Intro to NVivo – January 31 10:00 a.m. – 12:30 p.m.
440 Blegen Hall
NVivo is a qualitative data management, coding and markup tool, that facilitates powerful querying and exploration of source materials for both mixed methods and qualitative analysis. It integrates well with tools that assist in data collection and can handle a wide variety of source materials. This workshop introduces the basic functions of NVivo, with no prior experience necessary. The session is held in a computer lab with the software already installed. Register.
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Last year, researchers at Oxford University found that 70 countries had political disinformation campaigns over two years.
Perhaps the most notable of such campaigns was that initiated by a Russian propaganda group to influence the 2016 US election result.
he US Federal Communications Commission hosted a period in 2017 where the public could comment on its plans to repeal net neutrality. Harvard Kennedy School lecturer Bruce Schneier notes that while the agency received 22 million comments, many of them were made by fake identities.
Schneier argues that the escalating prevalence of computer-generated personas could “starve” people of democracy
Until now, technology that readily identifies everyone based on his or her face has been taboo because of its radical erosion of privacy. Tech companies capable of releasing such a tool have refrained from doing so; in 2011, Google’s chairman at the time said it was the one technology the company had held back because it could be used “in a very bad way.” Some large cities, including San Francisco, have barred police from using facial
But without public scrutiny, more than 600 law enforcement agencies have started using Clearview in the past year, according to the company, which declined to provide a list. recognition technology.
Facial recognition technology has always been controversial. It makes people nervous about Big Brother. It has a tendency to deliver false matches for certain groups, like people of color. And some facial recognition products used by the police — including Clearview’s — haven’t been vetted by independent experts.
Clearview deployed current and former Republican officials to approach police forces, offering free trials and annual licenses for as little as $2,000. Mr. Schwartz tapped his political connections to help make government officials aware of the tool, according to Mr. Ton-That.
“We have no data to suggest this tool is accurate,” said Clare Garvie, a researcher at Georgetown University’s Center on Privacy and Technology, who has studied the government’s use of facial recognition. “The larger the database, the larger the risk of misidentification because of the doppelgänger effect. They’re talking about a massive database of random people they’ve found on the internet.”
Part of the problem stems from a lack of oversight. There has been no real public input into adoption of Clearview’s software, and the company’s ability to safeguard data hasn’t been tested in practice. Clearview itself remained highly secretive until late 2019.
The software also appears to explicitly violate policies at Facebook and elsewhere against collecting users’ images en masse.
while there’s underlying code that could theoretically be used for augmented reality glasses that could identify people on the street, Ton-That said there were no plans for such a design.
facial recognition bans are the wrong way to fight against modern surveillance. Focusing on one particular identification method misconstrues the nature of the surveillance society we’re in the process of building. Ubiquitous mass surveillance is increasingly the norm. In countries like China, a surveillance infrastructure is being built by the government for social control. In countries like the United States, it’s being built by corporations in order to influence our buying behavior, and is incidentally used by the government.
People can be identified at a distance by their heart beat or by their gait, using a laser-based system. Cameras are so good that they can read fingerprints and irispatterns from meters away. And even without any of these technologies, we can always be identified because our smartphones broadcast unique numbers called MAC addresses.
The data broker industry is almost entirely unregulated; there’s only one law — passed in Vermont in 2018 — that requires data brokers to register and explain in broad terms what kind of data they collect.
Until now, technology that readily identifies everyone based on his or her face has been taboo because of its radical erosion of privacy. Tech companies capable of releasing such a tool have refrained from doing so; in 2011, Google’s chairman at the time said it was the one technology the company had held back because it could be used “in a very bad way.” Some large cities, including San Francisco, have barred police from using facial recognition technology.
Even on seemingly-serious websites, credibility is not a given. When I was in middle and high school, we were taught that we could trust .org websites. Now, with the practice of astroturfing, responsible consumers of information must dig deeper and go further to verify the legitimacy of information. https://www.merriam-webster.com/dictionary/astroturfing
Experiences like these, where students are challenged to consider the validity of information and sort what’s real from what’s fake, would better prepare them not only to be savvier consumers of news, but also to someday digest contradictory information to make complicated decisions about their own health care, finances or civic engagement.
freely available resources to help educators teach how to vet information and think critically about real-world topics.