Application of Artificial Intelligence in the Media Industry

Application of Artificial Intelligence in the Media Industry
Team Name:
Member Names:
Course/Section Number:
Turnitin score: 6%
Institution:
Executive summary
Artificial Intelligence (AI) has had immense impacts in almost every industry. For that reason, AI is regarded as being omnipresent because it can be implemented to boost the potentials and capabilities of every sphere of the world. This paper will examine the application of Artificial Intelligence in the media industry. Specifically, the paper will evaluate how AI has been put in place in areas such as data analysis, content personalization search, and classification, innovation stimulation, automation of tasks, discovering clues to news and marketing and advertisements. Additionally, the paper will examine some of the negative and positive implications of AI on organization management.
Introduction
Artificial intelligence (AI) is an area in computer science that specializes in the creation of intelligent machines that think, react and work like the humans and mimic the way a person reacts. The ideal feature of (AI) is its potential to rationalize and implement actions that have the best chance of attaining a specified goal. The media and entertainment industry is a diverse sector that is comprised of multiple segments which include television, film, and media streamed online. Over the last few years, the landscape of the media industry has greatly changed. From the creative process behind the scenes to content delivery and audience engagements, AI is having a profound effect on the industry.
It is also important to note that previously, AI was mainly focused on advertising and improving the experiences of the media consumers. As a result of technological advancements, AI has managed to control and enhance these applications and many others. The main question to answer in this paper is how IA has impacted the media industry? This paper will examine and explain the different areas in the media industry where AI has been successfully applied.
Data Analysis
Data analysis is a major constituent of data mining which is essential in gaining insights that drive business decisions. Ordinarily, enterprises, organizations, and companies will analyze data from several sources using big data management and customer experience management solutions which turns data into usable and useful insights. In the media industry, data may exist in the form of text, audio, and video (Kambhampaty, 2018). Data analytics studies focus on two key factors which are the content and the audience. By statistically comparing the design parameters of the content platforms, analytics can manage to predict the kind of content that is likely to engage well with the consumers. Likewise, by exploring and evaluating data about the time spent and page exit rates using variables such as story types, pictures, and video editors and designers may understand how to get visitors to stay longer on a site by providing them with contents that match their interests.
The main objectives why data analysis is used in businesses and enterprises is to understand and comprehend the requirements and the needs of the consumers and therefore, to provide them with the content that matches their wants. Effective analysis of consumer-related data results in efficient response to consumer requirements and may also help in improving the relevance of the contents offered by analytics and editors. A case example of data analysis software is the New York Times R&D Lab produced by The New York Times Research & Development group. The software is aimed at evaluating the trends and technologies in the future media. This editor tool is aimed at scanning texts and suggesting article tags and keywords in real time (Ellis, 2015). This is a strategic move that will enable readers to dig deeper into related topics and stories. This is an effective move for giving the audiences another way to discover stories.
Content Personalization
Content personalization is a strategy applied in digital marketing as well as web and user experience design. This method seeks to tailor a digital product to the specific needs of a certain group of users. Ordinarily, delivering the right content or the right person may be tricky and challenging sometimes. However, with AI it is possible to use visitors' data to deliver relevant content based on audience interests and motivations. In this age of big data personalization is a major customer expectation (Hall, 2018). AI aids in enhancing the user experience by boosting the user experience through surfacing relevant content to consumers. Additionally, by using recommender systems, contents developers may be able to deliver materials that match the interests of their audiences. AI has also made it possible to develop personalization engines which have the potential to adjust, modify and adapt the customer's experiences, to not only make it more relevant but also more likely to drive conversion actions.
Furthermore, AI-driven content personalization make use of both first and third party data to make insightful and smart decisions with each customer interaction across an organization's channels. Personalization systems can deliver content inform of product recommendation and personalized landing pages that are likely to appeal to an individual customer based on his or her past behaviors and browsing history. The main objective of content personalization is to create and develop an experience for consumers that cannot be replicated anywhere else and also enhance user satisfaction by delivering relevant content that keeps the consumers longer on the site. The rate of consumer satisfaction determines if the consumers remain loyal to the company or they move their business elsewhere.
An example of a personalization system is the recommended program that is used by Netflix. Netflix personalized recommendation system is aimed at getting the right titles of movies for each member at the right. The AI systems used by Netflix has made it possible to gather data for more than three hundred million customers and provide them with recommendations of movies that they should watch based on their watching history and movie preference. The company provides a catalog spanning thousands of movie titles that match the interests of the viewer (Chandrashekar, Amat, Basilico & Jebara, 2017). The algorithms used in Netflix recommender systems may suggest a movie by providing titles that are related to the customer's searches, an actor that the viewer may recognize, an exciting moment in the movie that a viewer may like and a dramatic incident in the movie that may be interesting to the viewer among others.
Search and Classification
The internet provided countless media works that may include video, audio, and text and can be easily transformed into digitalized copies which may be stored and spread so easily that it becomes difficult for individuals to find and locate exactly what they want online. Al has helped in optimizing the accuracy of search results. It is keynoting that IA systems also help content producers to manage their visual contents better and accelerate the process of media production. Previously, search robots were only programmed to only look for keywords in a static catalog of data. However, AI has made it possible to develop search engines that search terms and customize them based on users' behaviors. AI-based search systems also allow the search engines to perceive whether the searcher's needs have been met and also bump the most relevant Uniform Resource Locator (URL) to the top search results.
The objective of the search and classification systems is to make sure that customers take minimum time to locate their needed information by enhancing the quality of the search results. Additionally, these systems enhance the rate of performance by providing high precision and making the activities of search and exploration faster. The activities of search and classification tools also make it possible for organizations to analyze their customers' activities and also help in the correlation between internal and external information to increase the real value of knowledge. One example of the search and classification systems is the film digitalization program by Clarifai, an artificial intelligence company that focuses on computer vision and applications of machine learning. This film digitalization system helps in solving problems associated with understanding exactly what content is included in the film reel.
Stimulate Innovation
In the past books and magazines were the main medium for texts and images. Then, the introduction of film and television facilitated the introduction of moving pictures. Today, AI has promoted a new age of immersive experience for visual content through technologies such as Virtual Reality (VR) and Augmented Reality (AR) (Sarazen, 2018). The availability of machine learning algorithms and computer vision technologies, content developers can develop complex and holographic scenes with a pair of goggles. VR has hugely impacted the gaming industry, and multiple companies such as HTC and Samsung have invested in this particular field. IA provides the necessary technical req...