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DataScan: Issue #76

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Data ethics and privacy named by Gartner as a top strategic trend. The rise of second-party data deal
 

DataScan

October 21 · Issue #76 · View online
Curated digest on the world of data.

Data ethics and privacy named by Gartner as a top strategic trend. The rise of second-party data deals. How a rap crew stole surveillance tech that tracks almost every American. A future where everything is a computer is as creepy as you feared.

Gartner picks digital ethics and privacy as a strategic trend for 2019. Natasha Lomas reports on how Gartner’s top ten strategic technology trends for 2019 prioritises digital ethics and privacy; alongside AI-driven development, augmented analytics, quantum computing and smart spaces. Lomas explains how notable the inclusion of ethics and privacy is, as although the concept is “not reliant on any particular technology”, it’s becoming an integral “property of other already deployed (but unnamed) technologies”. Furthermore, Gartner notes:
While privacy and security are foundational components in building trust, trust is actually about more than just these components. Trust is the acceptance of the truth of a statement without evidence or investigation. Ultimately an organisation’s position on privacy must be driven by its broader position on ethics and trust. Shifting from privacy to ethics moves the conversation beyond ‘are we compliant’ toward ‘are we doing the right thing’.
Big banks, aggregators launch group to hash out data-sharing issues. JPMorgan Chase, Bank of America and Wells Fargo have come together to launch the Financial Data Exchange (FDX), in the bid to create a better and consistent way to share customer data. The goal of FDX is to provide interoperability “in a way that maintains consumer control, security and choice”. Check out the new FDX website here.
GDPR is leading to more second-party data deals. Digiday’s Jessica Davies covers how the GDPR has accelerated advertiser’s demand to collaborate with publishers and both bring together their first-party data, rather than using externally sourced third-party data. By doing so, the publisher and advertiser can create mutually beneficial and “customised audience datasets”, to provide a more tailored and relevant experience to their customers. This would also help the publishers “compete with the likes of Google, Amazon and Facebook”. But -
It needs to be a trade-off where the publisher gets the big deal, and in return they’ll share their first-party data for free, from the campaign in real time, so a buyer can execute using real-time-bidding, sequential messaging, and frequency capping all the way down the purchase funnel.
How an amateur rap crew stole surveillance tech that tracks almost every American. Thomas Brewster explores how a hip-hop crew was able to use a mass-monitoring tech, called TLO, to steal American’s identities and splash the cash. TLO, now owned by TransUnion, can be accessed by the police and debt collectors to “track most of the United States’ 325 million inhabitants via their Social Security numbers, license plates, address histories, names and dates of birth”. The group reportedly gained access through multiple routes, including a part-time debt collection agency employee called Lakesiah Norman -
Norman would query the database, find people with good credit ratings who were ripe targets for identity theft and sell their information, including name, Social Security number and date of birth. Norman did this for at least 20 people, charging just $100 for each victim’s data.
– EFF’s Quintin added that “as long as such a database exists, it is a threat to the privacy of every American.”
Miscellaneous
🙈 Google exposed user data, feared repercussions of disclosing.
🕵️ Facebook admits its Portal device can collect your data for ads.
🔍 Twitter under formal investigation for how it tracks users.
🍏 How to download your data from Apple.
📈 NVIDIA and Open-Source Ecosystem are accelerating data science.
💪 Building a better GOV.UK, step by step.
👻 A future where everything is a computer is as creepy as you feared.
Calculus made easy (1910).
🤖 A new course to teach people about fairness in machine learning.
🌇 Geoff Boeing visualises city street network orientations:
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