Why Is TikTok Banned From Government Phones – And Should The Rest Of Us Be Worried?
TikTok is wildly popular, with more than 1 billion people consuming its short video posts around the world. But the app is less favoured by politicians in key markets such as the US and UK, where it has been banned from government-issued phones over security fears. We answer your questions about why TikTok has become a lightning rod for suspicion of Chinese state espionage – and whether nationwide bans are likely.
Why has TikTok been banned from UK government phones?
The main concerns with TikTok relate to data and the fact that it is owned by the Beijing-based ByteDance, a Chinese internet company. Could the Chinese state demand access to data generated by TikTok’s global user base and, for instance, create profiles of people it is interested in, such as government employees in other countries?
The UK government raised data concerns in its statement explaining why it was taking the “prudent” step of removing TikTok from government-issued devices. It said the app was able to access user data from devices, including contacts and geolocation. According to a report by the Australian-US cybersecurity firm Internet 2.0, TikTok’s app can access a user’s calendar, other running applications, wifi networks, and even the sim card serial number.
Referring to similar bans by the US, Canada and the European Commission, the UK government said: “The government, along with our international partners, is concerned about the way in which this data may be used.”
TikTok maintains that its data is stored outside China in Singapore and the US. It is also proposing to store American and European user data in third-party servers in the US, Ireland and Norway. This has not been enough to assuage the concerns of critics, who also fear that the Chinese state could manipulate TikTok’s recommendation algorithm, which curates what people see on the app’s For You feed.
Why is it not being banned from personal phones in the UK?
The government said the “proportionate step” did not extend to personal devices for civil servants, ministers or the general public. However, it added that individuals should be aware of “each social media platform’s data policies” before downloading them.
“The bottom line is that if there is a cybersecurity issue for the government users, the same applies to all of us,” says Alan Woodward, a professor of cybersecurity at Surrey University. “The only argument might be that boring users such as me are not of interest, but there are plenty of professionals outside government where confidentiality is very important. Journalism, legal, medical and so on. If there is a security issue that nobody has found – and many have looked – then please tell us all so we can all delete it.”
Why are there concerns about the Chinese state accessing TikTok data and its algorithm?
TikTok is owned by Beijing-based ByteDance, which has led to politicians in the US, the UK and elsewhere voicing fears that Chinese officials could demand access to TikTok’s user data and source code under domestic laws including the National Intelligence Law of 2017, which states that all organisations and citizens shall “support, assist and cooperate” with national intelligence efforts. TikTok says it has not received a request from the Chinese government for its data and that, if it did, it would refuse.
The US government does not believe TikTok, and this week confirmed that the Biden administration had asked TikTok’s Chinese owners to sell their stakes in the company or face a complete ban in a key market where it has more than 100 million users. TikTok says ByteDance is 60% owned by external investors including the US private equity firm KKR, 20% by its employees and 20% by its founders, Zhang Yiming and Liang Rubo, who carry stronger voting rights than the other shareholders.
Can TikTok user data be accessed within China, including by the Chinese state?
TikTok has long insisted that user data from western nations does not enter China, where ByteDance is based. But time and again, the company has admitted exceptions to this rule.
In 2022, a BuzzFeed investigation revealed a rash of situations in which engineers in China would have access to US data, lasting at least until January 2022. The data was “stored” in the US, but with access controls that allowed staff elsewhere to access it, according to the investigation.
The similar functionality of TikTok and its Chinese sister app Douyin suggests overlap between the engineering teams, but the extent to which resources are shared has remained fuzzy. Analysis of both apps suggests that they may share parts of their source code and are developed from a common code base, according to CitizenLab. TikTok’s credibility was also damaged last year when ByteDance admitted that employees had used the app to spy on reporters.
Can the recommendation algorithm be manipulated by a state actor?
The app’s much vaunted “For You” page has a complex recommendation algorithm that takes into account a huge range of signals, both explicit and implicit, to decide what content a given user should be shown. Despite efforts to introduce transparency to how the company operates, the “FYP” is, like many recommendation algorithms, a black box for users: the total count of signals, how they are applied, and how they result in any given piece of content appearing is ultimately impossible to see from the outside, and difficult even for TikTok itself to answer, given the nature of modern machine learning techniques.
That means it is also difficult for the company to counter fears that the recommendation algorithm could be silently tampered with by a state actor, either through pressure at a corporate level, or through corrupting a small number of employees directly. In 2019, the Guardian revealed that TikTok’s moderation guidelines helped promote Beijing’s view of foreign policy, banning the promotion of separatist agendas in Tibet and Northern Ireland; the company says it now writes its moderation guidelines locally, but some fear that a similar approach would be harder to uncover if applied through automatic selective promotion and demotion of videos.
India’s deadly train crash renews questions over safety as government pushes railway upgrade | International
India’s prime minister had been scheduled to inaugurate an electrical semi-high-speed train equipped with a safety feature — another step in the modernization of an antiquated railway that is the lifeline of the world’s most populous nation.
Instead on Saturday, Narendra Modi traveled to eastern Odisha state to deal with one of the country’s worst train disasters that left over 280 dead and hundreds injured. The massive derailment on Friday night involving two passenger trains is a stark reminder of safety issues that continue to challenge the vast railway system that transports nearly 22 million passengers each day.
India, a country of 1.42 billion people, has one of the world’s most extensive and complicated railways built during the British colonial era: more than 40,000 miles (64,000 kilometers) of tracks, 14,000 passenger trains and 8,000 stations. Spread across the country from the Himalayas in the north to the beaches in the south, it is also a system that is weakened by decades of mismanagement and neglect. Despite efforts to improve safety, several hundred accidents happen every year.
From 2017 to 2021, there were more than 100,000 train-related deaths in India, according to a 2022 report published by the National Crime Records Bureau. That figure includes cases in which passengers fell from the trains, collisions, and people being mowed by speeding trains on the tracks.
Official data also suggests derailments are the most common form of rail accidents in India, but have been on a decline in recent years.
According to India’s Comptroller and Auditor General, Indian Railways recorded 2,017 accidents from 2017 to 2021. Derailments accounted for 69% of the accidents, resulting in 293 deaths.
The report found multiple factors including track defects, maintenance issues, outdated signaling equipment, and human errors as main causes of the derailments. It also said lack of money or non-utilization of available funds for track restorations led to 26% of the accidents.
Even though the railway safety in India has improved compared to earlier years when serious crashes and accidents near unmanned crossings were more frequent, scores have still died and hundreds have been injured.
In 2016, a passenger train slid off the tracks between the cities of Indore and Patna, killing 146 people. A year later, a derailment in southern India killed at least 36 passengers.
The Modi government, in power for nine years, has invested tens of billions of dollars in the railways. The money has been spent on renovating or replacing the old tracks laid by the British in the 19th century, introducing new trains and removing thousands of unmanned railway crossings.
The train Modi was supposed to inaugurate Saturday was India’s 19th Vande Bharat Express, connecting the western city of Mumbai and the southern state of Goa.
The modern trains are designed to help reduce the risk of crashes and derailments. They will be paired with a countrywide automatic train collision protection system, a technology that will make travel safe, according to Railway Minister Ashwini Vaishnaw.
But the system was not yet installed on the track where Friday’s crash took place. It wasn’t clear what caused the trains to derail and an investigation has started.
Experts suggest that the country’s railway system needs to prioritize safe tracks and collision protection.
“India has achieved some success in making train journeys safer over the years, but a lot more needs to be done. The entire system needs a realignment and distributed development. We can’t just focus on modern trains and have tracks that aren’t safe,” said Swapnil Garg, a former officer of the Indian Railway Service of Mechanical Engineers.
Garg said the crash should “shake up the whole railway system” and prompt authorities to look at the “lax safety culture.”
“I don’t expect authorities to turn the key and fix things quickly. The Indian railway system is huge and it will take time to make it more safer. But there needs to be a will,” he said.
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‘You’re looking to die’: the Brazil river where illegal fishing threatens lives | Brazil
José Maria Batista Damasceno weeps as he describes his decades dodging death in the Brazilian Amazon.
There was the time, along the Japurá River, that an illegal fisherman threatened to butcher him if he didn’t get out of town. “You’d better leave or we’ll harpoon you,” Damasceno remembers being told.
A few years later he narrowly escaped being ambushed and murdered in another remote corner of the rainforest – just as Bruno Pereira and Dom Phillips were last year.
“It was really, really heavy,” Damasceno says, breaking down as he describes how the failure of his boat’s engine saved him from running into a group of heavily armed assassins who were lying in wait.
Damasceno isn’t an Indigenous activist or journalist, like Pereira and Phillips, whose killings exposed the environmental battle raging deep in South America’s rainforests.
He is a fishing engineer who has dedicated his life to convincing small riverside communities that sustainable fishing programs will benefit them more than the quick, short-term profits offered by the illegal fishing mafias that pillage the region’s rivers and Indigenous lands.
Those efforts to encourage green living have put Damasceno on the wrong side of environmental criminals, yet he insists on fighting on.
“I’ve always relied on God to protect me from evil – and here I am carrying on with my mission,” says the softly spoken sustainable fishing evangelist, who recently travelled to the region where Pereira and Phillips were killed hoping to promote sustainable fishing there.
The world in which Damasceno operates is one of hidden dangers, cut-throat rules and huge illegal profits, where highly organized gangs of poachers with suspected ties to international drug trafficking groups prey on endangered Amazon species such as the pirarucu.
In the wake of last year’s killings, members of Jair Bolsonaro’s far-right government portrayed the crime as the fruit of a local conflict unconnected to the devastation inflicted on the Amazon by his anti-environmental policies and dismantling of Indigenous protections.
But the killings exposed a far uglier reality: the rampant and highly lucrative illegal trade in fish and wildlife that plagues Brazil’s isolated and lawless tri-border with Colombia and Peru.
At the centre of that trade is Atalaia do Norte, the shabby, poverty-stricken river town where Pereira and Phillips began their final journey on 2 June last year.
As the nearest town to the entrance of the Javari valley territory, Brazil’s second largest Indigenous reserve, Atalaia serves as a base for the Indigenous activists on whose work Phillips was reporting when he was killed. Its potholed streets offer an astonishing snapshot of the cultural and linguistic diversity of a region which is home to six Indigenous peoples, including the Matis and the Marubo, as well as 16 groups with little or no contact with the outside world.
But in recent years Atalaia has also become a key part of a transnational poaching network with suspected links to the drug factions who move vast quantities of Peruvian cocaine through what police now consider Brazil’s second most important drug smuggling route.
After visiting Atalaia last year, congressional investigators concluded that “heavily armed and wealthy criminal associations” and “highly dangerous criminals” had set up camp in the region, bankrolling groups of illegal fishermen who plunder the protected waters and forests of the Indigenous reserve where wildlife is more abundant.
“We are certain that illegal fishing in the Javari valley region isn’t about river-dwellers trying to make a living but actually much larger organizations, making sizable investments and outrageous profits,” the investigators wrote.
Bruno Pereira’s attempts to fight that illegal trade by organizing Indigenous patrol teams put him on a collision course with such criminals. “It’s because of this that Dom Phillips and Bruno Pereira were killed,” a friend and former colleague, Armando Soares, told Forbidden Stories, the Paris-based non-profit coordinating the Bruno and Dom project. Earlier this year police named an alleged local illegal fishing boss as the mastermind behind the crime.
The Javari valley’s most prized asset is the arapaima, a giant air-breathing fish which Brazilians call the pirarucu and Peruvians know as paiche. One of the world’s largest freshwater fish, the arapaima can grow up to three metres (10ft) in length and often weighs about 90kg (200lb). It is considered a delicacy in major Latin American cities such as Lima, São Paulo and Bogotá.
Years of unregulated overfishing have pummeled arapaima stocks in the waters outside the Javari’s protected Indigenous lands – which outsiders are forbidden from entering without permission and where commercial fishing is banned. As a result poachers have increasingly taken to invading the territory to extract huge boat-fulls of the fish, as well as a river turtle called the tracajá.
“They use small boats and travel in small groups,” said Orlando Possuelo, an Indigenous expert who is continuing Pereira’s work with the patrol groups battling to thwart such invaders. “They are specialists in the area. Many of them were born in there [before the territory was officially created in 2001] so it’s not easy to find them.”
After being smuggled out of the Indigenous territory in wooden barges packed with ice, the fish are sold in a constellation of border towns including Leticia in Colombia, Islandia in Peru and Benjamin Constant, an edgy river town near Atalaia named after one of the founders of the Brazilian republic.
A year-long investigation by Forbidden Stories found that the illegal trade continues to flourish in the tri-border region between Brazil, Colombia and Peru, despite government pledges to stamp out environmental crime following last year’s killings. None of the three countries there have rigid controls over the origin of the arapaima being sold.
Brazil has yet to reopen the offices of its environmental agency, Ibama, in Tabatinga, the city nearest to the Javari, after it was shut down in 2019. Peru’s regional production department has no fishing inspectors in Santa Rosa de Yavarí, the Peruvian town across the river from Tabatinga. And Colombian authorities do not control the quantity of fish being caught by the 40 companies registered to operate in Leticia, on the Colombian side of the border.
Outside scrutiny is unwelcome. “There’s nothing here. You’re looking to fucking die,” one man warned a reporter from Peru’s OjoPúblico, one of 16 media outlets involved in the Bruno and Dom project, when he visited a riverside fishing warehouse in the Colombian border town looking for illegal fish.
Activists say the almost complete lack of controls means the illegal fishing trade continues to thrive despite the international scandal caused by the killings of Pereira and Phillips.
“I don’t think anything has changed,” said Possuelo, remembering how Indigenous activists received reports of illegal poachers operating within the Javari territory even in the days after the two men vanished on 5 June last year.
Despite the risks, Damasceno said he was determined to continue with his crusade to bring sustainable fishing to some of the most isolated and dangerous corners of the Brazilian Amazon, where he was born and raised.
Now 65, the fishing engineer plans to retire after what will be his last – and perhaps most difficult – assignment: implementing such projects in São Rafael, São Gabriel and Ladário, the three fishing communities from which the alleged killers of Pereira and Phillips came.
Doing so involves helping those communities set up three different kinds of lakes that will help local pirarucu stocks recover and, hopefully, stop fishermen invading Indigenous lands: “permanent protection lakes” where fishing is forbidden, “maintenance lakes” which local families can fish to feed themselves, and “management lakes” where a quota of up to 30% of adult fish can be legally extracted after their numbers have reached certain levels. “So if there are 100 fish you can take 30, so stocks can recover,” Damasceno said.
The fishing engineer argued sustainable fishing was the only way to avoid further violence along the Itaquaí River and help deprived local families resist the temptation of supplying fish for organized crime. As proof that it was possible, he remembered how the fisherman who once threatened to harpoon him had since embraced sustainable fishing and become a close friend.
“I always say that sustainable fishing is the way out of this kind of conflict. It unites people. It raises awareness. It opens the door to equality, rights and acceptance,” insisted Damasceno, who hopes to retire to write a book about the pirarucu once his mission is complete. He plans to call it: “The union of people and sustainability in the Amazon.”
On a recent trip to the fishing villages near where Pereira and Phillips were killed, Damasceno urged locals to embrace the idea of legal, long-term survival rather than short-term, illegal gain.
“Lift up your heads. You must carry on,” he told them. “Think of your kids.”
Additional reporting by Ana Ionova (The Guardian), Rodrigo Pedroso (OjoPúblico) and Cécile Andrzejewski and Mariana Abreu (Forbidden Stories)
Explaining AI Black Box
Prof Saurabh Bagchi from Purdue University explains the purpose of AI black boxes and why researchers are moving towards ‘explainable AI’.
For some people, the term ‘black box’ brings to mind the recording devices in airplanes that are valuable for postmortem analyses if the unthinkable happens. For others, it evokes small, minimally outfitted theatres. But ‘black box’ is also an important term in the world of artificial intelligence.
AI black boxes refer to AI systems with internal workings that are invisible to the user. You can feed them input and get output, but you cannot examine the system’s code or the logic that produced the output.
Machine learning is the dominant subset of artificial intelligence. It underlies generative AI systems like ChatGPT and DALL-E 2. There are three components to machine learning: an algorithm or a set of algorithms, training data and a model.
An algorithm is a set of procedures. In machine learning, an algorithm learns to identify patterns after being trained on a large set of examples – the training data. Once a machine-learning algorithm has been trained, the result is a machine-learning model. The model is what people use.
For example, a machine-learning algorithm could be designed to identify patterns in images and the training data could be images of dogs. The resulting machine-learning model would be a dog spotter. You would feed it an image as input and get as output whether and where in the image a set of pixels represents a dog.
Any of the three components of a machine-learning system can be hidden, or in a black box. As is often the case, the algorithm is publicly known, which makes putting it in a black box less effective. So, to protect their intellectual property, AI developers often put the model in a black box. Another approach software developers take is to obscure the data used to train the model – in other words, put the training data in a black box.
The opposite of a black box is sometimes referred to as a glass box. An AI glass box is a system whose algorithms, training data and model are all available for anyone to see. But researchers sometimes characterise aspects of even these as black box.
That’s because researchers don’t fully understand how machine-learning algorithms, particularly deep-learning algorithms, operate. The field of explainable AI is working to develop algorithms that, while not necessarily glass box, can be better understood by humans.
Thinking Outside The Black Box
In many cases, there is good reason to be wary of black box machine-learning algorithms and models. Suppose a machine-learning model has made a diagnosis about your health. Would you want the model to be black box or glass box? What about the physician prescribing your course of treatment? Perhaps she would like to know how the model arrived at its decision.
What if a machine-learning model that determines whether you qualify for a business loan from a bank turns you down? Wouldn’t you like to know why? If you did, you could more effectively appeal the decision, or change your situation to increase your chances of getting a loan the next time.
Black boxes also have important implications for software system security. For years, many people in the computing field thought that keeping software in a black box would prevent hackers from examining it and therefore it would be secure. This assumption has largely been proven wrong because hackers can reverse engineer software – that is, build a facsimile by closely observing how a piece of software works – and discover vulnerabilities to exploit.
If software is in a glass box, software testers and well-intentioned hackers can examine it and inform the creators of weaknesses, thereby minimising cyberattacks.
Saurabh Bagchi is professor of electrical and computer engineering and director of corporate partnerships in the School of Electrical and Computer Engineering at Purdue University in the US. His research interests include dependable computing and distributed systems.
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