Here's How Much Tech Companies Made From LA Unified School District During the Pandemic

Sarah Favot

Favot is an award-winning journalist and adjunct instructor at USC's Annenberg School for Communication and Journalism. She previously was an investigative and data reporter at national education news site The 74 and local news site LA School Report. She's also worked at the Los Angeles Daily News. She was a Livingston Award finalist in 2011 and holds a Master's degree in journalism from Boston University and BA from the University of Windsor in Ontario, Canada.

Here's How Much Tech Companies Made From LA Unified School District During the Pandemic
Image by Ian Hurley

In the early days of the pandemic, there was a mad dash to get technology and broadband internet service into students' homes. About 1 in 3 Los Angeles Unified School District families didn't have a desktop or laptop computer or high-speed internet, according to an April 2020 study by USC Annenberg.

To improve tech access and to make other COVID-related purchases, the Board of Education granted authority to then-Superintendent Austin Beutner to spend "any dollar amount necessary" to respond to the crisis. In 13 months, the district spent $390.5 million.


Over the course of the 13 months of data, the single largest purchase — $51.3 million — went to SummerBio, a Silicon Valley COVID testing company.

All told, $227.6 million went to tech companies or 58% of the district's total spending in that time frame.

The spending went to tech companies like Apple, T-Mobile, Verizon and a COVID testing company, records obtained by dot.LA through a Public Records Act request show.

Los Angeles school district spending from March 2020 through April 2021 show that money was spent on line items from iPads and broadband to food for students and families, and masks and sanitizing supplies for schools.

In March 2020 alone, 94% of the $72.3 million the district spent using emergency funds went to tech companies.

"It took a procurement team working around the clock to scour the globe and find devices and a technology team to make sure the devices had the proper software installed and every student was connected to the internet," Beutner said in May 2020.

It also began purchasing COVID-19 supplies, including 100,000 N95 masks and 300,000 surgical masks, for $2.4 million, and food for the district's "Grab n Go" meal program, like $450,000 on cases of chicken tenders and drumsticks.

John Rogers, an education professor at UCLA, said the district took decisive action to get necessary technology into student's hands.

"It was a herculean task to shift in-person instruction to remote learning in a district that serves many families who previously did not own a computing device or had regular access to the internet," he said. "Many other districts around the county lagged behind LAUSD in their efforts to provide a baseline of access to learning."

Here are the total amounts large tech companies were paid:

Apple

$51.3 million

Apple was paid virtually the same amount as SummerBio in total, just $9,000 less. It is unclear from the data exactly how many iPads and other devices were purchased and distributed, as a $37.8 million purchase for iPads doesn't list a quantity of items.

Arey Jones

$49.2 million

San Diego-based Arey Jones, which has relationships with Microsoft, Google, Intel, HP and other companies, is a conduit for school districts to procure technology equipment and software. LAUSD purchased Dell, Samsung and HP Chromebooks, monitors and iPad integration services and cases. In March 2020 alone, the company received $22 million.

CDW Government, LLC

$8.6 million

LAUSD purchased 1,000 video conferencing bars from CDW Government, LLC, a technology provider for state and local governments, for $8.5 million.

Amazon

$2.0 million

As online learning extended beyond the few weeks that many were expecting, it became clear that some households had multiple students and adults working at home. Headphones were a solution to help students block out the noise of a busy home to focus on their studies. About a month into the pandemic, LAUSD purchased 131,000 pairs of headphones for $1.9 million.

Mergent

$8.1 million

In December, the district spent $8.1 million for 490,000 headphones, enough for a pair for every student.

Edgenuity

$6.7 million

LAUSD opened up summer school to all students for enrichment courses, like guitar lessons and language classes, in addition to classes where students can make up credits. About 100,000 or about a quarter of the district's students enrolled in summer school. The district paid for a platform called Edgenuity for credit recovery for 30,000 high school courses and 40,000 middle school courses, according to the data. It's a software program that the district has used for years. The district also used the program as classes turned online and continues to use it in its online independent study program.

Verizon

$6.1 million

The district agreed to pay Verizon up to $4.6 million in March 2020 for mobile broadband services and devices. It later paid another $1.5 million for additional service and devices.

IVCi

$4.3 million

Audio visual company IVCi sold 5,000 video conferencing bars for $4.3 million.

T-Mobile

$3.7 million

The first purchase the district made was to increase its contract with T-Mobile for mobile broadband and devices by $500,000 to $750,000. In March 2020, it paid a total of $2.4 million and later made an additional $1.3 million payment.

Discovery

$3.1 million

The district purchased a districtwide licensing agreement.

Reading Horizons

$3 million

The district bought a license for the training and curriculum tool software for teachers teaching science.

Rosetta Stone

$3 million

The district bought licenses for 100,000 students from the language software company.

Microsoft

$2.3 million

The district described this purchase as "various applications." Microsoft developed an app called the Daily Pass that must be scanned for each student and staff that enters a campus. That contract was for gratuitous services.

Nearpod

$2 million

The district purchased a license for the instructional platform for teachers.

Crayon Software Experts

$1.7 million

LAUSD paid Crayon Software Experts, a software asset management managed services company, for Microsoft Power Apps licenses to implement its COVID vaccination program.

IXL Learning

$1.7 million

The district bought site licenses for 300,000 students from the integrated learning platform that supports personalized learning in math, English language arts, science, social studies and Spanish.

Blackboard

$1.2 million

The district purchased a districtwide enterprise license for the online learning platform for additional teacher to student notification functions.

Zoom

$1 million

The tool that many of us became familiar with during the pandemic, the district spent about a half million on software licenses for 66,500 employees, 500,000 students and 2,000 others.

Newsela

$995,000

Elementary schools purchased licenses for Newsela, a literacy-focused startup with content in English and Spanish.

Renaissance Learning

$995,000

The district bought licenses for Renaissance Learning, a math and reading software.

Edpuzzle

$730,000

LAUSD bought a districtwide license for Edpuzzle, which teachers can use to make interactive videos.

HopSkipDrive

$500,000

Pasadena start-up HopSkipDrive, an ridesharing company for students, was paid $500,000 to take students to and from COVID-19 testing sites.

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One way to measure just how white-hot AI development has become: the world is running out of the advanced graphics chips necessary to power AI programs. While Intel central processing units were once the most sought-after industry leaders, advanced graphics chips like Nvidia’s are designed to run multiple computations simultaneously, a baseline necessity for many AI models.

An early version of ChatGPT required around 10,000 graphics chips to run. By some estimates, newer updates require 3-5 times that amount of processing power. As a result of this skyrocketing demand, shares of Nvidia have jumped 165% so far this year.

Building on this momentum, this week, Nvidia revealed a line-up of new AI-related projects including an Israeli supercomputer project and a platform utilizing AI to help video game developers. For smaller companies and startups, however, getting access to the vital underlying technology that powers AI development is already becoming less about meritocracy and more about “who you know.” According to the Wall Street Journal, Elon Musk scooped up a valuable share of server space from Oracle this year before anyone else got a crack at it for his new OpenAI rival, X.AI.

The massive demand for Nvidia-style chips has also created a lucrative secondary market, where smaller companies and startups are often outbid by larger and more established rivals. One startup founder compares the fevered crush of the current chip marketplace to toilet paper in the early days of the pandemic. For those companies that don’t get access to the most powerful chips or enough server space in the cloud, often the only remaining option is to simplify their AI models, so they can run more efficiently.

Beyond just the design of new AI products, we’re also at a key moment for users and consumers, who are still figuring out what sorts of applications are ideal for AI and which ones are less effective, or potentially even unethical or dangerous. There’s now mounting evidence that the hype around some of these AI tools is reaching a lot further than the warnings about its drawbacks.

JP Morgan Chase is training a new AI chatbot to help customers choose financial securities and stocks, known as IndexGPT. For now, they insist that it’s purely supplemental, designed to advise and not replace money managers, but it may just be a matter of time before job losses begin to hit financial planners along with everyone else.

A lawyer in New York just this week was busted by a judge for using ChatGPT as part of his background research. When questioned by the judge, lawyer Peter LoDuco revealed that he’d farmed out some research to a colleague, Steven A. Schwartz, who had consulted with ChatGPT on the case. Schwartz was apparently unaware that the AI chatbot was able to lie – transcripts even show him questioning ChatGPT’s responses and the bot assuring him that these were, in fact, real cases and citations.

New research by Marucie Jakesch, a doctoral student from Cornell University, suggests that even users who are more aware than Schwartz about how AI works and its limitations may still be impacted in subtle and subconscious ways by its output.

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But therein lies the big drawback to using ChatGPT and other AI tools for education. At least so far, they’re reliant on the end user writing good prompts and having some sense about how to organize a lesson plan for themselves. Human tutors, on the other hand, have a lot of personal experience in these kinds of areas. Someone who instructs others in foreign languages professionally probably has a good inherent sense of when you need to focus on expanding your vocabulary vs. drilling certain kinds of verb and tense conjugations. They’ve helped many other students prepare for tests, quizzes, and real-world challenges, while computer software can only guess at what kinds of scenarios its proteges will face.

A recent Forbes editorial by academic Thomas Davenport suggests that, while AI is getting all the hype right now, other forms of computing or machine learning are still going to be more effective for a lot of basic tasks. From a marketing perspective in 2023, it’s helpful for a tech company to throw the “AI” brand around, but it’s not magically going to be the answer for every problem.

Davenport points to a similar (if smaller) whirlwind of excitement around IBM’s “Watson” in the early 2010s, when it was famously able to take out human “Jeopardy!’ champions. It turns out, Watson was a general knowledge engine, really best suited for jobs like playing “Jeopardy.” But after the software gained celebrity status, people tried to use it for all sorts of advanced applications, like designing cancer drugs or providing investment advice. Today, few people turn to Watson for these kinds of solutions. It’s just the wrong tool for the job. In that same way, Davenport suggests that generative AI is in danger of being misapplied.

While the industry and end users both race to solve the AI puzzle in real time, governments are also feeling pressure to step in and potentially regulate the AI industry. This is much easier said than done, though, as politicians face the same kinds of questions and uncertainty as everyone else.

OpenAI CEO Sam Altman has been calling for governments to begin regulating AI, but just this week, he suggested that the company might pull out of the European Union entirely if the regulations were too onerous. Specifically, Altman worries that attempts to narrow what kinds of data can be used to train AI systems – specifically blocking copyrighted material – might well prove impossible. “If we can comply, we will, and if we can’t, we’ll cease operating,” Altman told Time. “We will try, but there are technical limits to what’s possible.” (Altman has already started walking this threat back, suggesting he has no immediate plans to exit the EU.)

In the US, The White House has been working on a “Blueprint for an AI Bill of Rights,” but it’s non-binding, just a collection of largely vague suggestions. It’s one thing to agree “consumers shouldn’t face discrimination from an algorithm” and “everyone should be protected from abusive data practices and have agency over how their data is used.” But enforcement is an entirely different animal. A lot of these issues already exist in tech, and are much larger than AI, and the US government already doesn’t do much about them.

Additionally, it’s possible AI regulations won’t work well at all if they aren’t global. Even if you set some policies and get an entire nation’s government to agree, how to set similar worldwide protocols? What if US and Europe agree but India doesn’t? Everyone around the world accesses roughly the same internet, so without any kind of international standard, it’s going to be much harder for individual nations to enforce specific rules. As with so many other AI developments, there’s inherent danger in patchwork regulations; it could allow some companies, or regions, or players to move forward while others are unfairly or ineffectively stymied or held back.

The same kinds of socio-economic concerns around AI that we have nationally – some sectors of the work force left behind, the wealthiest and most established players coming in to the new market with massive advantages, the rapid spread of misinformation – are all, in actuality, global concerns. Just as the hegemony of Microsoft and Google threaten the ability of new players to enter the AI space, the West’s early dominance of AI tech threatens to push out companies and innovations from emerging markets like Southeast Asia, Subsaharan Africa, and Central America. Left unfettered, AI could potentially deepen social, economic, and digital divisions both within and between all of these societies.

Undaunted, some governments aren’t waiting around for these tools to develop any further before they start attempting to regulate them. New York City has already set up some rules about how AI can be used during the hiring process while will take effect in July. The law requires any company using AI software in hiring to notify candidates that it’s being used, and to have independent auditors check the system annually for bias.

This sort of piecemeal figure-it-out-as-we-go approach is probably what’s going to be necessary, at least short-term, as AI development shows zero signs of slowing down or stopping any time soon. Though there’s some disagreement among experts, most analysts agree with Wharton professor and economist Jeremy Siegel, who told CNBC this week that AI is not yet a bubble. He pointed to the Nvidia earnings as a sign the market remains healthy and not overly frothy. So, at least for now, the feverish excitement around AI is not going to burst like a late ‘90s startup stock. The world needs to prepare as if this technology is going to be with us for a while.

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