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5 Ways Tech Can Revolutionize Education

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Professor Sally Smith, Dean of School of Computing at Edinburgh Napier University, was in South Africa to share how tech can revolutionize education and what Africa can learn.


With the Fourth  Industrial Revolution gaining speed, the nature of work and economic activity is set to dramatically change. One woman is on a mission to prepare the education system for such changes.

Professor Sally Smith, the Dean of School of Computing at Edinburgh Napier University, traveled from Scotland to South Africa to share her know-how, as one of the speakers at the Future of the Education Summit in Johannesburg.

Hosted by Africa Business News, the summit brought together thought-leaders and professors from all over the world. Smith met FORBES AFRICA a day before the summit to speak about her experiences in the education industry for 26 years:

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1.What trends have you picked up in the sector over the years?

In terms of technology, it has been very fast-moving so the big challenge for universities is conducting research and translating that into useful programs for students when they graduate.

In terms of the kind of trends and developments, we have seen huge growth in areas such as creative computing. There have been developments around designing meaningful interactions with computers, and that’s no longer just [limited to] a desktop computer; that will be your mobile phone, it’ll be augmented reality systems, virtual reality systems and other recent trends like cyber security.

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With more of our lives being conducted online, there’s a need to make sure we secure our data security, our identity is secure and businesses as well need to protect themselves. Those have been really interesting ways in which I have seen a big change in recent years.

And the other thing that has changed is there has been a lot of growth in AI. Some of those kinds of machine learning tools are now being put to wider use than ever before by things like self-driving cars. So that’s an area of great interest now to our students and when they graduate to apply these algorithms.

2.What do you think are the challenges in this sector?

One of the things we’ve been disappointed with in much of the western world is how few women are interested in studying computer science and it has been fairly constant at sub-20% of our undergraduate program since I have been in academia. And we have really been unable to make any great inroads into changing that.

3.What differences have you picked up between education in Scotland and South Africa?

Making sure graduates have the right skills to go to work, and part of that is getting work experience and it’s a challenge for all of us to make the case for businesses to take on a student so they can take on relevant work experience before they graduate. Some of the challenges I have seen around are about trying to get those partnerships.

4.How do you see collaborations of universities around the world with the 4th Industrial Revolution?

Yes, I think there are fantastic ways we collaborate over research and a lot of the big funds now are only interested in collaborations where we can draw on the strengths of universities from different countries and I think that the same will be true about teaching.

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At the moment, we are competing with each other but if we can put great programs together that draw on the strength of different universities, there’s a future for more collaborative work.

5.How can the private sector help upskill young people?

We’ve introduced a new way in which people can get degree level qualifications in the UK and degree level apprenticeships. Industry will employ someone and they attend university 20% of the time and work towards their degree while they are in work.

So that is a new way to make sure the degree is appropriate for employers and these programs are employer-led so employers are part of designing the program. The other project we have is a digital skills partnership which is where we try and get industry and lecturers to work more closely together on things like developing curriculum.

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Banks Are Promoting ‘Female’ Chatbots To Help Customers, Raising Concerns Of Stereotyping

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Meet Amy. And also Debbie, Inga, Mia, Erica, Eva and Cora.

These aren’t the members of a new, all-female rock group, but names that several large banks have been giving to their automated digital assistants.

So-called chatbots have become a useful cost-cutting tools for companies with large subscriber bases (think banks, insurance firms and mobile phone operators). As they replace human call-center workers, such bots will help save banks an estimated $7.3 billion in operational costs by 2023, Juniper Research predicts.

But the proliferation of bots with female names raises questions about whether they might also perpetuate gender stereotypes, particularly around the notion of women in the role of assistants. That criticism has already been levelled at Amazon’s digital assistant Alexa and Apple’s Siri.

Now a Forbes analysis of Europe’s 10 biggest banks ranked by assets shows that at least three have deployed chatbots with female names on their websites and apps. HSBC has a chatbot named Amy; Deutsche Bank’s Debbie helps market traders; ING of the Netherlands has Inga, a chatbot that will “respond with empathy” to customer problems such as losing a card.

ING’s other chatbot Marie, available to retail customers on Facebook Messenger, was given the name “because it conjures up an image of someone who is helpful and friendly,” Tim Daniels, a programme manager for ING was quoted as saying on the bank’s website. (ING has a male chatbot named Bill, aimed at dealing with corporate customers.)

Among the other lenders, Santander, Barclays and Societe Generale appear to have unnamed chatbot assistants. Credit Agricole has an internal chatbot with a male name: Hector.

Female chatbots abound in other regions and industries. Bank of America recently deployed a digital assistant called Erica, while Mia, the chatbot released by Australian digital bank UBank, was described by the company earlier this month as “empathetic,” “fun” and “a little bit cheeky.”

IPSoft, a New York-based software company that sells chatbot technology to banks like Sweden’s SEB as well as mobile network giant Vodafone, has its own white-label version of a customer-facing chatbot, named Amelia.

IPSoft’s CEO Chetan Dube denied that the chatbot’s name perpetuated stereotypes, when asked by Forbes during an interview in December, and said it instead highlights “the thought leadership that is represented in females.”

“She was the first female aviator that tried to go around the world,” Dube added, referring to the 1930’s aviator Amelia Earhart.

Forbes revealed earlier this month that Vodafone was measuring the success of its chatbots on how many staff could be replaced by the software. While that may be an uncomfortable metric, the more worrying consequence of chatbots, according to four industry experts questioned by Forbes, is the risk that they could reinforce certain stereotypes.

“Gender bias is an increasingly serious issue in chatbot design, especially for voice-based chatbots,” says John Taylor, CEO of action.ai, a British startup that makes chatbot software for banks and travel companies. “These assistants often perform tasks that many view as menial.”

Vitor Shereiber, a language specialist at the German language-learning app Babbel, says that focus-group testing might lead companies to assign a gender to a chatbot on the notion that it makes customer feel more comfortable.

But, he adds, bots could spread unrealistic expectations of how women should present themselves professionally, just as photoshopped pictures have done for women’s perceptions of their bodies.

Part of the challenge for companies is finding a balance between automating customer service without putting customers off. PwC recently described chatbots as being able to “massively enhance customer delight and loyalty” because of their “personal touch.”

Taylor suggests software designers should try creating more chatbots with male names and male voices.

On the sidelines of a technology conference in London on Wednesday, Seth Juarez, an artificial-intelligence engineer based in Redmond, Washington takes it a step further. He calls Siri up on is iPhone to ask the time, and a male voice responds.

“I make it a guy specifically because I find it morally reprehensible that all of the service-based bots are female, and all the intelligence based bots [like IBM’s Watson] are named after dudes.”

He added that artificial intelligence generally shouldn’t be anthropomorphised. Chatbots should be used to manage “cheap thoughts,” or “stuff that a human would do robotically” rather than on more complex issues. “I would leave those problems to humans.”

-Parmy Olson;Forbes Staff

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BMW And Daimler Pool Resources On Automated Driving Technology

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Daimler and BMW deepened their alliance on Thursday to share spiraling development costs for highly automated driving technologies, even as each carmaker pursues separate efforts to develop fully self-driving cars.


The enormous cost of designing and building computer-powered vehicles has already prompted Honda to pool its efforts with General Motors, while Volkswagen is pursuing talks with Ford about an alliance on autonomous cars.

BMW and Daimler deepened their alliance for similar reasons, said Michael Hafner, head of automated driving at Mercedes-Benz research and development said in a blog post which accompanied a joint press release by the companies on Thursday.

“We have learned that the development of these systems is a bit like climbing a mountain,” he said.

“Taking the first few meters from the base station to the summit seems easy. But the closer you come to the goal, the thinner the air around you becomes, the more strength is required for each further step, and the more complex become the challenges you have to resolve.”

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It made sense to distribute the technological and financial challenges of automated driving, Hafner said, so BMW and Daimler will jointly develop technology to enable automated driving on highways.

“Initially, the focus will be on advancing the development of next-generation technologies for driver assistance systems, automated driving on highways and parking features,” the companies said in the statement.

“In addition, the two partners plan to discuss the possibility of extending their collaboration to cover higher levels of automation, both on highways and in urban areas.”

BMW and Daimler’s move comes as even deep pocketed technology companies struggle to gain traction in autonomous driving. Apple Inc said on Wednesday it planned to lay off 190 employees in its self-driving car program, Project Titan.

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The market for advanced driver assistance systems and autonomous vehicles is expected to grow to $96 billion in 2025 and $290 billion in 2035 from about $3 billion in 2015, according to Goldman Sachs.

BMW and Daimler already cooperate in high-definition mapping with HERE and in the area of procurement, and earlier this month unveiled a joint ride-hailing, parking and electric car charging business.

They said on Thursday their new partnership will center on so-called level 3 and level 4 automated driving technologies, including cars that still require steering wheels and drivers.

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Daimler will pursue a separate development alliance for level 5 robotaxis between its luxury brand Mercedes-Benz and supplier Robert Bosch. Level 5 cars require no driver.

BMW, for its part, continues its development alliance for robotaxis with Israeli autonomous vehicle tech company Mobileye and chip maker Intel, with the aim of putting autonomous cars on the road by 2021. -Reuters

-Edward Taylor

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Navigating Bitcoin, Ethereum, XRP: How Google Is Quietly Making Blockchains Searchable

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It’s a balmy 80 degrees on a mid-December day in Singapore, and something is puzzling Allen Day, a 41-year-old data scientist. Using the tools he has developed at Google, he can see a mysterious concerted usage of artificial intelligence on the blockchain for Ethereum.

Ether is the world’s third-largest cryptocurrency (after bitcoin and XRP), and it still sports a market cap of some $11 billion despite losing 83% of its value in 2018. Peering into its blockchain—the distributed database of transactions underpinning the cryptocurrency—Day detects a “whole bunch” of “autonomous agents” moving funds around “in an automated fashion.”

While he doesn’t yet know who has created the AI, he suspects they could be the agents of cryptocurrency exchanges trading among themselves in order to artificially inflate ether’s price.

“It’s not really just single agents doing things on their own,” Day says from Google’s Asia-Pacific headquarters. “They’re forming with other agents to have some larger group effect.”

Day’s official title is senior developer advocate for Google Cloud, but he describes his role as “customer zero” for the company’s cloud computing efforts.

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As such it’s his job to anticipate demand before a product even exists, and he thinks making the blockchain more accessible is the next big thing.

Just as Google enabled (and ultimately profited) from making the internet more usable 20 years ago, its next billions may come from shining a bright light on blockchains. If Day is successful, the world will know whether blockchain’s real usage is living up to its hype.

Danish researcher Thomas Silkjaer is using Google’s BigQuery to map publicly available information about XRP cryptocurrency addresses. The craters represent some of cryptocurrency’s largest exchanges.

Last year Day and a small team of open-source developers quietly began loading data for the entire Bitcoin and Ethereum blockchains into Google’s big-data analytics platform, BigQuery. Then, with the help of lead developer Evgeny Medvedev, he created a suite of sophisticated software to search the data.

In spite of a total lack of publicity, word of the project spread quickly among crypto-minded coders. In the past year, more than 500 projects were created using the new tools, trying to do everything from predicting the price of bitcoin to analyzing wealth disparity among ether holders.

When it comes to cloud computing, Google is far behind Amazon and Microsoft. Last year Google pocketed an estimated $3 billion in revenue from cloud ser­vices. Amazon and Microsoft, meanwhile, generated about $27 billion and $10 billion, respectively.

Day is hoping that his project, known as Blockchain ETL (extract, transform, load), will help even the playing field. But even here Google is trying to catch up. Amazon entered blockchain in a big way in 2018 with a suite of tools for building and managing distributed ledgers.

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Microsoft got into the space in 2015, when it released tools for Ethereum’s blockchain. It now hosts a range of services as part of its Azure Blockchain Workbench. But while Amazon and Microsoft are focusing on making it easier to build blockchain apps, Day is focusing on exposing how blockchains are actually being used, and by whom.

“In the future, moving more economic activity on chain won’t just require a consensus level of trust,” says Day, referring to the core validating mechanism of blockchain technology.

“It will require having some trust in knowing about who it is you’re actually interacting with.” In other words, if blockchain is to go mainstream, some of its beloved anonymity features will have to be abandoned.

A native of Placer County, California, Day got his first computer at the age of 5 and a few years later started writing simple programs. A fascination with volcanoes and dinosaurs turned his interest to life sciences, and he ultimately graduated from the University of Oregon with a dual degree in biology and Mandarin in 2000. From there he headed to UCLA to pursue a doctorate in human genetics and helped build a computer program to browse the genome.

This Silkjaer image uses data for the XRP cryptocurrency to show the movement of funds across the entire ledger of transactions, culminating in a snapshot of funds in an actual user’s wallet.

It was at UCLA where Day began relying on distributed computing, a concept that is core to blockchains, which store their data on a large network of individual computers. In the early 2000s Day needed to analyze the massive amounts of data that make up the human genome. To solve this problem he hooked many small computers together, vastly increasing their power.

“Distributed-systems technology has been in my tool kit for a while,” Day says.

“I could see there were interesting characteristics of blockchains that could run a global supercomputer.”

Hired in 2016 to work in the health and bio­informatics areas of Google, Day segued to blockchains, the hottest distributed-computing effort on the planet. But the talents he had honed—sequencing genomes for infectious diseases in real time and using AI to increase rice yields—were not easily applied to decoding blockchain.

Before Day and Medvedev released their tools, just searching a blockchain required specialized software called “block explorers,” which let users hunt only for specific transactions, each labeled with a unique tangle of 26-plus alphanumeric characters. Google’s Blockchain ETL, by contrast, lets users make more generalized searches of entire ecosystems of transactions.

To demonstrate how customers could use Blockchain ETL to make improvements to the crypto economy, Day has used his tools to examine the so-called hard fork, or an irrevocable split in a blockchain database, that created a new cryptocurrency—bitcoin cash—from bitcoin in the summer of 2017.

This particular split was the result of a Hatfield and McCoy “war” within the bitcoin community between a group who wanted to leave bitcoin as it was and another who wanted to develop a currency that, like cash, was cheaper and faster to use for small payments.

Using Google’s BigQuery, Day discovered that bitcoin cash, rather than increasing so-called micro-transactions, as the defecting developers claimed, was actually being hoarded among big holders of bitcoin cash.

“I’m very interested to quantify what’s happening so that we can see where the legitimate use cases are for blockchain,” Day says. “Then we can move to the next use case and develop out what these technologies are really appropriate for.”

Day’s work is inspiring others. Tomasz Kolinko is a Warsaw-based programmer and the creator of a service that analyzes smart contracts, a feature of certain blockchains that is designed to transparently enforce contractual obligations like collateralized loans but with less reliance on third parties, like lawyers. Kolinko was frustrated with his blockchain queries.

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In December, Kolinko met Day at a hackathon in Singapore. Within a month of the meeting, Kolinko was using Google’s tools to search for a smart contract feature called a “selfdestruct,” designed to limit a contract’s life span. Using his own software in conjunction with Day’s, Kolinko took 23 seconds to search 1.2 million smart contracts—something that would have taken hours before.

The result: Almost 700 of them had left open a selfdestruct feature that would let anyone instantly kill the smart contract, whether that person was authorized or not. “In the past you couldn’t just easily check all the contracts that were using it,” Kolinko says. “This tool is both the most scary and most inspiring I’ve ever built.”

Day is now expanding beyond bitcoin and ethereum. Litecoin, zcash, dash, bitcoin cash, ethereum classic and dogecoin are being added to BigQuery. Independent developers are loading their own crypto data sets on Google.

Last August, a Dutch developer named Wietse Wind uploaded the entire 400 gigabytes of transaction data from Ripple’s XRP blockchain, another popular cryptocurrency, into BigQuery.

Wind’s data, which he updates every 15 minutes, prompted a Danish designer named Thomas Silkjaer to create a heat map of crypto flows. The resulting colorful orb reveals at a glance more than a million crypto wallets, including big ex­changes like Binance and London’s crypto debit card startup Wirex, which are neck deep in XRP transactions.

“Google has been a bit of a sleeping giant in blockchain,” says BlockApps CEO Kieren James-Lubin, who is partnering with Google to sell enterprise blockchain apps.

In addition to Day’s work, Google has filed numerous patents related to the blockchain, including one in 2018 to use a “lattice” of interoperating blockchains to increase security, a big deal in a world where untold millions of crypto have been stolen by hackers.

The company is also pushing its developers to build apps on the Ethereum blockchain, and Google’s venture arm, GV, has made a number of significant investments in crypto startups.

The giant, it seems, is waking up.

-Michael del Castillo; Forbes Staff

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