Sunday, July 12, 2020

Bias and Nostalgia in Hergé’s Tintin

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Anant Jani

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Bias and Nostalgia in Hergé’s Tintin

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Global Views 360

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July 12, 2020

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A collection of Tintin Comics

A collection of Tintin Comics | Source: Mills Baker via Flickr

Some of my fondest memories involve sitting under the guava or the European gumtree, perched on the wall of our garden as the sunlight dappled on an old copy of a Tintin comic. For some years, at least, before the gumtree was cut down, the leaves bore witness to me following the globe-trotting adventures of the Belgian reporter, replete with hilariously-named companions and witty play of words. My nostalgia is as much for the inked characters and words on the paper, as for the musty smell of the oft-thumbed and yellowed pages of the comic, and the permanently romanticized view of the sunny garden. The comics have left a palpable imprint on my sense of humour and love of a certain kind of literature. And perhaps it is this imprint, along with my pleasant nostalgia, that makes it a struggling task to accept Hergé’s racism through his Tintin comics.

Hergé’s (or Georges Prosper Remi’s) writings were, undeniably, a product of their times. His first two series in the Adventures of Tintin comics, Tintin in the land of the Soviets (1929) and Tintin in Congo (1931), have famously been the subject of much debate, since the late 1900s. In Soviets, Hergé offers a crude critique against Marxism – meant to inculcate anti- Soviet sentiments in the European youth at the time, by portraying the Bolsheviks as inherently evil without a full comprehension of how they rose to power or what their political views were.

In Congo, African tribes and leaders are portrayed as either infantile, or in need of saving, to the extent that Tintin becomes the embodiment of fairness for young Africans, even having a temple made after him. Congo itself was a colony of Belgium from 1908 to 1960, one of the two colonies that Belgium governed, and the comics grossly ignore the labour politics of the Congolese and their efforts in both the World Wars. It was not until after the decolonisation of Africa that European perception of ex-African colonies changed.

Much of the modern debate surrounding the banning of select Tintin comics is centred around the depicitons of big-game hunting in Congo and the anti-Semitism in the The Shooting Star. Besides the uncomfortable portrayals of the Congolese, a few panels in the 1931 edition of Congo depicted Tintin drilling a hole into a live Rhinoceros, filled with dynamite, and blown up. In the 1946 edition, this scene was replaced, with Herge apologizing for what he recognized as “youthful transgressions''. In the Shooting Star, the villainous financer was renamed, from the Jewish Blumstein to the innocuous Bohlwinkel.

Hergé’s subsequent works became politically neutral, written after the German occupation of Belgium and the German takeover of Le Vingtième Siècle, the conservative Catholic newspaper he wrote for. While the white-saviour narrative continued with Tintin leading as the embodiment of Europe that “natives” had to follow, the later works are much less politically biased.

However, he prefaced Tintin in America with a critique against the racism in the United States, alongside his anti-imperial stance in The Blue Lotus. He is also known, famously, for not joining with the far-right extremist forces in German-occupied Belgium at the time, as many of his colleagues had. Michael Farr, a British expert on The Adventures of Tintin series, claimed after a meeting with Hergé that “you couldn’t meet someone more open and less racist”. Others have called him an opportunist, heaving towards the side that was popular. Perhaps this was indeed the case, or equally, perhaps Hergé did change his views, and his writings in Soviet and Congo are merely reflective of the predominant Belgian culture at the time.

At any rate, the question still remains: how do we read, or re-read, Hergé (or many such childhood-favourite authors, like Dr. Seuss)? Shelving the books and forgetting the authors is undoubtedly impossible, and misguided besides. A recognition of the biases, and a plethora of context surrounding these texts must be made available at all times. A celebration of a character or a person must not come at the cost of ignoring their uncomfortable stances.

The depiction of Africa in 20th century comics has been abysmal. A tendency of depicting the 'other' as a 'noble-savage' is a familiar concern to those readers who have spent much of their lives in recently liberated colonies. It is, perhaps, especially imperative for such readers to keep this in mind and not repeat them.

In our Consumerist times, it seems, we sometimes forget to start dialogues on themes that are unfamiliar and maybe even uncomfortable to us. We forget which stories desperately need to be told and which have not seen the light of day under the shadow of popular literature.

This, at least, is what I have strived to do: to maintain a balance between nostalgia and a recognition of biases. My memory of the Tintin comics will remain just as romantic as the idyllic memory I started with in the beginning of this article.

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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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