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How does 911 call routing work?
March 25, 2024

Tech Brew


It’s Monday. When phones were tethered to walls, routing emergency responders was pretty uncomplicated: Send the ambulance to the address where the call originated. But in the era of cell phones, that’s gotten a little trickier. How exactly does it work, and is it reliable? Tech Brew’s Kelcee Griffis investigated.

In today’s edition:

Kelcee Griffis, Patrick Kulp, Annie Saunders


Emergingency tech

911 phone call trying to locate where the calls are coming from Francis Scialabba

Cell phones have simplified so many parts of our lives. Need to schedule a ride? There’s an app for that. Need to deposit a check? Just snap a pic. Need to check in with your doctor? Book a video appointment.

But there’s one major thing they’ve complicated: emergency call response times. Now that people in distress can dial 911 from anywhere, mobile carriers and public safety officials have had to work out different systems for quickly identifying the precise locations of callers. As numerous stories show, in an emergency, every second matters.

Here’s how a 911 call makes it from the scene of an emergency to first responders.

Let’s start with a scenario: You’re at the scene of a car accident. You reach into your pocket for your cell phone and dial 911.

“At the time that the call is placed, your phone will use location services, sort of a special flavor of location services that’s for emergency calls,” Brandon Abley, CTO of the National Emergency Number Association, told Tech Brew. “It’s built into Apple and Google devices and will send the best available location it has for the purposes of routing.”

This “special flavor” can include aggregating data points like nearby wi-fi networks and third-party data from the caller’s phone to help pinpoint their location, he said.

Keep reading here.—KG



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Data deluge

A warning sign that says flood marking a flooded street Mikenicholson1955/Getty Images

Flooding is becoming more frequent and severe as the climate crisis intensifies, and it’s only likely to get worse. That can make the job of predicting where and when these disasters will hit challenging, especially in areas with little historical or real-time data from which to draw.

A new paper from researchers at Google posits that machine learning could hold some answers. The tech giant claims an AI model, which is trained on publicly available data, can predict river-based flooding up to five days in advance with a reliability “similar to or better” that of current systems.

Google VP of Engineering and Research Yossi Matias said what’s particularly notable about this model is that it’s broadly applicable on a global scale, which could provide more accurate forecasting for developing areas underserved by stream gauges, or water measurement stations along rivers.

“The real question was, how can we build a model that is not going to be built for one locale, but is a global model, where we can take whatever data [on what] happens anywhere in the world and put that into the prediction modeling,” Matias told Tech Brew. “The breakthrough is really to, one, show that we can actually take such a global model and do that and, two, to actually measure that in a systematic way.”

Keep reading here.—PK



Coworking with Grace Yee

Graphic featuring a headshot of Adobe's Grace Yee Grace Yee

Coworking is a weekly segment where we spotlight Tech Brew readers who work with emerging technologies. Click here if you’d like a chance to be featured.

How would you describe your job to someone who doesn’t work in tech?

As senior director of ethical innovation (AI ethics and accessibility), I drive Adobe’s global AI ethics governance structure by developing processes, tools, training, and other resources to ensure that our AI solutions reflect our core values. When we talk about AI ethics, we have outlined what that means for Adobe through our AI ethics principles of accountability, responsibility and transparency, but at the end of the day, my job is to make sure that our AI innovations are developed responsibly to deliver outputs that address the needs of our end-users, while minimizing harm and bias.

That means making sure we are training on safe and inclusive datasets, sending all AI-powered features through our AI ethics assessment, and, finally, ensuring high-risk AI features go through our AI Ethics Committee and Review Board.

Keep reading here.




AI’s ready for its close-up. Get this: 66% of folks say AI is the emerging video technology they’re most excited to use in 2024. Your brand needs to get cameras rollin’. Fortunately, Wistia built the 2024 State of Video report with all the deets on AI and video marketing. Get the scoop.


Stat: 27%. That’s how much spending on streaming services went up on average from last year, Gizmodo reported, citing a Deloitte study. American households spend an average of $61 a month on streaming, and half of the respondents to the Deloitte report said a $5 price hike would lead them to cancel a streaming subscription.

Quote: “The toxicity level in online conversations has been relatively consistent over time, challenging the perception of a continual decline in the quality of discourse.”—Walter Quattrociocchi, an author of a Nature study that considered “the presumption that online discourse is bad and worsening,” to Caitlin Dewey, who pens the must-read newsletter Links I Would Gchat You If We Were Friends.

Read: How a legacy media company dwarfed venture capitalists’ returns on Reddit (The Information)


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