DataDownload: Your Personal Data Is Super Valuable. Time to Cash In?

DataDownload: Your Personal Data Is Super Valuable. Time to Cash In? A weekly summary of all things Media, Data, Emerging Tech View this email in your browser

Dear Readers — Today, I have to tell you I’m sure of one thing. DATA is fast becoming super sexy. UC Berkley’s Dawn Song is building apps so that you can get paid by companies that want to use it. Data journalism is quickly becoming more than just a buzzword. AI is growing as a tool for journalism, with lots of juicy details being published next week at Hack/Hackers London. And our friend David Carroll argues that microtargeted political ads pervert the democratic process. His argument is political messaging is targeted on… data. Again, data privacy as a solution? Ok, let’s just say yes to that.

So — before Skynet becomes self-aware, it’s time to take control of the data, before it takes control of us. Unless it’s already happened.

Thoughtful feedback always welcome: Steve@NYCMediaLab.org.

Steven Rosenbaum
Managing Director
NYC Media Lab

Must-Read

In Data Journalism, Tech Matters Less Than the People
Ben Casselman’s LinkedIn description notes that the NYT journalist has a “specialty in data-driven storytelling” (a statement cemented by the fact that he was previously chief economics writer at FiveThirtyEight).

With a monitor littered with “charts, spreadsheets and way more Chrome tabs than any sane person would consider reasonable,” Casselman has a firm grasp of what it means to be a data journalist… and what it doesn’t.

In this interview, Casselman explains why data journalism isn’t just “staring at spreadsheets until a story magically appears,” the software he uses on a daily basis, and the minimum technical skills reporters today need.

6 min read Read More

For the Media

Wikipedia Co-Founder Wants to Give You an Alternative to Facebook and Twitter
Wikipedia co-founder Jimmy Wales launched Wikitribune to help fight fake news with original stories and citizen journalism. The publication floundered, so Wales pivoted the project to a “news focused social network” called WT:Social. Now for the vital differences: WT:Social will be funded by donations instead of ad dollars, will show the newest links first (no algorithmic curation, with a possible upvote button added in the future), and will support small niche communities.

How’s the social network faring so far? In the past month, 50k have signed up, but Wales is aiming for 500M.

2 min read Read More

There Could Be a Simple Solution to Facebook’s Political Ad Woes
Data-based renegade and The New School associate professor of media design David Carroll (for the uninitiated, read this) thinks Zuckerberg’s argument that political ads are expressions of free speech is fundamentally flawed (meanwhile, Twitter recently banned political ads).

The argument goes like this: Zuckerberg said users should debate among themselves to expose misinformation in political ads, while Carroll notes that “false ads are being targeted to only select voters that they can predict won’t challenge them.” He suggests Facebook continue allowing political ads, but eliminate the microtargeting that’s killing “informed conversation [between] neighbors.”

4 min read Read More

What We’re Watching

5 min watch Watch Now

Events & Announcements

Search Engine Land presents the clearest (and one of the lengthiest) elucidations of BERT we’ve seen. Why is an SEO publication diving into an NLP framework? Simply, “Google describes BERT as the largest change to its search system since the company introduced RankBrain, almost five years ago, and probably one of the largest changes in search ever.”

Besides succinctly describing the framework, SEL explores why BERT was such an important step forward, summarizing NLP’s issues with lexical ambiguity (ex. polysemy, homonymy, homographs, homophones, coreferences, etc.), the shortcomings of language learning methods like Word2Vec and Google Pygmalion, and how BERT’s transformer architecture changed the game.

49 min read Read More

A Visual Timeline of AI Predictions in Sci-Fi
Ever read an older sci-fi book and stumbled on an uncannily accurate description of a modern technology (or, remember that scene where 1991 Arnold says his brain runs on a neural net processor)? Even The Jetsons (and over a hundred years of concept art) got video calls right. Tech fantasies are coming into existence at an increasingly rapid pace — Noodle.ai’s infographic shows us the concepts that became reality from films and TV shows.

4 min read Read More

Transactions & Announcements

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