The era of AI use in the news industry: "Should we use it?" is over! What's the next challenge?
Hello, I'm John, a blog writer who explains AI technology in an easy-to-understand way!
Recently, we've been hearing the word "AI" more and more in various situations, such as when writing sentences or drawing pictures. In fact, even in the news industry, such as newspapers and TV stations that deliver the news we see every day, the topic of "how can we use AI in our work?" is currently the subject of heated discussion.
Until recently, people would ask questions like, "Can AI really be used for work?" or "It's kind of scary...", but those days are over now. Many news companies have come to the conclusion that "AI should be used," and the stage of the debate has shifted toFrom "Whether to use it" to "How to use it effectively"There is a big shift towards.
This time, I will explain in a way that anyone can understand about the current state of AI use in the news industry and the challenges that need to be overcome in the future!
Big challenge: "How do we spread AI across the company?"
When news companies try to adopt AI, they run into a big hurdle: How do they scale from experimental use to full-scale adoption across the entire company?
It's easy for one journalist to try out an AI tool, but it's extremely difficult to get hundreds of people in a company, including the editorial, sales, and marketing departments, to work together to use AI.
There are two main approaches to the problem of "how to spread AI."
Model 1: "Centralized model" managed by a "team of experts"
The first method is to create a department within the company called an "AI specialist team" and have that department take the lead in introducing AI and advancing projects."Centralized model"called.
This model has both advantages and disadvantages.
- 良い点：With a team of experts, we can provide high-quality, consistent AI usage. Another advantage is that it is easy to create large-scale strategies for the entire company.
- Difficult points:Too much work is concentrated in the specialized team, which tends to become a "bottleneck" that slows down the progress of the project. In addition, problems can arise where the specialized team has difficulty understanding the specific needs of the field (such as the department in charge of sports news).
Model 2: "Decentralized model" where each department is free to proceed
The second method is to have each department use AI tools freely and think about how to utilize them, without having to set up a specialized team."Distributed Model"called.
In this model, each department will have an "AI champion" who is knowledgeable about AI and teaches his or her colleagues how to use it, thereby spreading its use.
- 良い点：Tools that meet the needs of the workplace can be quickly introduced, and practical use will progress rapidly. Another benefit is that it makes it easier for each employee to feel familiar with AI.
- Difficult points:When viewed from a company-wide perspective, the tools and rules used by each department may be different. This is sometimes called "shadow IT," and it can lead to security risks and unnecessary costs.
Which is ideal? The answer is "hybrid model"
Both the "centralized" and "decentralized" models have their pros and cons, so what is the best approach for news companies?
Many experts think that the combination of these two is the answer."Hybrid model".
This might be easier to understand with the example of a school.
First, the "AI Specialist Team" (similar to a school board) that manages the entire company decides on basic rules for using AI and safe tools that should be used across the entire company.The "centralized" part.
Then, each department has an "AI promoter" (similar to a class representative) who thinks about how to use AI to help their work within those rules and spreads that knowledge to those around them.The "decentralized" part.
In this way, the overall policy and safety are managed by a specialized team, while the freedom of thought and speed of the people on the ground are also utilized. This balanced "hybrid model" is considered to be the key to successfully utilizing AI throughout the company.
Why is this approach so important?
Some of you may feel that this is just something that only happens within a company, and is difficult to understand. However, this "how to proceed with AI" is a very important topic that also affects the quality of the news we receive.
If AI can be used effectively, reporters will be freed from repetitive tasks and will be able to spend more time on deeper reporting and analysis. For example, by having AI analyze huge amounts of data, it will be possible to discover signs of previously unnoticed social problems and deliver news tailored to the interests of each individual reader.
Advancing the use of AI with a solid strategy is an unavoidable path for the news industry to continue delivering high-quality information to society.
A word from the author (John)
The theme of this article is not just about the news industry. Any large company will always face the problem of "Should we leave it to the expert team or leave it to the field" when introducing new technology. It's very interesting that the answer is a "hybrid" that combines the best of both worlds. It makes you realize how important a sense of balance is.
This article is based on the following original articles and is summarized from the author's perspective:
News companies need to talk about AI adoption,
scaling