DataDownload: Closing California’s privacy loopholes
DataDownload: Closing California’s privacy loopholes A weekly summary of all things Media, Data, Emerging Tech View this email in your browser
Today we’re thinking about data.
Consumer control of their own data is gaining steam. Polling data is deeply, maybe fatally flawed. Deepfakes are funny and scary. The WSJ gave readers a tool to search candidate comments about facts and quotes.
Then, after data, we took a journey into lasers. Terahertz lasers. Because terahertz lasers can provide medical imaging without damaging living tissues. Next week we’re excited to have Juan Enriquez give a book talk about his new book Right/Wrong — and we got a sneak peek.
The Coronavirus has a misinformation problem — a podcast with Steven Johnson and Wondery. And finally — AI Pioneer Geoff Hinton says “Deep Learning is going to be able to do everything.”
So, we’re looking forward. It’s complicated but strangely refreshing.
Enjoy the newsletter, and reach out with ideas, suggestions, or feedback.
Steve
Steve@NYCMediaLab.org
Steven Rosenbaum
Executive Director
The NYC Media Lab
Steve@NYCMediaLab.org Must-Read Proposition 24 Passes in California, Pushing Privacy Rights to the Forefront Again
California may be at the forefront of consumer privacy, but the California Consumer Protection Act harbored major loopholes since its inception in 2018. The company behind the Brave browser summed these up nicely in March 2019:
- Personal information: “We are concerned by the fact that the definition of “personal information” does not include publicly available information.”
- Deletion requests: “The CCPA allows a business to deny a deletion request if the data concerned are… useful for “security” [or] “debugging”, or to provide [a service for the consumer].”
- Business purposes exception: “We are troubled by the Act’s exception for personal information to be used or shared when necessary to perform a ‘business purpose.’”
- Sale: “The concept of the ‘sale’ of personal information may be too permissive. One company can share personal information with one or more other companies and benefit from this sharing.”
That last one particularly enticed Facebook. According to Datanami, “in private conference calls with major advertisers in October, Facebook stated its data collection qualified for the law’s exemption for sending data to ‘service providers’ and didn’t count as a ‘sale’ of data.” California voters recently approved Proposition 24, which helps close the “sale” loophole by allowing users to ask companies to not “share” their data as well — precisely what Brave was talking about above.
According to a Wired overview of the Proposition, it “creates a new category of Sensitive Personal Information (SPI), including race, sexuality, religion, and health data. Businesses must disclose to users if they plan to collect, share, or sell SPI. Once informed, users can prevent companies from sharing SPI. It also allocates $10 million to a new California Privacy Protection Agency that will enforce the law.”
3 min read
Read more The Polling Crisis Is a Catastrophe for American Democracy
“The only poll that matters is on Election Day.” — ancient American political cliché
Amidst all the confusion and anxiety, one thing is crystal clear: the polling industry was painfully off… again. The modern “poll-industrial complex” goes back to George Gallup in the 30s, but over the past two decades, polls have increasingly been dominant in politics and policy. But then 2016 happened. Pollsters scrambled to point out that “the popular vote had closely tracked national polling on Clinton versus Trump” and that many of the state polls weren’t off by much.
Now that things have been botched twice, confidence has diminished considerably among the press and public. The Atlantic sees two lines of defense this time around: first, “many pollsters insist that their polls are snapshots, not predictors.” And second, “the analysts will protest that they’re only as good as the polls, but who cares? Whatever the instructions on the bottle, the public uses opinion polls to try to understand what happens.”
7 min read
Read More Tech+Media The ‘South Park’ Guys Break Down Their Viral Deepfake Video Sassy Justice is the best use of deepfakes (and deepfake puppets) for entertainment/education we’ve seen yet — set aside 15 minutes to watch American Consumer Advocate and reporter Fred Sassy, played by British actor Peter Serafinowicz, dole out justice in Cheyenne, Wyoming.
If you thought something was off with Serafinowicz — he looks nothing like Pete from Shaun of the Dead, after all — well, that’s because the host himself is a wonderfully done deepfake. In a call with The NY Times, show creators Trey Parker and Matt Stone said the show was “partly their attempt to educate their viewers about deepfakes and demystify a potentially terrifying subject…. ‘We just wanted to make fun of it because it makes it less scary,’” said Stone.
Sassy Justice was originally meant to be a full-length deepfake movie, “in the spirit of comedies like ‘The Great Dictator’ and ‘Dave’.” Parker and Stone financed the project independently and hired a staff of about 20 deepfake artists and technicians. And then the pandemic hit, delaying the film indefinitely. Equipped with a deepfake crew, props like a $30k news van, and the Fred Sassy character, Parker and Stone decided to do a show instead.
8 min read Read More With Talk2020, the Wall Street Journal Turns an Internal Reporting Tool Into a Reusable News Product
WSJ conducted extensive focus groups last summer and found that “readers wanted to be able to quickly locate quotes and facts about a candidate’s record — and not just for their own edification.” So the paper released Talk2020, a tool that gathers a searchable database of transcripts from campaign speeches, media appearances, debates, and more. Check out the tool here and search for a candidate’s views on, well, anything you can think of, or navigate by particular issue. For example, when we searched for “What does Joe Biden say about China?” we got this as the first result (notice the Share button for those I told you so’s):
3 min read Read More Far-Infrared Now Near: Researchers Debut Compact Terahertz Laser
Applications for terahertz waves — or submillimeter radiation — are numerous: medical imaging that does not damage living tissue and DNA, security screening that can penetrate fabric and plastic to reveal concealed weapons or drugs, ultra-high-speed Wi-Fi (think terabits), packaged goods inspection in manufacturing, and much more.
Researchers at MIT and the University of Waterloo in Canada have come up with a compact quantum cascade laser — which previously needed a temperature of -63°C to operate — that can emit 4-terahertz light at temperatures up to -23°C. That means downgrading from bulky cryogenics to thermoelectric coolers — and a step closer to portable devices capable of leveraging terahertz waves.
2 min read
Read More What We’re Watching Right/Wrong: How Technology Transforms Our Ethics
Juan Enriquez — a leading expert on the economic and political impacts of life sciences — finished his latest book, Right/Wrong: How Technology Transforms Our Ethics, after six years of work. The book tackles “a series of technology-influenced ethical dilemmas, from sexual liberation to climate change to the ‘immortality’ of mistakes on social media.” Enriquez spoke for the Tallberg Foundation on these themes recently — it’s an engrossing 30-minute talk (also check out his gut-wrenching TED talk here).
30 min watch
Watch Now What We’re Listening To Podcast: Fighting Coronavirus | Stopping the Spread of Bad Information
According to the World Health Organization, “we’re not just in the midst of a pandemic. We’re living through an ‘infodemic,’ where misinformation is more readily available than facts.”
In this episode of American Innovations, Joan Donovan, Director of the Technology and Social Change Research Project at Harvard Kennedy’s Shorenstein Center, “shares how conspiracy theories spread and how each of us can practice good information hygiene.”
23 min listen
Listen Now Virtual Events Virtual Event: How Tech Transforms Our Ethics — A Book Talk w/ Juan Enriquez
Date: November 11, 11AM-12PM EST
NYC Media Lab — in partnership with GovLab, IDM, ITP, and the NYU Dept of Tech, Culture, & Society — invites you to a virtual book talk with author Juan Enriquez, who will discuss the main tenets of his latest book, “Right/Wrong: How Technology Transforms Our Ethics,” with a virtual audience Q&A to follow. Register Here.
Virtual Event: Trust Conference
Date: November 11, 4AM-2:30PM EST
Trust Conference is the Thomson Reuters Foundation’s flagship annual event and a leading human rights forum. Normally held in the heart of London each year, the conference brings together some 600 delegates from diverse sectors representing more than 60 countries. Register Here. A Deeper Look AI Pioneer Geoff Hinton: “Deep Learning Is Going to Be Able to Do Everything”
MIT Technology Review spoke with Turing Award winner Geoffrey Hinton on the future of deep learning. The researcher — who pioneered the field and has stuck with it since the 80s — needs little introduction, so we’ve gathered some of our favorite quotes from the piece.
Will we be able to approximate all human intelligence through deep learning?
“Yes. Particularly breakthroughs to do with how you get big vectors of neural activity to implement things like reason. But we also need a massive increase in scale. The human brain has about 100 trillion parameters, or synapses. What we now call a really big model, like GPT-3, has 175 billion. It’s a thousand times smaller than the brain.”
A lot of the people in the field believe that common sense is the next big capability to tackle. Do you agree?
“I agree that that’s one of the very important things. I also think motor control is very important, and deep neural nets are now getting good at that. In particular, some recent work at Google has shown that you can do fine motor control and combine that with language, so that you can open a drawer and take out a block, and the system can tell you in natural language what it’s doing.”
What do you believe to be your most contrarian view on the future of AI?
“Well, my problem is I have these contrarian views and then five years later, they’re mainstream. Most of my contrarian views from the 1980s are now kind of broadly accepted. It’s quite hard now to find people who disagree with them. So yeah, I’ve been sort of undermined in my contrarian views.”
5 min read
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