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Artificial Intelligence (AI) has been changing the way that different sectors of society operate. In the entertainment industry, AI has allowed media companies to produce high quality content faster and personalize the audience's experience to keep them more engaged (Morgan Stanley, “How AI Benefits- and Threatens- The Entertainment Industry.”)  In this Padlet wall, I chose to focus on how AI is applied in the entertainment industry because I consume lots of media on a daily basis, and I wanted to know how much AI influences the content that is presented to me. For example, as an avid Netflix user,  I’ve always noticed how accurate my recommendations are and wondered how the system “knows” what I’ll enjoy next. Throughout my Padlet wall, I’ll explore three major AI applications in entertainment: Amper Music, an AI-powered tool that helps users compose original music, Netflix’s recommendation system, which uses machine learning to personalize viewing, and procedural content generation in games like Minecraft, where AI builds unique, explorable worlds. These examples show how AI is transforming how content is created and experienced. This industry and its applications are significant to me  because entertainment and media are such a big part of my life. I grew up with applications like Netflix and Minecraft, but I never realized how much AI was behind the scenes making those experiences possible. Learning about it now makes me appreciate how technology and creativity work together. Additionally, we were able to explore AI music creation in EST110, and I actually want to learn about the mechanisms involved.

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Amper music is an AI-powered music platform that allows users to instantly create unique, professional, and royalty free music (“Amper Music AI, “Amper Music AI”.) The software enables anyone to create music, regardless of skill level or expertise. The way that Amper Music creates tracks is very interesting. First, users input  and customize their desired musical components such as genre, mood, tempo and instrumentation into the Amper Software. Then the Amper system uses the technologies deep learning and neural networks to generate music structures (Yan, “Comparison of Music Composing Structures”). Deep learning is a type of machine learning that uses many layers of connected computer “neurons”(neural networks)  to think and make decisions in a way that is  similar to the human brain. These layers help the system recognize patterns like sounds, images, or melodies, and learn from them over time (Holdsworth and Scapicchio, “ What is deep learning.”) Finally, the AI is able to analyze musical structures, create harmonized compositions, and generate royalty-free music on demand. The AI software has been very beneficial to Amper music. One way that Amper Music’s AI  is beneficial is its high quality production techniques like mixing and mastering(“Amper Music AI, “Amper Music AI”.). This ensures the final product is ready for professional use, without any extra post production steps, completely bypassing one of the most difficult parts of the music creating process.  But the system also has limitations. Amper music doesn’t allow for vocals to be added to tracks (“Amper Music AI, “Amper Music AI”.)  This is super inconvenient because users have to seek out another platform, or forgo their original idea, limiting the users creativity. Personally, I find Amper Music fascinating because it gives anyone, even those without musical training, the ability to create professional-quality music. I think this kind of accessibility could change the creative landscape by helping more people express themselves through music. At the same time, I think the lack of vocals limits its creative potential, because vocals are such an essential part of the emotional feel we get from songs. Overall, I see Amper Music as a powerful tool that expands creativity, but it still reminds me that AI cannot complete a song as well as a human would.

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Netflix is a subscription based streaming service that allows users to stream a variety of tv shows and movies on any internet connected device (Netflix, “What is Netflix?”). Besides just offering content, Netflix incorporates AI into its application by personalizing the viewing experience for each user through recommendations. Netflix uses machine learning, or algorithms that learn patterns from large data sets to make inferences about new data (IBM, “What is Machine Learning?”) The AI in the Netflix application takes data from what you watch (Your likes, interests, and watching habits) to provide you with recommendations on what to watch in  the near future ( Gokul, “How Netflix Uses Artificial Intelligence.”).  This allows users to discover shows and movies that match their unique tastes more easily, creating a more engaging and personalized viewing experience. One benefit of AI in Netflix is that is helps users to discover a show that aligns with their preferences that they may not have considered before (Gokul, “How Netflix Uses Artificial Intelligence.”) The AI not only makes finding shows easier, but also serves as a plus to Netflix because if users are finding more shows they like, they will engage with the platform more. But AI also has limitations. Netflix’s algorithm only collects data on what users do watch, not what they don’t want to watch (Buckley, “The Problem with Your Netflix Recommendations”).  For example, someone might watch many horror films, so Netflix suggests more horror, even if their real interest lies in genres not yet viewed, like Romance. This shows the system cannot distinguish between content a user is uninterested in, content they haven’t had time to watch, or content they would like if it were available. Personally, I find Netflix’s use of AI really interesting because it makes watching shows feel tailored to me. I love how it can suggest series like Scandal that match my taste, even when I wasn’t actively searching for something new. At the same time, I think it’s a little unsettling knowing that all my watching habits are constantly being tracked to make those suggestions. Overall, I think Netflix’s AI makes entertainment more convenient and personal, but it also reminds me how important it is for technology to respect user privacy in what it recommends.

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Procedural content generation (PCG)  is a method in video games where AI algorithms automatically create game content ( levels, maps, characters, quests, or items) rather than having designers manually build every element (Kenny, “Procedural Generation An Overview”). Basically, PCG uses patterns learned from existing data or rules defined by developers to generate new, unique content each time (Monserrat, “Procedural Content Generation for Video Games, A Friendly Approach”). A really interesting application of this AI technology is actually in one of my all time favorite video games, Minecraft. “Minecraft” uses the PCG to create vast open worlds filled with geographic diversity, where players can explore, build, and survive in environments that are unique to each game (Monserrat, “Procedural Content Generation for Video Games, A Friendly Approach”).” For example when a player starts a new world in Minecraft, the AI generates mountains, rivers, forests, caves, and villages in unpredictable ways. One benefit of PCG in Minecraft is that it allows for less repetitive game play (Kenny, “Procedural Generation An Overview”). No two worlds are exactly alike, for example I may have a desert world with orange mountains in one game, but then a desert world that has no mountains in another.  This keeps gameplay fresh and encourages exploration. But there are drawbacks to PCG. Sometimes the use of PCG in games can lead to illogical or  unplayable experiences (vAIber, “AI & PCG: Revolutionizing Game Development”). For example, In minecraft in Minecraft, the AI might generate a village floating on top of river, which makes it harder for the user to achieve certain goals in the game. Despite these occasional issues, PCG still allows players to enjoy unique and dynamic worlds every time they play, keeping the game engaging and full of surprises. Personally, what interests me is how the AI is able to create a vast amount of worlds so quickly. Every time I start a new Minecraft world, it feels like stepping into a completely different universe that was made just for me. I find it fascinating that a system can generate infinite landscapes in seconds, each with its own mix of biomes and challenges. It shows how AI can transform creativity and exploration in gaming, allowing players like me to experience something new every time we play.

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Future Trends and Ethical Considerations

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Future Trends and Ethical Considerations

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AI is rapidly transforming the entertainment industry, and its influence will only continue to grow. For instance, the film industry is moving towards the trend of using Agentic AI in studios and streaming platforms. Agentic AI refers to systems that can make creative or strategic decisions with minimal human direction such as fine tuning dubs and movie subtitles, and completing audio editing tasks based on cultural context, genre, or regional preferences (Krakowski, “Three AI Trends Reshaping the Future of Media and Entertainment”). This could completely reshape how entertainment content is personalized because  it allows media to adapt to different audiences on a deeper level. Viewers could experience films that sound and feel natural to their own language and culture, making global entertainment more accessible. Additionally, AI is increasingly being used in entertainment as a kind of creative partner for writers, musicians and other creators. AI allows creators to generate any content they want, rapidly and execute their ideas with minimal effort (Krakowski, “Three AI Trends Reshaping the Future of Media and Entertainment”). By handling repetitive tasks or sparking inspiration (e.g. getting rid of writer's block), AI allows creators to focus more on storytelling and artistic vision. But there are also ethical concerns regarding lack of creative originality. Since the AI relies on existing information rather than actual new creative concepts that only the human mind can produce, entertainment may lack emotional depth. Audiences need to feel authentic emotion and connection in storytelling, something AI cannot fully replicate.  Personally, I find this exciting because I love seeing how technology can help artists and bring new ideas to life faster. Still, I worry about what might be lost if AI starts replacing human creativity altogether. I believe the key to the future of AI in entertainment is balance. AI should enhance creativity and not replace it, allowing technology and the human mind to work together to create meaningful, rather than stale content.

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The use of AI in the Entertainment industry affects society in many ways. First, is the displacement of human workers. As AI begins to take on more creative tasks, there’s a risk that human artists and editors could be replaced. Jobs that once relied on human creativity, such as editors, writers, and designers, may become automated, which could reduce opportunities for new artists entering the industry (Expert Panel, “AI in Entertainment, 19 Practical and Ethical Challeneges”). This definitely raises the concern of a rise in the lack of emotional authenticity in storytelling, as the content is coming from the perspective of a software rather than a human. This is a huge disservice to entertainment lovers like me, who value new ideas that actually make us want to watch or listen to the content. Privacy is also a concern. AI systems in streaming platforms, like Netflix, track and collect large amounts of user data to recommend content (O'Flaherty, “All the Ways Netflix Tracks You and What You Watch.”). While this makes entertainment feel personalized, it also raises questions about how much information companies collect and how it’s being used, especially whether or not it is being used for good (e.g. selling private data) (O'Flaherty, “All the Ways Netflix Tracks You and What You Watch.”). Finally, bias in AI generated content is always an issue, even in entertainment. If the entertainment AI algorithms contain data sets that are not diverse, the AI generated content will then learn these patterns and produce biased content (Holdsworth, What is AI Bias”). This could lead to repeat cultural biases or underrepresentation of certain groups in media and film. These issues make me see AI in entertainment as both exciting and concerning. While I enjoy how streaming platforms recommend shows that match my taste, like "Scandal", which I might not have discovered on my own, I am uneasy knowing that my data is constantly tracked and analyzed. I also worry about the loss of creativity and representation. If AI learns from biased data, it could repeat stereotypes or overlook certain voices entirely. Overall, I think AI has the potential to transform entertainment for the better, but only if it is used thoughtfully to support both creators and audiences.

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1. Amper Music AI. (n.d.). Amper Music ai. https://ampermusic.ai/

Rationale: This article discusses Amper Music’s AI technology, strengths, and weaknesses which is important for understanding the platform as an application of AI in entertainment.

2. Buckley, D. (2021, July 13). The problem with your netflix recommendations. The Sundae.https://thesundae.net/2019/11/03/the-problem-with-your-netflix-recommendations/?utm_source

Rationale: This article discusses limitations to Netflix’s AI recommendation software, which is important for understanding the platform as an application of AI in entertainment.

3.  Gokul. (2023, March 28). How Netflix uses Artificial Intelligence. Argoid. https://www.argoid.ai/blog/netflix-ai

Rationale: This article discusses how AI deep learning is implemented in Netflix’s user recommendations which is important for understanding the platform as an application of AI in entertainment.

4. Holdsworth, James. (2025, July 22). What is Ai Bias?. IBM. https://www.ibm.com/think/topics/ai-bias

Rationale: This article discusses the causes, effects, and ethical implications of AI bias, which is crucial to examining how the ethical consideration of  AI bias on the entertainment industry.

5. Holdsworth, J., & Scapicchio, M. (2025, September 4). What is deep learning?. IBM. https://www.ibm.com/think/topics/deep-learning

Rationale: This article gives an in depth overview of deep learning to help better  understand the technological foundation of how deep learning is used in AI entertainment applications.

6. IBM. (2025, September 8). What is machine learning (ML) ? https://www.ibm.com/think/topics/machine-learning

Rationale: This article gives an in depth overview of machine learning to help better  understand the technological foundation of how machine learning is used in AI entertainment applications.

7. Kenny. (2021, February 24). Procedural generation: An overview. Medium. https://kentpawson123.medium.com/procedural-generation-an-overview-1b054a0f8d41

Rationale: This article gives an overview of procedural content generation, and how it is used in gaming, which helps us to better understand its application in Minecraft.

8. Krakowski, O. (2025, June 20). Three AI trends reshaping the future of Media & Entertainment. TV Tech. https://www.tvtechnology.com/opinion/three-ai-trends-reshaping-the-future-of-media-and-entertainment

Rationale: This article sheds light on recent AI trends in 2025, which gives us insight into what trends are expected to carry into the future of AI in  entertainment.

9. Montserrat, R. R. (2025, March 4). Procedural content generation for video games, a friendly approach. Level Up. https://www.levelup-gamedevhub.com/en/news/procedural-content-generation-for-video-games-a-friendly-approach/

Rationale: This article is an in-depth review of procedural content generation, focusing on more of the technologies involved, which is important to understanding the application of it in Minecraft.

10. O’Flaherty, K. (2021, October 10). All the ways netflix tracks you and what you watch. Wired. https://www.wired.com/story/netflix-data-tracking-privacy/

Rationale: This article talks about data privacy concerns with AI recommendations, which is important for understanding ethical and societal implications for AI in entertainment.

11. Panel, E. (2024, November 26). Ai in entertainment: 19 practical and ethical challenges. Forbes. https://www.forbes.com/councils/forbestechcouncil/2024/11/26/ai-in-entertainment-19-practical-and-ethical-challenges/

This article discusses AI’s possible displacement of humans in the entertainment industry, among other societal concerns, which is essential for understanding how AI’s application in entertainment affects society.

12. vAIber. (2025, June 18). Ai & PCG: Revolutionizing Game Development. DEV Community. https://dev.to/vaib/ai-pcg-revolutionizing-game-development-4le1#:~:text=Challenges%20and%20Future%20Outlook,to%20illogical%20or%20unplayable%20experiences.

Rationale: This article discusses the limitations of Procedural Content Generation, which is essential for understanding Minecraft as an application of AI in entertainment.

13. Yan, A. S. T. (2025, July 4). Comparison of music composing software: Amper Music, mlstudio and aiva. Applied and Computational Engineering. https://www.ewadirect.com/proceedings/ace/article/view/24667

Rationale: This article discusses the technologies applied in Amper music software  (deeplearning, and neural networks) which is essential for understanding the platform as an application of AI in entertainment.

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In creating the Padlet Sections for this assignment, I found the research process for AI in Entertainment to be very interesting and exciting. A lot of the information overlapped with some of the information I learned from my EST100 class, especially about how media uses AI to create content efficiently, and how bias in AI generated content affects society. What I enjoyed most about the research process was learning about Procedural Content Generation. I never knew that it was a thing until this assignment, and seeing how it allows games like Minecraft to generate endless, unique worlds was fascinating. Another part of the research process I enjoyed was researching the ethical considerations of AI in entertainment. It was interesting to see how much of users' data is implemented in AI recommendations for Platforms like Netflix, as well as recognizing that the displacement of human creative workers is a real possibility with the rise of AI in entertainment. One obstacle I endured while completing the research process was trying to find articles that clearly explained technical AI concepts in a way that was understandable and relevant to entertainment. Many sources were either too technical or too general, so I had to cross-reference multiple articles and simplify the information in my own words to make it clear and accurate. Despite the obstacles, I do believe that I’ve learned the impact of AI on the entertainment industry. AI has changed entertainment by making content creation faster (Amper Music), personalizing user experiences (Netflix), and expanding creative possibilities (Minecraft PCG), while also raising important questions about ethics, privacy, and the future role of human creators. I believe that if anything, this research and assignment has shown me that AI, in any industry, needs to be used responsibly as a creative tool, and not as a replacement for human thought processes or creativity.