The Beta channel has been updated to 94.0.4606.69 (Platform version: 14150.46.0) for most Chrome OS devices. This build contains a number of bug fixes, security updates and feature enhancements.
Hi, everyone! We've just released Chrome 94 (94.0.4606.71) for Android: it'll become available on Google Play over the next few days.
This release includes stability and performance improvements. You can see a full list of the changes in the Git log. If you find a new issue, please let us know by filing a bug.The Stable channel has been updated to 94.0.4606.71 for Windows, Mac and Linux which will roll out over the coming days/weeks. Extended stable channel has also been updated to 94.0.4606.71 for Windows and Mac which will roll out over the coming days/weeks
A full list of changes in this build is available in the log. Interested in switching release channels? Find out how here. If you find a new issue, please let us know by filing a bug. The community help forum is also a great place to reach out for help or learn about common issues.
Security Fixes and Rewards
Note: Access to bug details and links may be kept restricted until a majority of users are updated with a fix. We will also retain restrictions if the bug exists in a third party library that other projects similarly depend on, but haven’t yet fixed.
This update includes 4 security fixes. Below, we highlight fixes that were contributed by external researchers. Please see the Chrome Security Page for more information.
[$20000][1245578] High CVE-2021-37974 : Use after free in Safe Browsing. Reported by Weipeng Jiang (@Krace) from Codesafe Team of Legendsec at Qi'anxin Group on 2021-09-01
[$TBD][1252918] High CVE-2021-37975 : Use after free in V8. Reported by Anonymous on 2021-09-24
[$NA][1251787] Medium CVE-2021-37976 : Information leak in core. Reported by Clément Lecigne from Google TAG, with technical assistance from Sergei Glazunov and Mark Brand from Google Project Zero on 2021-09-21
We would also like to thank all security researchers that worked with us during the development cycle to prevent security bugs from ever reaching the stable channel.
Google is aware the exploits for CVE-2021-37975 and CVE-2021-37976 exist in the wild.
As usual, our ongoing internal security work was responsible for a wide range of fixes:
[1254756] Various fixes from internal audits, fuzzing and other initiatives
Many of our security bugs are detected using AddressSanitizer, MemorySanitizer, UndefinedBehaviorSanitizer, Control Flow Integrity, libFuzzer, or AFL.
Interested in switching release channels? Find out how here. If you find a new issue, please let us know by filing a bug. The community help forum is also a great place to reach out for help or learn about common issues.
Design techniques based on classical algorithms have proved useful for recent innovation on several large-scale problems, such as travel itineraries and routing challenges. For example, Dijkstra’s algorithm is often used to compute routes in graphs, but the size of the computation can increase quickly beyond the scale of a small town. The process of "partitioning" a road network, however, can greatly speed up algorithms by effectively shrinking how much of the graph is searched during computation.
In this post, we cover how we engineered a graph partitioning algorithm for road networks using ideas from classic algorithms, parts of which were presented in “Sketch-based Algorithms for Approximate Shortest Paths in Road Networks” at WWW 2021. Using random walks, a classical concept that is counterintuitively useful for computing shortest routes by decreasing the network size significantly, our algorithm can find a high quality partitioning of the whole road network of the North America continent nearly an order of magnitude faster1 than other partitioning algorithms with similar output qualities.
Using Graphs to Model Road Networks
There is a well-known and useful correspondence between road networks and graphs, where intersections become nodes and roads become edges.
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| Image from Wikipedia |
To understand how routing might benefit from partitioning, consider the most well-known solution for finding the fastest route: the Dijkstra algorithm, which works in a breadth-first search manner. The Dijkstra algorithm performs an exhaustive search starting from the source until it finds the destination. Because of this, as the distance between the source and the destination increases, the computation can become an order of magnitude slower. For example, it is faster to compute a route inside Seattle, WA than from Seattle, WA to San Francisco, CA. Moreover, even for intra-metro routes, the exhaustive volume of space explored by the Dijkstra algorithm during computation results in an impractical latency on the order of seconds. However, identifying regions that have more connections inside themselves, but fewer connections to the outside (such as Staten Island, NY) makes it possible to split the computation into multiple, smaller chunks.
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| Top: A routing problem around Staten Island, NY. Bottom: Corresponding partitioning as a graph. Blue nodes indicate the only entrances to/exits from Staten Island. |
Consider driving from point A to point B in the above image. Once one decides where to enter Staten Island (Outerbridge or Goethals) and where to exit (Verrazzano), the problem can be broken into the three smaller pieces of driving: To the entrance, the exit, and then the destination using the best route available. That means a routing algorithm only needs to consider these special points (beacons) to navigate between points A and B and can thus find the shortest accurate path faster.
Note that beacons are only useful as long as there are not too many of them—the fewer beacons there are, the fewer shortcuts need to be added, the smaller the search space, and the faster the computation—so a good partitioning should have relatively fewer beacons for the number of components (i.e., a particular area of a road network).
As the example of Staten Island illustrates, real-life road networks have many beacons (special points such as bridges, tunnels, or mountain passes) that result in some areas being very well-connected (e.g., with large grids of streets) and others being poorly connected (e.g., an island only accessible via a couple of bridges). The question becomes how to efficiently define the components and identify the smallest number of beacons that connect the road network.
Our Partitioning Algorithm
Because each connection between two components is a potential beacon, the approach we take to ensure there are not too many beacons is to divide the road network in a way that minimizes the number of connections between components.
To do this, we start by dividing the network into two balanced (i.e., of similar size) components while also minimizing the number of roads that connect those two components, which results in an effectively small ratio of beacons to roads in each component. Then, the algorithm keeps dividing the network into two at a time until all the components reach the desired size, in terms of the number of roads inside, that yields a useful multi-component partition. There is a careful balance here: If the size is too small, we will get too many beacons; whereas if it is too large, then it will be useful only for long routes. Therefore the size is left as an input parameter and found through experimentation when the algorithm is being finalized.
While there are numerous partitioning schemes, such as METIS (for general networks), PUNCH and inertial-flow (both optimized for road-network likes), our solution is based on the inertial-flow algorithm, augmented to run as efficiently on whole continents as it does on cities.
Balanced Partitioning for Road Networks
How does one divide a road network represented as a graph into two balanced components, as mentioned above? A first step is to make a graph smaller by grouping closely connected nodes together, which allows us to speed up the following two-way partitioning phase. This is where a random walk is useful.
Random walks enjoy many useful theoretical properties—which is why they have been used to study a range of topics from the motion of mosquitoes in a forest to heat diffusion—and that most relevant for our application is that they tend to get “trapped” in regions that are well connected inside but poorly connected outside. Consider a random walk on the streets of Staten Island for a fixed number of steps: because relatively few roads exit the island, most of the steps happen inside the island, and the probability of stepping outside the island is low.
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| Illustration of a random walk. Suppose the blue graph is a hypothetical road network corresponding to Staten Island. 50 random walks are performed, all starting at the middle point. Each random walk continues for 10 steps or until it steps out of the island. The numbers at each node depict how many times they were visited by a random walk. By the end, any node inside the island is visited much more frequently than the nodes outside. |
After finding these small components, which will be highly connected nodes grouped together (such as Staten Island in the above example), the algorithm contracts each group into a new, single node.
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| Reducing the size of the original graph (left) by finding groups of nodes (middle) and coalescing each group into a single “super” node (right). Example here chosen manually to better illustrate the rest of the algorithm. |
The final steps of the algorithm are to partition this much smaller graph into two parts and then refine the partitioning on this small graph to one on the original graph of the road network. We then use the inertial flow algorithm to find the cut on the smaller graph that minimizes the ratio of beacons (i.e., edges being cut) to nodes.
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| The algorithm evaluates different directions. For each direction, we find the division that minimizes the number of edges cut (e.g., beacons) between the first and last 10% of the nodes |
Having found a cut on the small graph, the algorithm performs a refinement step to project the cut back to the original graph of the road network.
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Conclusion
This work shows how classical algorithms offer many useful tools for solving problems at large scale. Graph partitioning can be used to break down a large scale graph problem into smaller subproblems to be solved independently and in parallel—which is particularly relevant in Google maps, where this partitioning algorithm is used to efficiently compute routes.
Acknowledgements
We thank our collaborators Lisa Fawcett, Sreenivas Gollapudi, Kostas Kollias, Ravi Kumar, Andrew Tomkins, Ameya Velingker from Google Research and Pablo Beltran, Geoff Hulten, Steve Jackson, Du Nguyen from Google Maps.
1This technique can also be used for any network structure, such as that for brain neurons. ↩
Editor's note: Today’s post is by Ravi Mohan, General Manager, and Diwesh Sahai, Head of Engineering, for MyGate. The India-based company provides software for managing 20,000 residential housing communities throughout the country.
MyGate is a fast-growing company in India that aims to simplify the living experience in gated communities. Residents in over 20,000 communities across India use the MyGate mobile app to grant visitors entry, pay their leases, and get health and safety notices directly from management.
Our app began with a focus on security management for residential communities, and has since become a central hub for updating residents about health and safety, and providing a marketplace for in-home services from third parties — with more features on the way. MyGate is currently used in over 3.5 million residences throughout India, and we’re continuing to scale our operations to bring these benefits to even more communities.
Android Enterprise is key to keeping our employees connected no matter where their day takes them, thanks to strong security and effortless management.
Our IT team uses Google endpoint management to enroll and manage our corporate-owned Android devices with the work profile. Our hybrid teams access Google Workspace from more than 2,000 devices, with a dedicated space for work apps in their profile.
Many of our teams prefer to complete quick tasks directly from their Android devices, like answering comments in a doc, replying to a thread in Gmail or updating a sheet.
Our sales teams are often on the go — regularly meeting with potential customers, checking in with current clients, and working from the office or at home. We use managed Google Play to enroll everyone’s device with the MyGate app, which our teams use to demonstrate to prospective customers how our service simplifies life in a gated housing community and gives residents a welcome and positive living experience.
Our employees are big fans of the work profile, especially the separation of company and personal apps. And our IT team appreciates the combination of security for company data and privacy for our employees. We allowlist the specific apps that are essential to our employees’ daily work, so they always have them in the work profile. Managing updates and installing new apps through managed Google Play helps us keep everyone up to date with the tools they need. And employees like the privacy for the personal side of their device, with the ability to disconnect when they need to by pausing their work profile.
Android Enterprise also complements our growing Chrome OS device deployment. With our Chrome Enterprise upgrade management capabilities, we’ve been able to quickly give employees devices that are simple to enroll and ready to use. Google Meet has also been essential for team meetings and quick syncs, and has helped us securely scale our contact center team operations.
At MyGate, our goal is to provide safety and convenience to housing residents, right from their mobile device. By managing our company-owned smartphones with Android Enterprise, we are confident that we can scale quickly with strong data and device protection, and management controls for our security needs.
Posted by Manuel Vicente Vivo, Android Developer Relations Engineer
Contributors: Mauricio Vergara, Product Marketing Manager, Developer Marketing, Marialaura Garcia, Associate Product Marketing Manager, Developer Marketing
Headspace was ready to launch new wellness and fitness features, but their app architecture wasn’t. They spent eight months refactoring to a Model-View-ViewModel architecture, rewriting in Kotlin and improving test coverage from 15 to 80%. The improved app experience increased MAU by 15% and increased review scores from 3.5 to 4.7 between Q2 and Q4 of 2020. To learn more about how Headspace’s focus on Android Excellence impacted their business, read the accompanying case study here.
Headspace has grown into a leader in mindfulness by creating an app which helps millions of people to meditate daily. Mindfulness goes far beyond meditation, it connects to all aspects of a person’s life. That idea prompted the most recent stage in Headspace’s evolution. In 2019, they decided to expand beyond meditation and add new fitness and wellness features to their Android app. Headspace realized that they would need a cross-functional team of engineers and designers to be able to deliver on the new product vision and create an excellent app experience for users. An exciting new phase for the company: their design team started the process by creating prototypes for the new experience, with fresh new designs.
With designs in hand, the only thing stopping Headspace from expanding their app and broadening users’ horizons was their existing Android software architecture. It wasn’t well structured to support all these new features. Headspace’s development team made the case to their leadership that building on the existing code would take longer than a complete rewrite. After sharing the vision and getting everyone on board, the team set out on a collective journey to write a new Android app in pursuit of app excellence.
Headspace’s Android development team first needed a convenient way to standardize how they built and implemented features. "Before we wrote a single line of code, our team spent a week evaluating some important implementation choices for the foundation of our app,” Aram Sheroyan, an Android developer at Headspace explains;
“This was crucial pre-work so that we were all on the same page when we actually started to build."
Immersing themselves in Google’s literature on the latest, best practices for Android development and app architecture, the team found a solution they could all confidently agree on. Google recommended refactoring their app using a new base architecture: model-view-view-model. MVVM is a widely-supported software pattern that is progressively becoming industry standard because it allows developers to create a clear separation of concerns, helping streamline an app’s architecture. “It allowed us to nicely separate our view logic," Sheroyan explained.
With MVVM as the base architecture, they identified Android’s Jetpack libraries, including Dagger and Hilt for dependency injection. The new tools made boilerplate code smaller and easier to structure, not to mention more predictable and efficient. Combined with MVVM, the libraries provided them with a more detailed understanding of how new features should be implemented. The team was also able to improve quality in passing arguments between functions. The app had previously suffered from crashes due to NullPointerException errors and incorrect arguments. Adopting the safeArgs library helped to eliminate errors when passing arguments.
In rewriting the app, the team further made sure to follow the Repository pattern to support a clearer separation of concerns. For example, instead of having one huge class that saves data in shared preferences, they decided that each repository’s local data source should handle the respective logic. This separation of data sources enables the team to test and reproduce business code outside of the live app for unit testing without having to change production code. Separating concerns in this way made the app more stable and the code more modular.
The team also took the opportunity to fully translate their app into the Kotlin programming language, which offered useful helper functions, sealed classes, and extension functions. Removing legacy code and replacing the mix of Java and Kotlin with pure Kotlin code decreased build time for the app. The new architecture also made it easier to write tests and allowed them to increase test coverage from around 15% to more than 80%. This resulted in faster deployments, higher quality code, and fewer crashes.
To capture the new user experience in the app’s reviews, Headspace implemented the Google Play In-App Review API. The new API allowed them to encourage all users to share reviews from within the app. The implementation increased review scores by 24%, and — as store listing reviews are tied to visibility on Google Play — helped draw attention to the app’s recent improvements.
The rewrite took eight months and with it came a new confidence in the code. Now that the codebase had 80%+ unit test coverage, they could develop and test new features with confidence rather than worries. The new architecture made this possible thanks to its improved logic separation, and a more reusable code, making it easier to plan and implement new features.
The build time for the app decreased dramatically and development velocity picked up. The team’s new clarity around best practices and architecture also reduced friction for onboarding new developers, since it was now based on Android industry standards. They could communicate more clearly with potential candidates during the interview process, as they now had a shared architectural language for discussing problem sets and potential solutions.
With velocity came faster implementation of features and an improved retention flow. They could now optimize their upsell process, which led to a 20% increase in the number of paid Android subscribers relative to other platforms where the app is published. The combination of a new app experience and the implementation of the new In-App Review API led to their review scores improving from 3.5 to 4.7 stars between Q2 and Q4 of 2020! Overall, the new focus on Android App Excellence and the improved ratings earned Headspace a 15% increase in MAU globally..
These were just a few of the payoffs from the significant investment Headspace made in app excellence. Their laser focus on quality paid off across the board, enabling them to continue to grow their community of users and lay a solid foundation for the future evolution of their app experience.
If you’re interested in getting your team on board for your own App Excellence journey, check out our condensed case study for product owners and executives linked here. To learn more about how consistent, intuitive app user experiences can grow your business, visit the App Excellence landing page.
As digital partner to the daily sports newspaper Diario AS, AS.com is a popular destination for sports fans looking for the latest news, statistics and commentary. Based in Madrid, AS.com publishes local editions in Spanish and English for readers around the world.
The AS.com homepage during the Tokyo 2020 Olympics featured a Web Stories carousel, articles and videos of sporting events and star athletes.
AS.com has always set its sights on new and innovative content formats. “Our main goal is to make an impact with the reader. Our journalists at AS are experts at finding the right format for each piece of content to maximize the impact on our audience,” says Diario AS Deputy Editor Tomás de Cos. But with so many online destinations for sports fans, the pressure was on for the team to not only retain but grow their audience. They found their solution with Web Stories.
The AS.com team first learned about Web Stories at the AMP Conference 2018 in Amsterdam. Later that year, they published their first Web Story, “Las Claves del Clásico contadas por AS” (“The Keys to the Clásico, explained by AS”), for the Barcelona vs. Real Madrid match — a face-off between the two biggest rivals in Spanish football. “It was a super fun and enriching experiment,” says Manuel Barrios, Deputy Director of Strategy, Digital Distribution and International Expansion at Diario AS. The team spent the next year researching how other media sites use Web Stories, while testing out different publishing tools for their own website.
“Next, we went for a much more ambitious project — a guide to the NBA, launched at the start of the 2020 playoffs,” Manuel shares. The guide included a series of Web Stories about each of the league’s 30 teams, which were featured in a carousel on the homepage.
During the 2020 playoffs, AS.com featured Web Stories profiling all NBA teams in a carousel format on its homepage.
Since its success with the NBA series, AS.com has used Web Stories to spotlight other major sporting events, including the 2020 UEFA European Football Championship (Euro 2020). AS.com placed the Euro 2020 Web Stories carousel at the top of the AS.com homepage to make sure visitors would see it.
“We are all too aware that the percentage of users who scroll down on news sites is very low, so our Web Stories had to be seen as soon as our homepage loaded,” Manuel explains. “The coverage from Euro 2020 was crying out for the Web Stories format, because we knew our journalists would be able to make the most of the format and create unique content.” For example, one Web Story shares a behind-the-scenes look at an AS.com journalist’s experience inside the EuroCup stadium.
A Web Story from a journalist’s perspective as they enter the EuroCup stadium.
With the help of their partner StatMuse, a Web Stories editor from BeSocy, and the Google Web Creators YouTube channel, AS.com editors have continued incorporating Web Stories into their special news features and events coverage.
“The global audience of our Stories hit 4.4 million pageviews for the European Championships, 3.4 million for the Tokyo Olympic Games, and more than one million for our LaLiga Guide (men’s pro soccer league),” Manuel notes. “Since we launched Web Stories for the European Championships, we’ve had a marked increase in our audience consumption — with the carousel published in a number of international editions of AS.com, such as AS México and AS USA,” Manuel shares. “On average, 15 pages per story were reached, indicating significant reading depth.”
The site hopes to use Web Stories to further boost their daily sports content. “One of our ‘obsessions’ is to have Web Stories integrated organically as a standard format on our site,” Manuel says.
Spanish football sensation #14 Marcos Llorente featured in an AS.com Euro 2020 Web Story.
They’re also using Web Stories for more long-form features, like the 2021 Formula 1 racing competition kickoff. This particular feature has a separate Web Story for each team, including snippets of video interviews in the pages of the story.
AS.com used Web Stories to cover the teams and race cars in the 2021 Formula 1 competition.
The team now hopes to take their success with Web Stories to the AS mobile app. “We loved Web Stories from the very first moment for their editorial potential, and their capacity for storytelling,” Deputy Editor Tomás says. “Web Stories let us create the dynamic content our audience is hungry for.”
Since its creation in 2011, Google Arts & Culture has made a wide range of cultural stories and experiences available to everyone, thanks to our collaboration with cultural organisations around the world. From experiencing dinosaurs and iconic fashion garments in 360 to getting immersed into masterpieces guided by your favourite actor or musician, and even projecting Neil Armstrong’s spacesuit into your home in AR, the platform offers curious minds many opportunities to learn.
Whether it's taking art selfies, playing puzzle parties with friends, or diving into richly documented resources about US Black History or Inventions and Discoveries in history, Google Arts & Culture has been a valuable learning companion to people of all ages and backgrounds.
And today, we are releasing a new Teacher Guide – a dedicated resource for educators to make learning with Arts & Culture and using the platform in class easier than ever. The guide, developed in partnership with education and instructional design experts at Google, was created to help teachers better understand how to use the platform to engage their students. It includes ready-to-use handouts and customizable activity templates, and compliments other popular experiences on Google Arts & Culture that were designed with educators in mind.
Take a Virtual Field Trip, Julia Allum, 2021, Google Arts & Culture
Teachers can take their students on a virtual field trip, with hundreds of expeditions now available on Google Arts & Culture. Fly to the Moon, dive to the Great Barrier Reef, zoom Inside a Cell, visit museums, uncover scientific theories and explore distant lands. You can still explore the world from the comfort of your desk or classroom, no headset needed.
Created by education experts, the lesson plans can also be used as worksheets.
Ten new downloadable lesson plans have been published, such as Uncovering Egypt’s Layered History, Milestones in the Pride Movement, and The History of Computing. All Google Arts & Culture lesson plans have been written by education experts. In addition, Get Smart with Art is a new resource created by the de Young Museum and designed to enable educators, with no prior knowledge of art, to get younger students to look at art works.
Learn with Google Arts & Culture, London Stories by Julia Allum, 2018, London Transport Museum
For those looking for information on a particular topic, the Learn about Arts & Culture page gathers materials and experiences from across the platform, based on subjects including natural history, physics, geography, art and music.
Google Experiments, Art Coloring Book, Dish of Apples by Paul Cezanne, c. 1876-77, Metropolitan Museum of Art
If a teacher wants to excite students about a subject, one of the Google Arts & Culture Experiments might get them hooked. Get them composing like Beethoven, Bach and Mozart by creating melodieswith AI. You want them to think about their global footprint? Then the CO2 footprint of food we eat might do the trick. There are also simple, fun ways to engage with art such as the art coloring book or the collaborative puzzle party.
The Google Arts & Culture home page changes daily
The homepage is usually where you start your journey on Google Arts & Culture. It is refreshed daily, so if you find something useful, make it a favorite by clicking on the heart shaped icon. That way you can locate it quickly next time you visit the site and you can share it on Google Classroom, using the share link. You can also do a quick search (magnifying glass, top right hand corner); from apples to zebras, you’re bound to find something of interest.
Whatever the future of teaching holds, educators can be sure that they will find something on Google Arts & Culture to keep their (online) class occupied, no matter what, or where, they are studying.
We hope that these resources will help everyone learn for life, and encourage you to also check out some other resources Google provides – now brought together on our new Learning site– to help everyone in the world learn anything in the world.
Posted by Toni Klopfenstein, Developer Relations Engineer
Today there are over 276 million smart home households globally, and the industry continues to see rapid growth every year. Users have never been more comfortable bringing home new smart home devices — but they also continue to expect more from their devices, and their smart homes. To meet and exceed these expectations, we want to make sure developers have the tools and support to build their best experience across the Google Home app, Nest, Android, and Assistant.
That’s why we’re excited to announce the return of the Google Smart Home Developer Summit on October 21, 2021! This year’s event is free to join, fully virtual and will be hosted on our website with broadcast times available for our developer communities in the AMER, EMEA, and APAC regions.
To kick things off, Michele Turner, Senior Director of Product for Google’s Smart Home Ecosystem, will share our vision for the home and preview upcoming tools and features to build your next devices and apps using Matter and Thread — technologies transforming the industry. This will be followed by a developer keynote to dig deeper into announcements, and a round of technical sessions, workshops, and more, hosted by Google's smart home leaders.
Building the best smart home platform means using trusted technology and intelligence to develop your integrations faster, provide tools to drive your innovation, and allow you new paths to growth. We can’t wait to engage with you and share more about how we can lead and grow the smart home together.
You can register for the Google Smart Home Developer Summit 2021 here, and follow along with the event using the tag #GoogleHomeSummit on social media. We hope to see you there!
When I joined Google as a site reliability engineer in 2018, I wasn’t a typical Noogler. I was 40 years old, seven years sober and starting my first-ever engineering job. At the time, I chose to be transparent to coworkers about my recovery from drugs and alcohol which was critical for my recovery. ThisNational Recovery Month I’m sharing my storyto convey how important finding a supportive community is to sobriety — both at work and outside of it.
I’m thankful to work for a company that supports people like me with compassion and respect. Google shares its commitment to helping all people lead better lives with itsRecover Together website, which includes a searchable map to find nearby recovery groups and support resources for people in recovery and their families.
The Google Recover Together website includes a searchable map to find nearby recovery groups and support resources.
Before coming to Google, I worked as a lawyer. But my life wasn't what you’d imagine for a young attorney building his career. I had a serious alcohol and drug problem that started in high school and continued into my early 30s.
My addiction made me unreliable to my family, friends and employers. This situation played out countless times. At work, my manager would ask me, “What’s wrong? What can I do to help?” I once caused a scene on a business trip and had to go to the hospital for stitches which left me feeling shame and despair. My employer gave me an ultimatum: get help or be let go.
Still, I cycled in and out of rehab and resumed alcohol use multiple times. Eventually, my family had an intervention, and I entered rehab once again. I felt like such a loser being back in the same place as before, feeling like I had learned nothing. In retrospect, I know that setbacks are often a part of recovery. It’s not a moral failing to have to work at sobriety before it sticks. I went back to drinking alcohol once more before I achieved continuous sobriety.
I’ve now been sober since I was 33 years old — a little over 10 years ago. For me, finding a community to support my recovery — from my recovery community and its regular meetings to family and friends and my coworkers at Google — made all the difference.
There’s a safety and an openness at Google that makes it easy for me to get help without feeling bad about it. When I’m around coworkers who are drinking, I’ll let them know why I don’t. After I assuage my coworkers’ concerns about whether their drinking in front of me might upset me (it doesn’t), they’re always quick to offer a non-alcoholic beverage. I remember when my team at Google had an offsite where drinks were served, a teammate quickly pointed my wife and me to the plentiful selection of non-alcoholic drinks.
Nick Arduini in front of Charlies cafe on Google's Mountain View campus, lit purple in support of international recovery day.
That’s not to say things were always easy. Early on, I suffered from imposter syndrome. Unlike other jobs where I felt I couldn’t tell my manager what was going on, at Google I was able to get the support I needed to function effectively at my job and, more importantly, to be happy as a person. A coworker recommended our Employee Assistance Program (EAP) that gave me access to therapy to help manage imposter syndrome. Recently, I was feeling burned out from working from home during the pandemic, and went through another round of therapy through EAP to better manage work-life balance. Through it all, my colleagues have been nothing but supportive. I feel like I landed on the best team in the best company.
I’m not alone in my need for a community to maintain my sobriety. The COVID-19 pandemic has severely impacted those struggling with addiction. The Centers for Disease Control (CDC) reported a 12-month record high of more than 93,000 drug overdose deaths. People with substance use disorders feel more isolated and desperate, and mental health services are strained to meet the demand. In fact in 2020, when Covid-19 restrictions impacted in-person support groups, searches for virtual connections were trending with queries like Alcoholics anonymous (AA) virtual meetings and Narcotics Anonymous (NA) meetings on zoom.
Knowing you’re not alone can help make recovery feel possible. For the more than 23 million Americans living in recovery, I hope they can all find the communities they need to feel supported.
In support of National Recovery Month, Google and YouTube are providing financial and technical support for Recover Out Loud, a livestream event taking place in Las Vegas on September 30. The event features artists and performers who are in recovery, and it’s part of a nationwide recovery initiative supported by iHeart Media and Variety and produced by Mobilize Recovery.
