Tom Austin

A member of the Gartner Blog Network

Tom Austin
VP & Gartner Fellow
20 years at Gartner
41 years IT industry

Tom Austin, VP, has been a Gartner Fellow since 1997. He drives Gartner's research content incubator (the Maverick Program) and is leading a new research community creating research on the emerging era of smart machines. Read Full Bio

Fridge Fantasies Redux

by Tom Austin  |  May 23, 2014  |  1 Comment

Read yet another piece where people were talking about IoT and how internet connected fridges would tell our smart phones to remind us when we came close to a grocery store that we only had 50 ml of Milk left so please pick some up. Oh, and by the way, buy brand Zed because it’s best (or so says one of 472,995 sponsors of this reminder service.)

Never mind the fantasies of the 1990’s where people were predicting — the same thing!

Think about all of the structural problems in making this come true. Even if people changed their refrigerators once every year (not very likely; there are better ways of spending money), how long will it take to modify all products you stick in the refrigerator to communicate their state to said box? What are the economics there? How do you instrument a poblano pepper to notify the crisper in the fridge that it’s getting lonely in there and it would like some more poblanos to keep it company? How much does this add to the cost of food? What’s the product life cycle for various food offerings, a factor which gates how quickly zero cost technology could be added? 

Then there’s the privacy issue. If the trash container and fridge get together and take stock of my consumption of red onions, broccoli and garlic, what kind of story could they fabricate? Maybe that my food wastage rate is 8% higher than that of other apartment owners in my complex. Or 17% less. And what if that news got out? Perish the thought (or cook it quickly so it doesn’t perish.)

I’ll confess. I don’t always keep tomatoes (fresh or canned) in the refrigerator. So how will my smart phone know to remind me about that inventory level?

A prediction: Before we have smart kitchen cabinets and smart cauliflower too, we’ll have useful (but not very smart) robots that can do a visual scan for you when you’re in the grocery aisle of your favorite food emporium and panic because you can’t remember if you’re over or understocked on jalapenos. Instead, you tell your video enabled relatively dumb remote assistant to go over to the refrigerator, open the door and point its camera at the crisper draw so you can figure it out for yourself.

And we’ll still be talking about intelligent fridge fantasies ten years from then…

 

 

 

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Smart Machines: How Will They Disrupt Your Career?

by Tom Austin  |  February 10, 2014  |  1 Comment

How susceptible is your job to computerization? According to Frey and Osborne, 47% of all current U.S. jobs are at risk over the next two decades because they consist primarily of tasks that can be automated in that time period.  (Left unanalyzed are the beneficial impacts — such as new capabilities people will pick up by collaborating with smart machines.)  

I recently wrote that smart machines will continue to enhance and threaten the abilities of employees to do their jobs. By 2020, Gartner Predicts that a majority of knowledge worker career paths will be disrupted by smart machines in both positive and negative ways. Read the full report, Gartner Top Predictions 2014: Plan for a Disruptive, but Constructive Future

Smart machines  — a broad and powerful range of new systems— are emerging this decade. They do what we thought only people could do and what we didn’t think technology could do. Smart machines and smart advisors exploit machine learning and algorithms —  they learn from results and work faster than humans – they make smart people smarter. Virtual personal assistants  – focused on user behavior (habits, activities, needs) — make smart people more effective.  

The smart machine market is small, but growing, threatening to upend knowledge workers careers by 2020 (see chart). Ignore at your own peril.

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How should you factor smart machines and machine-assisted tasks into your IT planning? View Gartner Top Predictions 2014: Plan for a Disruptive, but Constructive Future to see key findings, market implications and recommendations. Discover the competitive advantages that await early adopters.

For Gartner clients seeking more on the smart machines, view Predicts 2014: The Emerging Smart Machine Era and The IT Role in Helping High Impact Performers Thrive.

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When is a dumb machine smart?

by Tom Austin  |  January 3, 2014  |  Comments Off

I’ve been working on research on “smart machines” for most of 2013 (and tracking same for years before then) but I recently came across a wonderful invention that illustrates the point that not all machines need to have all the attributes we think of regarding smart machines.

Behold the Spoon Full of Sensors To Help Parkinson’s Patients Feed Themselves! The designers here recognized how the same accelerometers and actuators used for image stabilization in advanced cameras these days could be applied to help these people lead more normal lives. 

Here, the designers and engineers were smart and the specific product they created is a dumb machine but the end result is freedom and joy for the afflicted. What a smart dumb machine!

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What should technologies like IBM’s Watson and Google’s Knowledge Graph mean to you?

by Tom Austin  |  April 24, 2013  |  Comments Off

I’ve seen the future … and now it’s within grasp. It’s going to impact your life and your work before this decade is out.

We just published a note entitled Exploit the Intersect of IBM’s Social Business and Solution Selling Strategies

A part of that note, probably one quarter, dives into what has been fascinating me for many, many years. There’s only so many features you can stick into an email program or a content editing tool. Particularly if you’re text-centric. Where do we go after the 177th version of a personal productivity tool suite? The 34th iteration of instant messaging? The 500th document database? So much of what we’re doing now is reinventing and refining what we were already doing in the pre-client-server era. Back in the late 80’s at Digital Equipment, we had a vision and architecture for compound documents in GUI environments…how many more iterations of that do we really need?

There’s more coming, very different. It’s not a new kerning tool. Or the next great slide transition mechanism. It’s about the rise of smart assistants. Natural language processing. Semantic analysis. Massive parallelization. Rule-based systems with machine learning. Pattern recognition and matching. Marry that to the scale of what Google can do and what IBM, with Watson and co-development partners can do.

Start with Google. Witness, for example: 

Then look at IBM. Witness, again, for example:

  • Watson — as in Ken Jenning’s declaration on Jeopardy “I, for one, welcome our new computer overlords
  • Consider the Watson “Oncology Treatment Advisor”. IBM co-developed it with Wellpoint who is now selling it. It’s narrowly focused today on lung and breast cancer cases. It digests hundreds of millions of pages of published research and other reference data, considers the patient’s data (such as diagnostic test data, prior treatments and broader history) and suggests to the clinician a list of alternative treatments to consider. The list is ordered — based on a calculated likelihood of success — and provides access to all the relevant information the system has considered in constructing each recommendation. 
  • IBM is also working with Memorial Sloan-Kettering Cancer Center and others on additional, very narrow but high-value use cases in various medical fields. Other co-development projects are under way in other industries.
  • This isn’t just about game shows and slights of programmer-hands! 

Google Now represents analysis of a longitudinal array of information about what you do, where you go, what you say, who you pay attention to and whom you interact with across time so that Google (and, for that matter, Siri, it’s cross-valley competitor) can predict what you will need in your current context — before you even know it. There’s a staggering amount of personal information it can mine.

This isn’t just the Apple Knowledge Navigator reborn.

And then there’s Watson and the techniques IBM is using to evolve future generations of its capabilities…

I see radical change coming — glorious and depressing, liberating and enslaving, enriching all and only a few. This isn’t necessarily the optimistic world of Brynjolfsson and MacAfee’s Race Against The Machine..

How is this going to affect your organization (IT)? Your enterprise? industry? economy? society? What do you counsel your children to pursue as a career? as their passion?

 

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Type A Collaborative Environment and Culture

by Tom Austin  |  September 29, 2012  |  1 Comment

The following statement from users of a dead product (had its heyday in the 1980’s) reflects a lot of what we see in certain selected Type A pro-social (collaborative) cultures today.  

“The openness, the willingness to help out with the understanding that others would help you out, the desire to keep history alive even as you moved on to the new things, the personal relationships that transcended organizational relationships, the recognition of authority based on knowledge and helpfulness rather than just position – all of these things were reflected in, and supported by, … {insert product name here}” *
 
The company was Digital Equipment Corporation (DEC). The product was “Notes-11,” later “VAXNotes”. Product isn’t the issue. It’s all about culture.
 
With the right culture, collaborative tools can have a massive impact. (I’m not recommending “build it and they will come” enterprise wide deployments unless certain special preconditions are met.) In the wrong culture, you need a specific proscribed project with delineated needs, measures, rewards, observation, experimentation, iteration, implementation, governance, management, structure and so forth.
 
The Notes-11 and VAXNotes culture thrived 30 years ago. How sad it is that we still view the pro-social culture described in the italicized paragraph as “Type-A” behavior, probably found in less than 10% of large organizations worldwide.
 
(I have to thank Jerry Leicher, formerly of DEC (now of Google) for the quote above, from a posting he made in the Digital Alumni discussion group on Linked-In.)

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Making Fluid Teamwork More Effective

by Tom Austin  |  April 26, 2012  |  Comments Off

I’m inspired by Amy C. Emondson’s article, “Teamwork on the Fly” in the April 2012 Issue of Harvard Business Review. I’ve referred numerous clients to it over the last four weeks (since I first saw it).

The “in brief” summary of the piece reads as follows

 Idea in Brief

In today’s fast-moving, ultracompetitive global business environment, you can’t rely on stable teams to get the work done. Instead, you need “teaming.”

Teaming is flexible teamwork. It’s a way to gather experts from far-flung divisions and disciplines into temporary groups to tackle unexpected problems and identify emerging opportunities. It’s happening now in nearly every industry and type of company.

To “team” well, employees and organizations must embrace principles of project management—such as scoping out the project, structuring the group, and sorting tasks by level of interdependence—and of team leadership, such as emphasizing purpose, building psychological safety, and embracing failure and conflict.

Those who master teaming will reap benefits. Teaming allows individuals to acquire knowledge, skills, and networks, and it lets companies accelerate the delivery of current offerings while responding quickly to new challenges. Teaming is a way to get work done while figuring out how to do it better.

The reason this article is so important is it provides a context within which to think about how the IT organization might add value to the fluid (dynamic, virtual) teaming Amy writes about.

After all, it really isn’t IT’s mission to make Sharepoint or Jive or Connections or anyone else’s tools more effective. It’s about how to make human processes reflected in these fluid, dynamic, virtual teams more effective.

Here’s another quote from the piece to give you more context. 

“Stable teams of people who have learned over time to work well together can be powerful tools. But given the speed of change, the intensity of market competition, and the unpredictability of customers’ needs today, there often isn’t enough time to build that kind of team. Instead, organizations increasingly must bring together not only their own far-flung employees from various disciplines and divisions but also external specialists and stakeholders, only to disband them when they’ve achieved their goal or when a new opportunity arises. More and more people in nearly every industry and type of company are now working on multiple teams that vary in duration, have a constantly shifting membership, and pursue moving targets. Product design, patient care, strategy development, pharmaceutical research, and rescue operations are just a few of the domains in which teaming is essential.”

A few key observations about fluid, virtual, dynamic teams:

  • This is the world of ad hocracy (per Toffler’s Future Shock, 1970-1971).  
  • This is the place where there are large virtual barriers to success (one very instructive way to think about virtual teams is the presence of barriers to effectively working together — see “Discontinuities and Continuities: A New Way to Understand Virtual Work” by Mary Beth Watson-Manheim, et al and subsequent work related to it
  • This is a place where technology can help bridge discontinuities to help make these virtual teams more effective if the technology is applied intelligently
  • People on these teams constitute no more than 20% of white collar workers in a typical organization so success requires targeting, not just deploying a tool everywhere.  
  • It also involves people outside the organization, by the way, and the number of those contributors is large and the external cohort is constantly changing (and unpredictable). 
  • The highest return for people centered strategies will come from empowering these virtual, dynamic, ad hoc teams.

Have you found these types of teams anywhere in your enterprise? Have you looked? Can you describe them and how their needs relate to typical “collaboration” solutions the industry offers? Have you singled them out as specific target to invest in? Or are they simply part of the larger target audience you’re looking at and trying to service?

 

 

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Neuroscience Nonsense? Wilson Brilliance?

by Tom Austin  |  April 9, 2012  |  Comments Off

There’s a broad and grey line between the study of human behavior (which can very often be “irrational”) and the study of neuroscience (a study of the mechanisms that, at some level of abstraction, lie beneath the irrationality).

The Washington Post, today, in a blog posting entitled “Is neuroscience the new ‘Freakonomics’?” is playing fast and loose with the terms, likely in an attempt to attract attention (as they slyly imply in the text). Nonetheless, the post is a good read because it makes a few key points, most notably (in my own words):

Don’t ask people what they want (they don’t know). Instead, watch what they do. Offer alternatives (A/B or multivariate testing) and see what they choose.

Don’t do opinion surveys either. Well, OK, do some, in moderation, but by all means don’t rely on them to predict much of anything that’s broader than a survey! (Which elections are, of course. But this isn’t about politics.)

Don’t act on the assumption that people are conscious, rational beings, continuously (re)applying algorithms to weight alternatives as they approach choice points. Consciousness is a wooly term, a product of several hundred (thousand?) years of talk, probably best exemplified by Rene Descartes (in)famous mind-body dualism. There isn’t a single consciousness. There are likely at least 20 different processes that can be characterized as reflecting ‘consciousness’. People are governed by unconscious phenomena (from olfactory stimuli through the rules of the society and culture they live within).

E.O. Wilson’s new genetic hypothesis (selection works on groups and populations, not just individuals) is one great body of exciting (and highly controversial) thinking (see his new book, The Social Conquest of Earth). Michael Gazzaniga had an interesting review of the book in Saturday’s Wall St. Journal.

David Brooks writings (see The Social Animal) explore some of the many (unconscious, social and biological) dimensions controlling human behavior.

But let’s not call all of this “Neuroscience”. Maybe someday we’ll get to the level where we can tie neurosciences to the complex economic behavior of large collections of people. But we aren’t there yet.

 

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Is Social Contagion A Fiction?

by Tom Austin  |  April 4, 2012  |  Comments Off

The economist has a piece this week on a study of whether signing up for Facebook follows germ-contagion patterns or not.  The piece reports on a PNAS (Proceedings of the National Academy of Sciences) report that analyzed 54 million email invites users sent out to friends who had not yet joined Facebook.

So what did they find?

Signing up did not follow typical germ-contagion patterns.

The more *diverse* groups a person could interact with, the more likely they were to sign up.

What makes this interesting is one of the key premises behind Google plus and Google Hangouts is the value of being able  to separate circles of friends (and associates). Does this research invalidate the whole premise? How could we find out?

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Be Afraid: Read McAfee’s “The Robots Coming for Your Job” Blog Post

by Tom Austin  |  March 23, 2012  |  Comments Off

Andy just blogged on material that relates to the excellent book he and Erik Brynjolfsson wrote last year, “Race Against The Machine“. Read the blog. Then read the book — it’s short and to the point (and reflects many of my much less widely read musings of the last few years).

The video of “Big Dog” in his post is entertaining but the fundamental message is sobering. Technology is destroying jobs. Some of them — good riddance. But technology’s also moving up the value chain. And the deep issue here to me is how does society adapt?

Back in High School in the early 60’s, the claim was we’d all work only 15 hours a week by now — and take a few months off every year. Work would be automated, right? Well, now we’re getting closer to that in a mathematical way. How does society adjust? Pay everyone to work only, on average, 15 hours a week? I don’t think so. So how are our institutions going to change?

If they don’t change, and more and more money goes to the top few percent of the population, we’re going to see massive social strife right here in the US.

What can we do to redress this? Can we raise people’s game enough to raise their worth enough to offset this incomes shift?

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How does your digital self reflect your personal self?

by Tom Austin  |  March 22, 2012  |  Comments Off

I’m at the Adobe Summit in Salt Lake City, listening to Biz Stone (co-founder of Twitter) talking about his digital self and I’m realizing I’m somewhat conflicted about the basic question: does my digital self, as reflected on Twitter, Facebook, Flickr, Linked-in and a host of other much smaller sites reflect me as a person?

To what extent can it? How should I separate my personal and professional? Will my professional followers, for example, on Twitter, understand my personal Tweets?

Is it possible to maintain enough separation between personnae so they don’t get confused yet not have so large a gulf that your digital self no longer reflects your personal self?

How do you deal with this?

 

 

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