Google announced tonight that its Stadia cloud-gaming service will launch on November 19 (yes, Tuesday) with 22 titles, up from just 12 last week.
I’m not sure what changed so fast to allow Google to add 10 more titles, but last week’s announcement of just 12 titles was greeted as a pathetic line-up. Now Stadia has a much broader set of games to please more gamers.
“Alongside our publisher and developer partners, we’ve been working around the clock on getting ready for Stadia’s launch, and we are adding more incredible titles to our day one launch line-up,” the Stadia team said in an email. “Gamers will have a total of 22 titles available to choose from to experience Stadia for the first time on Tuesday, with more games coming by the end of the year.”
In addition, gamers will be able to claim both Destiny 2: The Collection and Samurai Shodown as part of the November Stadia Pro subscription.
Stadia’s day one titles include:
Assassin’s Creed Odyssey
Attack on Titan: Final Battle 2
Destiny 2: The Collection (available in Stadia Pro)
Farming Simulator 2019
Final Fantasy XV
Football Manager 2020
Just Dance 2020
Mortal Kombat 11
Rise of the Tomb Raider
Red Dead Redemption 2
Samurai Shodown (available in Stadia Pro)
Shadow of the Tomb Raider
Tomb Raider 2013
Additional games expected to be playable on Stadia by the end of the year include Borderlands 3, Ghost Recon: Breakpoint, Dragon Ball: Xenoverse and Darksiders Genesis.
There are many more titles that have been announced as coming to Stadia in 2020 including Doom: Eternal, WatchDogs: Legion, Gods & Monsters and Cyberpunk 2077.
For most of the past decade, people all around the world sat and watched as significant tech companies started to expand their reach into every part of our daily lives. In many cases, the results were positive, like bringing our favorite entertainment to every device we own. We loved being able to order food and consumer goods with unparalleled ease. Here’s how big tech faces data collection scrutiny — but big insurance might be next (we hope).
Big Tech Companies Hoarding, Our Data, is One Thing — Big Insurance Collection is Another.
Getting a better look at how companies have been making conveniences possible hasn’t been pretty. Companies like Facebook have been embroiled in one controversy after another, mostly revolving around how they treat user privacy concerns. At the same time, Google has courted a public relations nightmare surrounding its extensive and intrusive data collection practices.
Topping it all off, though, was the revelation that Microsoft, Apple, Google, and Amazon were allowing contracted employees to listen to voice recordings of users, sometimes without their knowledge.
The backlash generated by these events has grown with time, resulting in a renewed push to crackdown on big tech and the way it collects and uses user data. The problem is that the tech industry isn’t the only one that collects vast, unregulated amounts of user data.
The global insurance industry has been collecting all kinds of data on millions of individuals for years – and there are little regulation and even less attention paid to their activities.
Feeding a Big Data Machine
Anyone who follows the latest insurance technology trends should know that the industry is making a push into big data and AI in a big way. Their main goals are to streamline service delivery, enable faster claims processing, and increase profits. To do it, they’re ramping up efforts to get their hands on every scrap of data they can find about consumers.
Healthcare data carnivores — includes the collection and storage of vast quantities of so-called lifestyle data that are not even related to health.
The problem, as it relates to privacy, is that insurance companies are collecting data without anything by way of consent — especially within the realm of health insurance. What they’re doing is also not illegal,
by the way. In the US, at least, the vast majority of people don’t actually own their own medical data.
That means healthcare industry giants like Optum can collect as much private medical data as they want. They have already collected all your health information – for more than half of the total US population. The insurance companies can sell it to whomever they want.
It’s Not Just Medical Records
The enormous collection of data doesn’t stop with health records. Insurers of all stripes are tapping into data sources like social media histories, media consumption records, and even court records to use as data points. The idea is to build a profile of customers that presents a complete picture of who they are, how they live, and their specific preferences.
On the surface, that sounds like it could result in a net benefit for consumers. It should enable companies to more specifically tailor their offerings to each individual, rather than demographic subsets and risk pools. In practice, however, the early results haven’t been anywhere near that positive.
Already, insurers have started to use their data to engage in a practice they call “price optimization.”
The insurance increases your rates as a customer — not based on actual risk scoring, but based on predicted behaviors. For example, if an insurer’s data models show that an individual doesn’t take the time to shop around when purchasing other types of goods and services, it triggers a series of insurance price increases.
This price hike based solely on the prediction that you don’t shop around for price — so they can do what they want. Your insurance will be charged at higher rates.
What’s more, insurers generally have no obligation to provide any transparency into how they set rates. Most of the time, they’re able to claim that their actuarial models are trade secrets. The trade secret is even used when they are pressed for details by insurance regulators.
The result is a system that’s pulling in more varieties of consumer data, but with no oversight into how it’s being used. Worse still, consumers have no way to opt-out of the process or even find out what information an insurer has used in making their decisions.
Although the general public has remained fixated on the way that big tech firms are using – and some would say abusing their data, the same can’t be said about the data practices of the insurance industry.
The dishonest insurance industry has used the lack of attention to ramp up their data collection efforts both in plain sight as well as behind the scenes. So far, only the practice of price optimization has drawn any real attention from the public — because it’s very tangible. But other visible results of the insurance industry’s data-mining isn’t being addressed.
In the absence of any real oversight, some insurers are even beginning to move toward bleeding-edge technologies like facial analytics to augment their data collection repertoires.
With the rise of IoT and connected devices, we can expect every little detail of our lives to be documented, from GPS car tracking, to what groceries we have in our smart fridge. That’s a practice that could have some disturbing undertones, depending on how it’s put to use. The good news, if there is any, is that it’s starting to look like the insurance industry has started to draw the kind of attention that portends a coming regulatory reckoning.
A Reckoning May be Coming
Regulators in specific segments of the insurance industry have begun to launch probes into how the insurance industry is using all of the data it’s been collecting. Life insurers, in particular, are already facing some tough questions about how they’re using non-traditional data sources.
There have also been some early efforts in some states to restrict the ways that insurers can use non-health data in their underwriting procedures.
These moves probably won’t be the last word on the issue, however. As more regulators start to look into what the insurance industry’s been up to, there’s a good chance that the public will start to take notice, too. If the public finally wakes up and notices what’s happening — it’s all but certain to create an uproar similar to what big tech is experiencing right now.
Insurers would do well to pay careful attention to what happens to Facebook, Apple, Amazon, and other companies. The day for the spotlight to be turned on the insurance companies may be coming sooner than they think.
Andrej is a dedicated writer and digital evangelist. He is pursuing an ongoing mission to share the benefits of his years of hard-won expertise with business leaders and marketing professionals everywhere. He is a contributor to a wide range of technology-focused publications, where he may be found discussing everything from neural networks and natural language processing to the latest in smart home IoT devices. If there’s a new and exciting technology, there’s a good chance Andrej is writing about it somewhere out there.
Passwords can be a bear sometimes — particularly if you’re prone to forgetting them. In an effort to help users regain access to their Facebook profiles when they lose track of their login information, Facebook today announced that it’s rolling out updated login, registration, and recovery screens to its apps in regions where email addresses are less commonly used to create accounts, such as developing countries in Latin America, Asia, and Africa.
Typically, Facebook requests numbers from a phone’s primary SIM card to prefill fields on registration, login, and account recovery pages. The company works with service providers to enable this such that when people create new accounts or log into existing ones, it requests a current number from the mobile network to do things like automatically fill in relevant login fields.
The new screens disclose that Facebook requests and receives up-to-date phone numbers from said networks, and they provide users an opportunity to opt out of sharing their number for account access purposes. Additionally, on the Facebook app as well as Facebook Lite and Facebook’s mobile website, the logout screens have been updated with an option to save login information to make it easier to access accounts in the future.
In the newest Facebook apps and website, users in selected countries will see new tools allowing them to indicate whether they prefer to share their number. Those who choose not to won’t see their number from the mobile network to prefill various forms — but they might see it entered automatically if they’ve saved the number in-app or on-device or if they’ve previously logged in with it.
Facebook notes that when users make any change, their preference will only be saved for the device and app or browser they’re using. If they use a different browser, they’ll see the same screens again.
“In some cases, people are new not only to our apps and websites, but also to the internet as a whole. They may never have set up a username or password before,” wrote Facebook director of product management Jon Paris and product manager Vincent Gonguet in a blog post. “These tools are important to our efforts to help people access our services more easily, and we look forward to continued collaboration with our partners.”
Facebook has a mixed track record when it comes to the handling of users’ phone numbers. It received blowback this past summer for its implementation of SMS two-factor authentication, which allowed anyone to look up a person’s profile by a number they’d previously provided. Worse still, the social network last year admitted that it used these numbers to target users with advertisements.
In attempts at remediation, Facebook in 2018 added the option to set up two-factor authentication with third-party apps instead of a number, and it recently removed the ability to enter a number and email address into the Facebook search bar to find a person on the platform. It’s also experimented with alternative methods of verifying a person’s identity, such as a step that requires the capturing of a “video selfie” at login time.
Uber’s just-released U.S. Safety Report sets forth in some detail the number of fatal accidents, and the good news is that the overall rate per mile is about half the national average. But the report makes some puzzling choices as far as what is included and excluded.
To create the report, Uber took its internal reports of crashes, generated by drivers, users, or insurance companies, and compared it to the national Fatality Analysis Reporting System, or FARS, a database that tracks all automotive deaths. In this way Uber was able to confirm 97 fatal crashes with 107 total deaths in 2017 and 2018 combined.
As the company is careful to point out before this, more than 36,000 people died in car crashes in the U.S. in 2018 alone, so the total doesn’t really mean much on its own. So they (as others do in this field) put those accidents in context of miles traveled. After all, 1 crash in 100,000 miles doesn’t sound bad because it’s only one, but 10 crashes in a billion miles, which is closer to what Uber saw, is actually much better despite the first number being higher. To some this is blindingly obvious but perhaps not to others.
The actual numbers are that in 2017, there were 49 “Uber-related” fatalities over 8.2 billion miles, or approximately 0.59 per 100 million miles traveled; in 2018, there were 58 over 1.3 billion, or about 0.57 per 100 million miles. The national average is more than 1.1 per 100 million, so Uber sees about half as many fatalities per mile overall.
These crashes generally occurred at lower speeds than the national average, and were more likely by far to occur at night, in lighted areas of cities. That makes sense, since rideshare services are heavily weighted towards urban environments and shorter, lower-speed trips.
That’s great, but there are a couple flies in the ointment.
First, obviously, there is no mention whatsoever of non-fatal accidents. These are more difficult to track and categorize, but it seems odd not to include them at all. If the rates of Ubers getting into fender-benders or serious crashes where someone breaks an arm are lower than the national average, as one might expect from the fatality rates, why not say so?
When I asked about this, an Uber spokesperson said that non-fatal crashes are simply not as well defined or tracked, certainly not to the extent fatal crashes are, which makes reporting them consistently difficult. That makes sense, but it still feels like we’re missing an important piece here. Fatal accidents are comparatively rare and the data corpus on non-fatal accidents may provide other insights.
Second, Uber has its own definition of what constitutes an “Uber-related” crash. Naturally enough, this includes whenever a driver is picking up a rider or has a rider in their car. All the miles and crashes mentioned above are either en route to a pickup or during a ride.
But it’s well known that drivers also spend a non-trivial amount of time “deadheading,” or cruising around waiting to be hailed. Exactly how much time is difficult to estimate, as it would differ widely based on time of day, but I don’t think that Uber’s decision to exclude this time is correct. After all, taxi drivers are still on the clock when they are cruising for fares, and Uber drivers must travel to and from destinations, keep moving to get to hot spots, and so on. Driving without a passenger in the car is inarguably a major part of being an Uber driver.
It’s entirely possible that the time spent deadheading isn’t much, and that the accidents that occurred during that time are few in number. But the alternatives are also possible, and I think it’s important for Uber to disclose this data; Cities and riders alike are concerned with the effects of ride-hail services on traffic and such, and the cars don’t simply disappear or stop getting in accidents when they’re not hired.
When I asked Uber about this, a spokesperson said that crash data from trips is “more reliable,” since drivers may not report a crash if they’re not driving someone. That doesn’t seem right either, especially for fatal accidents, which would be reported one way or the other. Furthermore Uber would be able to compare FARS data to its internal metrics of whether a driver involved in a crash was online or not, so the data should be similarly if not identically reliable.
The spokesperson also explained that a driver may be “online” in Uber at a given moment but in fact driving someone around using another rideshare service, like Lyft. If so, and there is an accident, the report would almost certainly go to that other service. That’s understandable, but again it feels like this is a missing piece. At any rate it doesn’t juice the numbers at all, since deadheading miles aren’t included in the totals used above. So “online but not hired” miles will remain a sort of blind spot for now.