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Brazil: Recreational harassment | Opinion

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A march to defend women's rights in São Paulo in 2019.
A march to defend women’s rights in São Paulo in 2019.Cris Faga

The video traveled back and forth between Brazil and Egypt in less than 24 hours. The images were posted by a white Brazilian male, camera in hand as he filmed a young Egyptian woman selling papyrus products. While the woman described the merchandise to him, the man chatted away to her in Portuguese. The woman was smiling, as polite people do during intercultural, linguistic exchanges when they want the person who is attempting to communicate with them to feel at ease. She didn’t know it, but the anonymous Brazilian was sexually harassing her. Instead of asking questions about the papyrus, he was making obscene remarks about sex and the male organ: “You all like it nice and hard, right?” “Long is nice too, right?” he says on the recording, while he and another Brazilian man laugh. A case of recreational harassment.

Why “recreational harassment” and not just harassment? With recreational harassment, it is harder to identify the violence perpetrated against the victim, because when someone watches or shares the images, their amusement actually makes them complicit with the violence. Recreational harassment occurs when a woman is harassed as part of a project of domination implemented through other men’s laughter. It is not liberating laughter (ridendo castigat mores, a Latin phrase meaning that one corrects customs by laughing at them), but laughter grounded in stereotypes and regimes of domination. Here is how José Adilson Moreira has defined “recreational racism”: cultural politics grounded in discriminatory practices against racial minorities in the guise of oppressive laughter, which naturalize racial hostility and which the law rarely recognizes as illegal. Engaging in dialogue with Moreira, Carla Akotirene has written about the inseparability of recreational racism and sexism in situations where meme humor is a weapon used to ridicule Black women for various purposes, sometimes to stereotype manifestations of the bodily disempowerment wrought by poverty, like missing teeth, or at other times in an effort to control the non-submissive voices of Black female intellectuals by labeling them “divas” or “angry Black women.” The anonymous Egyptian victim was someone who fit an Islamophobic stereotype: a young Muslim woman wearing a veil.

The Egyptian police identified the physician, who is now being investigated for the crime of sexual harassment

The episode might be interpreted as an isolated incident involving a Latin American macho abroad. But it is not isolated. In 2014, this same Brazilian released another video of himself, this time harassing an Australian woman by asking her to repeat sexual phrases in Portuguese. There is a pattern to this harassment; people who feel superior employ mockery as a power tactic to humiliate people marked by gender or sexuality, race or religion. Hidden behind the obscene comments on the recent video are cultural and gender stereotypes about Egyptian women. The arrogance of this mockery draws from a sense of ethnic and gender superiority on the part of a white patriarchy that, at home or abroad, acts with the certainty that its naturalized privileges guarantee impunity. The Brazilian apparently found nothing embarrassing about what he had done, so he posted the images to his Instagram account, which has nearly one million followers.

This anonymous man roaming the streets of Luxor is a well-known figure in Brazil. He is a medical doctor, a coach specialized in fitness techniques, and a supporter of President Bolsonaro who, more than a year into the pandemic, continues using jargon with a pseudo-scientific veneer to defend treatments of no proven scientific value, like hydroxychloroquine. Yet it would be better to describe him beyond his nationality, as a representative-without-borders of the racist patriarchy that harasses women. When confronted about the scene, the man set his Instagram account to private and justified his actions by saying: “I’m like that. I’m a real jokester.” Brazilian feminists copied the video, translated it, and sent it to women’s groups in Egypt, like the online platform Speak Up, a “feminist initiative to support victims of violence.” This was followed by an immediate online mobilization, with hashtags circulating in both countries and in three languages, Arabic, English, and Portuguese: “expel the Brazilian harasser from Egypt,” “investigate the Brazilian harasser” and “we don’t want harassers in our country.”

The Egyptian police identified the physician, who is now being investigated for the crime of sexual harassment; punishment ranges from a monetary fine to between six months and three years in prison. It was feminists who identified the incident as an instance of sexual harassment – not Instagram, which allowed the images to be posted to the doctor’s account. Only after many young Brazilian and Egyptian feminists reacted and expressed their solidarity did the social media platform determine that the video breached its Community Guidelines, which prohibit “hate speech, bullying and abuse.” The doctor’s apology to the victim tells us what women are up against: “Since I saw what a smiley person you are and how you were joking along with us, I just ended up joking around.” No, victims don’t laugh; recreational mockery is only for the aggressor.

Debora Diniz is a Brazilian anthropologist and researcher at Brown University.

Giselle Carino is an Argentine political scientist and IPPF/WHR director.



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Climate change: Floods, fires, smog: AI delivers images of how climate change could affect your city | USA

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A simulation of New York's Times Square affected by flooding.
A simulation of New York’s Times Square affected by flooding.

The full brunt of the devastating effects of climate change is still a long way off. If we don’t experience the impact directly, it’s difficult to fully internalize the extreme seriousness of the climate crisis.

That’s why a team at the Mila-Quebec Artificial Intelligence Institute, led by Professor Yoshua Bengio, wants to bring it home – right to your doorstep in fact. His team has developed a tool that makes it possible to visualize the effects of floods, wildfires and smog anywhere in the world. Their simulation does this by making use of a generative adversarial network (GAN), a type of machine-learning algorithm. GANs can also produce things such as deepfake images, which are digitally composed of millions of images to create realistic photos of something (or someone) new.

For two years, 30 scientists have worked on the project, which is named after thispersondoesnotexist.com, a website portfolio of deepfake faces. Bengio’s version is called “This Climate Does Not Exist.” All a user has to do is type in an address or select a marker on Google Street View, and then indicate what kind of catastrophe they want to see: flood, wildfire or smog. The algorithm works its magic and returns the image with the requested effect. These images are not intended to be an accurate portrayal of what would happen at each specific location if no action on climate change is taken, but rather are a recreation of the worst possible effects in the scenario of the user’s choice.

The realism is particularly striking in the flooding option, which was the most difficult for Bengio’s team to produce. The algorithm takes the location proposed by the user, automatically places a layer of water on it and then adapts it to the environment of the image itself. The result is hyperrealistic.

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Cibeles Square in Madrid, before and after a hypothetical flooding created by ‘This Climate Does Not Exist.’ The original image is from Google Street View. This Climate Does Not Exist

“One of the most important challenges has been getting the algorithm to simulate flooding in a wide variety of images,” explains Alex Hernandez-Garcia, one of the project’s lead researchers. “One module of the algorithm is in charge of detecting which parts of the image should be covered with water and another module is in charge of generating the water texture by incorporating the context of the image, for example, the reflection of buildings. Finally, these results are combined to generate the final image.”

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The Capitol in Washington DC laboring under the effects of a toxic cloud and flooding, in a simulation created by the team at MILA. The original image is from Google Street View. This Climate Does Not Exist

To detect which parts to cover with water and which to leave unscathed, Hernandez-Garcia and his colleagues combined several artificial intelligence (AI) and machine-learning techniques. “We generated a virtual city that allowed us to make a series of images with and without water. We also adjusted an algorithm that was able to make good predictions in that virtual world, detecting the different parts of a scene: the ground, cars, buildings, trees, people and so on,” he explained. “However, the algorithm must be able to make good predictions based on real images [those from Google Street View].” For the latter, they used generative adversarial networks.

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Mexico City’s enormous Constitution Square, popularly known as El Zócalo, might look like this in a scenario of wildfires and flooding. The original image is from Google Street View. This Climate Does Not Exist

The process is completed in a few seconds, and before displaying the image to the user some information is provided about the causes and consequences of the selected weather phenomenon, and its relationship to climate change. For example, if a flood is chosen, it indicates that flash floods kill about 5,000 people a year, that sea levels are expected to rise by two meters by the end of the century and that this major disruption to the planet will forever alter the lives of at least one billion people by the end of 2050. “If we do nothing, soon we will face major climate catastrophes,” says Professor Bengio, the institute’s scientific director. “This website makes the risks of climate change much more real and personal to people,” he argues.

Generative adversarial networks

The quality of AI took a giant leap forward about a decade ago with the emergence and consolidation of machine learning and deep learning. These techniques are based on training a machine so that it is capable of performing complex tasks after reaching certain conclusions on its own. For example, if you want the algorithm to distinguish between blueberry muffins and chihuahuas, the programmer will feed it a series of examples of each category, followed by thousands of images that are not pre-sorted. The machine will establish which is which, and when it gets it wrong and is made aware of the error, will refine its criteria.

Bengio won the 2018 Turing Award, considered the Nobel Prize of computer science, along with Geoffrey Hinton and Yann LeCun, for their contribution to the development of neural networks. This is a further step in machine learning that attempts to mimic the functioning of the human brain: applying several simultaneous layers of processing to increase performance. Neural networks are behind the most complex classification systems, such as voice assistants or advanced prediction models.

Generative adversarial networks (GANs) go even further. They were invented at the Mila-Quebec Artificial Intelligence Institute in 2014 and are capable of generating new content that looks faultlessly real to the human eye. GANs are behind the increasingly sophisticated deepfake videos of Tom Cruise or Donald Trump now circulating online, in which politicians or celebrities say or act in whichever way their creator likes. They work thanks to competition between two neural networks: one tries to produce images that are as realistic as possible and the other tries to detect whether they are real or a fabrication. This tension is replicated thousands or millions of times and during this process, the generating network learns to create more and more successful images. When the first network succeeds in fooling the second, we have a winning image. From there, a perfectly rendered image of New York City’s Times Square inundated by flooding is just a click away.

The Quebec lab is now using a new type of GAN they have developed to generate the climate change images seen on their website. “In general, the limited availability of images and the need to adapt the algorithm to a multitude of situations have been the main technical challenges we have faced,” says Hernandez-Garcia.

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Assad regime ‘siphons millions in aid’ by manipulating Syria’s currency | Global development

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The Syrian government is siphoning off millions of dollars of foreign aid by forcing UN agencies to use a lower exchange rate, according to new research.

The Central Bank of Syria, which is sanctioned by the UK, US and EU, in effect made $60m (£44m) in 2020 by pocketing $0.51 of every aid dollar sent to Syria, making UN contracts one of the biggest money-making avenues for President Bashar al-Assad and his government, researchers from the Center for Strategic and International Studies (CSIS), the Operations & Policy Center thinktank and the Center for Operational Analysis and Research found.

Hit by new US sanctions and the collapse of the banking system in neighbouring Lebanon, cash-strapped Damascus is relying increasingly on unorthodox methods for raising funds – money either pocketed by officials in Damascus for their own personal wealth, or put towards the 10-year-old war effort.

Researchers analysed hundreds of UN contracts to procure goods and services for people living in government-held areas of Syria, where more than 90% of the population are living in poverty since the Syrian pound, or lira, crashed last year.

While the central bank’s official exchange rate has improved this year to SYP2,500 to the US dollar, the black market rate is SYP3,500. Legitimate traders and consumers prefer to use the black market rate, as they receive more Syrian pounds for foreign currency.

Since the UN is forced by the Syrian government to use the official rate, half of foreign aid money exchanged into Syrian pounds in 2020, when the rates were hugely divergent, was lost after being exchanged at the lower, official rate.

“This shows an incredibly systematic way of diverting aid before it even has a chance to be implemented or used on the ground,” said Natasha Hall, of the CSIS, a Washington-based thinktank that helped compile the research.

Syrian central bank staff stack wads of Syrian pounds in Damascus
Syrian central bank staff count SYR1,000 notes, featuring Hafez al-Assad, ex-president and father of Bashar, in 2010. The government makes millions exploiting the gap between the official and black market rate for the currency. Photograph: Hussein Malla/AP

“If the goal of sanctions overall is to deprive the regime of the resources to commit acts of violence against civilians and the goal of humanitarian aid is to reach people in need then we have this instance … where aid is at complete contradiction to those two stated goals.”

After 10 years of civil war in Syria, international donor fatigue, already seen in decreasing aid pledges, has turned to more overt political re-engagement with Assad’s regime.

Without the US playing a strong role in finding a political solution in Syria, which Washington still publicly advocates, Arab nations – including the US-allied Jordan, the United Arab Emirates, Saudi Arabia and Egypt – have recently restarted diplomatic talks, reopened borders for trade and signalled renewing economic cooperation.

The US allows Damascus to play a major role in funnelling Egyptian gas to Lebanon to power the country’s fuel-depleted power plants. Interpol allowed Syria to rejoin its network even as the fate of dissidents captured throughout the war remains unknown.

Examining 779 publicly available procurements for 2019 and 2020, listed on the UN Global Marketplace database, researchers found that up to $100m was lost in the exchange rate.

If salaries, cash-aid programmes and other funding streams not made public were included, the bank could be making hundreds of millions of dollars, according to researchers.

The funding has been channelled through various UN agencies – the Office for the Coordination of Humanitarian Affairs (OCHA); the World Food Programme; the UN Development Programme; the UNHCR; the Food and Agriculture Organisation; and Unicef.

The UN’s financial tracking system told the researchers it did not monitor the amount of money exchanged into Syrian pounds as “tracking such information was beyond the scope of their mission”.

More than 350,000 people have died in Syria over the past decade, and governments have donated on average $2.5bn a year to the UN’s Syria programmes since 2014.

In 2016, the UN was accused of aiding the regime by diverting billions of dollars in aid to government-held regions while leaving besieged areas without food and medicine.

Human Rights Watch (HRW) has warned that UN agencies and governments risked complicity in human rights violations in Syria if they did not ensure transparency and effective oversight.

Last year, the US announced an additional $700m in humanitarian assistance for Syria. The UK government has given £1.59bn in aid to Syria between February 2012 and June 2021.

A Foreign, Commonwealth and Development Office spokesperson said: “The UK does not provide any aid through the Assad regime … Robust processes are in place to ensure that our aid reaches those who need it most.”

Hall said there was a “reticence” about investigating how much aid had been diverted. She said donors were well aware of the problem. “I think it is about [them] choosing certain battles to fight. It’s just not clear to me that any battles are being fought when it comes to aid in Syrian government-held areas today,” she said.

“There’s really no way for us, as independent consultants, to know the full extent of how aid is spent inside the country … We just wanted to flag that, even through this limited portal to understanding how much is spent, it’s already tens of millions of dollars which is hoarded.”

She believes the UN should negotiate a preferential exchange rate with the Syrian government – – to at least reduce the amount siphoned off.

Sara Kayyali, of HRW, said “there was no due diligence in terms of human rights” within UN procurement to avoid bankrolling Syria.

“This should be a wake-up call to the UN … they need to revise the way they provide aid and revise how they consider their obligations to respect human rights in light of this, because it’s difficult to justify this idea that hundreds of millions of dollars are going to an abusive state apparatus,” she said.

Danielle Moylan, a spokesperson for the UN agencies mentioned, said: “The UN welcomes all independent scrutiny of humanitarian operations in Syria. Our foremost priority has, and always will be, assisting the people in need in Syria, guided by humanitarian principles, accountability to the affected populations, transparency, efficiency and effectiveness.

“The majority of UN’s procurement for our humanitarian response in Syria is made in international and regional markets and therefore not affected by the Syrian exchange rate. Otherwise, as is the case in any country, the UN in Syria is required to use the official exchange rate,” Moylan said.

“In the past, the UN and humanitarian partners have negotiated a ‘preferential’ exchange rate for humanitarian operations [and] continues to engage the Central Bank of Syria on the issue of ‘preferential’ exchange rates.”

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Alexei Navalny wins 2021 Sakharov Prize

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The European Parliament announced that Kremlin critic Alexei Navalny has won the Sakharov Prize for defending human rights. The parliament’s president David Sassoli wrote on Twitter: “Alexei Navalny is the winner of this year’s #SakharovPrize. He has fought tirelessly against the corruption of Vladimir Putin’s regime. This cost him his liberty and nearly his life. Today’s prize recognises his immense bravery and we reiterate our call for his immediate release.”

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