Sep 21 2024
How AI can help spot wildfires

This article is from The Spark, MIT Technology Review’s weekly climate newsletter. To receive it in your inbox every Wednesday, sign up here.

In February 2024, a broken utility pole brought down power lines near the small town of Stinnett, Texas. In the following weeks, the fire reportedly sparked by that equipment grew to burn over 1 million acres, the biggest wildfire in the state’s history.

Anything from stray fireworks to lightning strikes can start a wildfire. While it’s natural for many ecosystems to see some level of fire activity, the hotter, drier conditions brought on by climate change are fueling longer fire seasons with larger fires that burn more land.

This means that the need to spot wildfires earlier is becoming ever more crucial, and some groups are turning to technology to help. My colleague James Temple just wrote about a new effort from Google to fund an AI-powered wildfire-spotting satellite constellation. Read his full story for the details, and in the meantime, let’s dig into how this project fits into the world of fire-detection tech and some of the challenges that lie ahead.

The earliest moments in the progression of a fire can be crucial. Today, many fires are reported to authorities by bystanders who happen to spot them and call emergency services. Technologies could help officials by detecting fires earlier, well before they grow into monster blazes.

One such effort is called FireSat. It’s a project from the Earth Fire Alliance, a collaboration between Google’s nonprofit and research arms, the Environmental Defense Fund, Muon Space (a satellite company), and others. This planned system of 52 satellites should be able to spot fires as small as five by five meters (about 16 feet by 16 feet), and images will refresh every 20 minutes.

These wouldn’t be the first satellites to help with wildfire detection, but many existing efforts can either deliver high-resolution images or refresh often—not both, as the new project is aiming to do.

A startup based in Germany, called OroraTech, is also working to launch new satellites that specialize in wildfire detection. The small satellites (around the size of a shoebox) will orbit close to Earth and use sensors that detect heat. The company’s long-term goal is to launch 100 of the satellites into space and deliver images every 30 minutes.

Other companies are staying on Earth, deploying camera stations that can help officials identify, confirm, and monitor fires. Pano AI is using high-tech camera stations to try to spot fires earlier. The company mounts cameras on high vantage points, like the tops of mountains, and spins them around to get a full 360-degree view of the surrounding area. It says the tech can spot wildfire activity within a 15-mile radius. The cameras pair up with algorithms to automatically send an alert to human analysts when a potential fire is detected.

Having more tools to help detect wildfires is great. But whenever I hear about such efforts, I’m struck by a couple of major challenges for this field. 

First, prevention of any sort can often be undervalued, since a problem that never happens feels much less urgent than one that needs to be solved.

Pano AI, which has a few camera stations deployed, points to examples in which its technology detected fires earlier than bystander reports. In one case in Oregon, the company’s system issued a warning 14 minutes before the first emergency call came in, according to a report given to TechCrunch.

Intuitively, it makes sense that catching a blaze early is a good thing. And modeling can show what might have happened if a fire hadn’t been caught early. But it’s really difficult to determine the impact of something that didn’t happen. These systems will need to be deployed for a long time, and researchers will need to undertake large-scale, systematic studies, before we’ll be able to say for sure how effective they are at preventing damaging fires. 

The prospect of cost is also a tricky piece of this for me to wrap my head around. It’s in the public interest to prevent wildfires that will end up producing greenhouse-gas emissions, not to mention endangering human lives. But who’s going to pay for that?

Each of PanoAI’s stations costs something like $50,000 per year. The company’s customers include utilities, which have a vested interest in making sure their equipment doesn’t start fires and watching out for blazes that could damage its infrastructure.

The electric utility Xcel, whose equipment allegedly sparked that fire in Texas earlier this year, is facing lawsuits over its role. And utilities can face huge costs after fires. Last year’s deadly blazes in Hawaii caused billions of dollars in damages, and Hawaiian Electric recently agreed to pay roughly $2 billion for its role in those fires. 

The proposed satellite system from the Earth Fire Alliance will cost more than $400 million all told. The group has secured about two-thirds of what it needs for the first phase of the program, which includes the first four launches, but it’ll need to raise a lot more money to make its AI-powered wildfire-detecting satellite constellation a reality.

Now read the rest of The Spark

Related reading

Read more about how an AI-powered satellite constellation can help spot wildfires faster here. 

Other companies are aiming to use balloons that will surf on wind currents to track fires. Urban Sky is deploying balloons in Colorado this year. 

Satellite images can also be used to tally up the damage and emissions caused by fires. Earlier this year I wrote about last year’s Canadian wildfires, which produced more emissions than the fossil fuels in most countries in 2023. 

Another thing

We’re just two weeks away from EmTech MIT, our signature event on emerging technologies. I’ll be on stage speaking with tech leaders on topics like net-zero buildings and emissions from Big Tech. We’ll also be revealing our 2024 list of Climate Tech Companies to Watch. 

For a preview of the event, check out this conversation I had with MIT Technology Review executive editor Amy Nordrum and editor in chief Mat Honan. You can register to join us on September 30 and October 1 at the MIT campus or online—hope to see you there!

Keeping up with climate  

The US Postal Service is finally getting its long-awaited electric vehicles. They’re funny-looking, and the drivers seem to love them already. (Associated Press)

→ Check out this timeline I made in December 2022 of the multi-year saga it took for the agency to go all in on EVs. (MIT Technology Review)

Microsoft is billing itself as a leader in AI for climate innovation. At the same time, the tech giant is selling its technology to oil and gas companies. Check out this fascinating investigation from my former colleague Karen Hao. (The Atlantic)

Imagine solar panels that aren’t affected by a cloudy day … because they’re in space. Space-based solar power sounds like a dream, but advances in solar tech and falling launch costs have proponents arguing that it’s a dream closer than ever to becoming reality. Many are still skeptical. (Cipher)

Norway is the first country with more EVs on the road than gas-powered cars. Diesel vehicles are still the most common, though. (Washington Post) 

The emissions cost of delivering Amazon packages keeps ticking up. A new report from Stand.earth estimates that delivery emissions have increased by 75% since just 2019. (Wired)

BYD has been dominant in China’s EV market. The company is working to expand, but to compete in the UK and Europe, it will need to win over wary drivers. (Bloomberg)

Some companies want to make air-conditioning systems in big buildings smarter to help cut emissions. Grid-interactive efficient buildings can cut energy costs and demand at peak hours. (Canary Media)

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Sep 21 2024
Flu season is coming—and so is the risk of an all-new bird flu

This article first appeared in The Checkup, MIT Technology Review’s weekly biotech newsletter. To receive it in your inbox every Thursday, and read articles like this first, sign up here.

September will soon be drawing to a close. The kids are back to school, and those of us in the Northern Hemisphere are experiencing the joys the end of summer brings: the cooling temperatures, the falling leaves, and, inevitably, the start of flu season.

I was reminded of that fact when my littlest woke me for an early-morning cuddle, sneezed into my face, and wiped her nose on my pajamas. I booked her flu vaccine the next morning.

In the US, the Centers for Disease Control and Prevention recommends the flu vaccine for everyone over six months old. This year, following the spread of the “bird flu” H5N1 in cattle, the CDC is especially urging dairy farm workers to get vaccinated. At the end of July, the organization announced a $10 million plan to deliver free flu shots to people who work with livestock.

The goal is not only to protect those workers from seasonal flu, but to protect us all from a potentially more devastating consequence: the emergence of a new form of flu that could trigger another pandemic. That hasn’t happened yet, but unfortunately, it’s looking increasingly possible.

First, it’s worth noting that flu viruses experience subtle changes in their genetic makeup all the time. This allows the virus to evolve rapidly, and it is why flu vaccines need to be updated every year, depending on which form of the virus is most likely to be circulating.

More dramatic genetic changes can take place when multiple flu viruses infect a single animal. The genome of a flu virus is made up of eight segments. When two different viruses end up in the same cell, they can swap segments with each other.

These swapping events can create all-new viruses. It’s impossible to predict exactly what will result, but there’s always a chance that the new virus will be easily spread or cause more serious disease than either of its predecessors.

The fear is that farm workers who get seasonal flu could also pick up bird flu from cows. Those people could become unwitting incubators for deadly new flu strains and end up passing them on to the people around them. “That is exactly how we think pandemics start,” says Thomas Peacock, a virologist at the Pirbright Institute in Woking, UK.

The virus responsible for the 2009 swine flu pandemic is thought to have come about this way. Its genome suggested it had resulted from the genetic reassortment of a mix of flu viruses, including some thought to largely infect pigs and others that originated in birds. Viruses with genes from both a human flu and a bird flu are thought to have been responsible for pandemics in 1918, 1957, and 1968, too.

The CDC is hoping that vaccinating these individuals against seasonal flu might lower the risk of history repeating. But unfortunately, it’s not an airtight solution. For a start, not everyone will get vaccinated. Around 45% of US agricultural workers are undocumented migrants, a group that tends to have low vaccination rates. 

Even if every farm worker were to be vaccinated, not all of them would be fully protected against getting sick with flu. The flu vaccine used in the US in 2019-2020 was 39% effective, but the one used in the 2004-2005 flu season was only 10% effective.

“It’s not a bad idea, but I don’t think it can get anywhere close to mitigating the underlying risk,” says Peacock.

I last reported on bird flu in February 2023. Back then, the virus was decimating bird populations, but there were no signs that it was making the jump to mammals, and it didn’t appear to be posing a risk to humans. “We don’t need to panic about a bird flu pandemic—yet,” was my conclusion at the time. Today, the picture is different. After speaking to virologists and scientists who are trying to track the spread of the current bird flu, I’ll admit that I am much more concerned about the potential for another pandemic.

The main advice for people who don’t work on farms is to avoid raw milk and dead animals, both of which could be harboring the virus. For the most part, we’re reliant on government agencies to monitor and limit the spread of this virus. And the limited actions that have been taken to date don’t exactly inspire much confidence.

“The barn door’s already open,” says Peacock. “This virus is already out and about.”

Now read the rest of The Checkup

Read more from MIT Technology Review’s archive

We don’t know how many dairy herds in the US are infected with H5N1 as the virus continues to spread. It could end up sticking around in farms forever, virologists told me earlier this week.

Manufacturing flu vaccines is a slow process that relies on eggs. But scientists hope mRNA flu vaccines could offer a quicker, cheaper, and more effective alternative.

Some flu vaccines are already made without eggs. One makes use of a virus synthesized in insect cells. Egg-free vaccines might even work better than those made using eggs, as Cassandra Willyard reported earlier this year.

Chickens are especially vulnerable to H5N1. Some scientists are exploring ways to edit the animals’ genes to make them more resilient to the virus, as Abdullahi Tsanni reported last year.

From around the web

Microplastics are everywhere. They even get inside our brains, possibly via our noses. (JAMA Network Open)

The majority of face transplants survive for at least 10 years, research has found. Of the 50 first face transplants, which were carried out across 11 countries, 85% survived for five years, and 74% for 10 years. (JAMA Surgery)

Don’t throw away that placenta! The organ holds clues to health and disease, and instead of being disposed of after birth, it should be carefully studied instead, scientists say. (Trends in Molecular Medicine)

In June, the drug lenacapavir was shown to be 100% effective at preventing HIV in women and adolescent girls. But while the drug was tested on women in Africa, it remains unavailable to most of them. (STAT)

We’re still getting to grips with what endometriosis is, how it works, and how to treat it. Women with the condition appear to have differences in their brain’s gray matter that can’t be explained by pelvic pain alone. (Human Reproduction)

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Sep 21 2024
AI models let robots carry out tasks in unfamiliar environments

It’s tricky to get robots to do things in environments they’ve never seen before. Typically, researchers need to train them on new data for every new place they encounter, which can become very time-consuming and expensive.

Now researchers have developed a series of AI models that teach robots to complete basic tasks in new surroundings without further training or fine-tuning. The five AI models, called robot utility models (RUMs), allow machines to complete five separate tasks—opening doors and drawers, and picking up tissues, bags, and cylindrical objects—in unfamiliar environments with a 90% success rate. 

The team, consisting of researchers from New York University, Meta, and the robotics company Hello Robot, hopes its findings will make it quicker and easier to teach robots new skills while helping them function within previously unseen domains. The approach could make it easier and cheaper to deploy robots in our homes.

“In the past, people have focused a lot on the problem of ‘How do we get robots to do everything?’ but not really asking ‘How do we get robots to do the things that they do know how to do—everywhere?’” says Mahi Shafiullah, a PhD student at New York University who worked on the project. “We looked at ‘How do you teach a robot to, say, open any door, anywhere?’”

Teaching robots new skills generally requires a lot of data, which is pretty hard to come by. Because robotic training data needs to be collected physically—a time-consuming and expensive undertaking—it’s much harder to build and scale training databases for robots than it is for types of AI like large language models, which are trained on information scraped from the internet.

To make it faster to gather the data essential for teaching a robot a new skill, the researchers developed a new version of a tool it had used in previous research: an iPhone attached to a cheap reacher-grabber stick, the kind typically used to pick up trash. 

The team used the setup to record around 1,000 demonstrations in 40 different environments, including homes in New York City and Jersey City, for each of the five tasks—some of which had been gathered as part of previous research. Then they trained learning algorithms on the five data sets to create the five RUM models.

These models were deployed on Stretch, a robot consisting of a wheeled unit, a tall pole, and a retractable arm holding an iPhone, to test how successfully they were able to execute the tasks in new environments without additional tweaking. Although they achieved a completion rate of 74.4%, the researchers were able to increase this to a 90% success rate when they took images from the iPhone and the robot’s head-mounted camera,  gave them to OpenAI’s recent GPT-4o LLM model, and asked it if the task had been completed successfully. If GPT-4o said no, they simply reset the robot and tried again.

A significant challenge facing roboticists is that training and testing their models in lab environments isn’t representative of what could happen in the real world, meaning research that helps machines to behave more reliably in new settings is much welcomed, says Mohit Shridhar, a research scientist specializing in robotic manipulation who wasn’t involved in the work. 

“It’s nice to see that it’s being evaluated in all these diverse homes and kitchens, because if you can get a robot to work in the wild in a random house, that’s the true goal of robotics,” he says.

The project could serve as a general recipe to build other utility robotics models for other tasks, helping to teach robots new skills with minimal extra work and making it easier for people who aren’t trained roboticists to deploy future robots in their homes, says Shafiullah.

“The dream that we’re going for is that I could train something, put it on the internet, and you should be able to download and run it on a robot in your home,” he says.

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Sep 21 2024
The Download: training robots for unfamiliar environments, and all-new bird flu

This is today’s edition of The Download, our weekday newsletter that provides a daily dose of what’s going on in the world of technology.

AI models let robots carry out tasks in unfamiliar environments

What’s new: It’s tricky to get robots to do things in environments they’ve never seen before. Typically, researchers need to train them on new data for every new place they encounter, which can become very time-consuming and expensive. Now, researchers have developed a series of AI models that teach robots to complete basic tasks in new surroundings without further training or fine-tuning.

What they achieved: The five AI models, called robot utility models, (RUMs), allow machines to complete five separate tasks: opening doors and drawers, and picking up tissues, bags and cylindrical objects in unfamiliar environments with a 90% success rate. 

The big picture: The team hope their findings will make it quicker and easier to teach robots new skills while helping them function within previously-unseen domains. The approach could make it easier and cheaper to deploy robots in our homes in future. Read the full story.

—Rhiannon Williams

Flu season is coming—and so is the risk of an all-new bird flu

September will soon be drawing to a close. The kids are back to school, and those of us in the Northern Hemisphere are experiencing the joys the end of summer brings: the cooling temperatures, the falling leaves, and, inevitably, the start of flu season.

In the US, the Centers for Disease Control and Prevention recommends the flu vaccine for everyone over six months old. This year, following the spread of the “bird flu” H5N1 in cattle, the CDC is especially urging dairy farm workers to get vaccinated.

The goal is not only to protect those workers from seasonal flu, but to protect us all from a potentially more devastating consequence: the emergence of a new form of flu that could trigger another pandemic. That hasn’t happened yet, but unfortunately, it’s looking increasingly possible. Read the full story.

—Jessica Hamzelou

This story is from The Checkup, our weekly health and biotech newsletter. Sign up to receive it in your inbox every Thursday.

The must-reads

I’ve combed the internet to find you today’s most fun/important/scary/fascinating stories about technology.

1 Things aren’t looking good for the Doomsday Glacier
It’s rapidly melting, and its collapse appears imminent. (CNN)
+ If that happened, it’d be a disaster for global sea levels. (Bloomberg $)
+ But we still have time to influence how rapidly the process unfolds. (New Scientist $)
+ Interventional measures have been in place for years. (MIT Technology Review)

2 Major social media firms harvested vast amounts of user data
To the extent that it qualifies as mass surveillance. (NYT $)
+ The US FTC accused firms of failing to protect user privacy. (WP $)

3 Apple’s new Mac update is breaking cybersecurity systems
The Sequoia update has messed up tools from CrowdStrike and others. (TechCrunch)
+ The company’s suite of AI tools is now available to test out in public betas. (The Verge)

4 Tech companies are pushing to weaken the EU AI Act
It’s a last ditch attempt to lobby for lighter regulation before its codes of practice are finalized. (Reuters)
+ The AI Act is done. Here’s what will (and won’t) change. (MIT Technology Review)

5 To build better batteries, we need new anodes
Cathodes get all the attention, but other components are equally important. (Economist $)
+ Three takeaways about the current state of batteries. (MIT Technology Review)

6 Most of us can’t afford to avoid microplastics
Non-plastic alternatives are wildly expensive. So what can we do? (The Atlantic $)
+ Microplastics are everywhere. What does that mean for our immune systems? (MIT Technology Review)

7 Crypto thieves sold $243 million from a single person
The creditor of a defunct trading firm fell for a sophisticated scam. (CoinDesk)

8 Blue light glasses aren’t as useful as they claim to be
You’re better off taking regular screen breaks instead. (WP $)

9 This delivery robot knocked over a passing pedestrian
The robot actually drove away, reversed and hit them for a second time. (404 Media)
+ The company has offered the victim vouchers in compensation. (The Verge)

10 iPhones are nudging their owners to check in with their exes
No thanks! (Insider $)

Quote of the day

“Self-regulation has been a failure.”

—The Federal Trade Commission criticizes social media platforms and video streaming services’ surveillance of their users in a damning new report, the Verge reports.

The big story

Inside effective altruism, where the far future counts a lot more than the present

October 2022

Since its birth in the late 2000s, effective altruism has aimed to answer the question “How can those with means have the most impact on the world in a quantifiable way?”—and supplied methods for calculating the answer.

It’s no surprise that effective altruisms’ ideas have long faced criticism for reflecting white Western saviorism, alongside an avoidance of structural problems in favor of abstract math. And as believers pour even greater amounts of money into the movement’s increasingly sci-fi ideals, such charges are only intensifying. Read the full story.

—Rebecca Ackermann

We can still have nice things

A place for comfort, fun and distraction to brighten up your day. (Got any ideas? Drop me a line or tweet ’em at me.)

+ Mmmm, doughnuts 🍩
+ Gentlemen, step away from the chore jacket.
+ Once a spelling bee champion, always a spelling bee champion. But what do they do once they get older?
+ Why Hugh Grant is the perfect villain, actually.

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Sep 21 2024
The Best Use of AI for Business

Jacob Posel is a software engineer at Common Thread Collective, the ecommerce agency. He focuses on strategies for integrating artificial intelligence into a business. The best use, he says, is to streamline operational processes, those that might otherwise go to virtual assistants or inexpensive labor.

In our recent conversation, he addressed AI versus human creativity, image generation, cost, and more. The entire audio of that discussion is embedded below. The transcript is edited for length and clarity.

Eric Bandholz: Give us a rundown of what you do.

Jacob Posel: I’m a senior software engineer with Common Thread Collective. I spend most of my time integrating artificial intelligence into the creative and commercial process. I’ve been dealing with image generation lately. The work goes across the entire creative operating system.

The best use case for AI is daily business processes, particularly those assigned to virtual assistants or alternative forms of labor. Those tasks are usually well suited to AI. But let me define what I think of as AI right now because it’s become a buzzword.

Most people think of AI as a large language model, but it’s broader than that. For business processes, I’m referring to a system that understands human speech and text and a worldview that’s good enough to develop intuition. I would start by analyzing those processes and then determine how to make yourself and your team more efficient. What tools do you have available? How can you fully automate that process once you’ve nailed down how that fits into your process and business?

Eric Bandholz: Could you offer an example?

Jacob Posel: You can use it to get a more holistic picture of your business. You could pull sales data or reviews, for instance. Pull it into the Google sheet if you want, and then figure out the insight you’re trying to get from that data and the following action items. Explain that to an LLM and the AI. Share the data you’ve pulled in, and explain your thought process. Then, you can ask it to summarize that for you, provide insights, or inform you if there’s something you need to be aware of.

Eric Bandholz: How do we maintain the core skill of human creativity?

Jacob Posel: I read a research paper about this, where they try to train an LLM or an AI model based on its outputs and then see how many iterations of that it would take for the whole process to fail. After about 10 iterations, it was spitting out absolute nonsense. When you think about it, 80% of the code on the internet is AI-written, as is much of the text online. So, a genuine concern is that we’ll run out of training data to develop new models, and these new models will ultimately reach a point where they can’t progress any further.

The models are trying to scrape YouTube and videos to get more juice. But many very smart people are figuring out different techniques to improve these models beyond just the training data. Most models now grab as much training data as possible, spend as much money as possible on computation, and see what they produce. That cannot continue indefinitely.

The overall point is that AI empowers people to build their own software. Right now, you could build whatever you wanted. Even if you’re not technical, spending a little time setting up the best technologies might be frustrating, difficult initially, and imperfect, but you could do it. The future of programming languages won’t be Python, JavaScript, or SQL. The next iteration will be natural language. I think that’s pretty certain at this point.

Eric Bandholz: You’ve been generating images using AI. How are you doing that?

Jacob Posel: The underlying model I’ve been playing with is called Flux. It’s different from the Midjourney model. You’re able to fine-tune your own models. I primarily use Replicate, an interface where you can interact with graphic processing units and fine-tune your own models.

Midjourney is amazing for generating an image based on the text you provided. If you want to produce an image of a random guy sitting in an armchair underneath a tree in a lake, I would use Midjourney. But to create images with something specific within them that exists in the real world — a product or a person — you have to train your own custom model. You can’t do that with Midjourney. That’s why I use Flux.

 One note is that as you get more specific with the product, the model provides less creativity in the background and everything else in the image. So, with a very simple product like a t-shirt, you can put that anywhere on anyone, but when you need to get super specific, the model will hyper-focus on your product, making it difficult to get the rest right.

The training data is very important. If you want a specific angle, make sure you’ve given them a photo from that specific angle, ideally multiple times, and also make sure it’s in high definition.

Eric Bandholz: What does it cost?

Jacob Posel: Video is the most expensive right now. The cost goes from text, image, and video, as you would expect. Runway, for instance, uses a credit system. It’s dollars per credit. The unlimited plan is not terrible. It’s like $100 a month. It’s not the cheapest thing in the world, but it’s not prohibitive. It is expensive in terms of time, and it takes time to master those prompts.

Text-to-image is a bit more complicated because now you’re describing something more clearly. Then, text-to-video shows how many images are all put together. It becomes more expensive and more challenging to get it right. You must develop a sense of the wording used to train these models. You will understand photography and cinematic language as you get more advanced. But that’s why using more advanced tools is more complex and expensive.

The best thing to do is roll up your sleeves and figure it out yourself. That’s ultimately the best way to learn because the AIs have a personality at this point, and you won’t learn everything by reading. That’s how I think of the AIs. You have to understand what makes them tick and how to make them do what you want.

Start thinking of your business as different systems and processes. Don’t think of creating an ad as one thing. Break it down into the core steps and have that perspective and that foundation in mind because that’s how you build an engineering product. And that’s how AI is going to fit in. Communicating with someone who understands AI and how it integrates into your business will also be important.

Eric Bandholz: Where can people follow you?

Jacob Posel: @Dtcjacob on X, and I’m on LinkedIn.

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Sep 20 2024
Google Ads Tutorial: How to Leverage AI Video Enhancements via @sejournal, @brookeosmundson

Earlier this year, Google introduced new AI features into its Google Ads platform to help streamline work for many advertisers.

One of those new features comes in the form of AI video enhancements.

This is no surprise since video makes up over 65% of all internet traffic.

Read on to learn more about the AI video enhancements tutorial and how they can help streamline your PPC campaign optimization.

How do AI Video Enhancements Work?

In Google Ads, the AI video enhancement tool uses smart automation features to enhance your videos in a variety of ways.

It’s important to note that video enhancements are turned on by default but can easily be turned off at any time.

The feature can be found within your Google Ads campaign settings.

If you’re creating a new Google Ads campaign, this setting will only be available if you choose “Sales” as the goal and “Video” as the campaign type.

From there, go down to “Additional settings” to find the AI video enhancements settings:

New AI video enhancements tool for video campaigns.

Types of Enhancements Available

Google’s new AI video enhancements provide marketers with two areas to optimize current video assets.

#1: Additional video sizes and ratios

The first enhancement type can take existing horizontal videos and create additional versions for vertical and square ratios for optimal viewing.

The new ratio sizes that Google can create include:

  • 1:1
  • 4:5
  • 9:16

This feature can help the new video sizes feel more native to users viewing on mobile devices and create a better user experience.

#2: Get shorter versions of video ads

Say you’ve got a stellar video asset, but it may be too long to keep a user’s attention.

This new video enhancement uses Google AI to select key moments in the existing video to create shorter versions while keeping the original video message and appearance.

Per Google, these shorter video versions will automatically start running if they pass a quality review.

What are the benefits of using AI Video Enhancements?

As we come into Q4, time is of the essence for every marketer.

Resources are trying to do more with less, all while producing optimal PPC campaign results.

If you or your team are strapped for time or have a heavy workload, testing the Google AI video enhancements could be a key helper for your creative assets.

Some key benefits of testing out video enhancements include:

  • Reducing workload and budget
  • Takes the heavy lifting out of manually optimizing creatives
  • Can help boost campaign effectiveness
  • May help improve conversions

In Summary

With the ability to automatically generate different video sizes and ratios and create shorter versions of longer video ads, these tools are designed to save time and reduce the manual effort of video editing.

As marketers head into Q4 and face increasing demands, utilizing Google’s AI video enhancements can help lighten workloads, improve campaign effectiveness, and potentially increase conversions while keeping within budget constraints.

Featured image: monticello/Shutterstock

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Sep 20 2024
Snapchat Marketing: An In-Depth Guide For Businesses via @sejournal, @annabellenyst

Social media marketing is all about being where your audience is.

If your target audience is active on a platform, then you should be, too. And if you’re looking to speak to a younger demographic, Snapchat can be a powerful marketing tool for your business.

Snapchat is the fifth largest social media network in the world – but it’s one of the most misunderstood (and underestimated) by marketers.

So, if you’re concerned about missing the boat on this platform, you’re not alone. You’re also not out of touch – you just need a comprehensive guide to get started. And you’re in the right place.

In this updated guide to Snapchat marketing, we’ll provide you with a deep dive into the multimedia messaging platform, explain who’s using it, and give you the strategies you need to add it effectively to your marketing mix.

Why Use Snapchat For Marketing? (Is It Still Relevant?)

Successful marketers focus on grasping every opportunity to reach potential customers – and Snapchat continues to offer unique opportunities.

As of 2024, Snapchat boasts over 406 million active daily users, with more than 80% of them being 34 or younger. The platform reaches 90% of the 13-24-year-old population worldwide and 75% of 13-34-year-olds in over 25 countries.

This makes it an ideal platform for targeting Millennials, Gen Z, and, increasingly, Gen Alpha.

While it might not have the massive user base of Facebook or YouTube, it drives impressive engagement. According to recent data, the average Snapchat user opens the app over 40 times per day and spends about 30+ minutes daily on the platform – which means people interact with their social circles on Snapchat more than any other social network.

Yet, when it comes to marketing, Snapchat is a relatively untapped territory. While every brand seems to have a Facebook and Instagram presence these days, comparatively few have a foothold on Snapchat. And that just means more opportunity for your brand.

The boon of Snapchat is how it’s optimized for authenticity. Given the ephemeral nature of the app and the more unfiltered style of content approach, brands can use the platform to connect with their audience in ways that feel genuine and immediate – which is more valuable than ever.

And, as if all of this wasn’t enough, Snapchat has established itself as a competitive force in the social commerce market. With its augmented reality (AR) shopping experiences, you’re able to build immersive shopping experiences for users through the app – something most other platforms can’t compete with.

By now, it should be crystal clear why Snapchat could be a strong addition to your marketing strategy. So, how do you get started? Let’s break it down.

How Does Snapchat Work? A Brief Overview

If your social media experience is primarily with platforms like Facebook, Instagram, or X (Twitter), Snapchat’s interface may initially feel like a whole new world.

Snapchat’s design is unique – it’s built for spontaneity, exclusivity, and in-the-moment content creation. When you open the app, it goes directly to the camera, making it super easy for you to capture and share videos and photos (called “Snaps”) in just a few seconds.

You can then edit these Snaps using a variety of filters, stickers, and AR Lenses before sending them directly to your chosen friends or adding to your “Story,” which remains viewable for 24 hours. There’s also a newer Spotlight feature, similar to TikTok, for sharing short-form videos with wider audiences.

The app offers a host of other features, including a Snap Map, an AI-powered chatbot, and disappearing direct messages. Long story short: There are a bunch of innovative and creative ways for brands to engage with audiences on Snapchat.

What Brands Are Best Suited To Snapchat Marketing?

Let me be clear: Snapchat isn’t for every brand. There’s a reason why it’s less frequented than some other social media platforms. That said, if your target audience includes younger consumers, it’s absolutely worth considering.

Brands that are best suited to Snapchat are those that present a youthful image and tone and prioritize authenticity, “realness,” and creativity. If your brand image is highly professional or you have red tape around your marketing efforts, you should likely look elsewhere.

Lifestyle brands, fashion labels, beauty products, entertainment companies, and tech startups – these are the kinds of companies that typically see success on the app.

But really, the opportunity exists for any type of brand that is interested in using Snapchat’s tools to create immersive, engaging content that resonates with the platform’s users.

How To Get the Right “Tone Of Voice” For Snapchat

I mentioned tone above – and on Snapchat, tone of voice is a big deal. The platform itself is playful and casual, so you’re not likely to find success using an overly formal or professional tone.

Instead, your brand should focus on having a genuine conversation with users and infusing your content with humor.

Here are some tips for nailing the Snapchat tone of voice:

  • Keep it light: People go to Snapchat to be entertained. Leave your hard sales pitch at the door.
  • Prioritize authenticity: It’s a place to show the human side of your brand, whether it’s through user-generated content or behind-the-scenes Snaps.
  • Engage, engage, engage: Snapchat has a ton of interactive tools for engaging directly with users, like polls, Q&As, and more. Put them to use!

How To Create A Snapchat Strategy For Business

So, you want to create a successful Snapchat strategy. You can just start posting content sporadically, right? Wrong.

You need to start by understanding your brand’s goals and audience, and then determining the type of content that will best help you reach those people on Snapchat specifically. Here are some steps you can take to start building your Snapchat strategy:

  • Decide what you want to achieve on the platform. Maybe it’s brand awareness, community building, or increasing sales – once you know your goals, you can build your content approach around them.
  • Know your audience. As with any kind of marketing strategy, this is crucial.
  • Experiment and be creative. Try your hand with some of Snapchat’s different tools (like Bitmoji, AR Lenses, filters, etc.) to create content that resonates with your audience. Don’t just choose one type of content and settle – you can (and should) experiment with a variety of Snaps, Stories, and Spotlight videos.
  • Be consistent. All great marketers know that consistency is key – and it’s the same story on Snapchat.
  • Keep a good balance. Of course, you want to sell your brand to users, but don’t go all in on self-promotional content. Make sure you’re balancing organic, engaging storytelling with talking about yourself.
  • Learn (and follow) Snapchat best practices. This is a no-brainer. Spend time on the platform to find what works, and see how you can adopt it in your own strategy.

Types Of Content That Work Best On Snapchat

Snapchat is all about driving engagement. What does that look like in action? Here are some examples of content approaches that work particularly well on the platform.

1. Sneak Peeks & Teasers

Launching a new product or service? Snapchat is a great place to drive excitement by giving your audience teasers or sneak peeks at what’s to come.

You might think about dropping hints about the product, sharing a quick glimpse, or some other behind-the-scenes moments to encourage anticipation among your Snapchat followers.

Warner Bros., for example, has used teaser content to promote its upcoming movie releases.

Screenshot from Snapchat.com, August 2024Screenshot from Snapchat.com, August 2024

2. Behind-The-Scenes Content

Speaking of behind-the-scenes, this type of content is tailor-made for Snapchat.

Showing your audience what goes on behind the curtain at your brand is a clever way to create a sense of exclusivity and make people feel like insiders.

3. User-Generated Content (UGC)

You’ve heard about user-generated content – well, Snapchat is a place where UGC really thrives. Consider prompting your followers to create their own Snaps that feature your products or brand, and then share them along with a custom hashtag. Then, you can amplify the strongest ones in your own Stories.

UGC is proven to be a highly effective way to generate social proof, increase brand loyalty, and build a stronger social community.

Javy Coffee is one example of a brand that leveraged UGC by featuring real customer testimonials and stories about how they enjoy the coffee concentrate. This helped the company create relatable ads that resonated with its audience.

Screenshot from Snapchat.com, August 2024Screenshot from Snapchat.com, August 2024

4. Interactive Content

One thing that separates Snapchat from most other social media platforms is its interactivity. And brands have plenty of opportunities to get in on the action!

Try devising interactive moments for your followers, whether it’s a simple poll, a challenge, or a unique AR Lens. These allow users to really get involved and have a fun experience with your brand – and can lead to new UGC for you, as well.

For example, e.l.f. Cosmetics used AR Lenses combined with Bitmoji to allow users to virtually try on makeup, creating a highly interactive experience for its audience.

Screenshot from Snapchat.com, August 2024Screenshot from Snapchat.com, August 2024

5. Exclusive Offers

Want to really impress your Snapchat followers? Reward them. From promo codes to exclusive discounts or early bird access to new products, there is no shortage of ways to treat your audience.

It’s great for them but beneficial for you, too. It gives people a reason to keep engaging with your content and following your brand.

Advertising On Snapchat

While organic content is at the heart of Snapchat, the platform also offers some unique and powerful paid advertising options. The company also rolled out a new ad platform update in August 2024 that provides enhanced analytics, improved targeting, and more.

1. Snapchat Ads

Served to users in between user-generated content, these are full-screen, vertical video ads.  They’re not dissimilar to Instagram Stories, and can include interactive elements such as having a user swipe up to visit a website.

The Salvation Army’s Snapchat Ads featured videos depicting real-life stories of individuals impacted by its services, emphasizing themes of hope and transformation. These ads connected emotionally with viewers and included a swipe-up option to learn more or donate, making the content both impactful and actionable.

Screenshot from Snapchat.com, August 2024Screenshot from Snapchat.com, August 2024

2. Sponsored AR Lenses

One of Snapchat’s unique offerings is its custom AR Lenses, which brands can create for users to experience.

You can create Lenses that allow users to virtually “try on” products, for example, put people in a humorous visual setting or even have them play games. At times, they can even respond to users’ movements or the environment around them.

These can be hyper-engaging and drive a lot of interactions – like Volkswagen did when it used an AR Lens to enable people to experience its ID.3 electric vehicle virtually. Using the Lens, people could place a virtual model of the car in their environment, explore its features, and even change the color.

Screenshot from Snapchat.com, August 2024Screenshot from Snapchat.com, August 2024

3. Filters

These are static overlays that you can apply to your Snaps once they’re created – and brands are able to design their own to delight Snapchat users. These are typically non-interactive but are fun visual enhancements that enable people to add some creative flair to their content.

Post Consumer Brands created its own custom Snapchat Filter to promote its Honeycomb cereal – and it was very sweet!

Screenshot from Snapchat.com, August 2024Screenshot from Snapchat.com, August 2024

4. Dynamic Ads

Snapchat’s Dynamic Ads enable brands to automatically create and deliver personalized ads to users based on their behavior and interactions with your company. For example, if a user visits your website and looks at a specific hat, Snapchat might serve them an ad for that product.

If you work for an ecommerce company, these might be particularly interesting to you, as you can automate ad creation based on your product catalog – so you don’t need to lift a finger.

Fashion brand Free People has used Dynamic Ads to automate personalized ads for users, ensuring that those who viewed specific items on its website were later served ads featuring those exact products on Snapchat. It resulted in a 396% increase in demand.

Screenshot from Snapchat.com, August 2024Screenshot from Snapchat.com, August 2024

5. Commercials

These are non-skippable Snapchat video ads that usually appear within the platform’s premium content, like Snap Originals.

They’re short – three to six seconds for a Standard Commercial and up to 180 seconds for an Extended Play Commercial (though users can skip after the first 6 seconds) – and are optimized for high visibility.

They typically focus more on storytelling than some of the other ads on the network.

Let’s Get Snapping!

Yes, Snapchat is still an effective marketing platform for reaching younger audiences – but you must be mindful about your strategy and approach.

With its unique blend of high engagement, unique creative tools, and loyal audience, Snapchat offers brands a variety of ways to connect with their target consumers.

Hopefully, this guide has given you the insights and inspiration you need to build a successful Snapchat marketing strategy in 2024.

Now, it’s time to put these ideas into action and start Snapping your way to success.

More resources: 

Featured Image: Andrey_Popov/Shutterstock

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Sep 20 2024
B2B Dev Buys D2C Brand, Part 2: Holiday Prep

Lori McDonald is a pioneering B2B ecommerce developer, having founded Brilliance Business Solutions, an agency, in 1998. In February she acquired Norsland Lefse, a direct-to-consumer food manufacturer.

Now revving up Norsland with new tools and strategies, she has agreed to share the journey with us. In July, she discussed her rationale and goals for purchasing the business. In this conversation, she addressed customer feedback, holiday sales preparation, and more.

The entire audio of our conversation is below. The transcript is edited for length and clarity.

Practical Ecommerce: In February, you acquired a D2C food manufacturer. Give us a rundown of the first seven months.

Lori McDonald: Yes, we acquired Norsland Lefse in Rushford, Minnesota. The company manufactures lefse, a traditional Norwegian flatbread similar to a potato-based tortilla, and sells other Scandinavian foods and gifts. It’s been an exciting year, and I’ve learned so much.

We’ve migrated to BigCommerce from Wix, and that process has gone well. We no longer sell certain products on Amazon or our own site because they weren’t making enough money. I’ve learned it’s crucial to have systems in place to track profitability on every item.

Sales in August from our own site were more than double last year. A top goal of the acquisition is to grow direct revenue because we have higher margins there.

Our advertising is increasingly efficient. We advertise on Google and Meta (for Facebook and Instagram). We’re seeing great responses to Meta campaigns especially.

Our email campaigns with Klaviyo are going well too. In addition to sales promotions, we have email campaigns that invite customers to return and review products. It has helped us to collect some great reviews on our products and provide feedback for improvements. For example, some reviewers had experienced our lefse flatbread sticking together. So we started packaging the lefse with wax paper sheets between them.

PEC: Do you manage ad campaigns in-house?

McDonald: We’re working with OX Optimal, a creative agency. They’ve designed and tested ads. The best performers include photos of the lefse itself, like when coming off our manufacturing floor, to see how thin it is and what it looks like.

Early on we brought in a photographer who provided some terrific images that we’ve used for ad creative on and on our website.

PEC: How do you manage inventory and profitability on Amazon?

McDonald: We haven’t integrated Amazon with our BigCommerce backend. We’re tracking our inventory and profitability in Excel and updating the item quantities on BigCommerce and Amazon. It’s a manual process. We’re looking at automated solutions, such as Feedonomics, owned by BigCommerce.

There are different ways to manage multichannel selling. We’re looking at the best options for our situation. But our priority now, in September, is ensuring we’re ready for holiday sales.

PEC: It will be your first busy season!

McDonald: Yes. It’s critical we we make enough lefse for that period. We will start producing it in early September. We can freeze and store it for up to a year.

Sales in November and December have historically been 10 times higher than the rest of the year. So I anticipate being really busy. We’re just trying to ensure that we have the staff in place to make enough lefse and that we’re efficient in our process.

We’re improving our product descriptions so folks can understand why they should buy our lefse. We’re making improvements on our BigCommerce site, such as including categories in site search, moving out-of-stock items to the bottom of the page, and implementing better analytics.

We launched an exit survey using Hotjar that gives us feedback on the user experience and helps us understand why visitors leave our site. That’s provided us with some good information.

It’s so important to listen to customers. A frequent feedback item is that our shipping costs are too high. We’re now looking at better communication — shipping perishable goods is expensive. We’re also reassessing our shipping charges for accuracy. We offer free shipping for purchases of $200 or more. We ship via FedEx 2Day. We recently implemented ShipperHQ to help manage it all. We use a local carrier for nearby orders and XPS Ship to print all labels. It integrates with BigCommerce and Amazon.

We won’t be able to do everything I dream of by this holiday season. Our goal is to implement what we can, learn from it, and improve next year.

PEC: You’re also the founder of Brilliance Business Solutions, a busy B2B ecommerce agency. How has the lefse acquisition impacted that company?

McDonald: It’s largely positive. We’re all learning a lot and incorporating those insights into how we help our development customers. Based on our lefse experience, we could develop specialty themes and features to help those customers, for example. The analytics capabilities we build for Norsland Lefse could help them too.

Norsland Lefse has helped me become more focused while creating opportunities at Brilliance for our fabulous team members. Many have stepped into doing some of the things I used to do.

PEC: How can folks reach out?

McDonald: Brilliance Business Solutions is at BrillianceWeb.com. Norsland is at NorslandLefse.com.

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Sep 20 2024
New Ecommerce Tools: September 19, 2024

This week’s installment of new products and services for ecommerce merchants includes influencer marketing, virtual try-ons, digital payments, ecommerce platforms, financing, and global and last-mile logistics.

Got an ecommerce product release? Email releases@practicalecommerce.com.

New Tools for Merchants: September 19, 2024

PayPal partners with Shopify Payments in the U.S. PayPal has expanded its partnership with Shopify in the U.S. PayPal will become an additional online credit and debit card processor for Shopify Payments through PayPal Complete Payments, an offering for marketplaces and platforms. PayPal wallet transactions will integrate into Shopify Payments in the U.S., which will streamline managing orders, payouts, reporting, and chargeback flows. The enhancement creates a single, unified experience for PayPal and Shopify merchants.

Web page for Shopify Payments

Shopify Payments

TD to launch an ecommerce platform for Canadian small businesses. TD Bank Group has launched TD eCommerce Solutions, a customizable ecommerce platform for Canadian small businesses. At launch, TD eCommerce Solutions, powered by BigCommerce, will be available to all new and existing TD Business Banking customers, offering accounting features, search engine optimization, fraud detection, multiple payment acceptance offerings, and more. TD customers can use same-day deposits and streamlined billing, allowing businesses to manage payments to multiple parties.

Alibaba logistics arm Cainiao launches next-day delivery in Europe. Cainiao, a global ecommerce logistics provider owned by Alibaba, has expanded its local express delivery services, now operational in 10 countries and regions worldwide, in addition to its presence in China. Cainiao Europe now can offer next-day delivery for €2 (roughly USD 2.25) within the home country, along with three-day delivery options ranging from €3 to €5 for other European countries. ​​Cainiao also announced the development of a second batch of global ecommerce logistics hubs, called e-hubs.

Amazon ads to appear in Rufus shopping assistant. To help shoppers discover more products, Amazon may insert ads in Rufus, its generative AI-powered shopping assistant. According to Amazon, Rufus can generate accompanying text based on the context of the conversation. Amazon’s campaign reports won’t include Rufus metrics. Amazon’s tests with Rufus ads are running in the U.S. only.

Web page for Rufus

Amazon’s Rufus

Humanz launches its influencer marketing platform in the U.S. Humanz, a collaborative AI-powered marketing platform for creators and brands, is entering the U.S. market alongside a partnership with Valeria Lipovetsky, a global influencer in beauty and fashion with more than 6 million followers. By providing a transparent and data-driven platform that gives real-time insight into a campaign’s performance, Humanz aims to empower creators to make informed decisions and optimize their content.

Fero launches embedded personalization ecommerce tool in U.K. Dutch fintech Fero has launched a personalization ecommerce tool, Checkout Companion, for Shopify-based businesses in the U.K. Fero says it can provide online shops with 430 data points to understand and act on why shoppers abandon purchases, including details such as when a customer lands on a site and the number searches and affiliate marketing referral sources.

Walmart Marketplace and Parafin collaborate for seller financing. Walmart Marketplace and Parafin have announced an initiative to provide sellers with financing through the Walmart Marketplace Capital program. Eligible sellers can access funding through Parafin, an approved Walmart Marketplace solution provider, to grow their businesses and prepare for the upcoming holiday retail season. Parafin offers financing services and employs machine learning to analyze sales data from millions of businesses to determine eligibility and terms.

Home page for Parafin

Parafin

Bold Commerce announces a collaboration with PayPal. Bold Commerce, a customized checkout provider, has announced a partnership with PayPal to integrate Fastlane by PayPal with Adobe Commerce. This integration aims to streamline the checkout process for U.S.-based retailers using Adobe Commerce, allowing them to deploy Fastlane by PayPal without switching platforms. Merchants can now add Fastlane by PayPal to their Adobe Commerce setups through Bold’s Magento extension.

Amazon launches “LastMileTram” in Germany for zero-tailpipe emissions. Amazon is working with partners to use a package transport tram (a vehicle running on rails) to deliver packages to the center of Frankfurt, from where electric cargo bikes complete the delivery, creating a zero-tailpipe emission journey from the delivery station to the customer. The pilot project is part of research from Frankfurt University of Applied Sciences, together with Verkehrsgesellschaft Frankfurt am Main and Intermodal City Injections, a collaboration between Amazon Transportation Services and Amazon Logistics teams.

DNA Payments launches Apple Pay Express Checkout for ecommerce. DNA Payments, an integrated omnichannel payment provider based in the U.K., has introduced Apple Pay Express Checkout, giving ecommerce merchants a new way to accept customer payments. Merchants can offer Apple Pay at checkout or via the Express option through the Safari browser. DNA Payments serves merchants in the U.K., helping them accept transactions through point-of-sale devices, via websites and payment links, or over the phone.

Google adds dresses to its AI shopping tool. Google is expanding its virtual try-on to dresses. Shoppers can now visualize dresses from hundreds of brands across Google’s Shopping Graph. Shoppers can search for dresses on Google and click any style that includes a “try-on” badge. From there, they can see what that garment looks like on a diverse set of real models, ranging from XXS to XXXL. Then, they pick a dress and click to the retailer’s site to buy it.

Screenshot from Google of virtual dress try ons.

Google’s virtual try-on for dresses.

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Sep 19 2024
Why we need an AI safety hotline

In the past couple of years, regulators have been caught off guard again and again as tech companies compete to launch ever more advanced AI models. It’s only a matter of time before labs release another round of models that pose new regulatory challenges. We’re likely just weeks away, for example, from OpenAI’s release of ChatGPT-5, which promises to push AI capabilities further than ever before. As it stands, it seems there’s little anyone can do to delay or prevent the release of a model that poses excessive risks.

Testing AI models before they’re released is a common approach to mitigating certain risks, and it may help regulators weigh up the costs and benefits—and potentially block models from being released if they’re deemed too dangerous. But the accuracy and comprehensiveness of these tests leaves a lot to be desired. AI models may “sandbag” the evaluation—hiding some of their capabilities to avoid raising any safety concerns. The evaluations may also fail to reliably uncover the full set of risks posed by any one model. Evaluations likewise suffer from limited scope—current tests are unlikely to uncover all the risks that warrant further investigation. There’s also the question of who conducts the evaluations and how their biases may influence testing efforts. For those reasons, evaluations need to be used alongside other governance tools. 

One such tool could be internal reporting mechanisms within the labs. Ideally, employees should feel empowered to regularly and fully share their AI safety concerns with their colleagues, and they should feel those colleagues can then be counted on to act on the concerns. However, there’s growing evidence that, far from being promoted, open criticism is becoming rarer in AI labs. Just three months ago, 13 former and current workers from OpenAI and other labs penned an open letter expressing fear of retaliation if they attempt to disclose questionable corporate behaviors that fall short of breaking the law. 

How to sound the alarm

In theory, external whistleblower protections could play a valuable role in the detection of AI risks. These could protect employees fired for disclosing corporate actions, and they could help make up for inadequate internal reporting mechanisms. Nearly every state has a public policy exception to at-will employment termination—in other words, terminated employees can seek recourse against their employers if they were retaliated against for calling out unsafe or illegal corporate practices. However, in practice this exception offers employees few assurances. Judges tend to favor employers in whistleblower cases. The likelihood of AI labs’ surviving such suits seems particularly high given that society has yet to reach any sort of consensus as to what qualifies as unsafe AI development and deployment. 

These and other shortcomings explain why the aforementioned 13 AI workers, including ex-OpenAI employee William Saunders, called for a novel “right to warn.” Companies would have to offer employees an anonymous process for disclosing risk-related concerns to the lab’s board, a regulatory authority, and an independent third body made up of subject-matter experts. The ins and outs of this process have yet to be figured out, but it would presumably be a formal, bureaucratic mechanism. The board, regulator, and third party would all need to make a record of the disclosure. It’s likely that each body would then initiate some sort of investigation. Subsequent meetings and hearings also seem like a necessary part of the process. Yet if Saunders is to be taken at his word, what AI workers really want is something different. 

When Saunders went on the Big Technology Podcast to outline his ideal process for sharing safety concerns, his focus was not on formal avenues for reporting established risks. Instead, he indicated a desire for some intermediate, informal step. He wants a chance to receive neutral, expert feedback on whether a safety concern is substantial enough to go through a “high stakes” process such as a right-to-warn system. Current government regulators, as Saunders says, could not serve that role. 

For one thing, they likely lack the expertise to help an AI worker think through safety concerns. What’s more, few workers will pick up the phone if they know it’s a government official on the other end—that sort of call may be “very intimidating,” as Saunders himself said on the podcast. Instead, he envisages being able to call an expert to discuss his concerns. In an ideal scenario, he’d be told that the risk in question does not seem that severe or likely to materialize, freeing him up to return to whatever he was doing with more peace of mind. 

Lowering the stakes

What Saunders is asking for in this podcast isn’t a right to warn, then, as that suggests the employee is already convinced there’s unsafe or illegal activity afoot. What he’s really calling for is a gut check—an opportunity to verify whether a suspicion of unsafe or illegal behavior seems warranted. The stakes would be much lower, so the regulatory response could be lighter. The third party responsible for weighing up these gut checks could be a much more informal one. For example, AI PhD students, retired AI industry workers, and other individuals with AI expertise could volunteer for an AI safety hotline. They could be tasked with quickly and expertly discussing safety matters with employees via a confidential and anonymous phone conversation. Hotline volunteers would have familiarity with leading safety practices, as well as extensive knowledge of what options, such as right-to-warn mechanisms, may be available to the employee. 

As Saunders indicated, few employees will likely want to go from 0 to 100 with their safety concerns—straight from colleagues to the board or even a government body. They are much more likely to raise their issues if an intermediary, informal step is available.

Studying examples elsewhere

The details of how precisely an AI safety hotline would work deserve more debate among AI community members, regulators, and civil society. For the hotline to realize its full potential, for instance, it may need some way to escalate the most urgent, verified reports to the appropriate authorities. How to ensure the confidentiality of hotline conversations is another matter that needs thorough investigation. How to recruit and retain volunteers is another key question. Given leading experts’ broad concern about AI risk, some may be willing to participate simply out of a desire to lend a hand. Should too few folks step forward, other incentives may be necessary. The essential first step, though, is acknowledging this missing piece in the puzzle of AI safety regulation. The next step is looking for models to emulate in building out the first AI hotline. 

One place to start is with ombudspersons. Other industries have recognized the value of identifying these neutral, independent individuals as resources for evaluating the seriousness of employee concerns. Ombudspersons exist in academia, nonprofits, and the private sector. The distinguishing attribute of these individuals and their staffers is neutrality—they have no incentive to favor one side or the other, and thus they’re more likely to be trusted by all. A glance at the use of ombudspersons in the federal government shows that when they are available, issues may be raised and resolved sooner than they would be otherwise.

This concept is relatively new. The US Department of Commerce established the first federal ombudsman in 1971. The office was tasked with helping citizens resolve disputes with the agency and investigate agency actions. Other agencies, including the Social Security Administration and the Internal Revenue Service, soon followed suit. A retrospective review of these early efforts concluded that effective ombudspersons can meaningfully improve citizen-government relations. On the whole, ombudspersons were associated with an uptick in voluntary compliance with regulations and cooperation with the government. 

An AI ombudsperson or safety hotline would surely have different tasks and staff from an ombudsperson in a federal agency. Nevertheless, the general concept is worthy of study by those advocating safeguards in the AI industry. 

A right to warn may play a role in getting AI safety concerns aired, but we need to set up more intermediate, informal steps as well. An AI safety hotline is low-hanging regulatory fruit. A pilot made up of volunteers could be organized in relatively short order and provide an immediate outlet for those, like Saunders, who merely want a sounding board.

Kevin Frazier is an assistant professor at St. Thomas University College of Law and senior research fellow in the Constitutional Studies Program at the University of Texas at Austin.

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