Office workers want their workplace to be flexible, adaptable and free from processes and systems that slow down productivity. But what do they expect for the future of the workplace?

In 2017, enterprise work and project management company Workfront surveyed of over 2000 workers across US companies to determine what the US office will look like in five years’ time.

It wanted to capture how workers felt about the challenges of today and the potential challenges of the future workplace.

Legacy Systems. Antiquated systems such as email get heavily criticized in the report. Over the past few years, poorly used meetings and email topped the list of things that prevent productivity amongst knowledge workers.

US workers say they have an average of 199 unopened emails in their inboxes at any given time. Of the 68 emails received per day by the average knowledge worker, 21 are junk mails, and only 27 demand some answer or action.

Email, although useful, seems to create issues. It is accused of stealing workers' time and preventing them from finding critical project information. For the majority of knowledge workers, the inability to convey or find essential information in email is a significant problem according to the report.

These tools and practices are supposed to improve worker productivity and collaboration. Unfortunately, wasteful meetings and excessive emails top the list of productivity killers, with 15% of the working day spent dealing with email.

20% of respondents answered that email would no longer be used as a primary collaboration tool in the future and 31% believe that collaboration software will eliminate most conference calls. A further 28% think that printers will become obsolete because everything will be available digitally.

The Casual Workplace. Workers are convinced that the way we work will change dramatically over the next five years. Almost half of the respondents (49%) believe that dress codes will become more relaxed and over a quarter (28%) feel certain that fixed desk space will become a thing of the past.

The New World of Work. So, what will the office of the next few years look like? Although 42% of workers do not have the opportunity to work from home, the average worker works from home one day per week.

Almost two-thirds of respondents (61%) said that video conference calls would enable remote working and half think that mobile phones will become the mobile office.

One in ten will not adopt flexible working due to negative perceptions. Almost a third (31%) believe that social media will become a significant work tool.
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Although knowledge workers are optimistic about the future, they felt that technology will release employees to work wherever and whenever they want to. The challenge for enterprises is to find the systems and technology to make this a cost-effective reality.

The case that could transform privacy law in the digital era began with the armed robbery of a Radio Shack store in Detroit, a couple of weeks before Christmas in 2010. In the next three months, eight more stores in Michigan and Ohio were robbed at gunpoint.

The robbers took bags filled with smartphones. Their phones would help send them to prison.
This past week, the Supreme Court considered whether prosecutors violated the Fourth Amendment, which bars unreasonable searches, by collecting vast amounts of data from cellphone companies showing the movements of the man they say organized most of the robberies.

Experts in privacy law state the case, Carpenter v. United States, No. 16-402, is a potential blockbuster.

The court’s decision, expected by June, will apply the Fourth Amendment, drafted in the 18th century, to a world in which people’s movements are continuously recorded by devices in their cars, pockets, and purses, by toll plazas and by transit systems. The court’s reasoning may also apply to email and text messages, internet searches, and bank and credit card records.

The case concerns Timothy Ivory Carpenter, who witnesses said had planned the robberies, supplied guns and served as a lookout, typically waiting in a stolen car across the street. “At his signal, the robbers entered the store, brandished their guns, herded customers and employees to the back, and ordered the employees to fill the robbers’ bags with new smartphones,” a court decision said, summarizing the evidence against him.

In addition to presenting testimony, prosecutors relied on months of records obtained from cellphone companies to prove their case. The documents showed that Mr. Carpenter’s phone had been nearby when several of the robberies happened. He was convicted and sentenced to 116 years in prison.
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“If the court squarely recognizes what it’s been suggesting in recent cases, namely that we do have an expectation of privacy in our digital data and public movements and that the Fourth Amendment prohibits the government from tracking us door to door for weeks in public, that would be an occasion for dancing in the streets,” he said. “If the court holds that we don’t have an expectation of privacy in public except when there is some sort of physical trespass involved, that could be a huge setback for privacy.”

Deloitte just announced the availability of audit technology for smaller accounting firms through a new venture it recently formed.

Deloitte created Auvenir as an in-house startup and tasked it with developing its own auditing technology that could be offered to small firms. Next week, Deloitte plans to announce the North American launch of the technology, known as the Auvenir Audit Smarter platform, which leverages artificial intelligence to help auditors with their work.

Auvenir doesn’t use Deloitte’s own proprietary auditing technology, but it was developed with input from Deloitte’s audit team. The Auvenir team also interviewed a number of small to midsized audit firms and their clients across North America to identify the issues they encounter with audits. It has been beta testing the Audit Smarter technology with several auditing firms in Canada.

Deloitte global audit and assurance innovation leader Chris Thatcher said he was tasked by his boss with coming up with the kind of technology that a startup might develop in competition with Deloitte. “One of the things he was quite concerned about, that kept him up at nights, was a couple of guys in a garage thinking about how you could do audit completely differently to how we would have done it traditionally in the past,” he said. “My boss basically challenged me to think about defending ourselves from disruption.”

 “From our perspective at Auvenir, we spoke to hundreds of auditors and clients, primarily in that part of the market, the smaller auditing firms and smaller clients, and what we found is that a lot of the technology that’s available to them is not the right size technology for the size of engagements they’re dealing with,” Auvenir CEO Pete Myers said. “We want to open this up for any accounting firm. We’re not restricting who uses it. It’s available to any firm out there.”

The platform uses cloud-based storage, machine learning and artificial intelligence to improve workflow and collaboration between auditors and their clients.

The machine learning component helps auditors judge whether there is a low or high risk from the trends they are seeing. “It would be like saying nine out of 10 auditors when they were looking at this industry thought this was a high risk, but giving those insights in a real way,” said Myers. “It’s really providing those insights and tips, as someone who is working through the engagement or going through their decision-making to just have somewhat more confidence in the decisions they’re making. One thing that’s very clear, as a platform we’re not taking on the audit itself. We’re just a tool to be used by auditors, and we’re not making any of the decisions that need to be made in coming to an opinion.”

Deloitte admitted last month to a data breach in which hackers were able to access client data from its internal email system (see Deloitte email platform and client data hit by cyberattack). However, Auvenir is using separate servers and is emphasizing security.

“We host the data, and it’s completely separate from where Deloitte hosts their data,” said Myers. “Data security is one of our most important governing principles. In conversations with auditors and clients, it’s top of mind that the data is secure. Basically all of our customer and application data is encrypted whenever it’s being transmitted between our servers or with a customer device. It’s also encrypted anytime it’s stored on our servers. The data is never stored or transferred to a customer without strong encryption and then our encryption algorithms are all compliant or exceed ISO and NISD standards. And in addition to that, we’re making sure we’re going through an independent SOC 2 certification to make sure we’re complying with the SOC 2 and ISO 27001 security standards.”
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Deloitte sees the technology as an innovation for the audit profession. “We believe this is quite radical innovation,” said Thatcher. “This is radically different innovation from what we’ve seen traditionally from ourselves and from others in the market. This is the very first venture we have done as a global audit business and certainly we hope it is not our last.”

Apple CEO Tim Cook made a surprise appearance at a Cisco event in Las Vegas recently, revealing plans to help businesses with discounts on cyber-security insurance if they use products from both companies. Following the event, Cisco announced another outcome of its Apple partnership, the Cisco Security Connector app for iPhone and iPad.

"The thinking we share here is that if your enterprise or company is using Cisco and Apple, that the combination of these should make that insurance cost significantly less," Cook said according to Reuters. "This is something we're going to spend some energy on. You should reap that benefit."

The Security Connector app will launch this fall, and offer "security functionality from Cisco Umbrella and Cisco Clarity in a single app," Cisco said. Specifically, the app will aid in the investigation of incidents, block people from connecting to malicious websites, and encrypt DNS requests.

Organizations will have to deploy the app via a mobile device management platform — most likely Cisco's Meraki Systems Manager. Before this fall, organizations will be able to test Security Connector by way of a beta program.
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Apple and Cisco first announced their collaboration in Aug. 2015, intended to ensure iPhones and iPads were optimized for Cisco networks, and vice versa.

The Thermia online health educational tool, developed at Boston Children’s Hospital, has enabled one-month-faster prediction of seasonal influenza outbreaks in China, via its digital integration with a commercially-available wearable thermometer. The findings appear in a new study published in the American Journal of Public Health. 

“The fact that we were able to predict influenza outbreaks faster than China’s national surveillance programs really shows the capacity for everyday, wearable digital health devices to track the spread of disease at the population level,” says the study’s lead author Yulin Hswen, who is a research fellow in Boston Children’s Computational Epidemiology Group and a doctoral candidate at the Harvard T. H. Chan School of Public Health.

Although the Boston Children’s team has previously demonstrated that social media can be used to track disease, this is the first time they’ve shown that outbreaks can be predicted through an integrated wearable device and online tool.

“Collectively, we are still coming to terms with the data deluge from wearable devices, but it is imperative that we begin to generate value from this data,” says the study’s senior author Jared Hawkins, PhD, who is the director of informatics at Boston Children’s Innovation and Digital Health Accelerator (IDHA). “From a public health perspective — as we have shown with this latest study — there is enormous potential for tapping this data for research, surveillance and influencing policy.”

Thermia, a fever educational tool created by the Boston Children’s team, works as a standalone digital application or can receive a child’s temperature reading directly through the iThermonitor, an FDA-approved, patch-like thermometer that is worn under the arm. This integration is possible under a license agreement between Boston Children’s and the iThermonitor’s manufacturer, Raiing Medical Inc., which is based in China. Although the wearable is available around the world, consumers in China have been the earliest adopters of the device.

In China, the Thermia-empowered iThermonitor has quickly gained popularity among digitally-savvy parents who have purchased the wearable device to monitor their child’s temperature. When iThermonitor detects a fever, parents can access Thermia via web or mobile and answer online questions about the child’s current symptoms and medical history.

Data collected from these interactions is anonymized and analyzed by the Boston Children’s team to track disease at the population level. Using this method, the team collected nearly 45,000 data points from China’s Thermia users between 2014 and 2016. They discovered that outbreaks of “influenza-like illnesses”, which had the hallmark signs of influenza, could be detected digitally in real time.

In comparison to the influenza surveillance data collected by the National Health and Family Planning Commission (NHFPC) of the People’s Republic of China, the data from iThermonitor and Thermia identified emerging outbreaks of the flu an entire month earlier.

In contrast, China has 620 million mobile internet users who can theoretically access the standalone Thermia application from any computer, smartphone or even the Amazon Alexa assistant.

“In geographically large and densely populated countries like China, tools like Thermia can provide better on-the-ground disease surveillance than by relying on data that is only captured at the point of treatment in the clinic,” says Hswen.
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You can access Thermia to learn about your child’s symptoms and contribute to Boston Children’s anonymized disease database.

This year, I have covered Blockchain technology with four different articles (Issues 3-17, 3-24, 3-25, 3-31). Blockchain's claim to fame is its ability to fully encrypt personal data on the internet, allowing for the digital translation of assets and the elimination of need for a protective middle man. Essentially, this new crypto-technology enables secure-funds transactions and ensures that data cannot be hacked by outsiders.

Epstein explained that blockchain is a "distributed ledger." It's not a database sitting in an office. It's a database that everyone can access.

"We're seeing decentralization and a paradigm shift of moving from institutions to ourselves. Power has been given back to the business owners, who no longer need to rely on the permission of banks and governments to send money electronically," says blockchain expert Jeremy Epstein.

When you use a bank as an intermediary to transfer funds to another person by check, each person involved in the transaction has a separate record. The bank doesn't know right away that the person writing the check has a balance to cover the amount written out--there is an element of trust, and things can go wrong.
"We've been built to have other organizations be custodians of our assets (like banks). However, there have been more and more violations of our data,” Epstein added.

Conversely, Blockchain allows for privacy in the combination of records and the elimination of any intermediaries. Both parties can view the encrypted ledger and see any mutual transactions, but no one party controls it. Rather, each transaction is a block that is added to a chain once all parties affirm the block is correct. The chain itself is protected by cryptography.

"With blockchain, everyone can clearly see who the owner of the asset is, but only the person with the right key can unlock the door of that asset.

Think about the title of the asset - it would be in your control. This is why people buy title insurance. Blockchain lets us buy and sell any asset without an intermediary. Additionally, the asset is programmable, so you can set up business rules and computational logic for each asset. For instance, you could put in place a rule that states, 'I can't sell this without others signing off.' Thus, the asset cannot be not sold unless business rules are met."

According to Harvard research, Blockchain also maximizes transparency and anonymity. Each transaction is seen by anyone who has access to the chain; however, since each node (or user) has a unique alphanumeric identifier, each user can decide whether to remain anonymous in the transaction between addresses. These transactions can also be programmed with algorithms that can automate transactions between users.

So, if blockchain is so good, why hasn’t it caught on yet? There are four reasons to that question.

• Trust Issues. Epstein emphasized the issue of believability and gaining trust of users. He said, "How will people get their head around this technology? Building trust and credibility will take time.
• Stigma. Harvard found that some industries may view blockchain as "disruptive" because it "can attach a traditional business model with a lower-cost solution and overtake incumbent firms quickly." However, they argue that blockchain is most importantly a foundational technology that can be used to create new business models and underpin business, economic, and social infrastructure.
• Novelty. It will take decades for blockchain to seep into our economic and social infrastructure. The process of adoption will be gradual and steady. Epstein agrees, saying that, "it is still very, very early. Think Internet circa 1993."
• Adoption. Epstein indicates that the financial services industry has implemented blockchain technology more than any other. They're looking to improve efficiencies with cross-border transactions. Bitcoin is the most well-known blockchain application.
  

Essentially, "Email is to the internet the way bitcoin is to blockchain. There are multiple apps, just like there are multiple blockchains," says Epstein.

Blockchain is still in its early stages, and new crypto-technology applications and advancements are regularly occurring. We expect big changes over the next few years, as over $1 billion has been invested into this tech by venture capitalists.

A new kind of attack is targeting unsecured Internet of Things devices by scrambling their software and rendering them useless.

Security firm Radware first spotted the newly-found "BrickerBot" malware last month after it started hitting its own devices, logging hundreds of infection attempts over a few days. When the malware connects to a device with their default usernames and passwords – often easily found on the internet – the malware corrupts the device's storage, leading to a state of permanent denial-of-service (PDoS) attack, known as "bricking."

In other words, this attack, "damages a system so badly that it requires replacement or reinstallation of hardware," said Radware.

Like the Mirai botnet, most famous for bringing down wide swathes of the US internet last year in a massive distributed denial-of-service (DDoS) attack, the BrickerBot also uses "the same exploit vector" by brute-forcing telnet accounts with lists of available usernames and passwords.

The researchers say that the attackers also have an affinity for targeting devices on Ubiquiti networks. Once inside, the malware runs a sequence of commands, which "try to remove the default gateway and disable TCP timestamps as well as limiting the max number of kernel threads to one," which would scramble the device's memory.
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"Unfortunately, even after performing the factory reset, the camera device was not recovered and hence it was effectively bricked," said Radware.

The ongoing war between malicious hackers and technology security specialists has been waging for as long as the Internet has been widely used. One tool in the arsenal is called a Botnet. A Botnet essentially is a number of devices which are connected by the internet and controlled remotely by the botnet’s owner. But how are these made? Why are they almost always associated with nefarious activities? And are there any botnets out there doing good?

There are a few ways for someone to start amassing a botnet. The most common involves an individual purchasing or building a malicious program that will infect a targeted computer or network of computers. Usually this is in the form of a Trojan Horse, but it can be done with drive-by downloading or exploitation of browser vulnerabilities. The program then logs into the victim’s command and control server, and as simple as that the infected computer is now at the mercy of the botnet’s owner.

Botnets can be rather small, to impressively massive in scale. However, the only individuals who may have any guess as to how large these networks are would be the botnet operators themselves. This is because the infected computers rarely experience any disruptions in normal service except when they are being used for various tasks that the owner has commanded them to take part in. Also most attempts to track botnets by the number of IP addresses within them may lead to inaccurate estimates, since the owner may be tumbling through numerous IPs.

Botnets usually get a bad reputation because of the overwhelming number of malicious activities that they have been used in. Especially with media outlets reporting sensationalist stories of attacks using botnets – which seem to always blame the Internet more than the actual human attackers.

That being said, botnets usually are used for things like distributed denial of service (DDoS) attacks. These DDoS attacks have played large roles in attacking financial institutions and other organizations in the past. It makes sense, as a botnet can provide an incredible amount of traffic/power to an attack like that with the keystrokes of a single actor. But botnets are also used in spyware campaigns, click fraud, and dubious bitcoin mining.

However, not all botnets are used for such activities. The difference between botnets used in illegal activities and botnets which are helpful for benevolent and benign applications, appears to be what we call them and how we acquire them. Cloud computing applications like Amazon Web Services seems to share a large amount of characteristics of botnets as far as their usability. The difference, of course, is that we call that “Infrastructure as a Service” and all of the computing power is legally rented out to users.
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So some types of botnets can be used for good – provided that the companies and individuals renting out AWS are on the level. But with the reputation that botnets have, it’s easy to understand why AWS and other similar services would call themselves “Cloud Computing” as opposed to “Botnet.”

Confirming rumors, Samsung last week revealed the existence of "Bixby," a new AI assistant that debuted with the Galaxy S8 and will challenge Apple's Siri with some new technologies.

Bixby, for instance, can handle many tasks that otherwise use touch or button input, Samsung said. Siri —and other AIs, like Google Assistant – typically only support a small selection of voice commands. Through contextual awareness, Bixby users should even be able to mix touch and voice input.

Bixby will also offer what Samsung describes as "cognitive tolerance," allowing it to recognize commands with incomplete information. As needed, it will prompt for more details.

In iOS 10 and macOS Sierra, Siri still requires that people use specific, fully-formed voice commands, which also don't adapt to what's onscreen. Google Assistant is more flexible, but doesn't support a mix of touch and voice.

The S8 has a dedicated Bixby button letting people trigger the assistant at any time, Samsung noted. Just a handful of pre-installed apps will support the platform at first however, and the company will only "eventually" release an SDK for third-party developers.
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First-party support should gradually extend to other Samsung hardware, including not just phones but devices like TVs and air conditioners. 

When people speak of IBM Watson, they do so in hushed tones in the corner of rooms, whispering for fear it will jinx it and the promise will not be realized. ‘Did you hear? Watson will cure cancer.’ Watson is, in many ways, the Chuck Norris of cognitive computing. 

Watson’s reputation stems, in no small part, from IBM itself, who are not modest when it comes to blowing their own horn. Dr. John Kelly, who heads up the Watson team at IBM, has claimed that ‘This is brand new technology. It’s going to change the world.’ Not to be outdone, Ann Rubin, IBM's VP of branded content and global creative, said that Watson enables users to ‘outthink cancer, outthink risk, outthink doubt, outthink competitors.’ Big promises. But is this hype warranted, or, as some believe, is the emperor running amok completely naked? 

IBM established itself as a leader in the artificial intelligence field back in 1996 when its Deep Blue chess playing computer defeated Russian chess Grandmaster Garry Kasparov. Then Watson’s Jeopardy victory in 2011 cemented its reputation. Shortly after the Jeopardy victory in 2014, IBM broke down Watson’s capabilities into 40 different components each serving a particular business problem, which is the business model it still uses today. 

IBM pitches Watson as a solution for a variety of industries, from healthcare to financial services. It crunches through vast amounts of data to understand problems and environments in the same way humans do, a process known as cognitive computing. It then uses these insights to provide predictions and make decisions. According to IBM, the business is growing. It is at the center of the company's ‘strategic imperatives’ - which include cloud, mobile and analytics - that contributed $32.8 billion in revenue in 2016. However, further details around the return on investment are scant, as it is lumped in with the other technologies in the company’s financial statements. In February last year, chief executive Ginni Rometty explained that it does not provide much information because Watson is new and growing, telling the annual IBM analyst meeting, ’We are building an era, a platform, an industry, and making a market with it. We have competitors who don’t disclose for a decade, [so] I’m going to protect it and nurture it — we will disclose eventually’. 

Rometty’s position is understandable, but evidence of success may at least help to counter the growing body of criticism. Among these critics is Meg Whitman, CEO of IBM competitor Hewlett-Packard Enterprise. Last year she noted that ‘We're in a lot of customers where actually from a Watson perspective it's not as far along in terms of real-world applications as you might imagine from the advertising.’ This could easily be dismissed as a competitor trying to get one over on a rival, but her’s is not a lone voice. Many others are starting to argue that Watson is just a thinly veiled advertising campaign, exploiting the notoriety achieved from its Jeopardy! win to promote its consultancy services and the technologies it has put under the Watson umbrella that are not especially groundbreaking. 

Also among the dissenters is Roger Schank Ph.D., founder of the Institute for the Learning Sciences at Northwestern University. He accuses Watson of false advertising, writing in an excoriating blog post that Watson is essentially just a ‘word counter’ little different from Google search. He says that it is incapable of any non-trivial reasoning, contrary to how IBM presents it in its advertising, noting specifically an ad campaign IBM ran that showed Watson’s analysis of Bob Dylan songs for key themes, which it identified as ‘love fades’ and ‘time passes’ - themes Schank argued no Dylan fan would ever put down as his most important. Although, Dylan says those themes sound ‘about right’ in the advert, so it could just be that Schank is misremembering. 
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IBM refutes accusations that it is not the high-end proposition it claims. Dr. Kelly says that ‘Everything we brand Watson analytics is very high-end AI,’ and you will find little argument that IBM’s Watson artificial intelligence system is an incredible piece of technology. It’s more than capable of searching across vast repositories of unstructured digital data and returning answers remarkably quickly and has done amazing things, particularly in healthcare and refining diagnoses. The problem is not whether it's a market leader, though, it’s the promises it is making. Watson has suffered from the goals it has set for itself, from curing cancer to being the solution to cybersecurity. These are important things to resolve, and IBM needs to be honest with how much Watson can really do. Overhyping AI is dangerous, as we saw when inflated expectations and subsequent disillusionment in the 1980s led to the so-called AI Winter, bringing investment to a grinding halt and pushing research ‘underground.’ Obviously, IBM wants to sell its product, and because it is such a nascent technology it needs big targets like cancer and cybersecurity to put itself on the map and gain customer support. However, in the long term, it could be shooting itself in the foot. The thaw has been hard earned, and although another setback of the same magnitude is unlikely for AI, expectations should still be managed.