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DataScan: Issue #29

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How else will Echo Look judge users? Has your email data been sold to Uber? Do you unknowingly pay fo
 

DataScan

April 30 · Issue #29 · View online
Curated digest on the world of data.

How else will Echo Look judge users? Has your email data been sold to Uber? Do you unknowingly pay for “free” online services with personal data? What are the implications of removing net neutrality rules? How can “anonymised” data be traced back to the individual user? How does Elon Musk learn faster and better than everyone else? What is the current state of AI?
Happy reading! ✌

Amazon announced Echo Look - a smart camera with a built-in AI assistant. 👀  James Vincent pointed out: Amazon says the Echo Look will help users dress and give them fashion advice, but what other judgements could it make? For example
Amazon’s computer vision could be attuned to look for all sorts of personal signifiers beyond what you’re wearing. It could tell if you’re pregnant, and start offering you maternity clothes, cribs, and diapers; it could tell if you’re unhappy, and offer you music and movies you like (or possibly alcohol); it could tell if you’re tired and suggest some coffee; and it could tell if you’re overweight and suggest a Fitbit—the possibilities to sell you things when a company has a device that can infer your life from photographs are relatively infinite.
Amazon claim the collected data will only be used to analyse users’ fashion choices, but they “can’t speculate” if this could change in the future - and snoop on a lot more than just your clothes. ⛔
The New York Times published an interesting article on the risk taking of the CEO of Uber, Travis Kalanick. Lengthy but worthwhile insight into the “competitive” tactics of the controversial company🚗  Side note: Uber have updated their privacy settings so users can finally easily delete their account. 
ALSO - nestled in the article includes details of how Unroll.me sold email data to Uber. 💰 The cofounders both published responses, somewhat apologising:
A reminder to be wary of free services? – Ashley Carman summarises -nothing is free online because you are paying for it in the form of your data, which can be sold to third-party advertisers and / or used to target you with ads. 😶
The current Federal Communications Commission chairman, Ajit Pai, claims that removing net neutrality rules will “restore internet freedom for all Americans”. 😔  However – removing regulations on the big cable companies will allow them to “erect barriers and tolls that impede the free movement of data around the internet”, which 800 US startups claim will finish them. 👎
Facebook and Google were conned out of $100m in phishing scheme - “proving not even the biggest technology companies in the world are immune from the increasingly sophisticated attacks of online scammers”. 😱 Read more about Fortune’s investigation here
EXCELLENT report by Boris Lubarsky for The Georgetown Law Technology Review on the re-identification of “anonymised” data. 🔐 If personally identifiable information is “scrubbed” from a dataset - it is then consider “anonymised” and can then “be be sold to anyone and used for any purposes”. 😰  Furthermore, Lubarsky explains how easily “scrubbed data can now be traced back to the individual user”, which creates far reaching privacy implications:
There is no comprehensive data privacy law in America – it is regulated on an ad-hoc industry-by-industry basis. None of this patchwork of laws and regulations sets limits on the use or sale of “anonymised” data. There is no duty to report if data has been re-identified. There is no private cause of action for an individual seeking redress for re-identified data, and no external way to verify if a private entity has privately de-identified “anonymised” data exists. The theory that data scrubbed of personally identifying information cannot be re-identified has time and again been shown to no longer hold true. Our current ad-hoc approach is antiquated and inadequate for addressing the new technological challenges re-identified data presents.
HIGHLY recommend reading the full report. ✅
Miscellaneous
A debatably funny list of some stupid security flaws. 🙈
How does Elon Musk learn faster and better than everyone else? INSIGHTFUL read. 🤔 📚
Azeem Azhar explains the current state of AI: How did we get here, and where are we going nextHIGHLY RECOMMEND. 🤖
COOL: Pictones extracts the colours from any picture. 🖌
Are we approaching the end of human doctors? Interesting discussion by Luke Oakden-Rayner. 💉
Where Europe lives, in some 15 lines of R:
Where Europe lives, via DataisBeautiful sub-reddit
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