129 research outputs found

    Stopping Police in Their Tracks: Protecting Cellular Location Information Privacy in the Twenty-First Century

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    Only a small fraction of law enforcement agencies in the United States obtain a warrant before tracking the cell phones of suspects and persons of interest. This is due, in part, to the fact that courts have struggled to keep pace with a changing technological landscape. Indeed, courts around the country have issued a disparate array of holdings on the issue of warrantless cell phone tracking. This lack of judicial uniformity has led to confusion for both law enforcement agencies and the public alike. In order to protect reasonable expectations of privacy in the twenty-first century, Congress should pass legislation requiring law-enforcement agencies to obtain a warrant based upon probable cause before they can track a cell phone except in a limited set of time-sensitive situations and emergencies. This Issue Brief describes the technology police use to track cell phones, discusses the need for federal legislation, concludes that current Fourth Amendment jurisprudence is inadequate to address cell phone tracking, analyzes two bills dealing with “geolocation information” privacy that legislators have introduced in Congress, and ultimately concludes that one of those bills is superior to the other

    Still Waiting: Green Card Problems Persist for High Skill Immigrants

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    Over the past several months, skilled foreign nationals have seen no improvement in their prospects for obtaining green cards and, in fact, wait times are likely to increase in employment-based immigration categories. The U.S. Department of State reports a wait time may be developing for prospective immigrants in the employment-based first preference (EB-1) category, which previously had no backlog. In another new development, skilled foreign nationals from countries other than China and India in the employment-based second preference (EB-2) will soon experience backlogs. And for at least the rest of Fiscal Year 2012, the U.S. Department of State is not accepting new green card applications for nationals of China and India in the EB-2 category. An October 2011 analysis by the National Foundation for American Policy concluded wait times for employment-based green cards sponsored today can last 5 years or even decades, depending on the category and country of origin. The analysis found projected waits for Indians of 8 years or more in the EB-2 category and up to 70 years for Indians in the EB-3 (employment-based third preference) category if sponsored today for an employment-based green card, while a Chinese immigrant sponsored today in the EB-3 category could wait two decades

    Cedar Mesa Proposal Good for All

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    A coalition of tribes, led by the Hopi and the Navajo, and including the Utes of Colorado and Utah and several of New Mexico’s pueblos have asked President Obama to use the Antiquities Act to declare this landscape a national monument to be protected alongside other nearby national treasures, such as Arches, Canyonlands, Bryce Canyon and Zion National Parks

    On the Possibilities of AI-Generated Text Detection

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    Our work focuses on the challenge of detecting outputs generated by Large Language Models (LLMs) from those generated by humans. The ability to distinguish between the two is of utmost importance in numerous applications. However, the possibility and impossibility of such discernment have been subjects of debate within the community. Therefore, a central question is whether we can detect AI-generated text and, if so, when. In this work, we provide evidence that it should almost always be possible to detect the AI-generated text unless the distributions of human and machine generated texts are exactly the same over the entire support. This observation follows from the standard results in information theory and relies on the fact that if the machine text is becoming more like a human, we need more samples to detect it. We derive a precise sample complexity bound of AI-generated text detection, which tells how many samples are needed to detect. This gives rise to additional challenges of designing more complicated detectors that take in n samples to detect than just one, which is the scope of future research on this topic. Our empirical evaluations support our claim about the existence of better detectors demonstrating that AI-Generated text detection should be achievable in the majority of scenarios. Our results emphasize the importance of continued research in this are

    Cybervandalism or Digital Act of War? America\u27s Muddled Approach to Cyber Incidents Will Not Deter More Crises

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    If experts say a malicious [cyber] code \u27 has similar effects to a physical bomb, \u27 and that code actually causes a stunning breach of global internet stability, is it really accurate to call that event merely an instance of a cyber attack ? Moreover, can you really expect to deter state and non-state actors from employing such code and similarly hostile cyber methodologies if all they think that they are risking is being labeled as a cyber-vandal subject only to law enforcement measures? Or might they act differently if it were made clear to them that such activity is considered an armed attack \u27 against the United States and that they are in jeopardy of being on the receiving end of a forceful, law-of-war response by the most powerful military on the planet? Of course, if something really is just vandalism, the law enforcement paradigm, with its very limited response options, would suffice. But when malevolent cyber activity endangers the reliability of the internet in a world heavily dependent on a secure cyberspace, it is not merely vandalism. Rather, it is a national and international security threat that ought to be characterized and treated as such. Unfortunately, the United States\u27 current approach is too inscrutable and even contradictory to send an effective deterrence message to potential cyber actors. This needs to change
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