of dubious business benefits.
Recently, The New York Times even filed a lawsuit against Open AI, the creators of ChatGPT, and its corporate patron, Microsoft, accusing them of illegally using the newspaper’s content to train AI models without proper licensing agreements.
According to the lawsuit, the two companies allegedly obtained unfair financial benefits in this way. The New York Times estimates that up to 66 million articles from its websites were used to train ChatGPT without the publisher’s permission or compensation. A legal dispute is thus underway over the rules for using other people’s content in developing commercial applications of artificial intelligence.
Source: Reuters (https://www.reuters.com/legal/transactional/ny-times-sues-openai-microsoft-infringing-copyrighted-work-2023-12-27/)
Artificial intelligence is not just the domain of media giants. In smaller companies and editorial offices, too, AI can take over a range of routine tasks from media employees that are time-consuming but simple and repetitive:
For example, Bertie, a CMS created by Forbes magazine, can independently process data from companies’ financial reports and write articles with key facts and figures based on the data.
However, according to a survey published by Forbes, up to 76% of American adults are concerned about the potential misinformation that could be caused by the use of artificial intelligence in the media. People worry that intelligent machines will lead to a collapse of journalistic standards. Automatically generated content could contain errors, spread unverified facts, or be manipulated. That’s why many people are skeptical of over-reliance on AI by editors.
Another application of artificial intelligence in media is the personalization of content for individual user tastes and interests. This involves analyzing the activity of audiences on media sites and then selecting personalized recommendations for each of them.
Spotify, for example, tracks listening history and song preferences and offers more tailored playlists and new music discovery features to specific users. Similarly, Netflix analyzes its subscribers’ movie choices and delivers personalized recommendations, trailers, and in-app graphics.
Personalized recommendations are the most effective way to discover new movies, series, or programs. By using AI in this way, media companies can significantly increase audience engagement and loyalty.
Another application of artificial intelligence in the media is intelligent ad targeting. Algorithms analyze user behavior to tailor advertising messages to specific audiences. This increases the effectiveness of campaigns and therefore their profitability. For example, Netflix’s recommendation system is responsible for unexpected hits like “La Casa de Papel” – the production targeted viewers interested in thrillers.Artificial intelligence is also being applied to the creation of multimedia content. New AI models, known as generative AI models, can independently generate images, text, and even audio tracks based on natural language descriptions. Such systems can automatically prototype graphics, suggest movie scripts, write plot summaries, or generate character dialogs.
Specialized AI models can also imitate specific voices of famous actors, creating a fully synthesized soundtrack. This opens up new possibilities for dubbing video games or animated films without the need for expensive actors. Artificial intelligence is improving the production of video and audio content and creating entirely new entertainment formats.
Artificial intelligence can analyze content to identify fake news and disinformation. Algorithms detect typical characteristics of fake news, such as lack of sources, emotional language, or manipulation. AI tools verify facts and point out questionable parts of texts. This type of monitoring can help media organizations improve the credibility of their messages and gain the trust of their audiences.
In a nutshell, artificial intelligence is profoundly changing the media and entertainment industry. Machine learning algorithms are automating the work of journalists, personalizing content, streamlining media production, and helping to precisely target ads. By analyzing user activity, AI models also predict future trends in media consumption and shape them in a controlled way.
Companies like Netflix, Spotify, and The New York Times are experimenting with various applications of artificial intelligence. However, controversies still arise over the transparency of algorithmic operations and the respect for the rights of content creators used for training AI models. Therefore, the further development of this technology in the media industry will require a wise, ethical, and responsible approach.
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Author: Robert Whitney
JavaScript expert and instructor who coaches IT departments. His main goal is to up-level team productivity by teaching others how to effectively cooperate while coding.
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