Julia Bernd

Give Robots ‘Personhood’ Status, EU Committee Argues

The Guardian, 1/12/2017

The European Parliament is considering a proposed legal framework to define the rights and responsibilities of autonomous artificial intelligences and of the companies and engineers who make them, including who is responsible for errors and who benefits from products created by AIs. The framework also suggests measures to reduce the negative economic impacts on the human labor force.

Ultrasound Tracking Could Be Used to Deanonymize Tor Users

Bleeping Computer, 1/3/2017

Cybersecurity researchers recently discovered that ultrasound cross-device tracking (uXDT), in which a web page plays an ultrasound signal that prompts nearby devices to identify themselves via ultrasound, could be effective even when users are using the anonymization proxy Tor. This provides an example of the continual arms race between privacy-enhancing technologies and privacy-invading technologies.

Machine-Learning Algorithm Can Show Whether State Secrets Are Properly Classified

MIT Technology Review, 11/14/2016

Researchers from Columbia University and a Brazilian think tank have developed a machine-learning algorithm to predict whether now-declassified U.S. State Department cables from the 1970’s were unclassified, limited official use, confidential, or secret, based on contents and metadata such as sender and recipient. The study provides insight into how the information was classified, but also carries potential national security implications by highlighting trends in erroneous information classification — and systematic gaps where secret cables should have been declassified.

Was New York’s Mass-Text Manhunt Really Unprecedented?

The Verge, 9/20/2016

New York City police used the Wireless Emergency Alert system recently to send out a “Wanted” text message about a bombing suspect, and they plan to use the system for similar purposes in future. However, they have received heavy criticism, mainly saying that the short, pictureless message may have encouraged mass racial profiling, and that overuse of the system might lead to people ignoring it.

Big Pixel Initiative Develops Remote Sensing Analysis to Help Map Global Urbanization

UC San Diego News Center, 9/14/2016

An interdisciplinary research team developed a large dataset of 21,030 high-resolution satellite images of India labeled for whether they show built-up areas. The dataset can be used as input to algorithms for detecting urban areas; for example, the team used it to map urbanization in India. This allows scientists and governments to study changes in urbanization and industrialization over time.

Stanford Engineers Propose a Technology to Break the Net Neutrality Deadlock

Stanford News, 9/13/2016

The debate over net neutrality has largely focused on whether Internet service providers should allow some content providers to negotiate faster/cheaper access to their content for users. This article describes a prototyped system that would allow users to designate which content they want to special access to. Net neutrality has been seen as a digital divide issue; wide adoption of a user-choice system would change the parameters in that debate.

A Beauty Contest Was Judged by AI and the Robots Didn’t Like Dark Skin

The Guardian, 9/8/2016

Beauty.AI developed a set of algorithms to judge photos according to five factors in human standards of beauty; it disproportionately chose photos of white people. The article discusses the potential consequences of emergent bias in algorithms and/or datasets in general, including more consequential examples like predictive policing.

The Ad-Blocking Browser That Pays the Sites You Visit

Wired, 9/1/2016

The Brave web browser (released earlier this year) allows only ads that don’t track users from site to site; it has now added a feature to record how much time users spend on different sites and allow them to send micropayments to those publishers. The article raises examples of how the web has impacted the economics of media and publishing, and also touches on online tracking, data anonymization and de-anonymization, and even Bitcoin.

Inferring Urban Travel Patterns From Cellphone Data

MIT News, 8/29/2016

Researchers are using data on the locations people make calls from to model the movement patterns of Boston commuters; the system may replace or supplement surveys of residents. The article discusses the benefits of gathering and processing more data more quickly and cheaply, though students may be able to identify some disadvantages of using call data.

As FBI Warns Election Sites Got Hacked, All Eyes Are on Russia

Wired, 8/29/2016

Hackers have broken into the Illinois and Arizona state boards of elections’ records, following hacks of the Democratic National Committee and the Clinton campaign in the last couple of months. This highlights concerns about the security of voter records and even ballot integrity, including effects on U.S. citizens’ confidence in election results.

How an Algorithm Learned to Identify Depressed Individuals by Studying Their Instagram Photos

MIT Technology Review, 8/19/2016

Researchers have developed a machine-learning algorithm that achieves 70% recall in identifying depressed individuals by characteristics of their (pre-diagnosis) Instagram photo posts. This is a great example of a medical development with great potential for benefit (early diagnosis and treatment) that also raises serious concerns (privacy, misuse of the information, misprediction). It’s also an example of Mechanical Turk being used as a research platform.