Generative AI defined: What it is and why it matters to publishers
Because ChatGPT is the fastest-growing product in history, the language model has become synonymous with artificial intelligence. But ChatGPT is only one solution in a broader class of tools that fall under the banner of generative AI.
In addition to text-based solutions like ChatGPT, generative AI also includes solutions like MidJourney which can create art and others that can produce video. These tools are indeed generative: They help people make things. Because these models are trained on large data sets, the AI surmises what users are most likely looking for based on different inputs and then outputs the result. Though many analysts like speculating on how generative AI will change different industries, this category can already transform the creative field today. Generative AI provides numerous benefits to publishers.
Generative AI democratizes creation.
In the past, artistic creation was limited to specialists. To produce art, you had to go to art school. To create a video, you had to go to film school. But such intense specialization is needed less with generative AI, which allows even non-technical talent to now produce work.
With art or text, the heart of the productive activity is the prompt. A user types in a command, or prompt, which provides guidelines to the AI on what type of art or writing they want produced. Though this prompt engineering, as the field is now called, requires some skill, anyone can pick it up. It is similar to doing a Google search: It may take some trial and error to get exactly what you’re looking for, but anyone should be able to get it. Though generative AI for video does not rely on prompts, it is equally democratic.
For these tools, a model must be trained on a field-specific data set, so that the AI can identify key moments, such as home runs in baseball or knockouts in boxing. These key moments are made to correspond with different meta-tags, which a user can call to auto-generate a highlight reel, such as all the knockouts by Floyd Mayweather.
This kind of democratization makes publishers more agile. Rather than having to recruit specialists for their teams, they can broaden their talent pipeline to include more generalists. Once on board, talents can also be shifted to focus on different mediums as the business environment demands.
Generative AI redefines the productive capacity of workers.
There are fairly standard conventions on how much a specialist can produce in a given day. A writer, for example, can research and write one or two long-form articles in a day, while a producer may spend all day on a single video.
Generative AI changes these benchmarks. Rather than replace workers, as some doom-and-gloom articles suggest, generative AI will simply make them more productive. With the aid of ChatGPT, the writer will be able to produce 5x to 10x more long-form articles, and the producer may see similar improvements. People will be measured by how exponentially productive they are when paired with AI tools.
With worker productivity improving dramatically, brands can create more niche content. In the past, they would have had to prioritize: After an NBA game, a basketball publisher would have to choose the most popular player to make a game recap for. With the support of AI generated highlights, this publisher could conceivably make these game recaps for all the game’s players, providing diverse content to fans with increasingly specific interests.
Generative AI enables higher level work.
Creative professionals will become more productive not because they are simply doing the same work faster, but because they are moving onto higher level work. Take the case of the writer. With ChatGPT on his side, he can instruct the language model to produce X number of articles. When these articles are produced, the writer will now function as an editor.
He will revise the AI-generated articles, fact-check them, SEO-optimize them, and altogether get them ready for publication. Freed from the grind of writing articles from scratch, he can exert his editorial imprint on a broader range of content. The same goes for video editors. Rather than get lost in the production cycle, they can act in an editorial capacity for all AI sports highlights. They can also exert a greater influence downstream, such as by coming up with more ideas on how to market and publicize these AI sports highlights.
When generative AI becomes commonplace, professionals are not replaced, nor moved laterally: They instead take on greater roles for their publisher, who benefit from this higher level of work.
Generative AI in a nutshell
Most people understand that the “generative” part of generative AI refers to the output it produces. But it is also generative in many other ways: It enables professionals to build a deeper pipeline of creativity, take on a higher level of editorial or marketing roles, and even contribute to areas in which they may have no direct specialization. Audiences win here: When a richer variety of content is generated, they get more writing, art, and video to enjoy.
