Summer fun at a state fair can get dangerous quickly when bad weather enters the area. In today's example, we see a series of messages; one issued to prevent injury and the second to return fair-goers to their fun at the midway. In early September, the Evergreen State Fair issued a geo-targeted warning to persons within the fairgrounds, alerting them to "go indoors now" and to "SHELTER IN PLACE until further notice." Lightning had been detected within 10 miles of the fairgr

All clear messages are an important part of the communication lifecycle for alerts and warnings. When an alert is issued, it opens up a "conversation" by telling people about a hazard, its impacts, the location of the impact, and what people should do to protect themselves. Ideally, if a person is at risk, they will engage in protective action and remain safe until they are instructed to do otherwise. This can come as an additional notification as the event is ongoing, or

For several years now, I've been pondering how to better name a hazard in a message that describes an active police incident. We know that not naming the hazard affects message understanding (a key outcome measured by scientists who study the effects of warning messages) and this relates directly to feelings of self-efficacy, that is, feeling like you can take the right action to protect yourself, leading to protective action. We studied this in response to a message for civ

A 360 character WEA about a missing person There's something really touching about this alert. It is missing almost all of the critical information that we know should be contained in any missing person alert. For instance, we don't know who issued the message, there is no description of the missing person, there is no license plate. We also don't know when she left Happy Camp and how long she had been gone. The entire message is written in CAPS and it contains no informatio

Wildfire alerts use jargon filled language. Use plain language to reach more people and communicate more effectively.

Have you heard of the acronym "FUBU?" It means "For Us By Us." It happens to be a brand name for clothing, but it also happens to represent the type of language that is commonly used within an organization to communicate complex ideas using shorthand. It's information created BY YOU for people LIKE YOU. You have to have insider knowledge to get the importance of the language and have education to understand the nuances of it's meaning. This reminds me of Gen Z language exp

Let's talk about AMBER Alerts. Again. It really is the alert type that pops up as one of the most problematic with public message receivers in terms of messaging and policy. The messages tend to lack actionable details and the timing at which they are sent is frequently questioned. In fact, these two issues, combined with the geographical scope of the alert itself, appear to contribute to the majority of people opting out of AMBER Alerts on their phones. Because the prob

Should we use a link in our emergency alerts? Will people click them? Are some more trustworthy than others? We have research to answer each of these questions. In 2019, WEA 2.0 made it possible for alerting authorities to include a URL to guide people to additional information. This was a huge win for the emergency management community! Until then, we were limited to shorter messages AND no way to offer additional information. Then, everything changed and it was suddenl

Coded language does not simplify a message, it makes it more complex. When it comes to communicating danger, we need to know what the danger is, why its a danger, and what we can do about it.

AI-generated Alerts and Warnings? Part 7 Originally posted on LinkedIn on May 2, 2026 as part of a series on AI-generated alerts and warnings. Test bank – answer key – grading rubric. Now under construction. To be honest, it took me quite a while to understand what my EM1 colleagues were interested in doing with an AI-generated Alert and Warning benchmark. It took months of back and forth before I was assured that I understood what they needed for running tests, including t

AI-generated Alerts and Warnings? Part 6 Originally published on LinkedIn on April 25, 2026 as part of a series on AI generated Alerts and Warnings. I recently had a conversation with a team of researchers who commented on how transparent I’ve been with my articles about building a benchmark for AI-generated alerts and warnings. Being so open about the planning, the process, and the steps we are taking is unexpected, it seems. And yet when EM1 asked me to come on board as a

AI-generated Alerts and Warnings? Part 5 Originally published on LinkedIn on April 18 as part of a series on AI-generated Alerts and Warnings “If we can’t measure it, we can’t improve.” That’s what Tyler Felous, CEO of EM1 said about benchmarks. And agree with this 100%. Using a data-driven approach means measuring success and failure in order to identify ways to improve. But what exactly would a benchmark measure? Last week, I described the ways that medical researchers

AI-Generated Alerts and Warnings? Part 4 Originally published on LinkedIn on April 11, 2026 as part of a series on AI-generated Alerts and Warnings For the past few weeks, I’ve been writing about AI for Alert and Warning and the need for benchmarks that set standards that LLMs should adhere to. I’ve had a few research groups reach out to me about this and I’m happy to see that there is academic and practitioner interest in the project that I have begun with my colleagues. I

AI-generated Alerts and Warnings? Part 3 Originally published on LinkedIn on April 4 as part of a series on AI generated Alerts and Warnings. In a previous article, I introduced the idea of establishing benchmarks for AI Alert and Warnings (see this link). I explained that AI A&W benchmarks can help to set standards that will increase trustworthy use of AI while also ensuring that AI-generated messages align with the state-of-the-art in research and practice. I also introduc

AI -Generated Alerts and Warnings? Part 2 Originally published on LinkedIn on March 28, 2026 as part of a series on AI generated Alert and Warnings. Why are benchmarks valuable to Emergency Managers and other public safety organizations? Well, without them, you don't have a standardized way of determining if something is “good enough.” In medicine, researchers conduct clinical trials to determine the effectiveness of a new drug. In public health, researchers conduct experim

AI Generated Alerts and Warnings Part 1 Originally posted on LinkedIn March 21, 2026 as part of a series on AI Generated Alerts and Warnings I've been thinking for a while about AI generated alerts and warnings. As AI capabilities increase, it's a reasonable thing to consider. After all, I've seen students in my training classes load my published papers into ChatGPT and prompt it to write a message that follows the guidance I've written. And it's no secret that there are some

Organizational response information isn't recommended by alert and warning researchers, and yet it sneaks its way into messages here and there, especially those written for law enforcement activity.

Are you prepared to issue a message for an unusual threat such as a dangerous animal? Every now and then we find a WEA that is sent for an unfamiliar hazard, such as a bear in a populated area, an aggressive moose, or a cat or skunk with rabies. They represent the kind of message that is urgent with potentially severe consequences, but they probably aren't part of most organizations' message libraries. Should they be? I don't think it's possible to have ALL threats in yo

During the month of March, states throughout the U.S. recognized severe weather awareness week by conducting tornado drills. These included Virginia, Indiana, Kentucky, Michigan; in at least one state, the statewide tornado drill was cancelled (Missouri) and in other states these drills included local tests of the Wireless Emergency Alert system. We collected a bunch of the test messages and thought we’d go on a bit of a road show to see how they compare. Hop on board and l