The Future Of Sensors: Business In High Definition

Kai Goerlich

All change begins with the ability to measure. For millennia, humans relied on our five senses to gauge the world around us in order to survive and thrive.

As civilization advanced, however, we started to use technology to expand those natural capabilities. We began building tools to measure time – first sundials and then sophisticated ones like the sky disc of Nebra and the Antikythera mechanism. Early maps on the walls of the Lascaux caves charted the night sky while the ancient Greek Anaximander drew the first map of the world. Beginning with telescopes and microscopes in the sixteenth and seventeenth centuries, and continuing today with the CERN particle collider, we’ve developed increasingly advanced tools to examine aspects of the universe beyond human perception.

Today, thanks to the explosion of low-cost sensors and high-powered processing and analytics capabilities, we are on the cusp of the next wave of magnifying our natural ability to assess the world around us and stretching the limits of human perception – if we can open our minds enough to let them.

The tiny engines driving the digital revolution

Sensors come in a variety of form factors and with wide-ranging functions: wearables like fitness and health trackers, infrared imaging and night vision sensors, motions sensors such as gyroscopes, chemical and biological sensors, accelerometers and torque sensors, light sensors, gestural sensors. Increasingly, we’re seeing combination sensors that are capable of gathering multiple types of data from the world.

Experts predict that the universe of sensors will grow exponentially in the near future, up to 100 trillion sensors by 2030, depending upon which estimate you believe. These tiny bits of technology are driving everything from robotics to self-diagnosing appliances.

A number of advancements are colluding to make these increasingly ubiquitous sensors both cheaper and more capable every day. Imagespeech, and voice recognition will advance to near 100% accuracy by 2025, according to the latest published research. Today, a passive RFID tag costs between seven and 15 cents to produce. While active tags are more expensive, the cost of these is also rapidly dropping. Emerging 3D printers will enable lower cost production of sensors (and nano-sensors) to embed in day-to-day items like glasses or apparel. These sensors will quickly make their way as standard issue into many places, including the 111 million new cars and the 2 billion smartphones that will be purchased in 2020. If you have one of the latest smartphones, you already have several sensors on board, including a magnetometer, barometer, thermometer, gyroscope, proximity sensor, accelerometer, and light sensor. Indeed, many future sensors will be practically invisible to us.

Perhaps more importantly, the analytics capabilities required to make sense of the staggering amounts of new sensor data – we could be talking brontobytes, or 1,000,000,000,000 petabytes – are also rapidly advancing. The speed of analytics will intensify thirty-fold by 2030, with 95% of queries answered in mere milliseconds, according to SAP estimates. That will be critical in transforming this truly big data into smaller, digestible bites of information. The question is whether or not we can cope with it. As Professor Dr. Yvonne Förster of Luephana University in Luneburg, Germany, points out, our devices already process and deliver information much faster than our human perception can track. As most of these technology-induced rhythms run outside our awareness, it will be interesting to see how we adapt to it.

Widening the doors of perception

Our innate biological senses and nervous systems are truly amazing. The human eye contains 2 x 108 sensors, the ear 3 x 104, and the nose 3 x 107. But with an expanding network of increasingly sophisticated and embedded sensors we’ll be able to expand our perception far beyond our human capabilities. Ultimately, we’ll be able to create an intelligent matrix of sensors and analytic tools to measure, detect, and analyze more data from the world around us. Looking beyond 2025, we will advance beyond data analysis as a distinct activity to more directly experiencing data as an additional aspect of life around us. We will experience the world in much finer detail using virtual reality and other technologies that tap into our biological senses at their roots.

Ultrasound, infrared, low frequency, and position sensors will increase our vision and hearing. Chemical sensors will amplify our ability to smell and taste. Mechanosensors will intensify what we can feel. Medical and biological sensors will monitor the health and status of humans, animals, and plants. And the mix of all the above sensors will be used to monitor a wide spectrum of parameters that are critical to the operation of machines, building, and living things.

Finally, there will be sensors that help us scan our environment for more precise navigation, logistics, weather prediction, agricultural planning, and pollution management. Sensors to watch for here include voice, facial recognition, chemical, biological, and 3D imaging sensors. Occipital Inc.’s 3D sensor provides a spatial view of the environment to be used in virtual and augmented reality and 3D scanning and printing.

We’ll certainly develop algorithms and analytics necessary to process sensor data in an increasingly automated and real-time fashion. But will our minds be able to grasp it all?

An approach that keeps the human at the center might prove helpful as we adapt to the new world of high-powered sensors. According to Professor Förster, we tend to consider technology as an enhancement of our biological nature and believe we can choose which types of technology we allow into our system. But when devices and sensors are ubiquitous, technology becomes like the air we breathe, rather than being a separate part of life, explains Förster. Thus the function of sensors should be to introduce new data streams that are compatible with our existing biological and value systems.

Getting under our skin

Researchers are already developing sensor technologies that are far more embedded than in the past. And they won’t just go into “things” like smart tennis rackets or ceiling fans. Nano-engineers at the University of California, San Diego, have developed a temporary tattoo that could enable non-invasive glucose testing. The FDA has accepted an application for the first digital drug-device that combines a pill for mental illness embedded with an ingestible sensor to track data on patients. MIT scientists have introduced a “Band-Aid of the future” that incorporates temperature sensors, and tiny, drug-delivering reservoirs.

In the future we will see more sensors embedded in humans, animals, plants, and all kinds of everyday items. But how much data do we actually need – and how much can we digest? Much of this data will exist in the background where algorithms will separate the insight from the noise, while new types of sensors will allow us to interact directly with our environment.

Company leaders should consider how they could benefit by combining existing data with the new sensor data that will soon be available. They should monitor the development of sensor technology with an emphasis on where sensor technology threatens to either bypass or optimize traditional business processes, and where new sensor capabilities widen the scope of what we can measure today. And they should keep an eye outside of their own domains for sensor advances that could transform their own businesses in different ways.

There’s no doubt that our five senses will soon be supplemented by these man-made sensors numbering in the billions and capable of measuring anything that we deem to be worthwhile. But deriving business value from them will require us to open our minds to the new possibilities.

Download the executive brief: Making Sense of Sensors

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To learn more about how exponential technology will affect business and life, see Digital Futures.

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Kai Goerlich

About Kai Goerlich

Kai Goerlich is the Chief Futurist at SAP Innovation Center network His specialties include Competitive Intelligence, Market Intelligence, Corporate Foresight, Trends, Futuring and ideation. Share your thoughts with Kai on Twitter @KaiGoe.heif Futu

Meet the Digital You: How Emerging Technologies Are Changing Life Sciences

Jacqueline Prause

“Imagine knowing whether your DNA encodes a risk for migraines even before a headache strikes.” The Yale Journal of Biology and Medicine suggests this as just one example for how emerging technologies will transform our perceptions of healthcare in the years to come.

What is driving this change? The disruption of the life sciences industry, which is experiencing unparalleled market and business changes due to breakthrough technologies like connected health, personalized medicine, health wearables, artificial intelligence, Internet of Things, machine learning, and augmented reality.

On a recent episode of the Internet talk radio program Changing the Game in Life Sciences, a special edition series of Coffee Break with Game-Changers, presented by SAP, a panel of three industry-leading experts discussed how new digital innovations in medical products, data management, and patient care are changing the ways in which the life sciences industry delivers valuable medical solutions – as well as our roles and responsibilities as patients.

Joining moderator Bonnie D. Graham on the panel were: Joe Miles, formerly global vice president of life sciences at SAP, now managing director for life sciences and healthcare at Deloitte Consulting; Robert H. Eubanks, principal, life sciences MALS business unit, at Capgemini; and Hussain Mooraj, partner at Deloitte Consulting.

The following are just some of the observations presented during the one-hour show. For more information, listen to the complete show on demand: How the Digital Economy is Changing Life Sciences.

Patient and medical device information connected through smart technology

Joe Miles: From both a cost and technology perspective, we now have the ability to leverage a variety of different types of devices and sensors that are really giving us an opportunity to manage our own health in the ways that were never really feasible previously, whether that be with a pacemaker or maybe an insulin pump. It’s really giving individuals the opportunity to take more control of their own health, to be more accountable, more responsible, and in most cases more knowledgeable.

Wearables are becoming more seamless. The ability to track health data is becoming more invisible, for example, by utilizing something ubiquitous as a cellphone. A lot of these devices and sensors – although starting out as an overt device that you would see or you would wear – now are just becoming integrated into your daily routine and it’s somewhat seamless. The simplicity and the ease of access is really driving a lot of value for all involved.

Robert Eubanks: Joe brought up a great point around the questions: Do you think people are going to get engaged in this? And how are they going to feel about giving up more of their personal health data? Probably early on there’s going to be some reluctance because there are going to be some very legitimate privacy concerns that people will have. Once we start to understand the power of this, however, people are going to become more comfortable with sharing their information because we’re going to see the improved health outcomes.

For example, someone may come out with a Class II device that’s actually a band and in effect allows you to monitor your glucose 24/7. Think about this with the integration of Siri and artificial intelligence. You wake up in the morning and you ask Siri or Alexa, “How am I doing?” It is going to let you know what your insulin levels look like and maybe make recommendations. It may have access to your calendar and ask if you plan to go out and exercise in the morning. If you say “Yes,” then maybe you need to adjust your nutritional intake that morning or your insulin levels. Likewise, if you’re out and you have location services turned on, and you walk into a Panera Bread, you could ask Siri, “How am I doing?” It will understand where your glucose levels are and then give maybe recommendations on what to have for lunch. Once they realize the health benefits of this, that’s going to be when people start getting more on board with it.

Hussain Mooraj: One of the reasons why healthcare costs have spiraled out of control in the past few decades is that we have been focused on the symptoms rather than prevention. What embedded technologies and remote monitoring capabilities can really allow you to do in healthcare is to move from being reactive towards being proactive: proactive health and prevention. That in itself has massive implications for reducing the overall cost of healthcare, or at least slowing down the pace of increase, but this does not come without its challenges.

Cybersecurity for patient data and medical products: An industry-wide challenge

Hussain: We can talk about embedded innovation and remote monitoring, but what about the issues that we have to deal with around them, which we never had to consider before, like security, cybersecurity, medical product security, and the ability to hack into these various systems? From an industry perspective, we still haven’t really gotten our heads around these and we still haven’t really put practical solutions in place to prevent them.

Joe: I would agree with Hussain, the cybersecurity element is probably one that’s a little bit newer to the discussion and probably has a lot more dire consequences. What we’ve seen from companies like 23andMe and others is that if people can see value from giving their information and it’s anonymized or aggregated into a group, then there’s a willingness and patience to forgo their privacy for that greater benefit. I would agree though that cybersecurity is really a concern given the bad actors that are out there these days.

Digital you: DNA and genome sequencing opens the way to precision medicine

Hussain: We now have the ability to do full genome sequencing. We can take a look at our microbial and the proteo, our metabolome, and come up with what we might want to call the “Digital You.” It’s really the true workings of our body and what makes us unique. Because we have this ability to see that we have predispositions, we can then start taking actions very early to ideally mitigate the disease state for me. If it shows that I may have a high level of sugar sensitivity, then obviously I might be a candidate. The idea is at some point I need to start taking early actions to watch my diet and exercise to prevent the onset of diabetes. The ability to be very predictive here or preventative is going to be a big win for our healthcare ecosystem.

On the other end of the spectrum, we have precision medicine, where when we do have diseases, how do we begin to tailor therapies that work on our unique genomic profile? This is going to be one of the big transformations that the life science industry is going to go through [in] the next decade. Right now we develop therapies based on population averages. We develop pills and therapies that ideally we can sell to the broadest population possible. With the information out there and the ability to crunch this information, we’re going to start designing therapies that work on much smaller populations.

That’s going to cause a big transformation within the industry. It also is going to see the emergence of new players for the companies that are very good at managing very large data sets. There will be some interesting challenges as the industry goes through that, but we are right on the cusp of the next decade or two of just incredible changes in the way we think about our health and the way we administer our health.

Listen to recorded episodes of Changing the Game in Life Sciences to hear how the digital economy is changing the life sciences industry. For more up-to-the minute business and technology news, listen to Coffee Break with Game-Changers broadcast live every Wednesday, 8:00 a.m. PT / 11:00 a.m. ETime on the VoiceAmerica Business Channel. And follow Game-Changers Radio on Twitter at @SAPRadio and #SAPRadio.

The experts’ comments have been edited and condensed for this space.

This article originally appeared on SAP News Center.

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Jacqueline Prause

About Jacqueline Prause

Jacqueline Prause is the Senior Managing Editor of Media Channels at SAP. She writes, edits, and coordinates journalistic content for SAP.info, SAP's global online news magazine for customers, partners, and business influencers .

How To Energize Blockchain's New CSP Business Options For Success

Julie Stoughton

The communication service provider (CSP) industry is evolving. It’s already at the forefront of data, networking, and telephone communications, but as digitization rolls forward, new technology and business models are appearing. One of these technologies that CSPs are starting to use is blockchain. About 39% of telecom operators are strongly considering investing in blockchain in the future. But what is it exactly? How can you use it to explore new business opportunities? Here’s a quick look at how to apply blockchain for your company’s success.

But isn’t blockchain for banks and credit unions?

Blockchain was originally designed for financial institutions and was also used for cryptocurrencies such as Bitcoin. The ledgers it created were automatically notarized, which created a high level of security. Blockchain automatically timestamps each entry and creates a link to a prior block, which makes the system very hard to tamper with. It can also be privately or publicly hosted.

But what does that mean for the real world? It means a private business network can be used by a brokerage firm, allowing individuals at the firm to access information while protecting it against outsiders. At the same time, blockchain can be publicly hosted for bank customers, enabling them to access their accounts anytime, even when the bank is closed. It’s already used by 80% of financial businesses, and within eight years it is expected to be the main platform used in financial services.

Blockchain’s potential for CSP services

In the same way blockchain has changed the financial sector, it can change the telecom industry. Today’s CSP has to deal with a range of inter-operators, currencies, and agreements. In a survey of telecom operators, 68% felt blockchain would be disruptive to telecoms. But with that disruption comes new opportunities. Blockchain supports innovative business models for new companies that disrupt the market.

Studies have shown that early adopters of new technology are seeing strong growth. Telecoms that are avoiding digitizing are losing ground. Blockchain has great potential for telecoms looking to succeed in the new economy. Using blockchain with new business models makes CSPs flexible and agile, able to more easily respond to change and disruption in the telecom market.

How to energize blockchain’s new CSP business options

Today’s communications are mobile. It doesn’t matter whether it’s text, email, phone, or data, as more users become mobile, the telecom system becomes more complex. CSPs have to have agreements and manage payments with other CSP companies. This can lead to a mountain of paperwork, which also creates a lot of costs as that paperwork is processed. Blockchain has the capability to simplify the process.

Let’s use Bitcoin as an example. Bitcoin is international, doesn’t have a specific bank, and isn’t tied to any government currency. It’s also easy to transfer, provides privacy to customers, and isn’t regulated. It doesn’t have to be transferred from one currency to another to determine value. In the same way, blockchain-based CSPs don’t have to change currencies to pay for roaming customers. Bitcoin isn’t regulated, so it doesn’t require a new agreement every time a transaction happens. Blockchain CSPs have smart agreements in place that don’t require additional work as a customer roams. This helps improve connectivity.

Possible opportunities for CSPs using blockchain

Because blockchain creates a direct connection from customer to CSP, the need for inter-operators is reduced or eliminated. This helps lower overall costs for the CSP, which can then offer lower rates to customers while enjoying higher profits. Nearly instant information exchange keeps billing up to date. CSPs know exactly where they stand financially.

Blockchain offers better security. Smart contracts allow CSPs to almost instantly verify subscriber ID, making it much easier to provide permission for them to use a visited operator’s services. It cuts down on fraud and scamming when customers are in a roaming area. CSPs and their customers are better protected by blockchain.

In the prepaid market, blockchain can instantly update balances so both the CSP and the customer know exactly where they stand. In both prepaid and postpaid markets, this can lower the cost of ownership on what has typically been an expensive infrastructure. New markets can be opened for CSPs that were too expensive in the past.

When a CSP uses blockchain to improve operations, it creates new partnership possibilities. In addition, by lowering the cost of operations, it opens opportunities in B2B and B2C revenues as well as Internet of Things and smart cities technologies.

Blockchain’s new platforms provide new opportunities for CSPs. New business models mean you have more opportunity for new growth in your company.

Learn how to bring new technologies and services together to power digital transformation by downloading The Future Services Sector: Connected Services for Continuous Delivery.

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Julie Stoughton

About Julie Stoughton

Julie Stoughton is the Head of Telecommunications Marketing & Communications at SAP. She is a seasoned professional with 16 years of marketing and product marketing experience in software and media technologies. Julie's specialties include strategic market development, positioning and messaging, customer segmentation, product launches, ROI analysis, and go-to-market execution.

More Than Noise: Digital Trends That Are Bigger Than You Think

By Maurizio Cattaneo, David Delaney, Volker Hildebrand, and Neal Ungerleider

In the tech world in 2017, several trends emerged as signals amid the noise, signifying much larger changes to come.

As we noted in last year’s More Than Noise list, things are changing—and the changes are occurring in ways that don’t necessarily fit into the prevailing narrative.

While many of 2017’s signals have a dark tint to them, perhaps reflecting the times we live in, we have sought out some rays of light to illuminate the way forward. The following signals differ considerably, but understanding them can help guide businesses in the right direction for 2018 and beyond.

When a team of psychologists, linguists, and software engineers created Woebot, an AI chatbot that helps people learn cognitive behavioral therapy techniques for managing mental health issues like anxiety and depression, they did something unusual, at least when it comes to chatbots: they submitted it for peer review.

Stanford University researchers recruited a sample group of 70 college-age participants on social media to take part in a randomized control study of Woebot. The researchers found that their creation was useful for improving anxiety and depression symptoms. A study of the user interaction with the bot was submitted for peer review and published in the Journal of Medical Internet Research Mental Health in June 2017.

While Woebot may not revolutionize the field of psychology, it could change the way we view AI development. Well-known figures such as Elon Musk and Bill Gates have expressed concerns that artificial intelligence is essentially ungovernable. Peer review, such as with the Stanford study, is one way to approach this challenge and figure out how to properly evaluate and find a place for these software programs.

The healthcare community could be onto something. We’ve already seen instances where AI chatbots have spun out of control, such as when internet trolls trained Microsoft’s Tay to become a hate-spewing misanthrope. Bots are only as good as their design; making sure they stay on message and don’t act in unexpected ways is crucial.

This is especially true in healthcare. When chatbots are offering therapeutic services, they must be properly designed, vetted, and tested to maintain patient safety.

It may be prudent to apply the same level of caution to a business setting. By treating chatbots as if they’re akin to medicine or drugs, we have a model for thorough vetting that, while not perfect, is generally effective and time tested.

It may seem like overkill to think of chatbots that manage pizza orders or help resolve parking tickets as potential health threats. But it’s already clear that AI can have unintended side effects that could extend far beyond Tay’s loathsome behavior.

For example, in July, Facebook shut down an experiment where it challenged two AIs to negotiate with each other over a trade. When the experiment began, the two chatbots quickly went rogue, developing linguistic shortcuts to reduce negotiating time and leaving their creators unable to understand what they were saying.

Do we want AIs interacting in a secret language because designers didn’t fully understand what they were designing?

The implications are chilling. Do we want AIs interacting in a secret language because designers didn’t fully understand what they were designing?

In this context, the healthcare community’s conservative approach doesn’t seem so farfetched. Woebot could ultimately become an example of the kind of oversight that’s needed for all AIs.

Meanwhile, it’s clear that chatbots have great potential in healthcare—not just for treating mental health issues but for helping patients understand symptoms, build treatment regimens, and more. They could also help unclog barriers to healthcare, which is plagued worldwide by high prices, long wait times, and other challenges. While they are not a substitute for actual humans, chatbots can be used by anyone with a computer or smartphone, 24 hours a day, seven days a week, regardless of financial status.

Finding the right governance for AI development won’t happen overnight. But peer review, extensive internal quality analysis, and other processes will go a long way to ensuring bots function as expected. Otherwise, companies and their customers could pay a big price.

Elon Musk is an expert at dominating the news cycle with his sci-fi premonitions about space travel and high-speed hyperloops. However, he captured media attention in Australia in April 2017 for something much more down to earth: how to deal with blackouts and power outages.

In 2016, a massive blackout hit the state of South Australia following a storm. Although power was restored quickly in Adelaide, the capital, people in the wide stretches of arid desert that surround it spent days waiting for the power to return. That hit South Australia’s wine and livestock industries especially hard.

South Australia’s electrical grid currently gets more than half of its energy from wind and solar, with coal and gas plants acting as backups for when the sun hides or the wind doesn’t blow, according to ABC News Australia. But this network is vulnerable to sudden loss of generation—which is exactly what happened in the storm that caused the 2016 blackout, when tornadoes ripped through some key transmission lines. Getting the system back on stable footing has been an issue ever since.

Displaying his usual talent for showmanship, Musk stepped in and promised to build the world’s largest battery to store backup energy for the network—and he pledged to complete it within 100 days of signing the contract or the battery would be free. Pen met paper with South Australia and French utility Neoen in September. As of press time in November, construction was underway.

For South Australia, the Tesla deal offers an easy and secure way to store renewable energy. Tesla’s 129 MWh battery will be the most powerful battery system in the world by 60% once completed, according to Gizmodo. The battery, which is stationed at a wind farm, will cover temporary drops in wind power and kick in to help conventional gas and coal plants balance generation with demand across the network. South Australian citizens and politicians largely support the project, which Tesla claims will be able to power 30,000 homes.

Until Musk made his bold promise, batteries did not figure much in renewable energy networks, mostly because they just aren’t that good. They have limited charges, are difficult to build, and are difficult to manage. Utilities also worry about relying on the same lithium-ion battery technology as cellphone makers like Samsung, whose Galaxy Note 7 had to be recalled in 2016 after some defective batteries burst into flames, according to CNET.

However, when made right, the batteries are safe. It’s just that they’ve traditionally been too expensive for large-scale uses such as renewable power storage. But battery innovations such as Tesla’s could radically change how we power the economy. According to a study that appeared this year in Nature, the continued drop in the cost of battery storage has made renewable energy price-competitive with traditional fossil fuels.

This is a massive shift. Or, as David Roberts of news site Vox puts it, “Batteries are soon going to disrupt power markets at all scales.” Furthermore, if the cost of batteries continues to drop, supply chains could experience radical energy cost savings. This could disrupt energy utilities, manufacturing, transportation, and construction, to name just a few, and create many opportunities while changing established business models. (For more on how renewable energy will affect business, read the feature “Tick Tock” in this issue.)

Battery research and development has become big business. Thanks to electric cars and powerful smartphones, there has been incredible pressure to make more powerful batteries that last longer between charges.

The proof of this is in the R&D funding pudding. A Brookings Institution report notes that both the Chinese and U.S. governments offer generous subsidies for lithium-ion battery advancement. Automakers such as Daimler and BMW have established divisions marketing residential and commercial energy storage products. Boeing, Airbus, Rolls-Royce, and General Electric are all experimenting with various electric propulsion systems for aircraft—which means that hybrid airplanes are also a possibility.

Meanwhile, governments around the world are accelerating battery research investment by banning internal combustion vehicles. Britain, France, India, and Norway are seeking to go all electric as early as 2025 and by 2040 at the latest.

In the meantime, expect huge investment and new battery innovation from interested parties across industries that all share a stake in the outcome. This past September, for example, Volkswagen announced a €50 billion research investment in batteries to help bring 300 electric vehicle models to market by 2030.

At first, it sounds like a narrative device from a science fiction novel or a particularly bad urban legend.

Powerful cameras in several Chinese cities capture photographs of jaywalkers as they cross the street and, several minutes later, display their photograph, name, and home address on a large screen posted at the intersection. Several days later, a summons appears in the offender’s mailbox demanding payment of a fine or fulfillment of community service.

As Orwellian as it seems, this technology is very real for residents of Jinan and several other Chinese cities. According to a Xinhua interview with Li Yong of the Jinan traffic police, “Since the new technology has been adopted, the cases of jaywalking have been reduced from 200 to 20 each day at the major intersection of Jingshi and Shungeng roads.”

The sophisticated cameras and facial recognition systems already used in China—and their near–real-time public shaming—are an example of how machine learning, mobile phone surveillance, and internet activity tracking are being used to censor and control populations. Most worryingly, the prospect of real-time surveillance makes running surveillance states such as the former East Germany and current North Korea much more financially efficient.

According to a 2015 discussion paper by the Institute for the Study of Labor, a German research center, by the 1980s almost 0.5% of the East German population was directly employed by the Stasi, the country’s state security service and secret police—1 for every 166 citizens. An additional 1.1% of the population (1 for every 66 citizens) were working as unofficial informers, which represented a massive economic drain. Automated, real-time, algorithm-driven monitoring could potentially drive the cost of controlling the population down substantially in police states—and elsewhere.

We could see a radical new era of censorship that is much more manipulative than anything that has come before. Previously, dissidents were identified when investigators manually combed through photos, read writings, or listened in on phone calls. Real-time algorithmic monitoring means that acts of perceived defiance can be identified and deleted in the moment and their perpetrators marked for swift judgment before they can make an impression on others.

Businesses need to be aware of the wider trend toward real-time, automated censorship and how it might be used in both commercial and governmental settings. These tools can easily be used in countries with unstable political dynamics and could become a real concern for businesses that operate across borders. Businesses must learn to educate and protect employees when technology can censor and punish in real time.

Indeed, the technologies used for this kind of repression could be easily adapted from those that have already been developed for businesses. For instance, both Facebook and Google use near–real-time facial identification algorithms that automatically identify people in images uploaded by users—which helps the companies build out their social graphs and target users with profitable advertisements. Automated algorithms also flag Facebook posts that potentially violate the company’s terms of service.

China is already using these technologies to control its own people in ways that are largely hidden to outsiders.

According to a report by the University of Toronto’s Citizen Lab, the popular Chinese social network WeChat operates under a policy its authors call “One App, Two Systems.” Users with Chinese phone numbers are subjected to dynamic keyword censorship that changes depending on current events and whether a user is in a private chat or in a group. Depending on the political winds, users are blocked from accessing a range of websites that report critically on China through WeChat’s internal browser. Non-Chinese users, however, are not subject to any of these restrictions.

The censorship is also designed to be invisible. Messages are blocked without any user notification, and China has intermittently blocked WhatsApp and other foreign social networks. As a result, Chinese users are steered toward national social networks, which are more compliant with government pressure.

China’s policies play into a larger global trend: the nationalization of the internet. China, Russia, the European Union, and the United States have all adopted different approaches to censorship, user privacy, and surveillance. Although there are social networks such as WeChat or Russia’s VKontakte that are popular in primarily one country, nationalizing the internet challenges users of multinational services such as Facebook and YouTube. These different approaches, which impact everything from data safe harbor laws to legal consequences for posting inflammatory material, have implications for businesses working in multiple countries, as well.

For instance, Twitter is legally obligated to hide Nazi and neo-fascist imagery and some tweets in Germany and France—but not elsewhere. YouTube was officially banned in Turkey for two years because of videos a Turkish court deemed “insulting to the memory of Mustafa Kemal Atatürk,” father of modern Turkey. In Russia, Google must keep Russian users’ personal data on servers located inside Russia to comply with government policy.

While China is a pioneer in the field of instant censorship, tech companies in the United States are matching China’s progress, which could potentially have a chilling effect on democracy. In 2016, Apple applied for a patent on technology that censors audio streams in real time—automating the previously manual process of censoring curse words in streaming audio.

In March, after U.S. President Donald Trump told Fox News, “I think maybe I wouldn’t be [president] if it wasn’t for Twitter,” Twitter founder Evan “Ev” Williams did something highly unusual for the creator of a massive social network.

He apologized.

Speaking with David Streitfeld of The New York Times, Williams said, “It’s a very bad thing, Twitter’s role in that. If it’s true that he wouldn’t be president if it weren’t for Twitter, then yeah, I’m sorry.”

Entrepreneurs tend to be very proud of their innovations. Williams, however, offers a far more ambivalent response to his creation’s success. Much of the 2016 presidential election’s rancor was fueled by Twitter, and the instant gratification of Twitter attracts trolls, bullies, and bigots just as easily as it attracts politicians, celebrities, comedians, and sports fans.

Services such as Twitter, Facebook, YouTube, and Instagram are designed through a mix of look and feel, algorithmic wizardry, and psychological techniques to hang on to users for as long as possible—which helps the services sell more advertisements and make more money. Toxic political discourse and online harassment are unintended side effects of the economic-driven urge to keep users engaged no matter what.

Keeping users’ eyeballs on their screens requires endless hours of multivariate testing, user research, and algorithm refinement. For instance, Casey Newton of tech publication The Verge notes that Google Brain, Google’s AI division, plays a key part in generating YouTube’s video recommendations.

According to Jim McFadden, the technical lead for YouTube recommendations, “Before, if I watch this video from a comedian, our recommendations were pretty good at saying, here’s another one just like it,” he told Newton. “But the Google Brain model figures out other comedians who are similar but not exactly the same—even more adjacent relationships. It’s able to see patterns that are less obvious.”

A never-ending flow of content that is interesting without being repetitive is harder to resist. With users glued to online services, addiction and other behavioral problems occur to an unhealthy degree. According to a 2016 poll by nonprofit research company Common Sense Media, 50% of American teenagers believe they are addicted to their smartphones.

This pattern is extending into the workplace. Seventy-five percent of companies told research company Harris Poll in 2016 that two or more hours a day are lost in productivity because employees are distracted. The number one reason? Cellphones and texting, according to 55% of those companies surveyed. Another 41% pointed to the internet.

Tristan Harris, a former design ethicist at Google, argues that many product designers for online services try to exploit psychological vulnerabilities in a bid to keep users engaged for longer periods. Harris refers to an iPhone as “a slot machine in my pocket” and argues that user interface (UI) and user experience (UX) designers need to adopt something akin to a Hippocratic Oath to stop exploiting users’ psychological vulnerabilities.

In fact, there is an entire school of study devoted to “dark UX”—small design tweaks to increase profits. These can be as innocuous as a “Buy Now” button in a visually pleasing color or as controversial as when Facebook tweaked its algorithm in 2012 to show a randomly selected group of almost 700,000 users (who had not given their permission) newsfeeds that skewed more positive to some users and more negative to others to gauge the impact on their respective emotional states, according to an article in Wired.

As computers, smartphones, and televisions come ever closer to convergence, these issues matter increasingly to businesses. Some of the universal side effects of addiction are lost productivity at work and poor health. Businesses should offer training and help for employees who can’t stop checking their smartphones.

Mindfulness-centered mobile apps such as Headspace, Calm, and Forest offer one way to break the habit. Users can also choose to break internet addiction by going for a walk, turning their computers off, or using tools like StayFocusd or Freedom to block addictive websites or apps.

Most importantly, companies in the business of creating tech products need to design software and hardware that discourages addictive behavior. This means avoiding bad designs that emphasize engagement metrics over human health. A world of advertising preroll showing up on smart refrigerator touchscreens at 2 a.m. benefits no one.

According to a 2014 study in Cyberpsychology, Behavior and Social Networking, approximately 6% of the world’s population suffers from internet addiction to one degree or another. As more users in emerging economies gain access to cheap data, smartphones, and laptops, that percentage will only increase. For businesses, getting a head start on stopping internet addiction will make employees happier and more productive. D!


About the Authors

Maurizio Cattaneo is Director, Delivery Execution, Energy, and Natural Resources, at SAP.

David Delaney is Global Vice President and Chief Medical Officer, SAP Health.

Volker Hildebrand is Global Vice President for SAP Hybris solutions.

Neal Ungerleider is a Los Angeles-based technology journalist and consultant.


Read more thought provoking articles in the latest issue of the Digitalist Magazine, Executive Quarterly.

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The “Purpose” Of Data

Timo Elliott

I’ve always been passionate about the ability of data and analytics to transform the world.

It has always seemed to me to be the closest thing we have to modern-day magic, with its ability to conjure up benefits from thin air. Over the last quarter century, I’ve had the honor of working with thousands of “wizards” in organizations around the world, turning information into value in every aspect of our daily lives.

The projects have been as simple as Disney using real-time analytics to move staff from one store to another to keep lines to a minimum: shorter lines led to bigger profits (you’re more likely to buy that Winnie-the-Pooh bear if there’s only one person ahead of you), but also higher customer satisfaction and happier children.

Or they’ve been as complex as the Port of Hamburg: constrained by its urban location, it couldn’t expand to meet the growing volume of traffic. But better use of information meant it was able to dramatically increase throughput – while improving the life of city residents with reduced pollution (less truck idling) and fewer traffic jams (smart lighting that automatically adapts to bridge closures).

I’ve seen analytics used to figure out why cheese was curdling in Wisconsin; count the number of bubbles in Champagne; keep track of excessive fouls in Swiss soccer, track bear sightings in Canada; avoid flooding in Argentina; detect chewing-gum-blocked metro machines in Brussels; uncover networks of tax fraud in Australia; stop trains from being stranded in the middle of the Tuscan countryside; find air travelers exposed to radioactive substances; help abused pets find new homes; find the best people to respond to hurricanes and other disasters; and much, much more.

The reality is that there’s a lot of inefficiency in the world. Most of the time it’s invisible, or we take it for granted. But analytics can help us shine a light on what’s going on, expose the problems, and show us what we can do better – in almost every area of human endeavor.

Data is a powerful weapon. Analytics isn’t just an opportunity to reduce costs and increase profits – it’s an opportunity to make the world a better place.

So to paraphrase a famous world leader, next time you embark on a new project:

“Ask not what you can do with your data, ask what your data can do for the world.”

What are your favorite “magical” examples, where analytics helped create win/win/win situations?

Download our free eBook for more insight on How the Port of Hamburg Doubled Capacity with Digitization.

This article originally appeared on Digital Business & Business Analytics.

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Timo Elliott

About Timo Elliott

Timo Elliott is an Innovation Evangelist for SAP and a passionate advocate of innovation, digital business, analytics, and artificial intelligence. He was the eighth employee of BusinessObjects and for the last 25 years he has worked closely with SAP customers around the world on new technology directions and their impact on real-world organizations. His articles have appeared in publications such as Harvard Business Review, Forbes, ZDNet, The Guardian, and Digitalist Magazine. He has worked in the UK, Hong Kong, New Zealand, and Silicon Valley, and currently lives in Paris, France. He has a degree in Econometrics and a patent in mobile analytics.