The Internet of Things (IoT) is a system of interrelated computing devices, mechanical and digital machines provided with unique identifiers and the ability to transfer data over a network without requiring human-to-human or human-to-computer interaction. Connected machines and objects in factories offer the potential for a ‘fourth industrial revolution’, and experts predict more than half of new businesses will run on the IoT by 2020.

IoT encompasses everything connected to the internet, but it is increasingly being used to define objects that “talk” to each other. The industrial sector is entering a new phase of digitalization, where businesses are being driven by data, and analytics, connectivity along with automation, which are propelling trade as the game changers. In such a scenario, the Internet of Things or IoT is being relied on heavily to offer innovation and evolution in the moderately-transforming sectors like logistics, transportation, supply chain, and marine industry. The main objective of utilizing IoT and its applications is to achieve better efficiency in terms of operations, minimize human errors & risks, and hence enhance quality service.

According to a Inmarsat Report: Industrial IoT, it is the maritime industry that has adopted IoT solutions more than any other sector and some sources even reveal that few of the leading shipping organizations plan to invest about $2.5 Million on IoT based solutions in the coming three years with an expectation of achieving around 14% cost-savings over the next 5-7 years.

Presently, with the help of IoT-based solutions, the marine sector is eyeing on reducing the administrative costs of regulatory compliance and enhancing security and safety. Adding more on that note, the technology is also assisting in making cargo handling and preemptive maintenance easier and quicker.

Another area of opportunity for IoT-based solutions in the marine sector is Energy and Fuel Consumption. The smart meters are enabling better and more accurate recording and tracking of the fuels, allowing the sector to not only save on cost but also go environment-friendly.

If we inspect the broader horizon, then most of the transportation and logistics companies have already embraced IoT solutions. Right from utilizing IoT solutions for predictive analytics that help organizations make smarter decisions for route and delivery planning task to identifying the problem-creating areas, creating a smart location management system, real-time inventory tracking and warehousing, introducing self-driven vehicles and drone-based deliveries, IoT is revolutionizing the sector to its very core.

In addition, the technology is also equipping the supply chain management across the globe in various ways. The integration of Radio-frequency Identification commonly referred to as RFID with IoT technology is being seen as one of the biggest impacts of IoT in Supply Chain Management. Through this integration, the supply chain management sector is looking forward to extensively improve its operations. Not only does it allow real-time updates but also helps the industry to combat counterfeit goods, enforce expiration on perishable goods, and detect the various factors that may impact the
quality of the product while in the delivery process.

Moreover, IoT based solutions are also helping the sectors to bring in transparency throughout the transportation system. The introduction of blockchain for supply management within the maritime sector with the help of IoT solutions is something that is currently making heads turn.

Internet of Things is a connected technology, which is filling in the gap between humans, machines, and data; in turn, is providing an edge to the transport sectors as they are now more than ready to embrace the definite role and flexible nature of IoT. It will not be wrong to say that in the foreseeable future IoT will not just transform the businesses but also the ways through which the world carries out its business-be it rail, road, air or sea.

IoT enables real-time tracking and monitoring of cargo at all levels to determine location, delivery and a host of realated matter. While IoT saves time and increases efficiency, security is one of the main challenges of successful IoT implementation.

Deploying and expanding IoT capabilities requires more than just technological breakthroughs. As stakeholders in the shipping and maritime industry advance towards IoT with more vigour, they will need to have their goals set. An effective stratgey, a well-defined goal, robust architecture and security should be on the checklist and the industry embraces IoT.

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Encountering altered videos and photoshopped images is almost a rite of passage on the internet. It’s rare these days that you’d visit social media and not come across some form of edited content — whether that be a simple selfie with a filter, a highly embellished meme or a video edited to add a soundtrack or enhance certain elements.

But while some forms of media are obviously edited, other alterations may be harder to spot. You may have heard the term “deepfake” in recent years — it first came about in 2017 to describe videos and images that implement deep learning algorithms to create videos and images that look real.

For example, take the moon disaster speech given by former president Richard Nixon when the Apollo 11 team crashed into the lunar surface. Just kidding — that never happened. But a hyper-realistic deepfake of Nixon paying tribute to a fallen Buzz Aldrin and Neil Armstrong appeared in a 2019 film, In Event of Moon Disaster, which showcased the convincing alteration of the president’s original speech.

Other current and former world leaders, such as John F. Kennedy, Barack Obama and Vladimir Putin have been the subjects of deepfake videos, too, in which they appear to say and do things that they never actually said or did. Though the rise of deepfakes in recent years has been discussed in popular media, the pool of academic literature on the topic remains relatively sparse.

But researchers have expressed concern that these doctored images and videos could present a growing security risk in the coming years. A report last week in Crime Science predicts that deepfakes will pose the most serious security threat in the next 15 years out of a host of other AI-powered technologies.

“Humans have a strong tendency to believe their own eyes and ears,” the researchers wrote in their concluded. So when the media we consume looks too good to be fake, it’s easy to fall victim to trickery. And the amount of deepfakes online continues to grow, though not always in the places you might expect.

What Makes a Deepfake?

The term deepfake doesn’t refer to just any convincing edited video or image — more specifically, the term is a conglomeration of “deep learning” and “fake.” This specific type of media relies on neural networks to alter audio and video.

The technology to create deepfakes has gotten easier to access over the years, with a handful of programs and websites cropping up that allow users to make their own, sometimes at a hefty price. Still, many of the deepfakes that populate various corners of the internet aren’t that convincing, says Giorgio Patrini. He’s the CEO and founder of Sensity, a company in Amsterdam that has been researching the spread of deepfakes since 2018. Patrini says most of the deepfakes he’s come across are made with the same few open-source tools. “The reason is they are very easy to use and they are very well-maintained and known by the communities,” he adds. And most media they find “in the wild,” as Patrini puts it, use the same few methods to alter digital footage

Recently, Facebook announced the results of a competition where experts built new algorithms to detect deepfakes — the winner was able to detect 82 percent of the AI-altered media they were exposed to. Some deepfakes can be created using methods that are still hard for current detection algorithms to spot, but Patrini says deepfake creators in the wild tend to use cheaper, simpler methods when making videos. The detection software we have now is actually pretty successful at sorting through the large swaths of media found online, he adds.

“I would say maybe 99 percent, or even more, of the deepfake videos that we find are … based on face swapping,” he says. “There are other ways to create fake videos, even changing the speech and lip movement, [or] changing the body movement.” But so far, those are not the most popular methods among deepfake connoisseurs, says Patrini, so current algorithms can still weed out much of the AI-altered content.

And though face-swapping technology can be applied to literally any photo or video with a human face in it, deepfake creators seem to have an affinity for one type of media in particular: pornography. An overwhelming amount of AI-altered videos are created to place one subject’s face onto the body of a porn star — a phenomenon that disproportionately targets women and hearkens back to the dark origins of deepfakes themselves.

The Porn Problem

In 2019, when Sensity released a report on the state of deepfakes under the name Deeptrace, they detected 14,678 total AI-altered videos online. Of those, 96 percent were used in pornographic content.

And the first deepfake videos, in fact, were made for the same reason. In 2017, users on Reddit started to post doctored videos of female celebrities whose faces were non-consensually swapped onto the bodies of porn stars. Reddit banned users from posting these explicit deepfakes in 2018, but reports show that other ethically problematic sites and apps still popped up in its place.

“We haven’t gone very far from it,” Patrini says. Despite widespread media coverage of political deepfakes, pornographic edits have been the reigning form of AI-altered content to spread across the web. And so far, women are pretty much always the targets — Sensity’s 2019 report found that 100 percent of detected pornographic deepfakes featured female subjects.

Just two months ago, Sensity identified 49,081 total deepfake videos online — a trend showing that the numbers are doubling nearly every six months. Lately, Patrini says, they’ve observed an increase in videos targeting people who are popular internet personalities, or influencers, on Youtube, Instagram and Twitch. “Maybe a year ago we saw that most of the content was featuring known celebrities that could be … from the entertainment industry,” he says. But deepfake creators are also targeting individuals, often women, who lead active lives online.

Can We Stop the Spread?

While AI-altered media might seem all bad, the technology itself isn’t inherently damaging. “For many people, deepfakes already have anintrinsically negative connotation,” Patrini says. But the technology behind it can be used for a host of creative projects — such as translation services or visual tricks in movies and TV shows.

Take the Nixon deepfake, for example. The directors didn’t present their creation to mislead viewers or make them think the history books got the Apollo 11 mission wrong. Rather, the film used an experimental new technology to showcase what an alternate historical timeline might have looked like, while educating viewers on how convincing deepfakes and video editing can be.

But that’s not to say deepfakes can’t mislead, nor that they aren’t already being used to carry out nefarious deeds. Besides the widespread use of non-consensual, doctored porn, Patrini says he’s also seen a rise in cases where deepfakes are used to impersonate someone trying to open a bank account or Bitcoin wallet. Video verification can be required for these processes, and it’s possible for a deepfake to trick the cameras.

“With some sophistication, people can actually fake an ID and also fake how they appear on the video,” Patrini says. Sometimes that can mean opening accounts under a stranger’s name, or a fake name and creating a persona that does not exist. For now, Patrini says, this kind of trickery does not appear to be widespread — but it does represent a more sinister application for deepfakes.

And with the technology getting easier to access, it’s likely that the spread of deepfakes will continue. We can only hope people will choose to use them for good.

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With more computers, internet, social media and tons of coding, there’s a greater chance of glitches occurring, costing businesses millions of dollars and a loss of prestige. With so much data to check and double-check, maybe artificial intelligence (AI) can help stop these “gremlins” from wreaking havoc online.

From Bugs Bunny to Business

Perhaps the most iconic World War II cartoon is the Warner Bros. episode “Falling Hare.” Bugs Bunny pooh-poohs the notion of gremlins committing sabotage on the Allied war effort, until those little creatures cause malfunctions in everything from bombs to planes, with devastating results in the Merrie Melodies classic.

According to Robert O. Harder, in a piece published by MHQ—The Quarterly Journal of Military History, “gremlins” were tall tales told by pilots of mischief makers that would infect aircraft, causing all kinds of maladies. Today, they’re the little glitches that seem harmless enough until they paralyze the titans of the technological age.

In the cartoon, the classic rabbit tries to defeat the gremlins without much success. But what if he had a smart computer to do the job?

Anodot = The Anti-Gremlin Company

To find out more, Observer talked with Ira Cohen, co-founder and chief data scientist of Anodot, a company dedicated to finding anomalies and glitches, like the gremlins that bedeviled warplanes 80 years ago. He must like cartoons, too, because he began our conversation by discussing a South Park episode—the one where Eric Cartman programs his Alexa to do all kinds of bizarre things. In fact, other Alexa devices started doing the same strange things that Cartman’s did. “Good monitoring would show lots of Alexas doing the same thing at the same time. We would catch these kinds of glitches,” he assured me.

How do they do it? “There are two ways our methods are better,” Cohen explained. “First is scale. There’s lots to look at… the sheer quantity of it all. Even small businesses have 100,000 things to check. The other is speed. You need to be able to look at things quickly and be able to find problems faster.”

Believe it or not, smaller companies are just as likely to take it on the chin when they get hit with gremlins. That’s because few of them currently use AI to check their products.

Cohen told a story about a company that had video players and ran a series of ads. Well, the player didn’t work very well with a particular version of Internet Explorer. “Few noticed it at the time. It took several months to discover, and that was done accidentally. It lost lots of ad revenue. Though it looked like a small percentage on paper, it wound up being a big deal in money. You need to look at everything.”

In another case, a cloud provider’s service went down. Anodot figured out what the problem was in 10 minutes and patched in a workaround. Other large companies went down for hours. Finally, the cloud provider revealed the problem, but things weren’t working for a period of time. “When someone else’s company that you rely on for service has a glitch, your customers don’t care about whose fault it is,” Cohen said. “They contract with you, and in their eyes, you didn’t get the job done.”

How about a story where Anodot came to the rescue?

“We found out that scooters that were being ridden were being tossed into the sea because riders in that area were leaving them around, frustrating nearby residents,” Cohen elaborated. “We could figure out pretty quick what was going on, giving the client more time to develop a plan to retrieve them.”

Back in 2014, co-founder and CEO David Drai was working on an Uber competitor for taxis, in charge of business monitoring of all of the variables (service provided, ride quality, money and right destination). He would look at the dashboard in the morning and wonder why service was being constantly interrupted in a place like Moscow. “He faced the pain of late detection and [saw] that an AI solution was needed, because they were always 24 hours too late,” Cohen explained.

And so the decision was made to invest in AI to spot and stop these gremlins, but does Anodot’s product exceed what a human can do? “We have an 80% reduction in error detection time, and we’ve done a webinar that shares the details of that head-to-head test. In fact, customers measure us as to how fast we can find something,” Cohen shared.

The Gremlin Finder’s Future, and Past
How does one start preparing for a future in catching computer glitches? Cohen began in electrical engineering in college, moving to image processing and computer visual practices, “a slippery slope to AI.” His first job was catching errors in computer chips associated with the production process.

But the lightbulb went off years earlier. In a tale of a fourth grade programmer, Cohen created an adventure game on an Apple II, programming in Basic. “It wasn’t about playing games but getting the computer to do what I wanted it to do—that was my hook,” Cohen elaborated. “So this is what all that math is for. It wasn’t just problems given by the teacher, but getting a machine to do a task. It made the abstract math real. Now, we find the defects that can cost a company a lot of money.”

So what can we expect over the next 10 years? “BI, or business intelligence, will gradually be replaced by AI. Visualization tools, dashboards, reporting, helping companies make better and quicker decisions will be the next step,” Cohen concluded. “There’s plenty of data and graphs that can be created. But without asking the right questions, you won’t get the right answers. AI will get involved in preparing us for the questions, even the ones we haven’t considered. More decisions will be automated, moving us away from a labor-intensive process.”

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Like any other country in the world, India, too, has its own socio-economic and governance problems. Some issues like economic slowdown, unemployment, deteriorating health care, education quality, and communalism have been worrying India since before independence.

These problems still persist and have held India tightly in their jaws. But, besides these conventional challenges which India is yet to resolve, the modern world has brought new problems for India to be tackled. The dynamic nature of the world economy, the disrupting innovation, and dominance of the market have brought India to the crossroads with a complex web of confrontations which, if not unraveled, may cause unprecedented harm. We will discuss three such modern enigmas that India is currently facing:

1. Public Data Mining And Privacy Rights: Privacy of Indian citizens is at the risk amidst the digital revolution, and the collection of personal data by the government and corporate. The potential of big data in artificial intelligence, product marketing, etc. has made it valuable like oil.Today, we enter our personal information, details of daily activities a thousand times a day in the virtual world. Apps like WhatsApp, Facebook have been found guilty of breaching the privacy of users many-a-times in the recent past, the latest case being the Pegasus case. Governments themselves sit on the biometric data of citizens without really having any data security framework. This data can be misused for crime, targeted advertising, terrorist activities or political propaganda even without the consent of citizens. The lackadaisical approach of the government over these issues makes it more worrisome. Despite the Supreme Court’s landmark judgment on rights to privacy (Puttaswamy vs. the Union of India) or the Justice Srikrishna committee’s report on data protection law, India has not yet taken any concrete steps over it.
2. The 4^th Industrial Revolution (IR): What a fancy word ‘revolution’ is, which indicates positive and transformative change. The fourth IR has introduced robots with human intelligence, IoT, higher productivity in factories, etc. Today’s strenuous work of switching on TV can be accomplished by Alexa, the AC in our homes can be controlled from tthe outside, and humans are being freed from daily mundane work.But, besides this, the 4^th IR is bringing many disruptive changes, that will be difficult to handle if remedial actions are delayed. The prime concern is the employment crisis. Manual jobs like computer operators, parts assembling in factories, and many more will be automated in the coming decades. China has already built a robot journalist to read the news in the studio. We can’t even imagine the level of crisis the economy may go through in this transition. Experts are speculating the possible consequences in their own way without any surety. The World Economic Forum (WEF) has already given its estimates on job loss in India due to automation.
3. Cybersecurity: It’s very common to read about online frauds done by hacking into bank accounts, hacking of educational institutes’ websites, the way card details of several account holders are leaked. People can’t even imagine that only by clicking on a link in a text message can pauperise them. We are surrounded by invisible thieves who are keeping an eye on our activities and are ready to loot us. Cyber terrorism has taken a great toll on the government’s capability to mitigate internal security risks. Hawala transactions are carried out in one click by overground groups, propaganda is spread out by posting a video or enticing lines/posts on social media. Any critical information possessed by several agencies regulated by the government is prone to leakage. The cyberspace is being misused at a gross level. We are still not prepared to tackle this challenge.

While we are still struggling with our conventional problems, these modern-day challenges have added to India’s worry. If we talk about the one-line solutions to these issues, these can be:

• India should frame a data protection law having unambiguous provisions and detailed responsibilities of every stakeholder like corporate and citizens to make a balance between the use of data for public welfare and privacy rights as soon as possible.
• Niti Ayog has already prepared a policy layout on artificial intelligence (AI). The foremost need to tackle the 4^th IR is the re-skilling of the workforce. It has to be corroborated by aligning the education curriculum to modern industrial needs, for example, starting professional courses on machine learning (ML), AI, etc. via an industry-academia collaboration. However, similar steps have already been taken by the Central Board of Secondary Education (CBSE), which introduced a chapter on AI in the school syllabus and IIT Hyderabad is starting a B.tech course on AI.
• Cybersecurity has to be ensured by the participation of all stakeholders like government, citizens, corporate, etc., a robust institutional mechanism should be established with capacity building of investigating teams, police reforms, etc. New technologies must be leveraged by the agencies like ED, NIA in investigations and evidence collection. Overall, I feel the government has to counter the misuse of cyberspace by cyber technologies itself.

India is on the path of sustainable development but before achieving that, it has to cross many new obstacles. So, it is imperative to be visionary and recognise the new challenges and possible disruptions from them in the future and be prepared for them.

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The big picture: As trade tensions between China and the US continue to make headlines, Apple has found itself in the general conversation once again. Apparently, the company shares some data with a Chinese tech giant, which has led some to believe that it isn’t able to hold up to its high standards for privacy. While most people would take that as “Apple bowing to China,” it’s more important to reflect on the fact that we don’t live in an ideal world where things are that simple.

Most may not be aware of it, but Apple’s web browser has been sending data to Google Safe Browsing for years. This is done to protect users against phishing scams, by using an interstitial screen that prevents you from visiting a known fraudulent website from Google’s list.

Now it appears that for everyone running the latest version of iOS, Apple is sending some of your web browsing history to Chinese Internet giant Tencent. This has sent critics up in flames about the potential privacy implications, especially since the feature is enabled by default and requires some digging to find it.

If you go to Settings > Safari, you’ll find some small print that has recently been changed to say that “before visiting a website, Safari may send information calculated from the website address to Google Safe Browsing and Tencent Safe Browsing to check if the website is fraudulent. These safe browsing providers may also log your IP address.”

Cryptography expert Matthew Green explains that this poses a privacy risk because it could reveal both your IP address as well as the web pages you are visiting. He says there’s also a great possibility that Google “may drop a cookie into your browser during some of these requests.” This essentially means that someone could use this information to piece together a profile of your browsing behavior.

Fortunately, Google has made some changes to the relevant API that should, in theory, provide anonymity using a locally stored database which contains hashes instead of the actual addresses of known malicious websites. Every time you visit a new website, Safari will hash the URL and check if it matches something from the local database.

However, this approach isn’t perfect. As you visit hundreds or even thousands of websites over time, you gradually leak your browsing history. It’s also worth noting that you need to trust Google not to make use of this vulnerability. The company is already under investigation by the Irish Data Protection Commission under allegations that it may have been circumventing GDPR rules to perform a more subtle form of data mining for advertisers.

The good news is you can easily turn off the “Fraudulent Website Warning” feature in Settings under Safari, but this still doesn’t explain why Apple didn’t see the need to be more transparent about it. The company released a statement to say that Tencent is only used as a source for the list of fraudulent websites if the region setting on the device is set to mainland China.

This isn’t the first time the company has been criticized for working with a Chinese entity to handle sensitive data. Last year it transfered iCloud servers for Chinese users to a state-run company, which yielded similar privacy concerns.

More recently, Apple has been under fire for its somewhat peculiar relationship with China. CEO Tim Cook had to defend the company’s stance after it removed a Hong Kong protest app from the App Store, a move that led many to believe Apple may be favoring Chinese interests as a way to appease the government of its third largest market.

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It can be hard to know how much we should care about our digital footprint – but like it or not, most of us have one.

From the first check of the phone in the morning, to the ride in to work, to lunchtime swiping of loyalty cards, we leave a trail of information behind us as we go about our lives.

Our movements, online activity and spending habits all paint a picture of who we are and – of special interest to marketers – what we buy.

Data collection can be a scary thought to some; a digital dystopia where our private information is collected without us really noticing and sold on.

But then again, maybe it’s a good thing.

Stuff journalist Katie Kenny, who reports on digital trends, says data collection has pros and cons.

 “It can make society a much fairer place if Governments are making really data-driven decisions around infrastructure and allocation of resources and things like that.

“On an individual level, there are conveniences. Even something as simple as a discount is an incentive to sign up for a loyalty club.

“The way that ads will pop up that are tailored to your previous browsing habits; some people think it’s creepy, some people think it’s helpful… but it can make life easier.”

But Kenny says the downside is that we run the risk of people knowing too much about us.

“At the extreme end, are we heading towards a surveillance society?

“We are very much in a society that I wouldn’t say is zero-privacy, but there’s certainly not a lot of privacy.”

While data collection is far from a new thing, Stats NZ’s latest information venture is looking to shake up the data game by accessing information held by phone companies.

Data Ventures is a commercial start-up from within Stats NZ. Its first project, Population Density, measures what the name suggests: how many people are in one place, at one time.

It does this by taking information provided by telcos from cell phone towers, and then compiles that information to show where all the people are.

Then that information’s sold on – initially, back to Government departments, but Data Ventures isn’t ruling out venturing into the private data market, either.

Kenny says that information will be used to plan for tourism peaks and troughs, and emergency planning too.

“You can use a big event like a rugby game, where you have 70,000 people gathered in open space, and then suddenly they’re leaving – this data would show hour by hour which highways are getting overloaded … and how quickly they’re able to get out of a central city area.  

The project’s attracted few privacy concerns. The Privacy Commissioner, Government ministers and phone providers Spark and Vodafone are all confident the anonymised nature of the data means no individual can be identified.

“It’s not the same as Google data, or other movement data, because it doesn’t track movements from A to B, it just provides a map of the number of people in a portion of a country,” says Kenny.

Not everyone is comfortable with it however.

A notable exception to this data train is 2 Degrees, which has opted out of the Population Density project over potential privacy concerns with future projects.

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Network traffic across the internet, within data centers and in end-user networks has increased rapidly over time and shows no signs of stopping. While 100 Gigabit Ethernet, or GbE, technology has only been available for a few years, a variety of applications already show a need for even higher data rates.

Industry experts expect large public cloud providers to be the initial adopters of 400 GbE switches. Yet, as links in cloud server racks upgrade to 50 or 100 Gb, IT teams must upgrade their network backbones to carry increasing amounts of traffic.

Large public cloud providers maintain geographically dispersed clouds to support worldwide enterprises and provide backup and failover. Traffic levels between clouds increase along with traffic levels within each cloud, so providers must also upgrade inter-cloud links.

Where will users see the effects of 400 GbE technology?

In addition to cloud environments, the internet also requires 400 GbE links. Traffic continues to grow rapidly due to multiple factors, including the following:

• Users stream popular TV networks, such as HBO and Netflix, over the internet.
• Viewers access a multitude of YouTube videos with individual end-user streams, which adds to internet traffic.
• Phone calls previously made over cell networks increasingly moved to the internet — e.g., WhatsApp, Skype and Wi-Fi Calling on iPhones and Androids.
• 5G greatly increases cell network data rates, and much of this traffic will travel over the internet for some portion of its route.
• Online shopping continues to increase, with many vendors providing video to showcase products.

All of these applications contribute to the need for transport networks that carry internet traffic to move toward higher data rates. Transport providers anticipated this growth and began trials as soon as early 400 GbE equipment was available. Now that these trials are complete, experts anticipate providers will now upgrade wide area links, as well.

Additional applications that require higher bandwidth communication generally involve efficient moving and processing of large data amounts, such as files used in advanced data mining activities and AI, including machine learning.

IEEE developments with 400 GbE

It takes time to develop technology that supports higher throughputs. Work on the Institute of Electrical and Electronics Engineers (IEEE) 802.3bs standard for 400 GbE began in 2013, and the IEEE completed the work in late 2017. The IEEE devoted its time between the standard’s release and product availability to interoperability testing, which ensures all components function and integrate as intended. With its work on 400 GbE complete, the IEEE began to develop the increased signaling rates needed to support even higher data rates.

400 GbE links are relatively new, and many prospective customers are still in the evaluation stage, but many networks will soon adopt 400 GbE to address support for increased traffic.

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President’s message calls for tackling legal, security, governance challenges

President Xi Jinping called on Sunday for strengthened cooperation among countries to explore opportunities of digital, internet-based intelligent development and to properly address legal, security and governance challenges arising from big data industry development.

He made the remarks in a congratulatory letter to the China International Big Data Industry Expo 2019, which kicked off in Guiyang, Guizhou province.

The new generation of information technology, represented by the internet, big data and artificial intelligence, is booming at present and has significant and profound influence on various countries’ economic development, social progress and people’s lives, Xi said in the letter.

China attaches great importance to the development of the big data industry and is willing to share opportunities of the digital economy’s development with other countries and jointly explore new growth drivers and development paths by exploring new technologies, new business forms and new models, Xi added.

With increasingly wider applications of digital technologies in China, the country is expected to generate and store 27.8 percent of global online data by 2025, up from 23.4 percent last year, according to a report by market researcher International Data Corp and data storage firm Seagate.

In comparison, the US share will stand at 17.5 percent by 2025, a drop from its 21 percent share in 2018, the report added.

United Nations Secretary-General Antonio Guterres said that from medicine to transportation to farming, big data presents the world with a remarkable tool to advance global progress, but with that opportunity also comes risk.

“We must work together to ensure that big data, and the technologies that it enables, are harnessed for the benefit of mankind while minimizing the risks to development, peace and security and human rights,” Guterres said in a congratulatory letter to the expo.

Miao Wei, minister of industry and information technology, said China has already made significant progress in bolstering the big data industry with a string of big data platforms established in sectors such as manufacturing, commerce, finance, transportation and medical care.

“We will make a fresh push to integrate cutting-edge information technologies into the real economy, including establishing a national industrial data center, to better power the country’s sprawling manufacturing sector,” Miao said at the opening ceremony of the big data expo.

According to the ministry, China’s digital economy reached a total volume of over 31 trillion yuan ($4.5 trillion), or 34.8 percent of its GDP, in 2018.

Yang Xiaowei, deputy head of the Cyberspace Administration of China, also called for more efforts to develop the homegrown big data sector and highlighted that stepping up research and development is key to mastering core technologies.

Paul Romer, co-recipient of the 2018 Nobel Prize in economics and professor of economics at New York University, said he is impressed by China’s proposal in cyber sovereignty which he understands as: Each nation must be able to write and enforce its own laws that regulate cyberspace, and ensure that cyberspace works to the benefit of everyone in the nation.

“China’s articulation and implementation of cyber sovereignty means it is a chance for the world to see a different kind of organization for cyberspace, and a chance to see that with the right structure, we can get tons of benefits,” Romer added.

Lu Yong, vice-president of Huawei Technologies Co, said China’s digital economy has thrived on the basis that China has built the world’s largest 4G network.

“5G is not just a faster 4G. It will fundamentally reshape how enterprises run businesses and overhaul a wide range of industries by using data to create more value,” Lu said.

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In a modern company like Amazon, almost all human activity is directed by computer programs. They not only monitor workers’ actions but are used to choose who should be employed. Yet it emerged last week that the company had scrapped an attempt to use artificial intelligence to select workers on the basis of their CVs since the results consistently discriminated against women.

This is a welcome decision that illuminates two important facts about machine learning, the most widely used technique of AI at the moment. The technical or operational point is that these programs, no matter how fast they learn, can only learn from the data presented to them. If this data reflects historic patterns of discrimination, the results will perpetuate those patterns.

That’s what Amazon found: by training its AI with the records of those job applicants who had been hired in the past, who were overwhelmingly men, it taught the program to discriminate against applications from women. Since the program had access to immense amounts of data about the applicants, it was able to infer their sex from factors such as whether they had attended an all-woman college. And since it had neither conscience nor consciousness, the machine behaved as if being female were a sign of inferiority, just as the industry it learned from had done.

This is an instance of a wider problem that has appeared in more sinister contexts, such as decisions over which prisoners should get parole. It is also one that is extremely hard to surmount. When you ask computers to detect patterns in data, which is the short description of machine learning, the patterns they find are usually genuine ones, even if we have not noticed them before.

This kind of mesh of inference is implicit in the way that language works, as Joanna Bryson, one of the authors of a ground-breaking study of the way that machine learning can expose the prejudices embedded in our use of language, points out. We can’t get away from it. It encodes both the wisdom and the folly of all those who have used language before us. Patterns of language describe the way the world is, whether or not it ought to be that way. So when we want to distinguish an “ought” from the “is” of usage, it requires a sustained collective effort.

The technical aspects of the story are not the only salient ones. What matters for the future is the recognition that the responsible actor in the story was Amazon itself, the company, and not the AI it built and used. Discussions of AI too often proceed as if the technology will appear among us like the monolith in the film 2001: something alien and immensely powerful but immediately recognisable and clearly distinguished from the hominids around it. It’s not happening like that at all.

AI is already all around us and is always a hybrid or symbiotic system, made up of the humans who tend the programs and feed them data quite as much as the computers themselves. Companies such as Google or Amazon – and even traditional media and retailers – are now partly constituted by the operations of their computer systems. It is therefore essential that moral and legal responsibility be attached to the human parts of the system.

We hold Facebook or Google responsible for the results of their algorithms. The example of Amazon shows that this principle must be more widely extended. AI is among us already, and the companies, the people, and the governments who use it must be accountable for the consequences.

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