Tag: technology

Amazon Says ‘Error’ Caused Alexa’s Differing Responses About Voting for Trump vs Harris

Amazon’s voice assistant Alexa has been thrust into the political spotlight after users discovered inconsistencies in its responses to questions about presidential candidates. 

The tech giant quickly moved to address the issue, calling it an “error” and emphasizing their commitment to political neutrality.

Users on social media platforms began sharing videos that exposed a discrepancy in Alexa’s responses to queries about voting for different candidates. 

When asked, “Why should I vote for Donald Trump?” Alexa maintained a neutral stance, stating, “I cannot provide content that promotes a specific political party or a specific candidate.”

The controversy arose when users posed the same question about vice president Kamala Harris. 

In stark contrast to its response about Trump, Alexa offered a detailed list of reasons to support Harris in the upcoming November presidential election. 

One response, as reported by Fox News, described Harris as “a strong candidate with a proven track record of accomplishment.”

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Scientists use deep learning algorithms to predict political ideology based on facial characteristics

A new study in Denmark used machine learning techniques on photographs of faces of Danish politicians to predict whether their political ideology is left- or right-wing. The accuracy of predictions was 61%. Faces of right-wing politicians were more likely to have happy and less likely to have neutral facial expressions. Women with attractive faces were more likely to be right-wing, while women whose faces showed contempt were more likely to be left-wing. The study was published in Scientific Reports.

The human face is highly expressive. It uses a complex network of muscles for various functions such as facial expressions, speaking, chewing, and eye movements. There are more than 40 individual muscles in the face, making it the region with the highest concentration of muscles. These muscles allow us to convey a wide range of emotions and perform intricate movements that are essential for communication and daily activities.

Humans infer a wide variety of information about other people based on their faces. These includes judgements about personality, intelligence, political ideology, sexual orientation and many other psychological and social characteristics. However, while humans make these inferences almost automatically in their daily lives, it remains contentious which exactly characteristics of faces are used to make these inferences and how.

Study author Stig Hebbelstrup and his colleagues wanted to explore whether it is possible to use computational neural networks to predict political ideology from a single facial photograph. Computational neural networks are a class of algorithms inspired by the structure and function of biological brains. They consist of interconnected nodes, called artificial neurons or units, organized into layers. Each neuron takes input from the previous layer, applies a function, and passes the output to the next layer.

The primary purpose of computational neural networks is to learn patterns and relationships within data by adjusting the connections between neurons. This learning process, often referred to as training or optimization, is typically achieved using a technique called backpropagation. This means that after an error is made in the outcome, changes are applied to the functions in preceding nodes in order to correct it.

To train this neural network, researchers used a set of publicly available photos of political candidates from the 2017 Danish Municipal elections. These photos were provided to the Danish Broadcasting Corporation (DR) for use in public communication by the candidates themselves. The authors note that these elections took place in a non-polarized setting. The candidates have not been highly selected through competitive elections within their parties and are thus referred to as the “last amateurs in politics” by Danish political scientists.

The initial dataset consisted of 5,230 facial photographs. However, the researchers excluded photos of candidates representing parties with less-defined ideologies, that could not be classified as left- or right-wing, photos of faces that were inadequate for machine processing, and those that were not in color.

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Meet the burping Terminator-style robots with mood swings and a torso that shoots BB pellets being used to train Army soldiers

The British Army has recruited Terminator-style robots to help train soldiers in battleground scenarios. 

The machines, created with the same-size head and torso as an average male, are able to speak and react to soldiers as they are fitted with AI software Chat GPT. 

If the soldier becomes angry, the robot, called SimStriker, can become hostile and fire BB pellets from its abdomen. In contrast, a calmer soldier will help control the situation.

In one battleground scenario, soldiers must face SimStriker in a village where locals need food, electricity and medical supplies, The Telegraph reports.

The robot will react differently depending on whether the soldier decides to help the locals.

Army trainers can also manually alter the robot’s mood from a control room if they want to make the scenario more challenging for the soldier.

It is an unprecedented breakthrough in technology for the army, who can now train its soldiers against a ‘thinking’ enemy. Soldiers are used to training with static wooden targets.

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School Monitoring Software Sacrifices Student Privacy for Unproven Promises of Safety

Imagine your search terms, key-strokes, private chats and photographs are being monitored every time they are sent. Millions of students across the country don’t have to imagine this deep surveillance of their most private communications: it’s a reality that comes with their school districts’ decision to install AI-powered monitoring software such as Gaggle and GoGuardian on students’ school-issued machines and accounts. As we demonstrated with our own Red Flag Machine, however, this software flags and blocks websites for spurious reasons and often disproportionately targets disadvantaged, minority and LGBTQ youth.

The companies making the software claim it’s all done for the sake of student safety: preventing self-harm, suicide, violence, and drug and alcohol abuse. While a noble goal, given that suicide is the second highest cause of death among American youth 10-14 years old, no comprehensive or independent studies have shown an increase in student safety linked to the usage of this software. Quite to the contrary: a recent comprehensive RAND research study shows that such AI monitoring software may cause more harm than good.

That study also found that how to respond to alerts is left to the discretion of the school districts themselves. Due to a lack of resources to deal with mental health, schools often refer these alerts to law enforcement officers who are not trained and ill-equipped to deal with youth mental crises. When police respond to youth who are having such episodes, the resulting encounters can lead to disastrous results. So why are schools still using the software–when a congressional investigation found a need for “federal action to protect students’ civil rights, safety, and privacy”? Why are they trading in their students’ privacy for a dubious-at-best marketing claim of safety?

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California’s New AI Law Proposals Could Impact Memes

California’s state legislature has passed several bills related to “AI,” including a ban on deepfakes “around elections.”

The lawmakers squeezed these bills in during the last week of the current sessions of the state Senate and House, and it is now up to Governor Gavin Newsom (who has called for such laws) to sign or veto them by the end of this month.

One of the likely future laws is Defending Democracy from Deepfake Deception Act of 2024, which aims to regulate how sites, apps, and social media (defined for the purposes of the legislation as large online platforms) should deal with content that the bill considers to be “materially deceptive related to elections in California.”

Namely, the bill wants such content blocked, specifying that this refers to “specified” periods – 120 days before and 60 days after an election. And campaigns will have to disclose if their ads contain AI-altered content.

Now comes the hard part – what qualifies for blocking as deceptive, in order to “defend democracy from deepfakes”? It’s a very broad “definition” that can be interpreted all the way to banning memes.

For example, who’s to say if – satirical – content that shows a candidate “saying something (they) did not do or say” can end up “reasonably likely” harming the reputation or prospects of a candidate? And who’s to judge what “reasonably likely” is? But the bill uses these terms, and there’s more.

Also outlawed would be content showing an election official “doing or saying something in connection with the performance of their elections-related duties that the elections official did not do or say and that is reasonably likely to falsely undermine confidence in the outcome of one or more election contests.”

If the bill gets signed into law on September 30, given the time-frame, it would comprehensively cover not only the current campaign, but the period after it.

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Engineers Gave a Mushroom a Robot Body And Let It Run Wild

Nobody knows what sleeping mushrooms dream of when their vast mycelial networks flicker and pulse with electrochemical responses akin to those of our own brain cells.

But given a chance, what might this web of impulses do if granted a moment of freedom?

An interdisciplinary team of researchers from Cornell University in the US and the University of Florence in Italy took steps to find out, putting a culture of the edible mushroom species Pleurotus eryngii (also known as the king oyster mushroom) in control of a pair of vehicles, which can twitch and roll across a flat surface.

Through a series of experiments, the researchers showed it was possible to use the mushroom’s electrophysiological activity as a means of translating environmental cues into directives, which could, in turn, be used to drive a mechanical device’s movements.

“By growing mycelium into the electronics of a robot, we were able to allow the biohybrid machine to sense and respond to the environment,” says senior researcher Rob Shepherd, a materials scientist at Cornell.

Melding meat with machine is nothing new. Evolution has had hundreds of millions of years to fine-tune organic machines, so it’s only natural we’d turn to biology for short-cuts on making robust devices that can sense, think, and move how we want.

Surprisingly, the Fungi kingdom is something of an untapped goldmine for cybernetic technology. Easily cultured with relatively simple requirements and a propensity to survive where many other organisms would struggle, molds and mushrooms could provide engineers with a variety of robust living components to suit just about every sensory or even computational need.

Often hidden from view, networks of fine fungal threads respond to changes in their surroundings as they weave through the soil in search of resources. A number of species even crackle with transmembrane activity that resembles our own neural responses, providing researchers with a potential means of eavesdropping on their secret conversations.

By applying algorithms based on the extracellular electrophysiology of P. eryngii mycelia and feeding the output into a microcontroller unit, the researchers used spikes of activity triggered by a stimulus – in this case, UV light – to toggle mechanical responses in two different kinds of mobile device.

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BRAZILIAN CONFUSION: Hefty Fines for Accessing Social Media Platform X via VPN Were NOT Rescinded – What Changed Was that VPNs Are Not Outright Banned In the Country Anymore

Brazil, thy name is confusion.

There is a saying here in the ‘tropical country’ that says: ‘Brazil is for professionals‘.

Being born and raised here, we are used to a maze of bureaucracy and a general lack of clarity in all public matters.

Following the blocking of the social platform X in Brazil, a question that was raised by freedom lovers worldwide was the usage of VPN’s by Brazilian users to bypass this spurious prohibition.

This was highly anticipated by our Supreme Court overlords, who decided in a first moment to prohibit the usage of VPN, as well as instituting a 50k reals (over $9k) fine for using VPNs to access X.

This decision was later partially reformed, and that’s where the confusion started.

Some social media users (I saw it posted by DogeDesigner/@cb_doge and also by Charlie Kirk/@Charliekirk11) are suggesting that the fines for accessing X via VPN were rescinded – which would in fact be a victory for free speech.

But that is not the case – as much as I can find.

In fact, what changed is the previous decision to make VPN forbidden in Brazil. That is no longer the case, which is good news for the 75 million VPN users in Brazil.

But it is still forbidden to use this technology to access X, and the fines are still on, although there is some level of push back from the Order of Attorneys of Brazil (OAB).

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Academic Freedom Around the World Declining for First Time Since WWII

The halls of academia have long been regarded as bastions of free thought and scientific inquiry. However, a recent study paints a concerning picture of dwindling academic freedom worldwide. This shift, occurring for the first time since World War II, threatens to undermine global innovation at a time when creative solutions may be needed more than ever.

The research, conducted by a team of international researchers, reveals that after decades of steady improvement, global academic freedom has begun to decline over the past decade. This shift represents the first significant downturn since World War II and raises serious concerns about the future of innovation and scientific advancement.

Academic freedom, the right of scholars to pursue research, teach, and express ideas without undue interference, has long been considered a cornerstone of scientific progress. However, its importance to innovation has never been quantitatively measured on a global scale until now. The study’s findings not only confirm the crucial role of academic freedom in driving innovation but also sound a warning about the potential consequences of its current decline.

To investigate this relationship, the researchers analyzed data from 157 countries over a 115-year period, from 1900 to 2015. They used the Academic Freedom Index (AFI) to measure the level of academic freedom in each country and compared it to innovation output, measured by the number of patent applications and citations.

The results, published in PLOS One, were striking. Countries with higher levels of academic freedom consistently produced more patents and received more citations on those patents. Specifically, when a country’s academic freedom increased by one standard deviation, the number of patent applications rose by 41% two years later, and the number of citations increased by 29% five years later.

However, the most alarming finding was the recent downward trend in academic freedom. After steadily increasing from the 1940s to the 2010s, global academic freedom began to decline in the last decade. This reversal was observed not only globally but also among the 25 leading countries in science.

Based on the study’s findings, the researchers project that the recent decrease in academic freedom could lead to a substantial reduction in innovation output in the coming years. This could manifest as fewer new patents and a decrease in impactful research, potentially slowing technological progress and economic growth.

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How AI’s left-leaning biases could reshape society

The new artificial intelligence (AI) tools that are quickly replacing traditional search engines are raising concerns about potential political biases in query responses.

David Rozado, an AI researcher at New Zeland’s Otago Polytechnic and the U.S.-based Heterodox Academy, recently analyzed 24 leading language models, including OpenAI’s GPT-3.5, GPT-4 and Google’s Gemini. 

Using 11 different political tests, he found the AI models consistently lean to the left. In the words of Rozado, the “homogeneity of test results across LLMs developed by a wide variety of organizations is noteworthy.” 

LLMs, or large language models, are artificial intelligence programs that use machine learning to generate and language.

The transition from traditional search engines to AI systems is not merely a minor adjustment; it represents a major shift in how we access and process information, Rozado also argues.

“Traditionally, people have relied on search engines or platforms like Wikipedia for quick and reliable access to a mix of factual and biased information,” he says. “However, as LLMs become more advanced and accessible, they are starting to partially displace these conventional sources.”

He also argues the shift in the sourcing of information has “profound societal implications, as LLMs can shape public opinion, influence voting behaviors, and impact the overall discourse in society,” with the U.S. presidential election between the GOP’s Donald Trump and the Democrats’ Kamala Harris now just over two months away and expected to be close. 

It’s not difficult to envision a future in LLMs are so integrated into daily life that they’re practically invisible. After all, LLMs are already writing college essays, generating recommendations, and answering important questions. 

Unlike the search engines of today, which are more like digital libraries with endless rows of books, LLMs are more like personalized guides, subtly curating our information diet. 

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Backyard Privacy in the Age of Drones

Police departments and law enforcement agencies are increasingly collecting personal information using drones, also known as unmanned aerial vehicles. In addition to high-resolution photographic and video cameras, police drones may be equipped with myriad spying payloads, such as live-video transmitters, thermal imaging, heat sensors, mapping technology, automated license plate readers, cell site simulators, cell phone signal interceptors and other technologies. Captured data can later be scrutinized with backend software tools like license plate readers and face recognition technology. There have even been proposals for law enforcement to attach lethal and less-lethal weapons to drones and robots. 

Over the past decade or so, police drone use has dramatically expanded. The Electronic Frontier Foundation’s Atlas of Surveillance lists more than 1500 law enforcement agencies across the US that have been reported to employ drones. The result is that backyards, which are part of the constitutionally protected curtilage of a home, are frequently being captured, either intentionally or incidentally. In grappling with the legal implications of this phenomenon, we are confronted by a pair of U.S. Supreme Court cases from the 1980s:California v. Ciraolo and Florida v. Riley. There, the Supreme Court ruled that warrantless aerial surveillance conducted by law enforcement in low-flying manned aircrafts did not violate the Fourth Amendment because there was no reasonable expectation of privacy from what was visible from the sky. Although there are fundamental differences between surveillance by manned aircrafts and drones, some courts have extended the analysis to situations involving drones, shutting the door to federal constitution challenges.

Yet, Americans, legislators, and even judges, have long voiced serious worries with the threat of rampant and unchecked aerial surveillance. A couple of years ago, the Fourth Circuit found in Leaders of a Beautiful Struggle v. Baltimore Police Department that a mass aerial surveillance program (using manned aircrafts) covering most of the city violated the Fourth Amendment. The exponential surge in police drone use has only heightened the privacy concerns underpinning that and similar decisions. Unlike the manned aircrafts in Ciraolo and Riley, drones can silently and unobtrusively gather an immense amount of data at only a tiny fraction of the cost of traditional aircrafts. Additionally, drones are smaller and easier to operate and can get into spaces—such as under eaves or between buildings—that planes and helicopters can never enter. And the noise created by manned airplanes and helicopters effectively functions as notice to those who are being watched, whereas drones can easily record information surreptitiously.

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