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Assent Compliance, a company that helps large manufacturers like GE and Rolls Royce manage complex supply chains through an online data exchange, announced a new tool this week that lets any company, whether they’re a customer or not, upload bills of materials and see on a map where COVID-19 is having an impact on their supply chain.
Company co-founder Matt Whitteker, says the Ottawa startup focuses on supply chain data management, which means it has the data and the tooling to develop a data-driven supply chain map based on WHO data identifying COVID hotspots. He believes that his is the only company to have done this.
“We’re the only ones that have taken supply chain data and applied it to this particular pandemic. And it’s something that’s really native to our platform. We have all that data on hand — we have location data for suppliers. So it’s just a matter of applying that with third-party data sources (like the WHO data), and then extracting valuable business intelligence from it,” he said.
If you want to participate, you simply go to the company website and fill out a form. A customer success employee will contact you and walk you through the process of uploading your data to the platform. Once they have your data, they generate a map showing the parts of the world where your supply chain is most likely to be disrupted, identifying the level of risk based on your individual data.

The company captures supply chain data as part of the act of doing business with 1,000 customers and 500,000 suppliers currently on their platform. “When companies are manufacturing products they have what’s called a bill of materials, kind of like a recipe. And companies upload their bill of materials that basically outlines all their parts, components and commodities, and who they get them from, which basically represents their supply chain,” Whitteker explained.
After the company uploads the bill of materials, Assent opens a portal for the companies to exchange data, which might be tax forms, proof of sourcing or any kind of information and documentation the manufacturer needs to comply with legal and regulatory rules around procurement of a given part.
They decided to start building the COVID-19 map application when they recognized that this was going to have the biggest supply chain disruption the world has seen since World War II. It took about a month to build it. It went into beta last week with customers and over 350 signed up in the first two hours. This week, they made the tool generally available to anyone, even non-customers, for free.
The company was founded in 2016 and has raised $220 million, according to Whitteker.
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Data management company Datastax, one of the largest contributors to the Apache Cassandra project, today announced that it has acquired The Last Pickle (and no, I don’t know what’s up with that name either), a New Zealand-based Cassandra consulting and services firm that’s behind a number of popular open-source tools for the distributed NoSQL database.
As Datastax Chief Strategy Officer Sam Ramji, who you may remember from his recent tenure at Apigee, the Cloud Foundry Foundation, Google and Autodesk, told me, The Last Pickle is one of the premier Apache Cassandra consulting and services companies. The team there has been building Cassandra-based open source solutions for the likes of Spotify, T Mobile and AT&T since it was founded back in 2012. And while The Last Pickle is based in New Zealand, the company has engineers all over the world that do the heavy lifting and help these companies successfully implement the Cassandra database technology.
It’s worth mentioning that Last Pickle CEO Aaron Morton first discovered Cassandra when he worked for WETA Digital on the special effects for Avatar, where the team used Cassandra to allow the VFX artists to store their data.
“There’s two parts to what they do,” Ramji explained. “One is the very visible consulting, which has led them to become world experts in the operation of Cassandra. So as we automate Cassandra and as we improve the operability of the project with enterprises, their embodied wisdom about how to operate and scale Apache Cassandra is as good as it gets — the best in the world.” And The Last Pickle’s experience in building systems with tens of thousands of nodes — and the challenges that its customers face — is something Datastax can then offer to its customers as well.
And Datastax, of course, also plans to productize The Last Pickle’s open-source tools like the automated repair tool Reaper and the Medusa backup and restore system.
As both Ramji and Datastax VP of Engineering Josh McKenzie stressed, Cassandra has seen a lot of commercial development in recent years, with the likes of AWS now offering a managed Cassandra service, for example, but there wasn’t all that much hype around the project anymore. But they argue that’s a good thing. Now that it is over ten years old, Cassandra has been battle-hardened. For the last ten years, Ramji argues, the industry tried to figure out what the de factor standard for scale-out computing should be. By 2019, it became clear that Kubernetes was the answer to that.
“This next decade is about what is the de facto standard for scale-out data? We think that’s got certain affordances, certain structural needs and we think that the decades that Cassandra has spent getting harden puts it in a position to be data for that wave.”
McKenzie also noted that Cassandra provides users with a number of built-in features like support for mutiple data centers and geo-replication, rolling updates and live scaling, as well as wide support across programming languages, give it a number of advantages over competing databases.
“It’s easy to forget how much Cassandra gives you for free just based on its architecture,” he said. “Losing the power in an entire datacenter, upgrading the version of the database, hardware failing every day? No problem. The cluster is 100 percent always still up and available. The tooling and expertise of The Last Pickle really help bring all this distributed and resilient power into the hands of the masses.”
The two companies did not disclose the price of the acquisition.
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App Annie, a go-to source for mobile app market data and analytics, is expanding its platform with the acquisition of mobile analytics provider Libring. The deal will allow App Annie to present its mobile app market data side by side with advertising analytics data in order to paint a more complete picture of an app’s performance and revenue.
Already, App Annie customers leverage its platform to track key metrics related to their app’s growth and usage, like downloads, active users, retention numbers, demographics, rankings, reviews, competitive analysis and more. But the company said it heard from publishers and brands how it’s still difficult to analyze their user acquisition efforts, including their ad spend and related costs.
With the addition of Libring, App Annie is integrating adtech insights into its platform.
This includes the ability to combine the ad spend and monetization insights from more than 325 data sources, including Supply Side Platforms (SSPs), Demand Side Platforms (DSPs), app stores and analytics platforms.
This data is then presented in a single dashboard so it’s easier to understand critical metrics — like the customer acquisition cost, the lifetime value, the return on ad spend and the return on investment.
It’s ideal for larger organizations that have outgrown the spreadsheet, as it’s been sort of the App Annie of revenue aggregation, so to speak.
“The most successful companies find a way to capitalize on mobile, yet they have been struggling to maximize its value to their business,” explained App Annie CEO Ted Krantz, in a statement about the acquisition. “Today, this requires custom work to stitch together multiple point solutions, spreadsheets, business intelligence teams, agencies and consultants. We are committed to solving this by applying data science and machine learning to automate these composite metrics for brands and publishers,” he said.
The deal comes at a time when mobile ad spend is continuing to grow rapidly — it’s expected to double to $375 billion globally by 2022, the company noted. It’s now a massive part of the overall app industry, at triple the amount of consumer spending on the app stores.
As a result of the deal, Libring’s 30-plus employees are joining App Annie.
In the near-term, Libring’s current customers will continue to use its product as they do today.
But App Annie tells us there’s only some overlap between the two companies’ respective customer bases. For now, App Annie will work with its customers who want to purchase the new analytics service and find out what sort of enhancements they are looking for in an analytics solution. Libring’s customers can also purchase App Annie’s analytics, if they choose.
Later, App Annie will migrate the Libring backend to the same infrastructure provider the rest of App Annie uses, and will then integrate the front-end so customers can log in and visualize the new analytics and other market data together. More information about how this will all work will be shared when those tools are closer to being available, which is still several months from now.
Going forward, App Annie says its data science team will also offer predictive and prescriptive insights based on the new data.
According to Libring’s website, its customers included SEGA, Slickdeals, Reddit, Jam City, Wooga, EA, Zynga, Next Games, Meet Me, GameInsight, Deviant Art, Webedia, Ubisoft, theChive, saambaa, badoo, textnow and others.
App Annie declined to disclose the deal terms.
Related to the changes and expansion, App Annie also today introduced a new brand that features a gem logomark. The gem is meant to be a tribute to mobile gaming and the idea of “leveling up” while also a reflection of the value of actionable data, the company says.

The acquisition comes on the heels of several notable milestones for App Annie, including the launch of a product development testing ground, App Annie Labs; plus the addition of mobile web analytics in March — the same time when App Annie passed $100 million in annual recurring revenue.
The company is soliciting feedback about its plans for Libring and will post updates about the project on App Annie Labs, it says.
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TikTok is being investigated in the U.K. for how it handles the safety and personal data of underage users. According to The Guardian, information commissioner Elizabeth Denham told a parliamentary committee that the probe started in February after the U.S. Federal Trade Commission levied a $5.7 million fine against TikTok for breaking children’s privacy law.
Denham told The Guardian that the commission is examining how TikTok collects private data and has concerns about the open messaging system, which may allow adult users to contact children. “We are looking at the transparency tools for children. We’re looking at the messaging system, which is completely open, we’re looking at the kind of videos that are collected and shared by children online. We do have an active investigation into TikTok right now, so watch this space,” she said.
The investigation will also examine if the popular app, owned by ByteDance, violates the General Data Protection Regulation (GDPR), which requires companies to put special protections in place for underage users and provide them with different services than adults.
The FTC’s investigation, which began when TikTok was still known as Musical.ly, ruled that the app broke the Children’s Online Privacy Protection Act by failing to seek parental consent before collecting names, email addresses and other personal information from users under 13. The ruling resulted in an age gate being added to an app that prevents users under 13 from filming and posting videos on it.
ByteDance, the Chinese media startup now valued at $75 billion, told The Guardian in a statement that “We cooperate with organizations such as the ICO to provide relevant information about our product to support their work. Ensuring data protection principles are upheld is a top priority for TikTok.”
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Fungible, a startup that wants to help data centers cope with the increasingly massive amounts of data produced by new technologies, has raised a $200 million Series C led by SoftBank Vision Fund, with participation from Norwest Venture Partners and its existing investors. As part of the round, SoftBank Investment Advisers senior managing partner Deep Nishar will join Fungible’s board of directors.
Founded in 2015, Fungible now counts about 200 employees and has raised more than $300 million in total funding. Its other investors include Battery Ventures, Mayfield Fund, Redline Capital and Walden Riverwood Ventures. Its new capital will be used to speed up product development. The company’s founders, CEO Pradeep Sindhu and Bertrand Serlet, say Fungible will release more information later this year about when its data processing units will be available and their on-boarding process, which they say will not require clients to change their existing applications, networking or server design.
Sindu previously founded Juniper Networks, where he held roles as chief scientist and CEO. Serlet was senior vice president of software engineering at Apple before leaving in 2011 and founding Upthere, a storage startup that was acquired by Western Digital in 2017. Sindu and Serlet describe Fungible’s objective as pivoting data centers from a “compute-centric” model to a data-centric one. While the company is often asked if they consider Intel and Nvidia competitors, they say Fungible Data Processing Units (DPU) complement tech, including central and graphics processing units, from other chip makers.
Sindhu describes Fungible’s DPUs as a new building block in data center infrastructure, allowing them to handle larger amounts of data more efficiently and also potentially enabling new kinds of applications. Its DPUs are fully programmable and connect with standard IPs over Ethernet local area networks and local buses, like the PCI Express, that in turn connect to CPUs, GPUs and storage. Placed between the two, the DPUs act like a “super-charged data traffic controller,” performing computations offloaded by the CPUs and GPUs, as well as converting the IP connection into high-speed data center fabric.
This better prepares data centers for the enormous amounts of data generated by new technology, including self-driving cars, and industries such as personalized healthcare, financial services, cloud gaming, agriculture, call centers and manufacturing, says Sindu.
In a press statement, Nishar said “As the global data explosion and AI revolution unfold, global computing, storage and networking infrastructure are undergoing a fundamental transformation. Fungible’s products enable data centers to leverage their existing hardware infrastructure and benefit from these new technology paradigms. We look forward to partnering with the company’s visionary and accomplished management team as they power the next generation of data centers.”
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Back in the 2010 timeframe, it was common to say that content was king, but after watching Google buy Looker for $2.6 billion last week and Salesforce nab Tableau for $15.7 billion this morning, it’s clear that data has ascended to the throne in a business context.
We have been hearing about Big Data for years, but we’ve probably reached a point in 2019 where the data onslaught is really having an impact on business. If you can find the key data nuggets in the big data pile, it can clearly be a competitive advantage, and companies like Google and Salesforce are pulling out their checkbooks to make sure they are in a position to help you out.
While Google, as a cloud infrastructure vendor, is trying to help companies on its platform and across the cloud understand and visualize all that data, Salesforce as a SaaS vendor might have a different reason — one that might surprise you — given that Salesforce was born in the cloud. But perhaps it recognizes something fundamental. If it truly wants to own the enterprise, it has to have a hybrid story, and with Mulesoft and Tableau, that’s precisely what it has — and why it was willing to spend around $23 billion to get it.
Certainly, Salesforce chairman Marc Benioff has no trouble seeing the connections between his two big purchases over the last year. He sees the combination of Mulesoft connecting to the data sources and Tableau providing a way to visualize as a “beautiful thing.”
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Couchbase, the company behind the eponymous NoSQL database, announced a major update to its mobile database today that brings some machine learning smarts, as well as improved synchronization features and enhanced stats and logging support, to the software.
“We’ve led the innovation and data management at the edge since the release of our mobile database five years ago,” Couchbase’s VP of Engineering Wayne Carter told me. “And we’re excited that others are doing that now. We feel that it’s very, very important for businesses to be able to utilize these emerging technologies that do sit on the edge to drive their businesses forward, and both making their employees more effective and their customer experience better.”
The latter part is what drove a lot of today’s updates, Carter noted. He also believes that the database is the right place to do some machine learning. So with this release, the company is adding predictive queries to its mobile database. This new API allows mobile apps to take pre-trained machine learning models and run predictive queries against the data that is stored locally. This would allow a retailer to create a tool that can use a phone’s camera to figure out what part a customer is looking for.
To support these predictive queries, Couchbase mobile is also getting support for predictive indexes. “Predictive indexes allow you to create an index on prediction, enabling correlation of real-time predictions with application data in milliseconds,” Carter said. In many ways, that’s also the unique value proposition for bringing machine learning into the database. “What you really need to do is you need to utilize the unique values of a database to be able to deliver the answer to those real-time questions within milliseconds,” explained Carter.
The other major new feature in this release is delta synchronization, which allows businesses to push far smaller updates to the databases on their employees’ mobile devices. That’s because they only have to receive the information that changed instead of a full updated database. Carter says this was a highly requested feature, but until now, the company always had to prioritize work on other components of Couchbase.
This is an especially useful feature for the company’s retail customers, a vertical where it has been quite successful. These users need to keep their catalogs up to data and quite a few of them supply their employees with mobile devices to help shoppers. Rumor has it that Apple, too, is a Couchbase user.
The update also includes a few new features that will be more of interest to operators, including advanced stats reporting and enhanced logging support.
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Like virtually every big enterprise company, a few years ago, the German auto giant Daimler decided to invest in its own on-premises data centers. And while those aren’t going away anytime soon, the company today announced that it has successfully moved its on-premises big data platform to Microsoft’s Azure cloud. This new platform, which the company calls eXtollo, is Daimler’s first major service to run outside of its own data centers, though it’ll probably not be the last.
As Daimler’s head of its corporate center of excellence for advanced analytics and big data Guido Vetter told me, the company started getting interested in big data about five years ago. “We invested in technology — the classical way, on-premise — and got a couple of people on it. And we were investigating what we could do with data because data is transforming our whole business as well,” he said.
By 2016, the size of the organization had grown to the point where a more formal structure was needed to enable the company to handle its data at a global scale. At the time, the buzz phrase was “data lakes” and the company started building its own in order to build out its analytics capacities.
Electric lineup, Daimler AG
“Sooner or later, we hit the limits as it’s not our core business to run these big environments,” Vetter said. “Flexibility and scalability are what you need for AI and advanced analytics and our whole operations are not set up for that. Our backend operations are set up for keeping a plant running and keeping everything safe and secure.” But in this new world of enterprise IT, companies need to be able to be flexible and experiment — and, if necessary, throw out failed experiments quickly.
So about a year and a half ago, Vetter’s team started the eXtollo project to bring all the company’s activities around advanced analytics, big data and artificial intelligence into the Azure Cloud, and just over two weeks ago, the team shut down its last on-premises servers after slowly turning on its solutions in Microsoft’s data centers in Europe, the U.S. and Asia. All in all, the actual transition between the on-premises data centers and the Azure cloud took about nine months. That may not seem fast, but for an enterprise project like this, that’s about as fast as it gets (and for a while, it fed all new data into both its on-premises data lake and Azure).
If you work for a startup, then all of this probably doesn’t seem like a big deal, but for a more traditional enterprise like Daimler, even just giving up control over the physical hardware where your data resides was a major culture change and something that took quite a bit of convincing. In the end, the solution came down to encryption.
“We needed the means to secure the data in the Microsoft data center with our own means that ensure that only we have access to the raw data and work with the data,” explained Vetter. In the end, the company decided to use the Azure Key Vault to manage and rotate its encryption keys. Indeed, Vetter noted that knowing that the company had full control over its own data was what allowed this project to move forward.
Vetter tells me the company obviously looked at Microsoft’s competitors as well, but he noted that his team didn’t find a compelling offer from other vendors in terms of functionality and the security features that it needed.
Today, Daimler’s big data unit uses tools like HD Insights and Azure Databricks, which covers more than 90 percents of the company’s current use cases. In the future, Vetter also wants to make it easier for less experienced users to use self-service tools to launch AI and analytics services.
While cost is often a factor that counts against the cloud, because renting server capacity isn’t cheap, Vetter argues that this move will actually save the company money and that storage costs, especially, are going to be cheaper in the cloud than in its on-premises data center (and chances are that Daimler, given its size and prestige as a customer, isn’t exactly paying the same rack rate that others are paying for the Azure services).
As with so many big data AI projects, predictions are the focus of much of what Daimler is doing. That may mean looking at a car’s data and error code and helping the technician diagnose an issue or doing predictive maintenance on a commercial vehicle. Interestingly, the company isn’t currently bringing to the cloud any of its own IoT data from its plants. That’s all managed in the company’s on-premises data centers because it wants to avoid the risk of having to shut down a plant because its tools lost the connection to a data center, for example.
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I remember watching MIT professor Andrew McAfee years ago telling stories about the importance of data over gut feeling, whether it was predicting successful wines or making sound business decisions. We have been hearing about big data and data-driven decision making for so long, you would think it has become hardened into our largest organizations by now. As it turns out, new research by NewVantage Partners finds that most large companies are having problems implementing an organization-wide, data-driven strategy.
McAfee was fond of saying that before the data deluge we have today, the way most large organizations made decisions was via the HiPPO — the highest paid person’s opinion. Then he would chide the audience that this was not the proper way to run your business. Data, not gut feelings, even those based on experience, should drive important organizational decisions.
While companies haven’t failed to recognize McAfee’s advice, the NVP report suggests they are having problems implementing data-driven decision making across organizations. There are plenty of technological solutions out there today to help them, from startups all the way to the largest enterprise vendors, but the data (see, you always need to go back to the data) suggests that it’s not a technology problem, it’s a people problem.
Executives can have farsighted vision that their organizations need to be data-driven. They can acquire all of the latest solutions to bring data to the forefront, but unless they combine that with a broad cultural shift and a deep understanding of how to use that data inside business processes, they will continue to struggle.
The study’s authors, Randy Bean and Thomas H. Davenport, wrote about the people problem in their study’s executive summary. “We hear little about initiatives devoted to changing human attitudes and behaviors around data. Unless the focus shifts to these types of activities, we are likely to see the same problem areas in the future that we’ve observed year after year in this survey.”
The survey found that 72 percent of respondents have failed in this regard, reporting they haven’t been able to create a data-driven culture, whatever that means to individual respondents. Meanwhile, 69 percent reported they had failed to create a data-driven organization, although it would seem that these two metrics would be closely aligned.
Perhaps most discouraging of all is that the data is trending the wrong way. Over the last several years, the report’s authors say that those organizations calling themselves data-driven has actually dropped each year from 37.1 percent in 2017 to 32.4 percent in 2018 to 31.0 percent in the latest survey.
This matters on so many levels, but consider that as companies shift to artificial intelligence and machine learning, these technologies rely on abundant amounts of data to work effectively. What’s more, every organization, regardless of its size, is generating vast amounts of data, simply as part of being a digital business in the 21st century. They need to find a way to control this data to make better decisions and understand their customers better. It’s essential.
There is so much talk about innovation and disruption, and understanding and affecting company culture, but so much of all this is linked. You need to be more agile. You need to be more digital. You need to be transformational. You need to be all of these things — and data is at the center of all of it.
Data has been called the new oil often enough to be cliché, but these results reveal that the lesson is failing to get through. Companies need to be data-driven now, this instant. This isn’t something to be working toward at this point. This is something you need to be doing, unless your ultimate goal is to become irrelevant.
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Few issues divide the tech community quite like privacy. Much of Silicon Valley’s wealth has been built on data-driven advertising platforms, and yet, there remain constant concerns about the invasiveness of those platforms.
Such concerns have intensified in just the last few weeks as France’s privacy regulator placed a record fine on Google under Europe’s General Data Protection Regulation (GDPR) rules which the company now plans to appeal. Yet with global platform usage and service sales continuing to tick up, we asked a panel of eight privacy experts: “Has anything fundamentally changed around privacy in tech in 2019? What is the state of privacy and has the outlook changed?”
This week’s participants include:
TechCrunch is experimenting with new content forms. Consider this a recurring venue for debate, where leading experts – with a diverse range of vantage points and opinions – provide us with thoughts on some of the biggest issues currently in tech, startups and venture. If you have any feedback, please reach out: Arman.Tabatabai@techcrunch.com.
Albert Gidari is the Consulting Director of Privacy at the Stanford Center for Internet and Society. He was a partner for over 20 years at Perkins Coie LLP, achieving a top-ranking in privacy law by Chambers, before retiring to consult with CIS on its privacy program. He negotiated the first-ever “privacy by design” consent decree with the Federal Trade Commission. A recognized expert on electronic surveillance law, he brought the first public lawsuit before the Foreign Intelligence Surveillance Court, seeking the right of providers to disclose the volume of national security demands received and the number of affected user accounts, ultimately resulting in greater public disclosure of such requests.
There is no doubt that the privacy environment changed in 2018 with the passage of California’s Consumer Privacy Act (CCPA), implementation of the European Union’s General Data Protection Regulation (GDPR), and new privacy laws enacted around the globe.
“While privacy regulation seeks to make tech companies betters stewards of the data they collect and their practices more transparent, in the end, it is a deception to think that users will have more “privacy.””
For one thing, large tech companies have grown huge privacy compliance organizations to meet their new regulatory obligations. For another, the major platforms now are lobbying for passage of a federal privacy law in the U.S. This is not surprising after a year of privacy miscues, breaches and negative privacy news. But does all of this mean a fundamental change is in store for privacy? I think not.
The fundamental model sustaining the Internet is based upon the exchange of user data for free service. As long as advertising dollars drive the growth of the Internet, regulation simply will tinker around the edges, setting sideboards to dictate the terms of the exchange. The tech companies may be more accountable for how they handle data and to whom they disclose it, but the fact is that data will continue to be collected from all manner of people, places and things.
Indeed, if the past year has shown anything it is that two rules are fundamental: (1) everything that can be connected to the Internet will be connected; and (2) everything that can be collected, will be collected, analyzed, used and monetized. It is inexorable.
While privacy regulation seeks to make tech companies betters stewards of the data they collect and their practices more transparent, in the end, it is a deception to think that users will have more “privacy.” No one even knows what “more privacy” means. If it means that users will have more control over the data they share, that is laudable but not achievable in a world where people have no idea how many times or with whom they have shared their information already. Can you name all the places over your lifetime where you provided your SSN and other identifying information? And given that the largest data collector (and likely least secure) is government, what does control really mean?
All this is not to say that privacy regulation is futile. But it is to recognize that nothing proposed today will result in a fundamental shift in privacy policy or provide a panacea of consumer protection. Better privacy hygiene and more accountability on the part of tech companies is a good thing, but it doesn’t solve the privacy paradox that those same users who want more privacy broadly share their information with others who are less trustworthy on social media (ask Jeff Bezos), or that the government hoovers up data at rate that makes tech companies look like pikers (visit a smart city near you).
Many years ago, I used to practice environmental law. I watched companies strive to comply with new laws intended to control pollution by creating compliance infrastructures and teams aimed at preventing, detecting and deterring violations. Today, I see the same thing at the large tech companies – hundreds of employees have been hired to do “privacy” compliance. The language is the same too: cradle to grave privacy documentation of data flows for a product or service; audits and assessments of privacy practices; data mapping; sustainable privacy practices. In short, privacy has become corporatized and industrialized.
True, we have cleaner air and cleaner water as a result of environmental law, but we also have made it lawful and built businesses around acceptable levels of pollution. Companies still lawfully dump arsenic in the water and belch volatile organic compounds in the air. And we still get environmental catastrophes. So don’t expect today’s “Clean Privacy Law” to eliminate data breaches or profiling or abuses.
The privacy world is complicated and few people truly understand the number and variety of companies involved in data collection and processing, and none of them are in Congress. The power to fundamentally change the privacy equation is in the hands of the people who use the technology (or choose not to) and in the hands of those who design it, and maybe that’s where it should be.
Gabriel Weinberg is the Founder and CEO of privacy-focused search engine DuckDuckGo.
Coming into 2019, interest in privacy solutions is truly mainstream. There are signs of this everywhere (media, politics, books, etc.) and also in DuckDuckGo’s growth, which has never been faster. With solid majorities now seeking out private alternatives and other ways to be tracked less online, we expect governments to continue to step up their regulatory scrutiny and for privacy companies like DuckDuckGo to continue to help more people take back their privacy.
“Consumers don’t necessarily feel they have anything to hide – but they just don’t want corporations to profit off their personal information, or be manipulated, or unfairly treated through misuse of that information.”
We’re also seeing companies take action beyond mere regulatory compliance, reflecting this new majority will of the people and its tangible effect on the market. Just this month we’ve seen Apple’s Tim Cook call for stronger privacy regulation and the New York Times report strong ad revenue in Europe after stopping the use of ad exchanges and behavioral targeting.
At its core, this groundswell is driven by the negative effects that stem from the surveillance business model. The percentage of people who have noticed ads following them around the Internet, or who have had their data exposed in a breach, or who have had a family member or friend experience some kind of credit card fraud or identity theft issue, reached a boiling point in 2018. On top of that, people learned of the extent to which the big platforms like Google and Facebook that collect the most data are used to propagate misinformation, discrimination, and polarization. Consumers don’t necessarily feel they have anything to hide – but they just don’t want corporations to profit off their personal information, or be manipulated, or unfairly treated through misuse of that information. Fortunately, there are alternatives to the surveillance business model and more companies are setting a new standard of trust online by showcasing alternative models.
Melika Carroll is Senior Vice President, Global Government Affairs at Internet Association, which represents over 45 of the world’s leading internet companies, including Google, Facebook, Amazon, Twitter, Uber, Airbnb and others.
We support a modern, national privacy law that provides people meaningful control over the data they provide to companies so they can make the most informed choices about how that data is used, seen, and shared.
“Any national privacy framework should provide the same protections for people’s data across industries, regardless of whether it is gathered offline or online.”
Internet companies believe all Americans should have the ability to access, correct, delete, and download the data they provide to companies.
Americans will benefit most from a federal approach to privacy – as opposed to a patchwork of state laws – that protects their privacy regardless of where they live. If someone in New York is video chatting with their grandmother in Florida, they should both benefit from the same privacy protections.
It’s also important to consider that all companies – both online and offline – use and collect data. Any national privacy framework should provide the same protections for people’s data across industries, regardless of whether it is gathered offline or online.
Two other important pieces of any federal privacy law include user expectations and the context in which data is shared with third parties. Expectations may vary based on a person’s relationship with a company, the service they expect to receive, and the sensitivity of the data they’re sharing. For example, you expect a car rental company to be able to track the location of the rented vehicle that doesn’t get returned. You don’t expect the car rental company to track your real-time location and sell that data to the highest bidder. Additionally, the same piece of data can have different sensitivities depending on the context in which it’s used or shared. For example, your name on a business card may not be as sensitive as your name on the sign in sheet at an addiction support group meeting.
This is a unique time in Washington as there is bipartisan support in both chambers of Congress as well as in the administration for a federal privacy law. Our industry is committed to working with policymakers and other stakeholders to find an American approach to privacy that protects individuals’ privacy and allows companies to innovate and develop products people love.
Dr. Johnny Ryan FRHistS is Chief Policy & Industry Relations Officer at Brave. His previous roles include Head of Ecosystem at PageFair, and Chief Innovation Officer of The Irish Times. He has a PhD from the University of Cambridge, and is a Fellow of the Royal Historical Society.
Tech companies will probably have to adapt to two privacy trends.
“As lawmakers and regulators in Europe and in the United States start to think of “purpose specification” as a tool for anti-trust enforcement, tech giants should beware.”
First, the GDPR is emerging as a de facto international standard.
In the coming years, the application of GDPR-like laws for commercial use of consumers’ personal data in the EU, Britain (post-EU), Japan, India, Brazil, South Korea, Malaysia, Argentina, and China will bring more than half of global GDP under a similar standard.
Whether this emerging standard helps or harms United States firms will be determined by whether the United States enacts and actively enforces robust federal privacy laws. Unless there is a federal GDPR-like law in the United States, there may be a degree of friction and the potential of isolation for United States companies.
However, there is an opportunity in this trend. The United States can assume the global lead by doing two things. First, enact a federal law that borrows from the GDPR, including a comprehensive definition of “personal data”, and robust “purpose specification”. Second, invest in world-leading regulation that pursues test cases, and defines practical standards. Cutting edge enforcement of common principles-based standards is de facto leadership.
Second, privacy and antitrust law are moving closer to each other, and might squeeze big tech companies very tightly indeed.
Big tech companies “cross-use” user data from one part of their business to prop up others. The result is that a company can leverage all the personal information accumulated from its users in one line of business, and for one purpose, to dominate other lines of business too.
This is likely to have anti-competitive effects. Rather than competing on the merits, the company can enjoy the unfair advantage of massive network effects even though it may be starting from scratch in a new line of business. This stifles competition and hurts innovation and consumer choice.
Antitrust authorities in other jurisdictions have addressed this. In 2015, the Belgian National Lottery was fined for re-using personal information acquired through its monopoly for a different, and incompatible, line of business.
As lawmakers and regulators in Europe and in the United States start to think of “purpose specification” as a tool for anti-trust enforcement, tech giants should beware.
John Miller is the VP for Global Policy and Law at the Information Technology Industry Council (ITI), a D.C. based advocate group for the high tech sector. Miller leads ITI’s work on cybersecurity, privacy, surveillance, and other technology and digital policy issues.
Data has long been the lifeblood of innovation. And protecting that data remains a priority for individuals, companies and governments alike. However, as times change and innovation progresses at a rapid rate, it’s clear the laws protecting consumers’ data and privacy must evolve as well.
“Data has long been the lifeblood of innovation. And protecting that data remains a priority for individuals, companies and governments alike.”
As the global regulatory landscape shifts, there is now widespread agreement among business, government, and consumers that we must modernize our privacy laws, and create an approach to protecting consumer privacy that works in today’s data-driven reality, while still delivering the innovations consumers and businesses demand.
More and more, lawmakers and stakeholders acknowledge that an effective privacy regime provides meaningful privacy protections for consumers regardless of where they live. Approaches, like the framework ITI released last fall, must offer an interoperable solution that can serve as a model for governments worldwide, providing an alternative to a patchwork of laws that could create confusion and uncertainty over what protections individuals have.
Companies are also increasingly aware of the critical role they play in protecting privacy. Looking ahead, the tech industry will continue to develop mechanisms to hold us accountable, including recommendations that any privacy law mandate companies identify, monitor, and document uses of known personal data, while ensuring the existence of meaningful enforcement mechanisms.
Nuala O’Connor is president and CEO of the Center for Democracy & Technology, a global nonprofit committed to the advancement of digital human rights and civil liberties, including privacy, freedom of expression, and human agency. O’Connor has served in a number of presidentially appointed positions, including as the first statutorily mandated chief privacy officer in U.S. federal government when she served at the U.S. Department of Homeland Security. O’Connor has held senior corporate leadership positions on privacy, data, and customer trust at Amazon, General Electric, and DoubleClick. She has practiced at several global law firms including Sidley Austin and Venable. She is an advocate for the use of data and internet-enabled technologies to improve equity and amplify marginalized voices.
For too long, Americans’ digital privacy has varied widely, depending on the technologies and services we use, the companies that provide those services, and our capacity to navigate confusing notices and settings.
“Americans deserve comprehensive protections for personal information – protections that can’t be signed, or check-boxed, away.”
We are burdened with trying to make informed choices that align with our personal privacy preferences on hundreds of devices and thousands of apps, and reading and parsing as many different policies and settings. No individual has the time nor capacity to manage their privacy in this way, nor is it a good use of time in our increasingly busy lives. These notices and choices and checkboxes have become privacy theater, but not privacy reality.
In 2019, the legal landscape for data privacy is changing, and so is the public perception of how companies handle data. As more information comes to light about the effects of companies’ data practices and myriad stewardship missteps, Americans are surprised and shocked about what they’re learning. They’re increasingly paying attention, and questioning why they are still overburdened and unprotected. And with intensifying scrutiny by the media, as well as state and local lawmakers, companies are recognizing the need for a clear and nationally consistent set of rules.
Personal privacy is the cornerstone of the digital future people want. Americans deserve comprehensive protections for personal information – protections that can’t be signed, or check-boxed, away. The Center for Democracy & Technology wants to help craft those legal principles to solidify Americans’ digital privacy rights for the first time.
Chris Baker is Senior Vice President and General Manager of EMEA at Box.
Last year saw data privacy hit the headlines as businesses and consumers alike were forced to navigate the implementation of GDPR. But it’s far from over.
“…customers will have trust in a business when they are given more control over how their data is used and processed”
2019 will be the year that the rest of the world catches up to the legislative example set by Europe, as similar data regulations come to the forefront. Organizations must ensure they are compliant with regional data privacy regulations, and more GDPR-like policies will start to have an impact. This can present a headache when it comes to data management, especially if you’re operating internationally. However, customers will have trust in a business when they are given more control over how their data is used and processed, and customers can rest assured knowing that no matter where they are in the world, businesses must meet the highest bar possible when it comes to data security.
Starting with the U.S., 2019 will see larger corporations opt-in to GDPR to support global business practices. At the same time, local data regulators will lift large sections of the EU legislative framework and implement these rules in their own countries. 2018 was the year of GDPR in Europe, and 2019 be the year of GDPR globally.
Christopher Wolf is the Founder and Chair of the Future of Privacy Forum think tank, and is senior counsel at Hogan Lovells focusing on internet law, privacy and data protection policy.
“Regardless of the outcome of the debate over a new federal privacy law, the issue of the privacy and protection of personal data is unlikely to recede.”
with the adoption of a highly-regulatory and broadly-applicable state privacy law in California last Summer (and similar laws adopted or proposed in other states), and with intense focus on the data collection and sharing practices of large tech companies, the time may have come where Congress will adopt a comprehensive federal privacy law. Complicating the adoption of a federal law will be the issue of preemption of state laws and what to do with the highly-developed sectoral laws like HIPPA and Gramm-Leach-Bliley. Also to be determined is the expansion of FTC regulatory powers. Regardless of the outcome of the debate over a new federal privacy law, the issue of the privacy and protection of personal data is unlikely to recede.
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