Friday, September 18, 2020

Restoration of Law & Order: The War-Cry which may help Trump defeat Joe Biden in November 2020

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Vanshita Banuana

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Restoration of Law & Order: The War-Cry which may help Trump defeat Joe Biden in November 2020

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Global Views 360

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September 18, 2020

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Donald Trump at a presidential elections rally

Donald Trump at a presidential elections rally | Source: Gage Skidmore via Flickr

At the peak of the “Black Lives Matter” protest in June 2020, against the brutal killing of George Floyd by the police, the US President Donald Trump signed an Executive Order on Safe Policing for Safe Communities. It is now September, and as Black Lives Matter protests— and the police brutality that ignited them— continue amidst a pandemic leaving over two hundred thousand Americans dead and millions infected, Trump’s fear-mongering distortions of events also continues.

The executive order sets requirements for police “certification and credentialing” of law enforcement agencies, and links the credentials to discretionary funding. It bans chokeholds except where deadly force is allowed by law. A database will be created to share information and track incidents of excessive use of force, terminations or de-certifications of officers, criminal convictions for on-duty conduct, and so on. Additionally, the order asks for surveys and community support programs to address mental health, homelessness and addiction in context of law enforcement’s response to them. Lastly, the order proposes that new legislation be developed to increase funding and resources provided to law enforcement.

While announcing the executive order, Trump called for a “restoration of law and order” and more funding for police at a time when Americans are protesting in cities across the country to reduce police funding and presence in order to combat police brutality. He claimed to want to put a stop to “looting and arson,” further remarking that Americans want law and order even if they “may not say it” or may not “even know that’s what they want”. Additionally, he believed the percentage of bad police officers to be very tiny.

The American Civil Liberties Union (ACLU) responded to the announcement, and called Trump’s call for “law and order” a racist dog-whistle specifically intended for his voter base in light of the upcoming election, and reiterated the need for lesser police presence. Allocation of discretionary funds, mentioned in the executive order, has been known to lead to increased militarisation of the police. They observed that Trump used the word “race” once and never used the word “racism,” and that he was surrounded by law enforcement officers throughout the announcement and his prepared remarks.

Use of fear-mongering to shore up the support for electoral benefit is not something new which Trump is employing, but a time-tested tool for many leaders in the Republican Party. The phrase “law and order” has a long cultural history in America, even before its use by politicians was popularised, and therefore racialised (if it wasn’t already).  

President Richard Nixon’s TV ads in the 60s showed middle-aged white women walking nervously down city streets at night. Trump’s false claims of Biden wanting to defund the police are complemented by his recent campaign ad that shows an elderly woman at home alone, who calls the police when a burglar breaks in. However, she is told that the police can no longer serve her due to being defunded. Setting aside the misconceptions about what defunding the police would look like, the ad is clearly designed to create panic at the thought of a fantasised future, one that Trump and his family like to call “Biden’s America” every time they post pictures of present-day Trump’s apocalyptic America.

It is definitely not unlike Trump to use racist rhetoric about crime meant to cause fear. It was one of his biggest selling points in the 2016 election as well, promising a border wall and anti-immigration policy to keep out immigrants— mostly Mexicans— who he claimed would bring crime and drugs into America. This year Trump has revived the argument by acting as the saviour of the suburbs, who he claims are under the attack of calls for desegregation. To that extent, at the 2020 Republic National Convention, Trump invited the McCloskeys, the couple who brandished firearms at Black Lives Matters protestors, to speak about “forced rezoning,” which they alleged would make their suburban neighbourhood unsafe. Nixon’s comments about the “city jungle” threatening the suburbs come to mind.

President Trump’s election campaign flag with Confederate flag | Source: Gilbert Mercier via Flickr

Many would notice that the racism in Trump’s statements is often barely covered up by his abstract and vague choice of words. The message, whether in 2016 or 2020, remains unmistakably the same: he is telling rich and middle class white people— painted as the peaceful victims— that he will protect them from violence caused by the ‘other,’ i.e., poor people of colour.

This fear of the ‘other,’ the angry Black American, is the same fear used by Republican Presidential candidate (and later President) Richard Nixon in 1968. The law-and-order rhetoric that evolved during that election period can be connected to 21st century ‘tough-on-crime’ policies, both of which have heavy racial undertones and are weaponized by Republicans as well as Democrats.

Is Donald Trump the new age Richard Nixon? That might seem to be overstretched, but quite a few traits and  similarities can be drawn between 2020 and 1968, perhaps most of all due to the widespread protests and clashes with police that erupted after the assassination of civil rights champion Martin Luther King Jr. Another major political and cultural event of the time was the Vietnam War, which led to a feeling of disorder that many Americans might be feeling at present as well. Trump is using promises of imposing “law and order” to project a strongman image; the desire to project such an image, however, hypocritically leads Trump to encourage violence where it benefits him.

However, these strategies aren’t as successful as Trump wants them to be— least of all successful enough to cover up his gross mishandling of the COVID-19 pandemic. Additionally, the suburbs have not remained as ‘pure’ as they might seem in Trump’s eyes; they have grown in diversity of wealth and race, almost parallel to cities. Trump is out of his depth when forced to reckon with mass unemployment, preventable deaths, and science, and he would do anything to bring the focus back to his comfort zone, which is why it is unsurprising when he uses Black Lives Matter protests and renewed conversation around policing to spread unfounded alarms about increased crime and violence.

According to recent polling data, while neither Trump nor Biden are viewed favourably by any significant margin when it comes to law enforcement, Biden is surely being viewed as more trustworthy when it comes to handling a crisis like the pandemic. Trump’s constant barrage of tweets and other announcements are less appreciated or supported when they cause further confusion in an already extremely chaotic environment. It is hard to imagine trusting a President who tweets “when the looting starts, the shooting starts” to remain calm, organised or level-headed in any manner.  

While many may have expected Trump’s voter base to fall for the same old, recycled talking points, the public health crisis and economic meltdown took the conversation away from it. Now President Trump is desperately trying to take control of the narrative and scare voters to back him in November 2020.

There is some method to his apparent madness. The US President is not elected by securing  the majority of the popular vote, they are chosen by securing a majority of votes in the electoral college. There are different modelling of US poll results which predicts that Trump may lose by over five million popular votes but still win the Presidency due to scoring a majority of electoral college votes.

The constant hammering of being the “Law and Order” President and painting Joe Biden’s support for Black Lives Matter protest as the “support for lawlessness” is the only plausible way for Trump to gain a majority of the electoral college vote and retain the US Presidency in November 2020. It is to be seen whether the voters fear the COVID-19 & economic meltdown more than the Law and Order.

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February 4, 2021 5:22 PM

Automated Facial Recognition System of India and its Implications

On 28th of June 2019, the National Crime Records Bureau (NCRB) opened bids and invited Turnkey Solution providers to implement a centralized Automated Facial Recognition System, or AFRS, in India. As the name suggests, AFRS is a facial recognition system which was proposed by the Indian Ministry of Home Affairs, geared towards modernizing the police force and to identify and track criminals using Facial Recognition Technology, or FRT.

The aforementioned technology uses databases of photos collected from criminal records, CCTV cameras, newspapers and media, driver’s license and government identities to collect facial data of people. FRT then identifies the people and uses their biometrics to map facial features and geometry of the face. The software then creates a “facial signature” based on the information collected. A mathematical formula is associated with each facial signature and it is subsequently compared to a database of known faces.

This article explores the implications of implementing Automated Facial Recognition technology in India.

Facial recognition software has become widely popular in the past decade. Several countries have been trying to establish efficient Facial Recognition systems for tackling crime and assembling an efficient criminal tracking system. Although there are a few potential benefits of using the technology, those benefits seem to be insignificant when compared to the several concerns about privacy and safety of people that the technology poses.

Images of every person captured by CCTV cameras and other sources will be regarded as images of potential criminals and will be matched against the Crime and Criminal Tracking Networks and Systems database (CCTNS) by the FRT. This implies that all of us will be treated as potential criminals when we walk past a CCTV camera. As a consequence, the assumption of “innocent until proven guilty” will be turned on its head.

You wouldn’t be surprised to know that China has installed the largest centralized FRT system in the world. In China, data can be collected and analyzed from over 200 million CCTVs that the country owns. Additionally, there are 20 million specialized facial recognition cameras which continuously collect data for analysis. These systems are currently used by China to track and manipulate the behavior of ethnic Uyghur minorities in the camps set up in Xinjiang region. FRT was also used by China during democracy protests of Hong Kong to profile protestors to identify them. These steps raised concerns worldwide about putting an end to a person’s freedom of expression, right to privacy and basic dignity.

It is very likely that the same consequences will be faced by Indians if AFRS is established across the country.

There are several underlying concerns about implementing AFRS.

Firstly, this system has proven to be inefficient in several instances. In August 2018, Delhi police used a facial recognition system which was reported to have an accuracy rate of 2%. The FRT software used by the UK's Metropolitan Police returned more than a staggering 98% of false positives. Another instance was when American Civil Liberties Union (ACLU) used Amazon’s face recognition software known as “Rekognition” to compare the images of the legislative members of American Congress with a database of criminal mugshots. To Amazon’s embarrassment, the results included 28 incorrect matches.. Another significant evidence of inefficiency was the outcome of an experiment performed by McAfee.  Here is what they did. The researchers used an algorithm known as CycleGAN which is used for image translation. CycleGAN is a software expert at morphing photographs. One can use the software to change horses into zebras and paintings into photographs. McAfee used the software to misdirect the Facial recognition algorithm. The team used 1500 photos of two members and fed them into CycleGAN which morphed them into one another and kept feeding the resulting images into different facial recognition algorithms to check who it recognized. After generating hundreds of such images, CycleGAN eventually generated a fake image which looked like person ‘A’ to the naked eye but managed to trick the FRT into thinking that it was person ‘B’. Owing to the dissatisfactory results, researchers expressed their concern about the inefficiency of FRTs. In fact mere eye-makeup can fool the FRT into allowing a person on a no-flight list to board the flight. This trend of inefficiency in the technology was noticed worldwide.

Secondly, facial recognition systems use machine learning technology. It is concerning and uncomfortable to note that FRT has often reflected the biases deployed in the society. Consequently, leading to several facial mismatches. A study by MIT shows that FRT routinely misidentifies people of color, women and young people. While the error rate was 8.1% for men, it was 20.6% for women. The error for women of color was 34%. The error values in the “supervised study” in a laboratory setting for a sample population is itself simply unacceptable. In the abovementioned American Civil Liberties Union study, the false matches were disproportionately African American and people of color. In India, 55% of prisoners undertrial are either Dalits, Adivasis, or Muslims although the combined population of all three just amounts to 39% of the total population (2011 census). If AFRS is trained on these records, it would definitely deploy the same socially held prejudices against the minority communities. Therefore, displaying inaccurate matches. The tender issued by the Ministry of Home Affairs had no indication of eliminating these biases nor did it have any mention of human-verifiable results. Using a system embedded with societal bias to replace biased human judgement defeats claims of technological neutrality. Deploying FRT systems in law enforcement will be ineffective at best and disastrous at worst.

Thirdly, the concerns of invasion of privacy and mass surveillance hasn’t been addressed satisfactorily. Facial Recognition makes data protection almost impossible as publicly available information is collected but they are analyzed to a point of intimacy. India does not have a well established data protection law given that “Personal data Protection Bill” is yet to be enforced. Implementing AFRS in the absence of a safeguard is a potential threat to our personal data. Moreover, police and other law enforcement agencies will have a great degree of discretion over our data which can lead to a mission creep. To add on to the list of privacy concerns, the bidder of AFRS will be largely responsible for maintaining confidentiality and integrity of data which will be stored apart from the established ISO standard. Additionally, the tender has no preference to “Make in India'' and shows absolutely no objections to foreign bidders and even to those having their headquarters in China, the hub of data breach .The is no governing system or legal limitations and restrictions to the technology. There is no legal standard set to ensure proportional use and protection to those who non-consensually interact with the system. Furthermore, the tender does not mention the definition of a “criminal”. Is a person considered a criminal when a charge sheet is filed against them? Or is it when the person is arrested? Or is it an individual convicted by the Court? Or is it any person who is a suspect? Since the word “criminal” isn’t definitely defined in the tender, the law enforcement agencies will ultimately be able to track a larger number of people than required.

The notion that AFRS will lead to greater efficacy must be critically questioned. San Francisco imposed a total ban on police use of facial recognition in May, 2019. Police departments in London are pressurized to put a stop to the use of FRT after several instances of discrimination and inefficiency. It would do well to India to learn from the mistakes of other countries rather than committing the same.

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