Monthly Archives: March 2021

Some 22,000 businesses, publishers, and nonprofits in Connecticut used Google products to increase their online presencelast year, generating $6.6 billion in economic activity, according to the tech giant.

Over 210,000 local businesses have connected with customers through Google services, the company said, noting that since 2009 it has awarded over $7 million in grants to nonprofits and other organizations in the state.

In 2020, Google provided $6.8 million in in-kind search advertising credit to Connecticut nonprofits through the Google Ad Grants program. Over 1,100 Connecticut residents have also enrolled in Googles IT Support Certificate programsince its launch in 2018.

A Connected Commerce Council poll, conducted Feb. 12-26, 2021, reported that 97% of U.S.-based small business owners say that digital tools have been helpful in running their business, with 81 percent incorporating new digital tools and strategies due to Covid.

Looking forward, small business owners remain optimistic about the future of their businesses, with 92% believing they will maintain or increase their use of digital tools post pandemic.

As previously reported, Google has also announced plans to invest more than $7 billion and create at least 10,000 new full time Google jobs across the United States this year.

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Google says CT use of its products generated $6.6 billion in economic activity last year - Westfair Online

The dust is slowly starting to settle after Googles announcement in early March that it wont build new ways to track users or support email-based IDs once third-party cookies are phased out in Chrome.

But the industry still has heaps of questions.

Will publisher-provided identifiers (PPIDs) be used on YouTube? Will buyers and sellers be able to use an encrypted pathway to pass hashed emails and/or the other new cookieless IDs being concocted by the industry? Do FLoCs actually solve the privacy problems associated with third-party cookies, or do they just create new ones?

And will Google, despite its claims to the contrary, eventually find a way to continue tracking users across the web as some in the industry believe it will do?

Senior AdExchanger editor Sarah Sluis put these questions and more to Chetna Bindra, Googles group product manager for user, trust, privacy and transparency, during a fireside chat at AdExchangers Innovation Labs: Identity Day event on Tuesday.

Are PPIDs essentially a workaround?

Last week, Google announced plans to expand the use of PPIDs, which are unique identifiers created by publishers based on a first-party cookie or login ID that can then be hashed and passed to buyers through Google Ad Manager.

PPIDs arent new theyve been around since roughly 2013 but theyre potentially newly useful as a way to make first-party cookies shareable with a demand-side platform.

But how does that development make sense in light of Googles assertion that email-based IDs are no bueno?

The difference is the focus on facilitating first-party relationships, Bindra said, and making sure that publishers can continue to use their first-party data to monetize their sites and only their sites through Googles sell-side platforms.

It is something we ensure is kept publisher specific, Bindra said. We are not pooling or enabling pooling to happen across publisher sites [and] as Google we will not be able to read or act on any data that represents a user being tracked across the web.

Good enough for me but what about thee?

Which is fine, but begs the question of whether Google plans to sip its own Kool-Aid and use PPIDs on YouTube.

Technically, the answer is no. Conceptually, though, the answer is yes.

The technology that YouTube uses to monetize via first-party data is not the same technology that underpins PPIDs, but the principle is the same, Bindra said.

It is absolutely consistent with YouTube or any other publisher property that we have where it will primarily be first-party personalized based on that direct relationship with the user, she said.

So, publishers are covered, but can brands connect their first-party data into a PPID?

As long as the data a brand brings to bear is first party, then bring it on.

Googles ad platforms will continue to support advertiser first-party data so that buyers can target users on different sites if those users are also represented within that particular publishers first-party data, Bindra said.

Thats as true for PPIDs as it is for the APIs in the Privacy Sandbox, including FLEDGE, TURTLEDOVE, et al.

Are FLoCs a can of privacy worms?

Speaking of the sandbox, though, big questions remain about one of the most talked about proposals under development Federated Learning of Cohorts and whether its truly a privacy safe replacement for third-party cookie-based behavioral advertising.

The Electronic Frontier Foundation, for example, doesnt think so.

Beyond valid questions as to the efficacy of cohort-based advertising a major topic of debate in the W3Cs Improving Web Advertising Business Group right now one of the biggest concerns about FLoCs is whether the unsupervised machine learning algorithm that will be used to create them could end up grouping users into sensitive categories.

Because its one thing to create a FLoC of auto intenders in a certain geo, and quite another to cluster a group of people based on religion, for example, ethnicity or whether theyre suffering from depression.

According to Bindra, Chrome is very focused on making sure that individuals will not be placed into groups that are deemed sensitive.

There is a lot of testing and technology being developed here before a cohort becomes active, she said.

One option, she said, is for the browser to analyze whether someone is visiting pages related to sensitive topics at a high rate and then, without the browser necessarily knowing what the specific topics are, to prevent the clustering of those people based on those categories.

(What could go wrong?)

Okay, sure, lets trust the machines. But how can people opt out of browser-created FLoCs?

The dialogue about how consent, opt-ins and opt-outs will function in the Privacy Sandbox is still ongoing, Bindra said.

The origin trials that are planned for later this month are focused on ensuring that users are able to opt out of FLoCs, she said. Its still in the early stages to really evaluate what that looks like.

But what about Googles inherent advantages over the rest of the ecosystem, like the fact that its got a proprietary browser that people can log into?

Google has no intention to build or use any type of technology to track individual people as they browse the web, Bindra said, including using the Chrome login which, is not meant to be core to do any of the ad monetization efforts moving forward.

Just to emphasize and underscore it and Jerry Dischler [Googles VP and GM of ads] said it at the IAB [Annual Leadership Meeting] last week, as well: We will not build backdoors, Bindra said. We will not build workarounds for ourselves to continue to track individual people as they browse across the web.

So, once and for all, Google will not support the Unified ID 2.0 initiative?

Bindra had a one-word answer for that one: Correct.

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Innovation Labs: Google's Chetna Bindra Gives The Lowdown On PPIDs, FLoCs And UID - AdExchanger

Google Maps is finally getting dark theme on its Android app for users around the globe.

"What do we want? Dark theme! Where do we want it? Google Maps!," Google wrote in a tweet via its Android handle.

While Google has been testing the dark mode for Google Maps since September last year, the global rollout for Android users has begun now.

To enable the dark theme, all you need to do is tap your profile icon in the top right corner in Google Maps, look for theme settings in the list of configuration options, and then enable the entry that activates the dark mode.

Users need to download the latest version of Android OS, that is, version 10.61.2, to access this feature.

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In addition, Google has also made available the Password Checkup feature for Android handsets.

The company said that the feature is now integrated into Android phones running Android 9 and above.

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Google Maps gets dark theme on its android app for users around the globe - Business Insider India

BELLEVUE, Wash., March 18, 2021 /PRNewswire-PRWeb/ -- Today, Restaurant Revolution Technologies (Revolution) is making it easier to order food directly through Google Search and Google Maps. Through Revolution's innovative digital ordering platform, Order One, supported restaurants will soon see an "Order Online" button appear on their Business Profile on Google.

"Digital food ordering is virtually all about convenience. With Google the ordering process is simplified, and together we provide a greater level of convenience for customers and additional ordering opportunities for our restaurant partners," said Revolution Chief Revenue Officer, Robert Taylor. "With restaurant partners being able to accept orders easily on Google, restaurants can extend their reach with customers and give users alternatives to engage directly with the restaurants."

Jason's Deli is the first Revolution partner available to order directly from Google Search and Google Maps. Orders received from Google leverage Revolution's Order One patented point of sale (POS) integration, so orders will flow directly into the restaurants' POS. Additionally, delivery orders on Google will trigger Order One's Ground Control delivery enablement feature, allowing restaurants to fulfill orders with their own fleet or through one of Revolution's delivery partners.

"Google's direct ordering feature as part of our customer experience optimizes online ordering opportunities for our restaurant operations and also dramatically improves convenience for our customers," said Amy Schuster, Director of IT of Jason's Deli.

For information on Revolution and accepting food orders on Google, visit rrtusa.com.

About Restaurant Revolution Technologies

RRT Holdings, LLC (Revolution) is an industry innovator, multi-patented technology owner and the off-premise partner for restaurants nationwide. Through its Order One platform, Revolution provides a unified web, mobile and voice order management software platform that seamlessly integrates into restaurant point of sale systems. Revolution's Ground Control delivery enablement program fulfilled by DoorDash, backend services, and data capture capabilities enable restaurants to seamlessly serve off-premise orders and provide a premium, branded start-to-finish experience for their customers. The company's marketplace order insertion program, Connect, allows restaurants to seamlessly submit orders from third party marketplaces directly to the POS for optimal operational efficiencies. Learn more at http://www.rrtusa.com or follow on Facebook, Twitter, and LinkedIn.

Media Contact

Rich Earle, Restaurant Revolution Technologies, Inc., 619-384-6042, rearle@rrtusa.com

Rich Earle, Restaurant Revolution Technologies, 800-277-1049, marketing@rrtusa.com

SOURCE Restaurant Revolution Technologies, Inc.

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Restaurant Revolution Technologies Expands Its Online Ordering Capabilities with Google - KHQ Right Now

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A 2020 womens leadership study from LeanIn.org and McKinsey & Co. found that American women held less than40% of corporate management positions, and women continue to fight underrepresentation when it comes toboard positions and CEO roles. They also face gender bias, harassment, and opposition to their management styles. Heres how one MIT Sloan alumna has pushed back on those statistics and used what shes learned along the way to help those behind her.

Anita Kibunguchy, MBA 15, product marketing lead at Google

In what ways is your professional life as a woman in the workplace different from how you imagined it would be when you started your career?

I always knew going into tech that there would be very few of us, especially Black women. When I did my undergrad at Sacramento State, my management information systems classes had three women, and we all knew each other, hung out together, and did most of our projects together. In the class, I was the only Black person. MIT was a similar experience, too. Yes, the classes were diverse, but in my MIT Sloan cohort, I was the only Black person. I don't think I expected the workplace to be any different. All I can hope for is that we continue doing more to hire and retain diverse talent, because diversity does bring upon creativity and is simply better for business overall.

Who was an ally or mentor for you as youve navigated your career? What made that person stand out, and how specifically did they help you get to the next level of your professional development?

I've been lucky to have mentors all along from when I was young. My mother and grandmother are incredible, strong women who I look up to every day. My dad instilled truthfulness he always said that the truth shall set you free.

Over time, I've met incredible people who've taken a chance on me. I've also had allies who've given me opportunities to grow, take on leadership positions, and let me be me. Most recently, two of my male, white bosses have come through for me, letting me lead a team and giving me the resources to do so. I am truly appreciative, because this is an opportunity of a lifetime, and not everyone is lucky to say so.

Certain industries are as male-dominated as ever. Where do you see progress in your own professional experience and how can we scale that throughout your industry?

With all the Black Lives Matter and other movements that took place in 2020, it was the first time you saw big tech companies really come out and make their voices heard about what was happening. All I can say is that it felt like a wake-up call, because people have been speaking of these injustices for a very long time.In the workplace, progress will come when we can hire diverse candidates and put structures in place to help them succeed and really soar. People always think it's only a talent issue, but it's more than that. Retention plays abigrole. Because once you retain folks, then others see them at these workplaces and choose to join them. People want to go where they see others like them and where they feel like they belong. Otherwise, you're the token representative, and that is a huge burden to carry.

Progress will come when we can hire diverse candidates and put structures in place to help them succeed and really soar.

How do you support women coming up behind you?

Mentorship is one of the biggest gifts you can give someone coming up behind you. I have been lucky to help many people along the way. Because of this, I started a career advice services company called AdviceMavens whoseaim is to connect, cultivate, and empower the community to advance their professional careers and personal lives. We believe that each one of us has something to give back to the community, whether from personal, educational, and/or professional experiences. I work with a lot of people to help guide them through resume, LinkedIn, and cover letter writing, as well as interview prep services.

What is the most difficult lesson youve learned in your professional life? In what unexpected ways did you grow from it?

Trust is a two-way street. Ive seen this manifest itself in both my personal and professional life. It helps foster a common understanding and you will see teammates and bosses go above and beyond to get things done once trust is built. It also helps foster psychological safety, which is a big ingredient for successful teams. I learned this lesson the hard way a few years ago, and now with the teams I lead, I try to ensure we have trust built between us, including the bosses I report to.

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This Google marketing pro sees diversity as a retention issue - MIT Sloan News

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Hundreds of people gathered for the first lecture at what had become the worlds most important conference on artificial intelligence row after row of faces. Some were East Asian, a few were Indian, and a few were women. But the vast majority were white men. More than 5,500 people attended the meeting, five years ago in Barcelona, Spain.

Timnit Gebru, then a graduate student at Stanford University, remembers counting only six Black people other than herself, all of whom she knew, all of whom were men.

The homogeneous crowd crystallized for her a glaring issue. The big thinkers of tech say A.I. is the future. It will underpin everything from search engines and email to the software that drives our cars, directs the policing of our streets and helps create our vaccines.

But it is being built in a way that replicates the biases of the almost entirely male, predominantly white work force making it.

In the nearly 10 years Ive written about artificial intelligence, two things have remained a constant: The technology relentlessly improves in fits and sudden, great leaps forward. And bias is a thread that subtly weaves through that work in a way that tech companies are reluctant to acknowledge.

On her first night home in Menlo Park, Calif., after the Barcelona conference, sitting cross-legged on the couch with her laptop, Dr. Gebru described the A.I. work force conundrum in a Facebook post.

Im not worried about machines taking over the world. Im worried about groupthink, insularity and arrogance in the A.I. community especially with the current hype and demand for people in the field, she wrote. The people creating the technology are a big part of the system. If many are actively excluded from its creation, this technology will benefit a few while harming a great many.

The A.I. community buzzed about the mini-manifesto. Soon after, Dr. Gebru helped create a new organization, Black in A.I. After finishing her Ph.D., she was hired by Google.

She teamed with Margaret Mitchell, who was building a group inside Google dedicated to ethical A.I. Dr. Mitchell had previously worked in the research lab at Microsoft. She had grabbed attention when she told Bloomberg News in 2016 that A.I. suffered from a sea of dudes problem. She estimated that she had worked with hundreds of men over the previous five years and about 10 women.

Their work was hailed as groundbreaking. The nascent A.I. industry, it had become clear, needed minders and people with different perspectives.

About six years ago, A.I. in a Google online photo service organized photos of Black people into a folder called gorillas. Four years ago, a researcher at a New York start-up noticed that the A.I. system she was working on was egregiously biased against Black people. Not long after, a Black researcher in Boston discovered that an A.I. system couldnt identify her face until she put on a white mask.

In 2018, when I told Googles public relations staff that I was working on a book about artificial intelligence, it arranged a long talk with Dr. Mitchell to discuss her work. As she described how she built the companys Ethical A.I. team and brought Dr. Gebru into the fold it was refreshing to hear from someone so closely focused on the bias problem.

But nearly three years later, Dr. Gebru was pushed out of the company without a clear explanation. She said she had been fired after criticizing Googles approach to minority hiring and, with a research paper, highlighting the harmful biases in the A.I. systems that underpin Googles search engine and other services.

Your life starts getting worse when you start advocating for underrepresented people, Dr. Gebru said in an email before her firing. You start making the other leaders upset.

As Dr. Mitchell defended Dr. Gebru, the company removed her, too. She had searched through her own Google email account for material that would support their position and forwarded emails to another account, which somehow got her into trouble. Google declined to comment for this article.

Their departure became a point of contention for A.I. researchers and other tech workers. Some saw a giant company no longer willing to listen, too eager to get technology out the door without considering its implications. I saw an old problem part technological and part sociological finally breaking into the open.

It should have been a wake-up call.

In June 2015, a friend sent Jacky Alcin, a 22-year-old software engineer living in Brooklyn, an internet link for snapshots the friend had posted to the new Google Photos service. Google Photos could analyze snapshots and automatically sort them into digital folders based on what was pictured. One folder might be dogs, another birthday party.

When Mr. Alcin clicked on the link, he noticed one of the folders was labeled gorillas. That made no sense to him, so he opened the folder. He found more than 80 photos he had taken nearly a year earlier of a friend during a concert in nearby Prospect Park. That friend was Black.

He might have let it go if Google had mistakenly tagged just one photo. But 80? He posted a screenshot on Twitter. Google Photos, yall, messed up, he wrote, using much saltier language. My friend is not a gorilla.

Like facial recognition services, talking digital assistants and conversational chatbots, Google Photos relied on an A.I. system that learned its skills by analyzing enormous amounts of digital data.

Called a neural network, this mathematical system could learn tasks that engineers could never code into a machine on their own. By analyzing thousands of photos of gorillas, it could learn to recognize a gorilla. It was also capable of egregious mistakes. The onus was on engineers to choose the right data when training these mathematical systems. (In this case, the easiest fix was to eliminate gorilla as a photo category.)

As a software engineer, Mr. Alcin understood the problem. He compared it to making lasagna. If you mess up the lasagna ingredients early, the whole thing is ruined, he said. It is the same thing with A.I. You have to be very intentional about what you put into it. Otherwise, it is very difficult to undo.

In 2017, Deborah Raji, a 21-year-old Black woman from Ottawa, sat at a desk inside the New York offices of Clarifai, the start-up where she was working. The company built technology that could automatically recognize objects in digital images and planned to sell it to businesses, police departments and government agencies.

She stared at a screen filled with faces images the company used to train its facial recognition software.

As she scrolled through page after page of these faces, she realized that most more than 80 percent were of white people. More than 70 percent of those white people were male. When Clarifai trained its system on this data, it might do a decent job of recognizing white people, Ms. Raji thought, but it would fail miserably with people of color, and probably women, too.

Clarifai was also building a content moderation system, a tool that could automatically identify and remove pornography from images people posted to social networks. The company trained this system on two sets of data: thousands of photos pulled from online pornography sites, and thousands of Grated images bought from stock photo services.

The system was supposed to learn the difference between the pornographic and the anodyne. The problem was that the Grated images were dominated by white people, and the pornography was not. The system was learning to identify Black people as pornographic.

The data we use to train these systems matters, Ms. Raji said. We cant just blindly pick our sources.

This was obvious to her, but to the rest of the company it was not. Because the people choosing the training data were mostly white men, they didnt realize their data was biased.

The issue of bias in facial recognition technologies is an evolving and important topic, Clarifais chief executive, Matt Zeiler, said in a statement. Measuring bias, he said, is an important step.

Before joining Google, Dr. Gebru collaborated on a study with a young computer scientist, Joy Buolamwini. A graduate student at the Massachusetts Institute of Technology, Ms. Buolamwini, who is Black, came from a family of academics. Her grandfather specialized in medicinal chemistry, and so did her father.

She gravitated toward facial recognition technology. Other researchers believed it was reaching maturity, but when she used it, she knew it wasnt.

In October 2016, a friend invited her for a night out in Boston with several other women. Well do masks, the friend said. Her friend meant skin care masks at a spa, but Ms. Buolamwini assumed Halloween masks. So she carried a white plastic Halloween mask to her office that morning.

It was still sitting on her desk a few days later as she struggled to finish a project for one of her classes. She was trying to get a detection system to track her face. No matter what she did, she couldnt quite get it to work.

In her frustration, she picked up the white mask from her desk and pulled it over her head. Before it was all the way on, the system recognized her face or, at least, it recognized the mask.

Black Skin, White Masks, she said in an interview, nodding to the 1952 critique of historical racism from the psychiatrist Frantz Fanon. The metaphor becomes the truth. You have to fit a norm, and that norm is not you.

Ms. Buolamwini started exploring commercial services designed to analyze faces and identify characteristics like age and sex, including tools from Microsoft and IBM.

She found that when the services read photos of lighter-skinned men, they misidentified sex about 1 percent of the time. But the darker the skin in the photo, the larger the error rate. It rose particularly high with images of women with dark skin. Microsofts error rate was about 21 percent. IBMs was 35.

Published in the winter of 2018, the study drove a backlash against facial recognition technology and, particularly, its use in law enforcement. Microsofts chief legal officer said the company had turned down sales to law enforcement when there was concern the technology could unreasonably infringe on peoples rights, and he made a public call for government regulation.

Twelve months later, Microsoft backed a bill in Washington State that would require notices to be posted in public places using facial recognition and ensure that government agencies obtained a court order when looking for specific people. The bill passed, and it takes effect later this year. The company, which did not respond to a request for comment for this article, did not back other legislation that would have provided stronger protections.

Ms. Buolamwini began to collaborate with Ms. Raji, who moved to M.I.T. They started testing facial recognition technology from a third American tech giant: Amazon. The company had started to market its technology to police departments and government agencies under the name Amazon Rekognition.

Ms. Buolamwini and Ms. Raji published a study showing that an Amazon face service also had trouble identifying the sex of female and darker-skinned faces. According to the study, the service mistook women for men 19 percent of the time and misidentified darker-skinned women for men 31 percent of the time. For lighter-skinned males, the error rate was zero.

Amazon called for government regulation of facial recognition. It also attacked the researchers in private emails and public blog posts.

The answer to anxieties over new technology is not to run tests inconsistent with how the service is designed to be used, and to amplify the tests false and misleading conclusions through the news media, an Amazon executive, Matt Wood, wrote in a blog post that disputed the study and a New York Times article that described it.

In an open letter, Dr. Mitchell and Dr. Gebru rejected Amazons argument and called on it to stop selling to law enforcement. The letter was signed by 25 artificial intelligence researchers from Google, Microsoft and academia.

Last June, Amazon backed down. It announced that it would not let the police use its technology for at least a year, saying it wanted to give Congress time to create rules for the ethical use of the technology. Congress has yet to take up the issue. Amazon declined to comment for this article.

Dr. Gebru and Dr. Mitchell had less success fighting for change inside their own company. Corporate gatekeepers at Google were heading them off with a new review system that had lawyers and even communications staff vetting research papers.

Dr. Gebrus dismissal in December stemmed, she said, from the companys treatment of a research paper she wrote alongside six other researchers, including Dr. Mitchell and three others at Google. The paper discussed ways that a new type of language technology, including a system built by Google that underpins its search engine, can show bias against women and people of color.

After she submitted the paper to an academic conference, Dr. Gebru said, a Google manager demanded that she either retract the paper or remove the names of Google employees. She said she would resign if the company could not tell her why it wanted her to retract the paper and answer other concerns.

The response: Her resignation was accepted immediately, and Google revoked her access to company email and other services. A month later, it removed Dr. Mitchells access after she searched through her own email in an effort to defend Dr. Gebru.

In a Google staff meeting last month, just after the company fired Dr. Mitchell, the head of the Google A.I. lab, Jeff Dean, said the company would create strict rules meant to limit its review of sensitive research papers. He also defended the reviews. He declined to discuss the details of Dr. Mitchells dismissal but said she had violated the companys code of conduct and security policies.

One of Mr. Deans new lieutenants, Zoubin Ghahramani, said the company must be willing to tackle hard issues. There are uncomfortable things that responsible A.I. will inevitably bring up, he said. We need to be comfortable with that discomfort.

But it will be difficult for Google to regain trust both inside the company and out.

They think they can get away with firing these people and it will not hurt them in the end, but they are absolutely shooting themselves in the foot, said Alex Hanna, a longtime part of Googles 10-member Ethical A.I. team. What they have done is incredibly myopic.

Cade Metz is a technology correspondent at The Times and the author of Genius Makers: The Mavericks Who Brought A.I. to Google, Facebook, and the World, from which this article is adapted.

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Who Is Making Sure the A.I. Machines Arent Racist? - The New York Times

OnePlus Watch won't come with Google's Wear OS and will run on a custom operating system, OnePlus Co-Founder and CEO Pete Lau confirmed on the company's forum. The anticipated smartwatch was initially speculated to run Wear OS. The company, however, appears to have preferred its custom solution for better power efficiency. The OnePlus Watch is also teased to have a burdenless design and offer seamless connectivity with other OnePlus devices. It will debut alongside the OnePlus 9 series on March 23.

Pete Lau said that instead of running Wear OS by Google, the OnePlus Watch will feature a smart wear operating system that was developed based on a real-time operating system (RTOS). [W]e believe it provides you a smooth and reliable experience while offering a great battery life, covering some of the biggest concerns we've been hearing from people looking to buy a smartwatch, he said while responding to a user on OnePlus Community forums.

In December, Lau said that OnePlus was working with Google to bring improvements including better interoperability to Wear OS. He, however, didn't explicitly mention any details about the presence of Google's operating system on the OnePlus Watch.

Lau took to the OnePlus Community forums to reveal some information about the OnePlus Watch. He said that the smartwatch comes with a stunning and burdenless design that makes it a distinct option in the market. He also highlighted seamless connectivity with OnePlus smartphones, audio peripherals, smart wearables, and OnePlus TVs. This will help users control connected devices directly from their wrist similar to how you can control music or attend voice calls using an Apple Watch.

Our priority for devices that are part of the OnePlus ecosystem is to offer fashionable designs, provide seamless connectivity and deliver a best-in-class user experience. And the new OnePlus Watch is no exception, Lau said.

The OnePlus Watch is also teased to have a best-in-class experience at an affordable price.

The OnePlus Watch is set to arrive alongside the OnePlus 9 series on March 23. It is rumoured to have an IP68-certified build, Warp Charge fast charging support, and built-in heart rate and SpO2 monitoring.

Alongside the OnePlus Watch, OnePlus is speculated to have a top-end OnePlus Watch RX in the works. The latter could run on Wear OS by Google or a tweaked Android version.

Is OnePlus 8T the best 'value flagship' of 2020? We discussed this on Orbital, our weekly technology podcast, which you can subscribe to via Apple Podcasts, Google Podcasts, or RSS, download the episode, or just hit the play button below.

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OnePlus Watch Wont Run on Wear OS by Google, Will Feature Burdenless Design - Gadgets 360