Large language models (LLMs) are increasingly capable of simulating human behavior, offering cost-effective ways to estimate user responses to various surveys and polls. However, the questions in these surveys usually reflect socially understood attitudes: the patterns of attitudes of old/young, liberal/conservative, as understood by both members and non-members of those groups. It is not clear whether the LLM binding is \emph{deep}, meaning the LLM answers as a member of a particular in-group would, or \emph{shallow}, meaning the LLM responds as an out-group member believes an in-group member would. To explore this difference, we use questions that expose known in-group/out-group biases. This level of fidelity is critical for applying LLMs to various political science studies, including timely topics on polarization dynamics, inter-group conflict, and democratic backsliding. To this end, we propose a novel methodology for constructing virtual personas with synthetic user "backstories" generated as extended, multi-turn interview transcripts. This approach is justified by the theory of \emph{narrative identity} which argues that personality at the highest level is \emph{constructed} from self-narratives. Our generated backstories are longer, rich in detail, and consistent in authentically describing a singular individual, compared to previous methods. We show that virtual personas conditioned on our backstories closely replicate human response distributions (up to an 87% improvement as measured by Wasserstein Distance) and produce effect sizes that closely match those observed in the original studies of in-group/out-group biases. Altogether, our work extends the applicability of LLMs beyond estimating socially understood responses, enabling their use in a broader range of human studies.

A former U.S. military interpreter says the Taliban have begun executing U.S. allies away from Kabul where there is not media attention. The House Problem Solvers Caucus has voted to officially call on President Joe Biden to extend the August 31 withdrawal date from Afghanistan as the administration scrambles to evacuate Americans stranded in Taliban-controlled Kabul. "As Democrats and Republicans, we stand united in our commitment to protecting U.S. citizens, diplomats, intelligence officers, and our foreign partners who are currently attempting to flee Afghanistan," the statement endorsed by the caucus read. "In this time of tremendous danger, politics must be put aside to advance our common goals. From this week's bipartisan Member briefing, it is apparent that the Administration's set date for departure from Afghanistan on August 31st does not provide enough time to evacuate all American citizens and our partners. We respectfully call on the Administration to reconsider its timeline and provide a clear plan to Congress that will result in the completion of our shared national objectives."

Face-scanning technology is inspiring a wave of privacy fears as the software creeps into every corner of life in the United States and Europe -- at border crossings, on police vehicles and in stadiums, airports and high schools. But efforts to check its spread are hitting a wall of resistance on both sides of the Atlantic. One big reason: Western governments are embracing this technology for their own use, valuing security and data collection over privacy and civil liberties. And in Washington, U.S. President Donald Trump's impeachment and the death of a key civil rights and privacy champion have snarled expectations for a congressional drive to enact restrictions. The result is an impasse that has left tech companies largely in control of where and how to deploy facial recognition, which they have sold to police agencies and embedded in consumers' apps and smartphones.

A government watchdog has revealed that the FBI has access to about 640 million photographs -- including from driver's licenses, passports and mugshots -- that can be searched using facial recognition technology. The figure reflects how the technology is becoming an increasingly powerful law enforcement tool, but is also stirring fears about the potential for authorities to intrude on the lives of Americans. It was reported by the Government Accountability Office (GOA) at a congressional hearing in which both Democrats and Republicans raised questions about the use of the technology. The FBI maintains a database known as the Interstate Photo System of mugshots that can help federal, state and local law enforcement officials. The images include driver's licenses, passports and mugshots - prompting concerns of pivacy invasion It contains about 36 million photographs, according to Gretta Goodwin of the GAO.

A virtual assistant, Alisa, is throwing its name in the hat to run against incumbent Vladmir Putin in the 2018 Russian presidential elections. First, let's just dismiss this idea as stupid. Okay, now let's give it a second look – because it actually makes a lot of sense. Maybe it's time to, academically at least, consider alternative political systems based on more logical and rational thought processes – like one that could elect Russia's Alisa. So far, the virtual assistant has over 80,000 "votes" from citizens requesting a place for it on the ballot next year.

The House voted Wednesday to speed the introduction of self-driving cars by giving the federal government authority to exempt automakers from safety standards not applicable to the technology, and to permit deployment of up to 100,000 of the vehicles annually over the next several years. The bill was passed by a voice vote, and now goes to the Senate. State and local officials have raised concern that it limits their ability to protect the safety of their citizens by giving to the federal government sole authority to regulate the vehicles' design and performance. The House voted Wednesday, Sept. 6, 2017, to speed the introduction of self-driving cars by giving the federal government authority to exempt automakers from safety standards not applicable to the technology, and to permit deployment of up to 100,000 of the vehicles annually over the next several years. Members of the Senate Commerce committee are also working on self-driving car legislation, but a bill hasn't been introduced.

Los Angeles Mayor Eric Garcetti urges the public to ask their members of Congress to support continued federal funding of the earthquake early warning system. Los Angeles Mayor Eric Garcetti urges the public to ask their members of Congress to support continued federal funding of the earthquake early warning system. In this hyper-partisan era, there may be one issue that unites California Democrats and Republicans: Earthquakes. Elected officials from both parties have supported an earthquake early warning system for the West Coast that, after years of work, was scheduled to begin its first limited public operation next year. But President Trump's budget proposal calls for cuts that experts say would kill the warning network.

Exploratory data analysis just got more fun. Feel free to use the Gitter community gitter.im/scattertext If you cannot (or don't want to) install spaCy, substitute nlp spacy.en.English() lines with nlp scattertext.WhitespaceNLP.whitespace_nlp. Note, this is not compatible with word_similarity_explorer, and the tokenization and sentence boundary detection capabilities will be low-performance regular expressions. Python 2.7 support is experimental.