Apple’s transparency report for the first half of 2018 reveals a continued rise in the number of government requests for user data.
Apple released its biannual transparency report on Thursday, which is now available in the traditional PDF format and a newly launched interactive format that’s designed to be easier for users to skip to sections of interest to them.
The new graphical format displays a snapshot of government requests in each country broken down into requests for access to data linked to a device, financial data, account information requests, and emergency requests. Country snapshots are organised alphabetically in a row.
Worldwide Apple received 32,342 law enforcement requests for access for customer data associated with a specific device in the first half of 2018, up from 29,718 in the second half of 2017. Apple provided user data for 80 percent of those requests, totaling 25,829.
In line with previous reports, by far the most requests came from Germany, which accounted for 42 percent of the worldwide total. Apple notes that the high volume of requests in Germany were “predominantly due to stolen devices investigations”.
The US was the second highest source of requests at 4,570 during the period, followed by Australia, where law enforcement made 2,357 requests. In the UK, Apple received 572 device requests and 172 emergency requests; in both cases Apple provided data in response to 76 percent of requests.
In China Apple only received 751 device requests, but there were 30,764 devices specified in those requests. Apple says the high number of devices specified were mostly due to insurance fraud and stolen device investigations.
Poland, Finland and South Korea had similar profiles for the same reason. For example, in Poland only 32 requests where 14,060 devices were specified, while in South Korea there were 92 requests spanning 39,423 devices.
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The US had by far the highest number of requests by agencies seeking customer data related to financial identifiers, such as credit card and fight. This totaled 918 for the period and was due mainly to “iTunes Gift Card and credit card fraud investigations” and “Reseller fraud, iTunes Gift Card fraud, and financial fraud investigations”.
Apple also recorded 14 requests made under Mutual Legal Assistance Treaties from law enforcement in countries outside of US legal jurisdiction. The company hasn’t yet published the number of national security letters due to a requirement to withhold the numbers for six months.
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Twitter unveils Birdwatch – TechCrunch
Twitter pilots a new tool to fight disinformation, Apple brings celebrity-guided walks to the Apple Watch and Clubhouses raises funding. This is your Daily Crunch for January 25, 2021.
The big story: Twitter unveils Birdwatch
Twitter launched a new product today that it says will offer “a community-based approach to misinformation.”
With Birdwatch, users will be able to flag tweets that they find misleading, write notes to add context to those tweets and rate the notes written by others. This is supposed to be a complement to the existing system where Twitter removes or labels particularly problematic tweets, rather than a replacement.
What remains to be seen: How Twitter will handle it when two or more people get locked into a battle and post a flurry of conflicting notes about whether a tweet is misleading or not.
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Debunk, don’t ‘prebunk,’ and other psychology lessons for social media moderation – TechCrunch
If social networks and other platforms are to get a handle on disinformation, it’s not enough to know what it is — you have to know how people react to it. Researchers at MIT and Cornell have some surprising but subtle findings that may affect how Twitter and Facebook should go about treating this problematic content.
MIT’s contribution is a counter-intuitive one. When someone encounters a misleading headline in their timeline, the logical thing to do would be to put a warning before it so that the reader knows it’s disputed from the start. Turns out that’s not quite the case.
In a study of nearly 3,000 people who evaluated the accuracy of headlines after receiving different (or no) warnings about them.
Going into the project, I had anticipated it would work best to give the correction beforehand, so that people already knew to disbelieve the false claim when they came into contact with it. To my surprise, we actually found the opposite,” said study co-author David Rand in an MIT news article. “Debunking the claim after they were exposed to it was the most effective.”
When a person was warned beforehand that the headline was misleading, they improved in their classification accuracy by 5.7 percent. When the warning came simultaneously with the headline, that improvement grew to 8.6 percent. But if shown the warning afterwards, they were 25 percent better. In other words, debunking beat “prebunking” by a fair margin.
The team speculated as to the cause of this, suggesting that it fits with other indications that people are more likely to incorporate feedback into a preexisting judgment rather than alter that judgment as it’s being formed. They warned that the problem is far deeper than a tweak like this can fix.
“There is no single magic bullet that can cure the problem of misinformation,” said co-author Adam Berinsky. “Studying basic questions in a systematic way is a critical step toward a portfolio of effective solutions.”
The study from Cornell is equal parts reassuring and frustrating. People viewing potentially misleading information were reliably influenced by the opinions of large groups — whether or not those groups were politically aligned with the reader.
It’s reassuring because it suggests that people are willing to trust that if 80 out of 100 people thought a story was a little fishy, even if 70 of those 80 were from the other party, there might just be something to it. It’s frustrating because of how seemingly easy it is to sway an opinion simply by saying that a large group thinks it’s one way or the other.
“In a practical way, we’re showing that people’s minds can be changed through social influence independent of politics,” said graduate student Maurice Jakesch, lead author of the paper. “This opens doors to use social influence in a way that may de-polarize online spaces and bring people together.”
Partisanship still played a role, it must be said — people were about 21 percent less likely to have their view swayed if the group opinion was led by people belonging to the other party. But even so people were very likely to be affected by the group’s judgment.
Part of why misinformation is so prevalent is because we don’t really understand why it’s so appealing to people, and what measures reduce that appeal, among other simple questions. As long as social media is blundering around in darkness they’re unlikely to stumble upon a solution, but every study like this makes a little more light.
Twitter’s Birdwatch fights misinformation with community notes – TechCrunch
Twitter is launching what it calls “a community-based approach to misinformation.”
The goal, as explained in a blog post by Twitter’s Vice President of Product Keith Coleman, is to expand beyond the labels that the company already applies to controversial or potentially misleading tweets, which he suggested are limited to “circumstances where something breaks our rules or receives widespread public attention.”
Coleman wrote that the Birdwatch approach will “broaden the range of voices that are part of tackling this problem.” That has brings a broader range of perspectives to these issues and goes beyond the simple question of, “Is this tweet true or not?” It may also take some of the heat off Twitter for individual content moderation decisions.
Users can sign up on the Birdwatch site to flag tweets that they find misleading, add context via notes and rate the notes written by other contributors, based on whether they’re helpful or not. These notes will only be visible on the Birdwatch site for now, but it sounds like the company’s goal is to incorporate them to the main Twitter experience.
“We believe this approach has the potential to respond quickly when misleading information spreads, adding context that people trust and find valuable,” Coleman said. “Eventually we aim to make notes visible directly on Tweets for the global Twitter audience, when there is consensus from a broad and diverse set of contributors.”
Given the potential for plenty of argument and back-and-froth on contentious tweets, it remains to be seen how Twitter will present these notes in a way that isn’t confusing or overwhelming, or how it can avoid weighing in on some of these arguments. The company said Birdwatch will use rank content based on algorithmic “reputation and consensus systems,” with the code shared publicly. (All notes contributed to Birdwatch will also be available for download.) You read more about the initial ranking system here.
“We know there are a number of challenges toward building a community-driven system like this — from making it resistant to manipulation attempts to ensuring it isn’t dominated by a simple majority or biased based on its distribution of contributors,” Coleman said. “We’ll be focused on these things throughout the pilot.”
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