How rules-based AI and generative AI solve different problems for local newsrooms

Since the arrival of publicly available generative AI (initially as ChatGPT) almost three years ago, AI has been one of the hottest topics in the news industry. At United Robots, we firmly believe that the focus of AI in local newsrooms should not be tech, but rather the problems it can solve. Problems like lack of newsroom resources and time, as well as lack of unique local content. Here, we’ll discuss what problems our rules-based AI solutions solve, versus what generative AI is best at.

Not all AI is created equal …

United Robots builds text robots using rules-based AI, and we sell the automated content they produce. The raw material is structured, verified data — meaning only facts available in the data set end up in the text. Hallucinations cannot happen because the type of AI we build is journalistically limited by design. The downside of building text robots, compared to using GPT, is that it requires expertise and is a complex process involving programmers, writers (the robots don’t actually create the text segments, people do), data experts and linguists. The upside is that the content generated is safe to publish straight to news sites — it’s immediate and it’s correct.

Use cases:

• Hyperlocal content, i.e., home sales on a neighborhood level, traffic updates or game reports from local sports. That means each small community gets stories very close to home, relevant to them.
• 24/7 coverage. Because the content is based on verified data and can be auto-published, it can be used to provide 24/7 instant updates of extreme weather warnings, wildfire alerts, hurricanes and earthquakes.

In contrast, generative AI based on Large Language Models simply looks for language patterns to create its texts and is inherently unable to distinguish between fact and fiction. It is, however, fast, flexible and creative.

Use cases: Excellent for tasks like transcribing, editing, summarizing and ideas generation for example.

… but clearly both can create value.

Most of our publisher partners use a combination of the two types of AI. We’ve mapped out what value(s) different types of AI / automation, in the context of local content, can bring to newsrooms as well as to the end user, the reader, as these two charts illustrate:

Values for local newsrooms:

Values for local readers:

Come discuss AI in the newsroom with us at the Senior Leadership Conference

Cecilia Campbell, senior advisor and CMO, and Antonia Mariassy, COO and product at United Robots

At SLC, United Robots COO Antonia Mariassy and Senior Advisor Cecilia Campbell will host a roundtable, where we’ll talk about how we address pain points in local newsrooms with automated content, how that complements other AI efforts and what it does for local readers.

Join us there!