Use of AI for Generating Creative Content
Content creation has been a focal point for media and entertainment companies since their inception. Initially, creators had to rely on their own creative process to develop stories and other materials. Early technology like the printing press helped spur this process, bringing content to the masses in ways that were originally inconceivable. By the 20th century, new developments in mass media and broadcasting expanded this exposure to an even larger, global audience with television and radio.
Now, with Artificial Intelligence (AI) and the internet, content creators are again reaching new heights, generating content that is much more personalized and aimed at niche audiences. This has led to an explosion of online content known as Web 2.0 and is expected to grow even larger with generative AI and Machine Learning.
What is AI-driven Creative Content?
With AI tools and applications becoming more advanced, specialized content is being generated rapidly and providing people with new opportunities to create their own media businesses online. Tools like GPT4, one the fastest adopted applications of all time, are giving content creators new methods of developing material in seconds instead of hours, exponentially speeding up their ability to deliver new content to viewers.
This newly generated content, which can be edited to portray a human touch, is being seen in nearly every aspect of media from written content to images and videos, even so far as creating entirely new music. AI-created content can even include chatbots which generate their own words and responses to human inputs online.
Benefits of Using AI for Content Creation
Generative AI content isn’t just about the final product either. There are multiple ways that it is benefiting creators, giving them newfound freedom to tackle more challenging prospects for their business.
Cost-Efficiency: Generative AI possesses the ability to reduce staffing needs with its ability to create content at high speeds. This is largely seen as something to fear by creatives, but the reduction in overhead costs is impossible to ignore.
Scalability: As businesses become larger, they need to produce content in multiple ways, not just through one medium. With generative AI, content creators can develop larger quantities of materials without sacrificing all their time.
Personalization: Depending on the training sets, generative AI is capable of creating personalized content in certain tones that are expected by audiences. This gives content creators more range in their materials with new ways of including comedic effects or emotionally charged themes.
Consistency: AI can maintain a sense of consistency so that content creators don’t risk losing viewers who begin disliking newer material. This can be especially helpful for TV shows that risk jumping the shark after too many seasons.
Data Analysis: Feedback loops can help AI reinforce aspects of content that are praised by viewers and reduce less enjoyable material by feeding algorithms with responses from comment sections and critics alike.
Challenges and Considerations
Despite its many benefits, many clear obstacles still need to be addressed before a business decides to rely solely on AI-generated content because humans can identify material that is created by AI models. While deep fakes and other images can be convincing to the human eye, themes and philosophical beliefs are easy to spot as they can be too generic or bland when explained by an AI whereas humans can express unique views that non-sentient AI models are unable to conceive.
This leads to the need for a human touch, which is necessary for effective content, especially in regards to the entertainment sector where recycled ideas can become stale quickly and lead to poor revenue. Currently, AI models are only able to repeat these beliefs instead of pondering new ones.
However, the largest and most immediate concern is how the advent of generative AI will impact the job market for professionals around the world. As mentioned earlier, AI can reduce overhead costs by a massive amount, removing the need for multiple creators which is worrying to many who have spent their entire careers in creative roles.
Case Studies and Real-world Applications
A leading example of generative AI is ChatGPT which was released in late 2021 and has reshaped how white-collar jobs function. The large language model is capable of creating a massive amount of content in just seconds and has become the fastest application to reach 100 million users in 2 months, beating TikTok’s original record by 7 months.
The ripple effect of ChatGPT can already be seen with shows like South Park satirizing it in their episode Deep Learning which used the large language model to complete the final act of the episode. While this was meant as a joke, many Hollywood writers fear that this will become a reality and have gone on strike to protest its use in film and television.
Future of AI in Creative Content Generation
Despite the fears of ChatGPT and other generative AI platforms taking over advanced creative roles, there is no doubt that its use in content creation will cease. Its ability to help creators speed up their process and maintain a certain level of expected quality means that it will become just as prominent as the printing press and the radio.
However, without a human touch, there simply won’t be a demand for content generated by AI because humans will find it stale and recycled. Instead, content creators will need to find new ways to interact with generative AI models, using them to enhance content that they have already begun developing.
