Tesla's recalls keep piling up. No one's sure what happens next.

Federal regulators are keeping a close eye on Tesla.

Tesla workers on the line in Fremont, California

Though NHTSA continues to chastise Tesla, the company hasn’t gotten any serious financial penalties for its continued recalls.

Photo: David Butow/Getty Images

Tesla’s back at it again with another recall. The nation’s largest EV manufacturer has had repeated run-ins with federal safety regulators recently, and has issued at least 10 recalls in the last four months, including four in the past few weeks alone, due to several risky features in its recent software updates. Of those four, two were due to Tesla making software decisions that violate federal safety standards.

The recent uptick in recalls could be a sign that the National Highway Traffic Safety Administration is keeping a closer eye on Tesla as the company continues to add controversial features in its software updates that have pushed the agency’s safety limits. While NHTSA is upping its scrutiny of Tesla’s releases, the company continues to “play a little fast and loose” with the safety of its features, said Michael Brooks, acting executive director for The Center for Auto Safety.

“They seem to like to ask for forgiveness rather than permission a lot,” Brooks said.

Though the agency continues to chastise Tesla, the company hasn’t gotten any serious financial penalties for the continued recalls, Brooks said. The NHTSA didn’t respond to Protocol’s request for comment. Tesla, of course, famously disbanded its communications department in 2020.

“I hope Tesla gets its act together,” Brooks said. “We think Tesla needs to do a little more due diligence.”

Here’s a rundown of all of Tesla’s recalls in the past four months.

Feb. 8: Windshield Defrosting

Tesla recalled nearly 27,000 U.S. vehicles over software that affects windshield visibility in cold temperatures. The software issue could allow the heat to stop working in cold conditions, affecting the defrosting capabilities, but Tesla said it isn’t aware of any collisions related to the problem. The recall affects some 2021-2022 Model 3, Model S, Model X and 2020-2022 Model Y cars, and Tesla said it will issue an over-the-air software update to fix it.

Feb. 4: Novelty “Boombox” software

Nearly 580,000 Teslas were recalled due to its “Boombox,” a music feature which allows drivers to play external sounds while in motion, potentially obscuring Pedestrian Warning System sounds. The company said it will update its software to disable the feature while the car is in drive, reverse or neutral. The recall affects certain 2020–2022 Tesla Model S, X and Y vehicles, as well as some 2017–2022 Tesla Model 3s that have the pedestrian warning system.

Feb. 1: Seat belt reminders

817,000 Teslas were recalled because the required sound alert for when the vehicle starts and the driver hasn’t buckled their seat belt did not go off. Tesla Model S and Model X from 2021-2022, Model 3 from 2017-2022 and Model Y from 2020-2022 were affected by the recall, as they don’t adhere to federal safety standards on crash protection. Tesla said it would fix the issue with a software update.

Jan. 27: Rolling stops

Nearly 54,000 Teslas were recalled because the car’s Full Self-Driving software allowed cars to pass stop signs without coming to a complete stop. Tesla said there haven’t been any known crashes due to this feature. The recall affects Model S sedans, X SUVs from 2016 through 2022, Model 3 sedans from 2017 to 2022 and 2020 through 2022 Model Y SUVs. The company said it plans to disable the rolling stop software in these vehicles.

Dec. 21: Rearview camera and hood latch

Tesla recalled 475,000 cars for two separate issues. Approximately 119,000 of the 2014 to 2021 Model S Teslas were recalled for issues with the hood latch, which could open without warning while driving and “obstruct the driver's visibility.” The other issue, affecting more than 356,000 Model 3 cars from 2017 to 2020, caused the rearview camera to not be visible on the car's display due to "repeated opening and closing of the trunk lid.” Owners were allowed to bring their vehicles in for repair, free of charge.

Nov. 21: Suspension knuckle fractures

In one of the smaller recent recalls, 826 Tesla Model Y vehicles from 2020 to 2022 were recalled for possible weak suspension knuckles, causing the suspension links to separate and increasing chances of collision. Owners were notified by Jan. 18, 2022, and can bring the cars in for repair free of charge.

Nov. 9: Airbag tears

7,600 Teslas were recalled because the airbags could tear when used. The issue affects some 2021 Model X and Model S Teslas.

Oct. 29: False forward-collision warning

Tesla recalled close to 12,000 cars due to false warnings of a possible forward collision, unexpectedly triggering the emergency brakes. Models S, X, 3 and Y sold from 2017 to 2021 were affected by the recall. Tesla uninstalled the version of the software that had this issue, which was available to a limited number of customers in beta.

Oct. 25: Loose suspension bolts

Over 2,800 Tesla Model 3 vehicles released between 2019 and 2021 and Model Y vehicles released between 2020 and 2021 were recalled due to loose front suspension bolts, an issue which could cause instability and “adversely impact vehicle controllability,” according to the NHTSA report.

Fintech

Judge Zia Faruqui is trying to teach you crypto, one ‘SNL’ reference at a time

His decisions on major cryptocurrency cases have quoted "The Big Lebowski," "SNL," and "Dr. Strangelove." That’s because he wants you — yes, you — to read them.

The ways Zia Faruqui (right) has weighed on cases that have come before him can give lawyers clues as to what legal frameworks will pass muster.

Photo: Carolyn Van Houten/The Washington Post via Getty Images

“Cryptocurrency and related software analytics tools are ‘The wave of the future, Dude. One hundred percent electronic.’”

That’s not a quote from "The Big Lebowski" — at least, not directly. It’s a quote from a Washington, D.C., district court memorandum opinion on the role cryptocurrency analytics tools can play in government investigations. The author is Magistrate Judge Zia Faruqui.

Keep Reading Show less
Veronica Irwin

Veronica Irwin (@vronirwin) is a San Francisco-based reporter at Protocol covering fintech. Previously she was at the San Francisco Examiner, covering tech from a hyper-local angle. Before that, her byline was featured in SF Weekly, The Nation, Techworker, Ms. Magazine and The Frisc.

The financial technology transformation is driving competition, creating consumer choice, and shaping the future of finance. Hear from seven fintech leaders who are reshaping the future of finance, and join the inaugural Financial Technology Association Fintech Summit to learn more.

Keep Reading Show less
FTA
The Financial Technology Association (FTA) represents industry leaders shaping the future of finance. We champion the power of technology-centered financial services and advocate for the modernization of financial regulation to support inclusion and responsible innovation.
Enterprise

AWS CEO: The cloud isn’t just about technology

As AWS preps for its annual re:Invent conference, Adam Selipsky talks product strategy, support for hybrid environments, and the value of the cloud in uncertain economic times.

Photo: Noah Berger/Getty Images for Amazon Web Services

AWS is gearing up for re:Invent, its annual cloud computing conference where announcements this year are expected to focus on its end-to-end data strategy and delivering new industry-specific services.

It will be the second re:Invent with CEO Adam Selipsky as leader of the industry’s largest cloud provider after his return last year to AWS from data visualization company Tableau Software.

Keep Reading Show less
Donna Goodison

Donna Goodison (@dgoodison) is Protocol's senior reporter focusing on enterprise infrastructure technology, from the 'Big 3' cloud computing providers to data centers. She previously covered the public cloud at CRN after 15 years as a business reporter for the Boston Herald. Based in Massachusetts, she also has worked as a Boston Globe freelancer, business reporter at the Boston Business Journal and real estate reporter at Banker & Tradesman after toiling at weekly newspapers.

Image: Protocol

We launched Protocol in February 2020 to cover the evolving power center of tech. It is with deep sadness that just under three years later, we are winding down the publication.

As of today, we will not publish any more stories. All of our newsletters, apart from our flagship, Source Code, will no longer be sent. Source Code will be published and sent for the next few weeks, but it will also close down in December.

Keep Reading Show less
Bennett Richardson

Bennett Richardson ( @bennettrich) is the president of Protocol. Prior to joining Protocol in 2019, Bennett was executive director of global strategic partnerships at POLITICO, where he led strategic growth efforts including POLITICO's European expansion in Brussels and POLITICO's creative agency POLITICO Focus during his six years with the company. Prior to POLITICO, Bennett was co-founder and CMO of Hinge, the mobile dating company recently acquired by Match Group. Bennett began his career in digital and social brand marketing working with major brands across tech, energy, and health care at leading marketing and communications agencies including Edelman and GMMB. Bennett is originally from Portland, Maine, and received his bachelor's degree from Colgate University.

Enterprise

Why large enterprises struggle to find suitable platforms for MLops

As companies expand their use of AI beyond running just a few machine learning models, and as larger enterprises go from deploying hundreds of models to thousands and even millions of models, ML practitioners say that they have yet to find what they need from prepackaged MLops systems.

As companies expand their use of AI beyond running just a few machine learning models, ML practitioners say that they have yet to find what they need from prepackaged MLops systems.

Photo: artpartner-images via Getty Images

On any given day, Lily AI runs hundreds of machine learning models using computer vision and natural language processing that are customized for its retail and ecommerce clients to make website product recommendations, forecast demand, and plan merchandising. But this spring when the company was in the market for a machine learning operations platform to manage its expanding model roster, it wasn’t easy to find a suitable off-the-shelf system that could handle such a large number of models in deployment while also meeting other criteria.

Some MLops platforms are not well-suited for maintaining even more than 10 machine learning models when it comes to keeping track of data, navigating their user interfaces, or reporting capabilities, Matthew Nokleby, machine learning manager for Lily AI’s product intelligence team, told Protocol earlier this year. “The duct tape starts to show,” he said.

Keep Reading Show less
Kate Kaye

Kate Kaye is an award-winning multimedia reporter digging deep and telling print, digital and audio stories. She covers AI and data for Protocol. Her reporting on AI and tech ethics issues has been published in OneZero, Fast Company, MIT Technology Review, CityLab, Ad Age and Digiday and heard on NPR. Kate is the creator of RedTailMedia.org and is the author of "Campaign '08: A Turning Point for Digital Media," a book about how the 2008 presidential campaigns used digital media and data.

Latest Stories
Bulletins