Author: Bob O'Donnell

Bring up the topic of wearables these days, and you’re likely to see rolled eyes, shrugged shoulders, and a general sense of “whatever.” The problem, of course, is that wearables were badly overhyped and haven’t even come close to living up to the expectations that many companies, analysts, and industry observers had for the category.

Sales in many of the most closely watched sub-categories, notably smartwatches, have not been anywhere near the level that would make them “the next big thing.” Sure, you could argue a few companies have done OK, but the short attention span of the tech industry has clearly been diverted to newer, sexier devices, like voice-controlled speakers, or AR and VR headsets.

Despite these issues, it may be that we’ve given up on wearables a bit too soon. The problem is that we’re thinking much too narrowly about what the concept, and implementation, of wearable computing really is. To be clear, I don’t see a big future for the individual products that we currently count as wearables, but I think the idea of several linked components that work together as a wearable computing system could have legs.

Imagine, for example, a combination of something you wear on your wrist, something you wear on your face, perhaps a foldable screen you carry in your pocket, along with a set of intelligent earbuds (which might be integrated into the glasses you wear on your face), all of which work together seamlessly.

The devices would each incorporate sensors and/or cameras that would enable real-world contextual information. They would all incorporate high-speed wireless connections, and the entire system would be reliably voice-controlled with an AI-powered digital assistant. Critically, I think a solution like this would need to be sold together as a system—though a componentized system might work as well.

Admittedly, there are some inherent challenges in a concept like this. It’s hard enough for people to always remember to carry their smartphones, so thinking that they’ll regularly walk around with 3 or 4 devices seems like a stretch. Remember, however, that certain elements of these solutions could eventually get integrated into other currently non-technical components of our lives, such as our clothing. Start thinking that way, and some of the concepts may not be quite so far-fetched.[pullquote]Arguably, what I’m really talking about is the next evolution beyond smartphones into a highly personalized, but much less visible form of personal computing.[/pullquote]

Arguably, what I’m really talking about is the next evolution beyond smartphones into a highly personalized, but much less visible form of personal computing. Given that I don’t think people are too eager to give up their smartphones yet, this connected wearable computing vision is still clearly a ways off—maybe even as much as 8-10 years. Nevertheless, if we start to formulate a goal for where computing is headed, we can more easily envision that path from our present to the future. More importantly, we can start thinking more clearly about potential stops—or product concepts and iterations—along the way.

At some point, wearable computing devices or solutions or whatever form they end up taking will be part of our lives. Of that, I am convinced. But in order to start moving towards that future vision, we need get past the broken, highly separated wearable product categories of today and start thinking about a more integrated wearable solution for tomorrow.

We’ve all seen the images. Happy young employees, working productively in open-air workspaces, easily collaborating with co-workers and outside colleagues all-over the world, utilizing persistent chat tools like Slack to keep on top of all their latest projects and other efforts. It sounds great, and in a few places in Silicon Valley, things do work that way—at least in theory.

But at most companies in the US (and likely the rest of the world), well, not so much. It’s not that companies aren’t looking at or starting to use some of these new communication and collaboration technologies. Some are, but the deployment levels are low at less than 30% overall; plus, employee habits haven’t really changed in many places.

Such are the results from the latest study on workplace trends completed by TECHnalysis Research. The study is based on a survey of 1,001 US-based working adults aged 18-74 at medium (100-999 employees) and large (1,000+ employees) companies across a range of industries. The survey goal was to understand how the modern workplace is evolving in terms of how and where people work, as well as the hardware, software, services and capabilities that employees expect from their employers.

I wrote about some of the surprising results regarding work habits and locations in a previous column called “The Workplace of the Future” but for this column I’m going to focus on some of the big picture implications of the research, as well as some technology-specific trends.

The key takeaway is that both technologies and habits rooted in the 20^th century are keeping the 21^st century vision of the modern workplace from becoming reality. For example, despite the appearance of modern communications and collaboration tools, it’s the “old school” methods of emails, phone calls and texts that make up 75% of all communications with co-workers. There are certainly some differences based on the age of the employee, but even for workers under 45, the number is 71% (emails and voice calls make up 58% for that age group).

From a device perspective, the most common tool by far is not a smartphone, but a company-owned desktop PC, which is used for just under half (48%) of all device-related work. (For the record, personally owned smartphones are only used for 7.5% of total work on average.) Partially as a result, some version of Windows is used for rougly 2/3 (65%) of all work, with Android at 11%, iOS at 10%, and the rest split among cloud-based platforms, Macs, Linux and other alternative options. Arguably, that is a drop from the days when Windows owned 90%+, but it still shows how dominant Microsoft is in the workplace.

Open air environments have received a great deal of attention and focus in modern workplaces, but there’s a potential gremlin in that future work vision: noise. In fact, in about 25% of outside the office alternative or shared workspaces (such as WeWork) and in 20% of inside the office alternative or shared workspaces, noise was cited as having a serious impact on productivity. Given these numbers, it’s not terribly surprising to see reports suggesting that some of these experiments in workplace flexibility are not working out as well as hoped.

From a conference room perspective, basic audioconferencing, guest WiFi, and wireless access to projectors (or other displays) are the most widely available services, but when asked which of these capabilities offers the greatest quality and utility, the story was very different. Modern tools such as HD videoconferencing, large interactive screens (a la Microsoft’s Surface Hub), electronic whiteboards, and dedicated computing devices designed to ease meeting collaboration(such as HP’s new Elite Slice, based on Intel’s Unite platform), scored the highest satisfaction levels, despite their currently low levels of usage. In other words, companies who invest in modern collaboration tools are likely to find higher usage and appreciation for those devices.[pullquote]Companies who invest in modern collaboration tools are likely to find higher usage and appreciation for those devices.”[/pullquote]

From a software perspective, it seems that old habits die hard. Emailing documents back and forth is still the most common methold of collaboration with co-workers at 35%, while the usage of cloud-based storage services is only 8% with co-workers and 7% with colleagues from other organizations. Similarly, real-time document collaboration tools, such as Microsoft’s Office 365 and Google Docs, which have now been available for several years, are only used with co-workers for collaboration purposes by 19% of respondents.

Modern forms of security, such as biometrics, are another key part of the ideal future workplace vision. In current-day reality, though, biometric security methods are only used 15% of the time for corporate data, 14% for physical facilities, and 12% for access to either corporate-owned or personally owned devices. Surprisingly, 41% of respondents said their company does not have any security policy for personal owned devices—yet those personal devices are used to complete 25% of the device-based work that they do. No wonder security issues at many organizations are a serious concern.

The tools and technologies are already available to deliver on a highly optimized, highly productive workplace of the future, but, as the survey results show, there’s still a long way to go before that vision becomes reality.

(If you’d like to dig a bit deeper, a free copy of a few survey highlights is available to download in PDF format here.)

Regardless of where you sit on the political spectrum, the maelstrom created by the last US presidential election uncovered a painful reality for the tech industry: a striking gap between it and much of mainstream America.

It’s not that Americans of all socioeconomic levels aren’t using the output of the tech industry. From smartphones to social media and PCs to online shopping, US citizens are, of course, voracious consumers of all things tech.

The problem is a serious lack of empathy and understanding from people who work within the tech industry to those outside their rarified milieu. To its credit, the tech industry has created enormous amounts of wealth and many high-paying jobs. Very few of those jobs, however, are relevant or available to a large swath of the US population. While I haven’t seen any official breakdowns, I’m not aware of many middle income jobs (according to US Census statistics, the average US family income in 2015 was $55,755) in the tech industry. Heck, interns at big tech companies often get paid more than that.

Not surprisingly, that kind of income disparity is bound to create some resentment. Yes, on the one hand, the significantly higher salaries often found in tech jobs do make the goal of working in tech an attractive one for many who aspire to break into the field. But not everyone can (nor wants to) work in tech.

A functioning society, of course, requires people to work across a range of jobs and at a range of income levels. But, it does seem rather disconcerting that an industry that is responsible for driving so much growth across the economy, and that houses the most well-known and well-respected brands in the world, does so little to employ people at mainstream income levels. For all of its focus on social justice and other progressive concerns, the tech industry displays a rather shocking lack of interest in economic inclusivity, which is arguably at the very heart of a just society.[pullquote]For all of its focus on social justice and other progressive concerns, the tech industry displays a rather shocking lack of interest in economic inclusivity, which is arguably at the very heart of a just society.”[/pullquote]

Of course, fixing the problem isn’t easy. But it does seem like there are a few basic ideas that could help and a lot more “thinking different” that might be worth a try. For one thing, the fact that the tech industry notoriously outsources (or subcontracts) nearly every lower and middle-income job to another firm (all in the name of cost-cutting) needs to be re-examined. From bus drivers, to janitorial and security staff to, yes, manufacturing jobs, it’s high time to start making people who do work for a company, employees of that company, with all the rights and benefits that entails. Yes, it could negatively impact the bottom line (though, in the big scheme of things, not by very much), but it would be a tremendously positive step for many. All it takes is some fiscal stamina and a bit of guts.

In addition, the whole mindset of gig-based companies (such as Uber) needs to be reconsidered. Maybe the original intentions for generating a bit of extra income were good, but when millions of people start trying to build their lives around pay-for-hire work, it’s time to start making them the middle-income employees they’ve earned the right to be.

It’s also time to start thinking about packaging and selling technology-driven products in entirely new ways. There might be ways to start building entire new sub-economies around, for example, helping farmers grow their crops more efficiently through the use of sensors and other IoT-based technologies. In addition, building products or services that allow the creation of small businesses, such as a tech franchise, which could help other local small businesses with their tech devices and software. For example, someone who could help local bakers, restaurants, florists or shoe repair shops to run their businesses a bit more efficiently, but provides “door-to-door” service.

Part of the problem is that the tech industry has become so obsessed with only offering the latest, most feature-rich products and services through high-income jobs that they have lost sight of the fact that some people only need very simple “older” tech that could be delivered in a more modest manner through comparatively lower-paying jobs.

Rather than planning for a societal collapse, it’s time to start mapping out a more positive, productive future that links Silicon Valley to Main Street in a useful, meaningful way.

The history of the technology industry has seen several swings back and forth between dependence on a network that can deliver the output of centralized computing resources, to client devices that do most of the computing work on their own.

As we start to head towards the Gigabit LTE and then 5G era, when increasingly fast wide-area wireless networks make access to massive cloud-based computing resources significantly easier, there’s a fundamental question that must be asked. Do we still need powerful client devices?

Having just witnessed a demo of Gigabit LTE put on by Australian telco carrier Telstra, along with network equipment provider Ericsson, mobile router maker Netgear, and modem maker Qualcomm, the question is becoming increasingly relevant. Thanks to advancements in network and modem (specifically Category 16 LTE) technologies, the group demonstrated broadband download speeds of over 900 Mb/s (conveniently rounded up to 1 Gb/s) that Telstra will officially unveil in two weeks. Best of all, Gigabit LTE is expected to come to over 15 carriers around the world (including several in the US) before the end of 2017.[pullquote]Gigabit LTE is expected to come to over 15 carriers around the world (including several in the US) before the end of 2017.[/pullquote]

Looking forward, the promise of 5G is not only these faster download speeds, but also nearly instantaneous (1 millisecond) response times. This latter point, referred to as ultra low latency, is critical for understanding the real potential impact of future network technology developments like 5G. Even today, the lack of completely consistent, reliable network speeds is a key reason why we continue to need (and use) an array of devices with a great deal of local computing power.

Sure, today’s 4G and WiFi networks can be very fast and work well for many applications, but there’s isn’t the kind of time-sensitive prioritization of the data on the networks to allow them to be completely relied on for mission critical applications. Plus, overloaded networks and other fairly common challenges to connectivity lead to the kinds of buffering, stuttering and other problems with which we are all quite familiar. If 5G can live up to its promise, however, very fast and very consistent network performance with little to no latency will allow it to be reliably used for applications like autonomous driving, where milliseconds could mean lives.

In fact, the speed and consistency of 5G could essentially turn cloud-based datacenters into the equivalent of directly-attached computing peripherals to our devices. Some of the throughput numbers from Gigabit LTE are now starting to match that of accessing local storage over an internal device connection, believe it or not. In other words, with these kinds of connection speeds, it’s essentially possible to make the cloud local.[pullquote]The speed and consistency of 5G could essentially turn cloud-based datacenters into the equivalent of directly-attached computing peripherals to our devices. [/pullquote]

Given that the amount of computing power in these cloud-based datacenters will always dwarf what’s available in any given device, the question again arises, what happens to client devices? Can they be dramatically simplified into what’s called a “thin client” that does little more than display the results of what the cloud-based datacenters generate?

As logical as that may at first sound, history has shown that it’s never quite that simple. Certainly, in some environments and for some applications, that model has a great deal of promise. Just as we continue to see some companies use thin clients in place of PCs for things like call centers, remote workers and other similar environments, so too, will we see certain applications where the need for local computing horsepower is very low.

In fact, smart speakers like the Amazon Echo and Google Home are modern-day thin clients that do very little computing locally and depend almost completely on a speedy network connection to a cloud-based datacenter to do their work.

When you start to dig a bit deeper into how these devices work, however, you start to realize why the notion of powerful computing clients will not only continue to exist, but likely even expand in the era of Gigabit LTE, 5G and even faster WiFi networks. In the case of something like an Echo, there are several tasks that must be done locally before any requests are sent to the cloud. First, you have to signify that you want it to listen, and then the audio needs to go through a pre-processing “cleanup” that helps ensure a more accurate response to what you’ve said.

Over time, those local steps are likely to increase, placing more demands on the local device. For example, having the ability to recognize who is speaking (speaker dependence) is a critical capability that will likely occur on the device. In addition, the ability to perform certain tasks without needing to access a network (such as locally controlling devices within your home), will drive demand for more local computing capability, particularly for AI-type applications like the natural language processing used by these devices.

AI-based computing requirements across several different applications, in fact, are likely going to drive computing demands on client devices for some time to come. From autonomous or assisted driving features on cars, to digital personal assistants on smartphones and PCs, the future will be filled with AI-based features across all our devices. Right now, most of the attention around AI has been in the datacenter because of the enormous computing requirements that it entails. Eventually, though, the ability to run more AI-based algorithms locally, a process often called inferencing, will be essential. Even more demanding tasks to build those algorithms, often called deep learning or machine learning, will continue to run in the data center. The results of those efforts will lead to the creation of more advanced inferencing algorithms, which can then be sent down to the local device in a virtuous cycle of AI development.

Admittedly, it can get a bit complicated to think through all of this, but the bottom line is that a future driven by a combination of fast networks and powerful computing devices working together offers the potential for some amazing applications. Early tech pioneer John Gage of Sun Microsystems famously argued that the network is the computer, but it increasingly looks like the computer is really the network and the sum of its connected powerful parts.

A great deal has been written recently on the growing importance of voice-driven computing devices, such as Amazon’s Echo, Google Home and others like it. At the same time, there’s been a long-held belief by many in the industry that software innovations will be the key drivers in moving the tech industry forward (“software eats the world”—as VC Marc Andreesen famously touted over 5 years ago).

The combination of these two—software for voice-based computing—would, therefore, seem to be at the very apex of tech industry developments. Indeed, there are many companies now doing cutting-edge work to create new types of software for these very different kinds of computing devices.

The problem is, expectations for this kind of software seems to be quickly surpassing reality. Just this week, in fact, there were several intriguing stories related to a new study which found that usage and retention rates were very low for add-on Alexa “skills”, and similar voice-based apps for the Google Assistant platform running inside Google Home.

Essentially, the takeaway from the study was that outside of the core functionality of what was included in the device, very few new add-on apps showed much potential. The implication, of course, is that maybe voice-based computing isn’t such a great opportunity after all.

While it’s easy to see how people could come to that conclusion, I believe it’s based on an incorrect way of looking at the results and thinking about the potential for these devices. The real problem is that people are trying to apply the business model and perspective of writing apps for mobile phones to these new kinds of devices. In this new world of voice-driven computing, that model will not work.

Of course, it’s common for people to apply old rules to new situations; that’s the easy way to do it. Remember, there was a time in the early days of smartphones when people didn’t really grasp the idea of mobile apps, because they were used to the large, monolithic applications that were found on PCs. Running big applications on tiny screens with what, at the time, were very underpowered mobile CPUs, didn’t make much sense.

In a conceptually similar way, we need to realize that smart speakers and other voice-driven computing devices are not just smartphones without a screen—they are very different animals with very different types of software requirements. Not all of these requirements are entirely clear yet—that’s the fun of trying to figure out what a new type of computing paradigm brings with it—but it shouldn’t be surprising to anyone that people aren’t going to proactively seek out software add-ons that don’t offer incredibly obvious value.

Plus, without the benefit of a screen, people can’t remember too wide a range of keywords to “trigger” these applications. Common sense suggests that the total possible number of “skills” that can be added to a device is going to be extremely limited. Finally, and probably most importantly, the whole idea of adding applications to a voice-based personal assistant is a difficult thing for many people to grasp. After all, the whole concept of an intelligent assistant is that you should be able to converse with it and it should understand what you request. The concept of “filling in holes” in its understanding (or even personality!) is going to be a tough one to overcome. People want a voice-based interaction to be natural and to work. Period. The company that can best succeed on that front will have a clear advantage.

Despite these concerns, that doesn’t mean the opportunity for voice-based computing devices will be small, but it probably does mean there won’t be a very large “skills” economy. Most of the capability is going to have to be delivered by the core device provider and most of the opportunity for revenue-generating services will likely come from the same company. In other words, owning the platform is going to be much more important for these devices than it was for smartphones, and companies need to think (and plan) accordingly.[pullquote]Existing business models and existing means for understanding the role that technologies play don’t always transfer to new environments, and new rules for voice-based computing still need to be developed.”[/pullquote]

That doesn’t mean there isn’t any opportunity for add-ons, however. Key services like music streaming, on-demand economy requests, and voice-based usage or configuration of key smart home hardware add-ons, for example, all seem like clearly valuable and viable capabilities that customers will be willing to add on to their devices. In each of those cases, it’s also important to realize that the software isn’t likely going to represent a revenue opportunity of its own; simply a means of accessing an existing service or piece of hardware.

New types of computing models take years to really enter the mainstream, and we’re arguably still in the early innings when it comes to voice-driven interfaces. But, it’s important to realize that existing business models and existing means for understanding the role that technologies play don’t always transfer to new environments, and new rules for voice-based computing still need to be developed.

Writing about security is kind of like writing about insurance. As a responsible adult, you know it’s something you should do every now then, but deep down, you’re really worried that many readers won’t make it past the second sentence. (I hope you’re still here.)

Having recently had the privilege of moderating a panel entitled “Inside the Mind of a Hacker” at the CyberSecurity Forum event that occurred as part of CES, however, I’ve decided it’s time. The panel was loaded with four smart and opinionated security professionals who hotly debated a variety of topics related to security and hacking.

Speaking to the theme of the panel, it became immediately clear that the motivations for the “bad guy” hackers (there was, of course, a brief, but strong show of support for the white hat “good” hackers) are exactly what you’d expect them to be: money, politics, pride, power and revenge.

Beyond some of the basics, however, I was surprised to hear the amount of dissent on the topics discussed, even by those with some impressive credentials (including work at the NSA, managing cyber intelligence for Fortune 500 companies and government agencies, etc.). One particularly interesting point, for example, highlighted that hackers are people too—meaning, they make mistakes. In fact, thankfully, apparently quite a lot of them. While in retrospect that seems rather obvious, given the aura of invincibility commonly attributed to hackers through popular media, it wasn’t something I expected to hear.

Another key point was the methodology used by most hackers. Most agreed that the top threat is from phishing attacks, where employees at a company or individuals at home are lured into opening an attachment or clicking on a link that triggers a series of, well, unfortunate events. Even with up-to-date anti-malware software and security-enhanced browsers, virtually everyone (and every company) is vulnerable to these increasingly sophisticated and tricky attacks. However, several panelists pointed out that too much attention is spent trying to remedy the bad situations created by phishing attacks, instead of educating people about how to avoid them in the first place.

Looking forward, the rapid growth of ransomware, when companies or individuals are locked out of their systems and/or data until a ransom is paid to unlock it, was one of the panelists’ biggest concerns. Attacks of this sort are growing quickly and most believe the problem will get much worse in 2017. In many cases, organized crime is behind these types of incidents, and with the popularity of demanding payment in bitcoin or other payment methods that are nearly impossible to trace, the issue is very challenging.

Another concern the panel tackled was security issues for Internet of Things (IoT) devices. Many companies getting involved with IoT have little to no security experience or knowledge and that’s led to some gaping security holes that automated hacking tools are quick to find and exploit. Thankfully, the group agreed there is some progress happening here with newer IoT devices, but given the wide range of products already in market, this problem will be with us for some time. One potential solution that was discussed was the idea of an IoT security standard (along the lines of a UL approval), which is a topic I wrote about several months back. (See “It’s Time for an IoT Security Standard”)[pullquote]There are few if any things that can be completely blocked from hacking efforts, but huge progress could be made in cyber security if companies and people would just start actually using some of the tools already available.”[/pullquote]

Another potential benefit could come from improved implementations of biometric authentication, such as fingerprint and iris scans, as well as leveraging what are commonly called “hardware roots of trust.” Essentially, this provides a kind of digital ID that can be used to verify the authenticity of a device, just as biometrics can help verify the authenticity of an individual. Both of these concepts enable more active use of multi-factor authentication, which can greatly strengthen security efforts when combined with encryption, stronger security software perimeters, and other common sense guidelines.

As the panel was quick to point out, there are few if any things that can be completely blocked from hacking efforts. Nevertheless, huge progress could be made in cyber security if companies and people would just start actually using some of the tools already available. Instead of worrying about solving the toughest corner cases, good security needs to start with the basics and build from there.

By now you’ve undoubtedly read or viewed several different CES stories across a wide range of publications and media sites. So, there’s no need to rehash the details about all the cool, crazy, or just plain interesting new products that were introduced at or around this year’s show.

But it usually takes a few days to think through the potential impact of what these announcements mean from a big picture perspective. Having spent time doing that, here are some thoughts.

The impact of technology on nearly all aspects of our lives continues to grow. Yes, I realize that seems somewhat obvious, but to actually see or at least read about the enormous range of products and services on display at this year’s show makes what is typically just a conceptual observation, very real. From food to sleep to shelter to work to entertainment (of all kinds!) to health to transportation and beyond, it’s nearly impossible to imagine an activity that humans engage in that wasn’t somehow addressed at this year’s show. Having attended approximately half of the 50 CES shows that have now occurred, the expanding breadth of the show never ceases to amaze me. In a related way, the range of companies that are now participating in some way, shape, or form is surprisingly diverse (and will only increase over time).

Software is essential, but hardware still matters. At the end of the day, it’s the experience with a product that ultimately determines its success or failure. However, when you’re surrounded by the products and services that will drive the tech industry’s agenda for the next 12 months, it’s immediately clear that hardware plays an enormously critical role. From subtle distinctions like the look and feel of materials, to the introduction of entirely new types of tech products, the importance of hardware devices and key hardware components continues to grow, not shrink (as some have suggested).

What’s old can be new again. Though TVs and PCs may sound like products from a different era to some, this year’s show once again proved that the right technological developments combined with human ingenuity can produce some very compelling new products. Even long-forgotten technologies like front projection can be transformed in ways that make them very intriguing once again. Plus, it’s becoming increasingly clear that, just like the fashion and music industries, the tech industry is developing a love affair with retro trends. From vinyl to Game Boys and beyond, it seems many types of older tech are going to be revisited and renewed.

We are on the cusp of some of the biggest changes in technology that we’ve seen in some time. The integration of “invisible” technologies that we can’t directly see but still interact with is going to drive some of the most profound developments, power shifts, and overall restructuring that’s ever occurred in the tech industry. Oh, and it’ll make for some incredibly useful and compelling new product experiences too.[pullquote]The integration of “invisible” technologies that we can’t directly see but still interact with is going to drive some of the most profound developments, power shifts, and overall restructuring that’s ever occurred in the tech industry.”[/pullquote]

Voice-control will certainly be part of this, but there will be much more. In fact, the range of new products and services, as well as enhancements and recreations of existing products and services that AI, deep learning, and other advanced types of software technologies can enable in combination with sensors, connectivity, and powerful distributing computing is going to be transformational. Sure, there’s been talk of adding intelligence to everything for quite some time, but many of the announcements from this year’s CES demonstrate that this promise is now becoming real.

Finally, trade shows still matter, even in tech. Yes, virtual reality may one day provide us with the freedom to avoid the crowds, hassles, and frustrations of trekking to an alternative location, and seemingly everyone who goes likes to complain about attending CES, but there’s nothing quite like being there. From serendipitous run-ins with industry contacts, to seeing how others react to products and technologies you find interesting, there are lots of reasons why it’s going to be difficult to completely virtualize a trade show for some time to come.