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Industry guru Ray Poynter, Author of The Handbook of Mobile Market Research, shares an excellent update on mobile market research. Originally published July 23, 2017 on LInkedin.
Bottom line: Most survey platforms are compatible on mobile but researchers need to adopt a mobile first mindset to make mobile research work.
For a few years there have been relatively few new findings about mobile market research. We have seen the share of online surveys completed via mobile increasing and we have seen the number of mobile only studies (studies that require a smartphone, for example location-based, in-the-moment and smartphone ethnography) increasing. But the overall picture has remained fairly constant in terms of advice and practice. However, the picture has now changed.
Last week saw five days of short courses and presentations in Lisbon, Portugal at the ESRA Conference (European Survey Research Association). There were over 700 presentations and most of the leading names in survey, web, and mobile research were present (including: Don Dillman, Mick Couper, Google’s Mario Callegaro, SurveyMonkey’s Sarah Cho, Edith de Leeuw, Roger Tourangeau, GfK’s Randall Thomas & Frances Barlas, and my colleague Sue York).
There were more than 20 presentations particularly relevant to mobile market research - making it one of the largest collections of reports and findings from experiments reported anywhere.
In this post I set out my key takeaways from the ESRA Conference in terms of mobile market research. But, I may update this post when I get access to all of the presentations and papers from the conference.
For many years, the prevailing wisdom has been that grids on smartphones are a much bigger problem than they are on PCs. However, several studies presented at this conference, especially the study presented by Mick Couper, showed that this does not have to be the case.
A mobile optimised grid performs in a very similar way to a grid on a PC. When we say performs in a very similar way, we mean it gives similar results, in most cases takes a similar amount of time, and attracts a similar level of dissatisfaction from the research participants.
In many ways a mobile optimised grid is the result of adopting a mobile first approach (something that Sue York spoke about at the conference). A mobile optimised grid can mean looking like a traditional grid, if the labels are short, the number of scale points is few, and if the software is responsive (meaning it fits nicely on the page).
Another way of dealing with grids is to present the rows of the grid one item at a time (and there are now a wide variety of ways of doing this). This one row at a time approach is usually called item-by-item. Most of the studies, presented in Lisbon, preferred using a scrolling approach to presenting the rows of the grid one item at a time. For example, after answering one row, the user scrolls down to the next question (or is auto-advanced down to the next row). In commercial projects the item-by-item approach is often achieved by showing each item on a new page.
The papers showed that survey results were very similar when using mobile optimised grid, when making the following comparisons:
Note, when item-by-item approaches were used with a new page per question (as often happens in commercial studies) the data were similar, but the surveys took longer to complete.
A point highlighted by Don Dillman was that if long labels are used for the rows it is hard to produce a grid that is mobile optimised. For example, if we have a question asking how important the following are in selecting a holiday destination
On a smartphone these long labels mean that there is not enough space to make several rows visible AND make the scale points visible AND ensure that the buttons or sliders are easy to use. If the labels are long, the mobile version needs to be achieved using an item-by-item approach.
Several studies showed that long labels (and long instructions and long questions) tend to be poorly understood by many research participants. This was true of all self-completion modes; web, mobile and paper. Several speakers stressed the need for cognitive interviews to be conducted when designing new questions and questionnaires – to assess what the participant thinks they are being asked and how they set about answering the question.
In the past, many researchers have felt that the best option is to ask research participants to use their phone in landscape mode, especially for things like scales and grids. However, several studies showed that (even when asked) only a few people do this. The people who did hold their phones in landscape mode tended to be younger and were perhaps familiar with using their phones to play games.
Facilitating mobile devices does change the results, because it increases the range of people taking the survey. This has been known for many years and nothing has happened to change this picture.
There are many groups of people who are less likely to complete a survey on a PC and if participants have the choice to use PC or mobile the coverage of the study improves. When the coverage improves the answers can change because some people are no longer being missed.
In her keynote speech, Edith de Leeuw made the point that mode effects comprise two elements. The first element is changes caused by the change in hardware, these are undesirable mode effects. Secondly, changes caused by improving the coverage of the study – these are desirable effects.
If your survey is badly designed for mobile, there will be mode effects. There is mixed evidence about open-ended responses on mobiles, with many people reporting that the open-ends are more limited from mobiles. There still seems to be agreement that multi-select grids when asked item-by-item on a mobile produce more answers that the multi-select grid asked on a PC as a conventional grid.
Not really. We can make grids on smartphones as good as grids on PCs. But on PCs and smartphones grids remain one of the items most disliked by participants. They are associated with more break offs, and, in interviews with research participants, they are regularly cited as reasons for not doing studies. Research still has a need to minimise the use of grids, to make grids smaller, and to make them easier.
Several people, for example Sue York, talked about the need to be more mobile first and to move away from long scales to simpler options, such as selecting rather than rating. Great evidence for this point of view was provided by GfK’s Randall Thomas & Frances Barlas. They showed that with fewer scale points the scales were easier to read on a smartphone, the information was very similar, and the differentiations (e.g. standard deviation) was greater.
Thomas and Barlas seemed to be recommending 3-point scales (e.g. Not Like, Neutral, and Like) – but they also offered support for 2-point scales.
Thomas and Barlas showed that in their studies, anchored scales produced results that were more consistent (between PC and mobile) than scales that were only anchored at the end points.
In most cases Thomas and Barlas found that within the USA bipolar scales tended to perform better than unipolar, for example Dislike, Neutral, and Like (as opposed to the unipolar Not like, Neutral, and Like). But they also noted that for many languages there are problems translating bipolar scales and these translations created differences in the data that were unwanted. Hence, the advice to use unipolar scales.
Several studies, for example data from SurveyMonkey, showed that when contacting people who were not part of research panels, almost 50% tend to use a mobile device. However, studies with panels (commercial research panels and the probability research panels favoured by social researchers) the proportion using mobiles is closer to 20% to 30%. Perhaps, the poor performance of mobiles in the past has discouraged mobile preferrers from being involved with these panels? If so, this is another reason that we need to adopt a more Mobile First approach.
Sue York presented data supplied by Research Now that showed that the proportion of Mobile Optimised surveys has not really improved over the last 3 years. The table from Sue York's presentation is shown below.
Despite the best efforts of panel companies, nearly one-third of the surveys being submitted to Research Now are judged to be ‘Mobile Impossible’, nearly a quarter ‘Mobile Possible’ – with fewer than half being mobile ‘Friendly’ or ‘Optimized’.
Some people have argued that specific types of questions only work on PC (for example large grids, or some types of interactive questions). However, in most cases, excluding people who will only take part via mobile is going to compromise your research – and this effect is likely to increase. If you have something that is PC only, try to re-design it (or re-envision it) so that it does work on a smartphone, or reconcile yourself to using an increasingly skewed sample.
There were some interesting papers in the use of sensors, for example using apps to collect media usage, audio capture to record broadcasts heard, and GPS to aid travel diaries. But none of them were without their challenges. The media capture approaches requires apps to be downloaded and significant ‘per participant’ incentives to take part.
The GPS tracking for travel diaries was perhaps the most illustrative of the benefits and challenges. A pilot study presented at the conference showed that the data collected could be quite useful, much richer than the paper diaries and more accurate in terms of things like distance travelled. However, the app under-recorded the number of journeys. One of the reasons for under-recording was that the app turned itself off when the battery indicator reached 20% remaining – which happened often enough to change the data.
The key lessons from the various uses of sensors are:
Market research is based on informed consent. A paper by Barbara Felderer and Annelies Blom highlighted some of the challenges with privacy and consent. In a study in Germany they asked people to type in their current location (with options such as address, post code etc). Well over 90% of participants did this. However, the survey also asked permission to collect the location of the phone automatically using GPS. About one third of people who typed in their address said no to their GPS location being collected. This suggests we should not simply be collecting GPS without consent, and that consent will not necessarily be given when we ask for it.
There are over 7 billion mobile phones in use around the world. Fewer than 3 billion of these phones are smartphones, so by focusing on smartphones we are excluding the majority of the world’s population. However, the rate of smartphone adoption means that soon this will be less of a problem, and is already a marginal problem in many countries.
The top takeaways are:
June 12, 2017: Data constantly collected and reported by smartphones can find numerous applications. A Swiss National Science Foundation funded project devoted to crowdsensing has found ways to improve privacy and localisation accuracy as well as reduce the impact on hardware.
Connecting data from the world's smartphones could put a global supercomputer into all of our pockets. Tapping into that processing power would improve the real-time collection and analysis of data, but technical hurdles and privacy concerns linger. Scientists from SwissSenseSynergy, a project funded by the Swiss National Science Foundation (SNSF), have addressed issues and proposed new ways to collect and use such information.
The main focus of the project is crowdsensing, in which access to a smartphone's sensors makes it possible to collect information about a particular area. A typical example are map applications which can infer traffic congestion data from the smartphones' accelerometers. As our connected devices gather insights about many facets of our environment -- motion, sound, people, air quality, etc. -- crowdsensing has the potential to guide decisions on where we eat, what we wear or how we travel.
"All of this information is useful in applications ranging from marketing predictions to predicting crowd behaviours," explains Torsten Braun from the University of Bern and coordinator for the project. Nonetheless, crowdsensing applications face significant challenges. In particular, there is a trade-off between data collection, user impact and privacy. Transmitting data drains hardware resources, for example, while poor security measures pose risks for identity theft.
Four teams developed new approaches to improve crowdsensing technology and establish best practices for its application. Researchers are exploring four key areas: improving location accuracy, increasing security, industry uses, and making data collection more efficient.
Localisation beyond GPS
The team led by Torsten Braun at the University of Bern improved location accuracy indoors and underground to 1.1 metres in 90% of cases. That is comparable to GPS, but relies only on the device's sensor data and radio signals, reaching areas behind walls and concrete where GPS signals are blocked. The researchers collect sensor measurements from the smartphones, alongside the Wifi radio's signal strength. This information is then passed through several machine learning algorithms. "The next step is to determine where users are going," Braun said. "This could have an impact on shopping centres or train stations, for example."
Scientists from the universities of Bern and Geneva collaborated to design a mobile application combining indoor localisation, mobile crowdsensing and smart spaces. The resulting mobile app integrates sophisticated localisation algorithms and location-stamped sensor measurements, which are pushed to the cloud. From there, the information is fed to the Internet of Things, allowing personalised and location-based automation applications across a number of smart objects and products.
A team at the University of Applied Sciences and Arts of Southern Switzerland in Lugano (SUPSI) has developed models that use predictive location data to distribute information through social media. The experiments showed that they could create rapid outreach on social networks such as Facebook and Twitter, but also in ad hoc physical networks of mobile devices. These messages could respond to local behaviours, assess feedback in real time and circulate more quickly among targeted users. The research provides a deeper understanding of social influence in human behaviour, and discovered correlations between physical locations, shared preferences and event-based social communities.
A balancing act
"A major problem for researchers is balancing data and privacy," explains Braun. "Accurate data can cost privacy." If user information is being swept up while collecting data, it discourages participation. To ensure security, the Chalmers University of Technology team in Sweden has developed machine learning methods for data analysis and automatic decision making that achieve "differential privacy." This protects the data of individuals by injecting carefully calibrated "noise" (random data) into information collected from a device.
Researchers at the University of Geneva addressed another challenge: the desire to collect large amounts of data against the burden that crowdsensing can have on hardware. If users fear a strain on their phone, they might reject applications which make use of otherwise idle sensors. This project is investigating game theory models for distributing such burdens among phones and users. In a field experiment, volunteers in San Francisco downloaded apps to map noise levels in the city, collecting useful data for the local government while testing competing methods for distributing loads among devices.
With its interdisciplinary approach, the SwissSenseSynergy project has yielded new techniques with potential benefits for research and applications. The project is developing a novel experimentation architecture, called Vivo, to involve volunteers in the experimental phase to support application development.
The SwissSenseSynergy project
The project gathers four partners: the Institute of Computer Science at the University of Bern, the Department of Computer Science at the University of Geneva, the Institute for Information Systems and Networking at SUPSI and the Department of Computer Science and Engineering at Chalmers University of Technology (Sweden). Swiss Sense Synergy is funded by the Sinergia programme of the SNSF until the end of 2017.
Materials provided by Swiss National Science Foundation (SNSF). Note: Content may be edited for style and length.
Source: Swiss National Science Foundation (SNSF)
From BoingBoing by David Pescovitz
What do you consider to be mobile research? Is it limited to the smart phone and tablets or does it extend to wearables and IoT devices? As we continue to shape the future of research, we should consider all opportunities to understand the customer in a mobile world.
MIT Media Lab spinoff company mPath has developed a wristwatch-like wearable that measures changes in skin conductance tied to stress, frustration, disinterest, or boredom. Combined with other data, the device is meant to help companies with "emotyping," the process of "undersand(ing) customers’ emotional needs or wants" during market research and product development," according to CEO Elliot Hedman. Their clients range from LEGO to Google to Best Buy. Most recently, they started working with the Boys and Girls Clubs in Denver that could lead to new ways to encourage reading. From MIT News:
This process combines the stress sensors with eye-tracking glasses or GoPro cameras, to identify where a person looked at the exact moment of an emotional spike or dip. Personal interviews are also conducted with all participants, who are shown the data and asked what they think they felt.
This entire process creates a more in-depth, precise emotional profile of consumers than traditional market research, which primarily involves interviews and occasionally video analysis, according to Hedman. “All these things combined together in emototyping tell us a deep story about the participant,” he says.
Emototyping is an especially useful tool when studying children’s experiences, according to Hedman. “It’s hard for kids to describe what they felt,” he says. “The sensors help tell the whole story..."
A study with the New World Symphony found that making songs shorter and performing classical compositions of modern pop music help engage new audiences in classical music. Studying movies such as “The Departed” revealed where some techniques or concepts (such as dark humor) can be implemented in films to keep audiences engaged. At one point, the startup even tracked patrons’ fear throughout parts of a haunted house.
One of mPath’s more unique recent projects was helping a toothpaste company understand people’s experience with brushing their teeth.
Amazing how fast 10 years goes by, and at the same time it's hard to imaging life without a smart phone. It wa only 10 years ago today that the 1st iPhone was released - here's a look back at how Steve Jobs announced it.
Curated from Business Insider, Written by Rob Price
"Ten years ago, June 29, 2007, was a milestone in the history of computing: the launch date of the first iPhone.
It wasn't the first "smartphone," or the first phone with a camera. It wasn't the first mobile device to have a touchscreen, or to let users install apps. (In fact, the App Store didn't even launch until 2008, a year after the first iPhone was released!)
But it tied numerous disparate features together in a cohesive, well-designed whole — kickstarting a mobile revolution that has transformed the modern world.
Today's app economy is bigger than Hollywood, and WhatsApp, Snapchat, Uber, Tinder, and more are essential parts of modern culture, collectively used by hundreds of millions of people every day. But 10 years ago, none of that existed, and the iPhone's success was by no means guaranteed.
It was announced by CEO Steve Jobs onstage at the company's Macworld conference on January 9, 2007. The now-iconic exec was not humble about its possibilities — calling it a "revolutionary device ... that changes everything."
Five months later, as customers queued for days, it hit shop shelves in the US.
And the rest is history.
Keep reading for the story behind the launch and to watch the full keynote ...
Source: The New York Times
We've rounded up even more here.
Apple Reinvents the Phone with iPhone
MACWORLD SAN FRANCISCO - January 9th, 2007
Apple today introduced iPhone, combining three products — a revolutionary mobile phone, a widescreen iPod with touch controls, and a breakthrough Internet communications device with desktop-class email, Web browsing, searching and maps — into one small and lightweight handheld device. iPhone introduces an entirely new user interface based on a large multi-touch display and pioneering new software, letting users control iPhone with just their fingers. iPhone also ushers in an era of software power and sophistication never before seen in a mobile device, which completely redefines what users can do on their mobile phones.
"iPhone is a revolutionary and magical product that is literally five years ahead of any other mobile phone", said Steve Jobs, Apple's CEO. "We are all born with the ultimate pointing device — our fingers — and iPhone uses them to create the most revolutionary user interface since the mouse".
Tom Bassett Founder at mindswarms | Published on June 1, 2017
A closer look at insights from our interview with Ogilvy NYC’s Leslie Stone
Following a recent mindswarms project with Leslie Stone, director of strategic services for Ogilvy NYC, I sat down with her in Brooklyn to talk about her perspective on using mobile video ethnography. You can watch that video here.
In our conversation, she raised a number of great points about the advantages of mobile video ethnography over in-person ethnography, and I’d like to take a closer look at a couple of them:
In no other methodology are people so self-directed. —Leslie Stone
Moderator bias and group-think are two common factors in live interview sessions. Mobile video surveys invoke the online disinhibition effect, whereby people communicate more openly and honestly without another person present because they feel less afraid of conflict or disappointing the interviewer. You can read more about this in my LinkedIn article, 5 lessons in Mobile Video Study Design for Emotional Results, about our study of Millennials & Home Cleaning.
In the study we did with Leslie and the Ogilvy team, we were asking people about their homes. Therefore, we had people answer questions from inside their homes and even give us a narrated Show + Tell tour of their favorite room.
From a study design standpoint, because people are typically very comfortable at home, they’re more relaxed and natural in their responses than they would be in another setting. Additionally, getting people moving and doing something unscripted helps people speak more freely because they’re not the focus of attention.
Leslie says she used to travel all the time, conducting in-depth interviews (IDIs) and ethnographic studies. Today, her responsibilities at Ogilvy mean she has less time for field research. Nevertheless, for the world-class, award-winning work that Ogilvy does, she still needs to achieve a deep understanding of consumers—and there’s no substitute for hearing from and observing people directly.
One huge benefit [of mindswarms] is that I don't have the time or resource to go do this myself. It's amazing to go home, come back in the next day and just watch videos. It saves a gigantic amount of operational time. —Leslie Stone
Despite the fast turnarounds made possible by online research tools, you don’t want to sacrifice quality for speed. (People want good sushi, fast; not just fast sushi.) That’s where totally DIY video survey platforms sometimes fall short.
With mobile video ethnography, it’s especially important to ask the right questions in the right ways. For that reason, at mindswarms we collaborate with researchers to design studies, closely screen participants, and curate the resulting video responses to keep quality high. We view our platform as an effective technology enabler of the fundamentally human-to-human act of ethnography.
One of the great strengths of mobile video ethnography is being able to see what’s in the periphery as people answer questions and to peer into people’s lives and environments.
Some of the richest insights came back from what we saw. And sometimes, that’s the richest and the biggest point. —Leslie Stone
That’s why mobile video is a great fit for in-home qualitative research. As Leslie said, “It’s a no-brainer for anything in the home. And ‘anything in the home’ could be any consumer goods or any food or anything in your closet or shopping.”
4. Hearing first-person accounts
There’s tremendous power in hearing directly from consumers in their own words. Mobile video ethnography is a great tool for collecting first-person stories rich in detail and emotion. It helps you understand the language actual customers use to talk about a brand, product or experience. It also helps you confirm you’re not making assumptions based on false familiarity.
Brand decks can be beautifully written and clearly articulated, but seeing and hearing how those ideas, platforms or concepts are manifested in the lives of real consumers helps bring teams closer to the people they are trying to reach.
I think it’s fair to say a lot of business presentations are...anesthetic. Uninspired and unengaging. Video, however, has become the new language of the world, as you’ve seen in the explosive growth and volume of online video. Bringing that rich, vivid cultural element into the world of business is a highly effective way to get a point across in an compelling way.
For the ad campaign Ogilvy was developing, Leslie needed to bring a broad array of stakeholders up to speed, quickly. So she selected clips from our mobile video study to share with the client, her creative team, PR and others involved in the ad campaign.
Even if you had already had your brief but you just wanted to pump it up with extra insight or give people thoughts to react to, [mindswarms] would be great. Or in the middle of a pitch to show clients people talking about your strategy, it helps to engage them. mindswarms can also be helpful when you're stuck. —Leslie Stone
The richly visual content and first-person stories were powerful for validating ad campaign strategy and building empathy for the campaign audience. This helped the Ogilvy team develop a unique and compelling ad campaign that connected with people in a genuine way.
You have to find a human connection to your audience if you want to elicit a human response. —Leslie Stone
You can watch watch our video interview with Leslie here.
On our website, you can also download several case studies showcasing the effective use of mobile video surveys for ad campaign testing and business pitches.
Special thanks to Leslie Stone for sharing her insights about the experience of using mobile video for qualitative research.
ABOUT THE AUTHOR
Tom Bassett is the Founder and CEO of mindswarms. For over 20 years he has traveled the world to interview people in-person, in situ, as part of consumer market research and strategy for some of the world’s most iconic brands: Nike, Apple, Google, Microsoft, Sonos and many others.
A specialist in using mobile video survey technology for ethnographic research, Tom has done mobile qualitative studies on behalf of Fortune 500 global brands in the US, Asia, Latin America and Europe. He also has led mindswarms collaborations with Carnegie Mellon’s Human Computing Interaction Masters program, Wharton’s MBA school, and Stanford Engineering.
Tom was a panelist on the London Design Festival’s Global Innovation Forum, and he has interviewed leading creative visionaries including Frank Gehry, David Rockwell, John Boiler, Yves Behar, John Jay and Maira Kalman for a documentary film he created and produced called “Briefly.”
by Laura Forer | June 1, 2017 | As published on MarketingProfs.com
Remember when we surfed the Internet on a computer or laptop while seated at a desk?
It wasn't that long ago, but times have changed. Now we consume content wherever we are, whether that's at home or at work or en route to a store. And our gadgets have changed from stationary computers to myriad mobile devices that we carry or wear.
Mobile brings a constantly connected mindset, and it's driving changes in the way we—including our customers—consume content and interact with brands, from voice search to chatbots, and from digital assistants to the Internet of Things (IoT).
DNN Software has created an infographic that illustrates stats and figures related to this phenomenon.
For instance, the infographic shows that active users of virtual digital assistants are forecast to grow from 390 million (in 2015) to 1.8 billion by the end of 2021. Those digital assistants are driving an increase in voice searches. In 2016, Google announced that 20% of mobile queries are coming from voice searches, according to the infographic.
To see more details about emerging technologies that are changing the way content reaches consumers, check out the infographic:
Laura Forer is the manager of MarketingProfs: Made to Order, Original Content Services, which helps clients generate leads, drive site traffic, and build their brands through useful, well-designed content.
LinkedIn: Laura Forer
The Insight Economy 2017 is an in-depth look at the hottest topics in the world of market research and consumer insight.
Published in The Times on the 24th of May, this 20-page special report is a must have for any decision maker wanting to better understanding the people that matter to their business.
We're excited to see video insight form an integral part of the discussion in 2017, and that Voxpopme CEO and MMRA Advisory Board Member Dave Carruthers was asked to contribute his thoughts to 'Seeing things through the eyes of the consumer' by Tim Phillips on page 12.
But before you rush out to buy your copy, your friends at Voxpopme have a free one just for you. Click the button below to download your copy.
We hope you enjoy!
By Maribel Lopez, Lopez Research
Originally published in TechTarget May 8, 2017
Newer consumer apps take advantage of mobile's unique features, such as location awareness and voice control, but enterprise software still has a long way to go. Most companies work within the confines of applications and experiences that were designed in the 1980s.
The challenges of embracing mobile-first aren't just about technology maturity. A mobile-first strategy requires companies to commit to overhauling business processes and workflows to take advantage of new data and device functionality. And it requires more than just focusing on mobile.
In several years, we won't even talk about mobility. Everything that we build will be designed to work across mobile, PCs and a variety of connected devices. The new IT world assumes we'll embrace and expand upon all of the mobile and cloud computing concepts developed over the past decade. In 2017, next-generation computing should deliver apps, services and business workflows that have four qualities:
They're built to operate and move seamlessly across devices. The best experiences allow a person to start a workflow or transaction on one device and seamlessly transfer it to another device. Apple and Microsoft both offer this type of portability through their Continuity and Windows Continuum features, respectively.
They're adaptable to the user and device context. Context in this case could refer to device size or to the availability of input mechanisms such as keyboard, voice, stylus, touch and gesture. Apps also need to sense what functions are available -- such as camera, GPS and biometric sensors -- and provide different options for actions the user can take based on these capabilities. Context-aware apps can also show different information based on location, such as bringing up certain notes or launching Microsoft PowerPoint when the user enters a meeting room in a specific building.
They're designed to collect and act on new data sources.Smartphones ushered in a new wave of sensors such as accelerometers and gyroscopes. Wearables and IoT devices add opportunities for gleaning sensor data such as heart rate and humidity. Next-generation computing requires deep integration with a wide range of connected devices. Wearable apps can collect data from sensors, for example, to provide more context for what the user is doing or feeling at a given moment -- and provide in-app options that react to that context.
They can learn and make predictions. Mobile brought to IT the concept of personalized services based on an understanding of user behavior. End-user computing in 2017 will take advantage of big data storage, analytics and machine learning to deliver services that provide users with the right information at the right time.
We're living in a mobile- and cloud-first world that relies on a diverse set of devices and ways to access business data. If you haven't embraced this approach, you're behind. The only question is, will you change your mobile-first strategy to take advantage of these tools? If not, you'll be even further behind when the next wave of change -- IoT, augmented and virtual reality, and artificial intelligence -- hits.
By Joseph Flaherty, March 2017
In 1967, Herman Kahn, a nuclear physicist and futurist at the Rand Corporation (who also served as inspiration for the character Dr. Strangelove), wrote a book called The Year 2000 in which he made 100 predictions about what the next 33 years would bring. He was surprisingly prescient in predicting mobile phones, real-time banking systems and a pervasive surveillance apparatus. His predictions that humans would hibernate in homes staffed by robots and powered by personal nuclear reactors haven’t held up so well.
Still, 50 years after Kahn made his bold predictions, we asked a group of academics, technologists and entrepreneurs to provide a shorter-term perspective on the most impactful technologies and trends that are likely to influence this year and beyond.
General purpose artificial intelligence that can think and communicate like a human—what computer scientists call “strong AI”—remains a sci-fi fantasy. However, artificial intelligence trained to excel at a narrow focus, or “weak AI,” has turned out to be a versatile technological solution to many vexing problems.
Using an elegant technique called deep learning, weak AI is what Facebook uses to tag people by name in photographs. It’s what allows Google to complete your searches before you even finish typing. Weak AI can develop new ways to beat video games, write sports stories based on a box score, create a creepily accurate copy of your voice and even write lyrics to a rap song. Weak AI has become powerful enough to best humans in the complex game of Go, decades sooner than experts had expected.
This progress has led credible technologists, economists and venture capitalists to believe we could soon have a future in which tax preparers, paralegals, insurance underwriters and others find themselves out of jobs. Estimates from the World Economic Forum suggest that AI-based automation could cause 5 million jobs, mostly white collar, to be lost by 2020. Worries about the availability of desk jobs have replaced fears of a destructive robot uprising.
But not everyone is certain that robots will rob humans of meaningful work. “Humans want to make things and to buy things. So I’m confident we won’t run out of work anytime soon, even as automation increases in some professions,” says Thomas Rid, a professor of security studies at King’s College in London and author of the book Rise of the Machines: A Cybernetic History. “And let’s not forget how difficult it is to automate jobs that require a high degree of adaptation and improvisation: Anybody who thinks robots should long have taken over from plumbers, dentists or construction workers probably has a fanciful notion of robotics and AI.”
Rid suggests that predictions should be based on real technologies, not science fiction. “Whenever we approach the machine-as-human—and the term AI does that, pretending that machines could become like us, with artificial brains—we tend to fool ourselves. Let’s not approach AI by looking at science fiction, but by looking at existing technology.”
By that measure, AI is an unqualified boon. AI gives artists new tools to create, provides real-time translation to facilitate cross-cultural communication, has made autonomous cars a reality and has given some health care providers the ability to provide more targeted cancer treatment.
But while AI makes some people wary, the most pressing cybernetic threat we face may be the tiny black box sitting under our TVs. Last October, hundreds of thousands of DVRs, webcams and other seemingly harmless internet-connected doohickeys launched a coordinated cyberattack that temporarily took down websites such as Twitter and Spotify. It was resolved quickly, but it did highlight weaknesses in our online infrastructure.
“Like an early version of our highway system, the internet was not architected to support the massive volume of content and data that it now supports,” says Kyle York, chief strategy officer at Dyn, a startup that provides critical back-end infrastructure to companies such as Twitter and National Geographic. “The internet is also more volatile and prone to disruption than most people would think.”
The Internet of Things, the umbrella term for the ecosystem of smart light bulbs, smoke alarms, door locks—most of which house small, though powerful, computers—can wreak havoc. These low-priced gadgets are rarely seen as threats and become ripe for hacking. A computer programmer recently demonstrated that a web camera was infected by a computer virus just 98 seconds after being plugged in. To give a sense of scale, there are 6.8 billion cellphone subscriptions across the globe, and experts forecast there will be 20 billion connected devices in people’s homes by 2020, increasing the risk for future attacks.
“Network security will continue to evolve as bad actors respond to the solutions that industry experts develop to patch vulnerabilities. It’s a wild game of cat and mouse,” York says. “Increased vigilance and the realization that advanced mitigation tools and techniques need to be employed to provide greater threat detection and security will help. Predictive technologies will become a major defense as companies aim to move from disaster recovery to more of a disaster avoidance posture.”
Not being able to access Twitter is a pain, but the scarier “cybersecurity” threats are personal. Imagine a scammer who disables the smart lock on your front door until you pay a $5 ransom via Bitcoin. Or a hacker who threatens to disable your smoke alarm unless you give him access to your Facebook account. There may come a time when you’ll need to buy antivirus software for your vacuum cleaner.
Tech has had a dark side since the days of dial-up, but until recently, it was possible to filter the good from the bad, even if it meant disconnecting. In 2017, tech’s dark side threatens to spill out into the real world, and the way we think about technology is going to have to change—quickly.
Amazon is Walmart on steroids, and Netflix is the logical extension of the corner video store, but the basic act of shopping isn’t that different from what existed before the internet—it’s just faster and better. But advances in artificial intelligence and cybersecurity promise to reshape our world in ways that are harder to predict. And whether you’re a cybernetic chicken little or an entrepreneur thrilled by emerging technology, one of the preeminent tech historians of our day says it’s mostly guesswork in the end: “History has a clear lesson: Most of today’s predictions are going to be wrong,” says Thomas Rid. “Futurists in the past got far more predictions wrong than they got right.”
In the words of Terminator’s John Connor, “There is no fate but what we make for ourselves.” Regardless, buckle up, because it’s going to be an exciting ride.
Nicole Nguyen, BuzzFeed News Reporter
When you sign up for a free online service, you’re usually giving up your personal info in return. Here’s how to find out just how egregious that data collection is.
If there’s only one thing you take away from this article, let it be this: there’s no such thing as a free lunch.
The New York Times recently reported that Unroll.me, an email management app that promises to de-clutter your inbox, sold its users’ anonymized Lyft receipt data to Uber. Unroll.me claims that it’s “trusted by millions of happy users” — but it’s likely that those users weren’t aware that they were forking over their personal emails to Slice Intelligence, a digital commerce analytics company. Now, some users are pledging to remove their inbox accessfrom Unroll.me and delete their accounts.
The Unroll.me/Uber fury is a good reminder of the ol’ Internet adage, “if you’re not paying for it, you’re not the customer, you’re the product.”
But some sites are much more egregious than others. So here are some ways you can assess an app’s trustworthiness and find out if your free faves are problematic.
When you sign up for a free online service, you’re most likely giving up something in return: your data. On sites like Facebook and Google, that means the service uses your personal information (like your interests, location, gender, marital status, or age) to show you advertisements they think you’d be interested in. Last year, Facebook made more than $26 billion from advertising.
For many people, this sounds like a good trade off: You get to use something legitimately useful, like Gmail, for free, and the most visible consequence is an advertisement. But other companies go much farther. Unroll.me, for example, didn’t use user data to target ads — it looked at individual emails and sent them to Uber.
And if you found that story about Target knowing a teen girl was pregnant before her father did thanks to extensive customer data collection to be pretty creepy, you should know that that same kind of analytics-based-advertising-influence has probably been exercised on you.
Be very careful about what kind of access you give apps. To do that, closely at what you’re agreeing to when you sign up.
For example, when you sign up for Unroll.me, you’re giving the service the ability to read, send, delete, and manage your email. This is a good time to ask yourself: Does the service really need all of these permissions? Do I trust this service?
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