Tag Archives: Web 2.0

Getting news in the mobile connected world

So, I’m driving to the nearby Barnes and Noble to use their Wifi and get some work done. Plus I get a discount on their coffee. I get a voicemail on my iPhone from my Mom saying she hopes I’m not in downtown Seattle, that it looks like a real mess.

Not having a clue to what she was talking about, I checked Google News. I found a couple of articles like this one, about a man wandering around near the Courthouse with some sort of device on his arm. The police has him in custody and were examining the device.

Then I ran across this article which quoted a Police tweet about the incident:

In a tweet, Seattle police said, “Adult male in 300 block of James has made general threats against persons and property. He has taped an unknown device to his left hand.”

Whoa. I had not thought about that at all. You can follow the whole incident on their Twitter page! Here is a picture of the description so far:


seattle pd twitter

Jeez. They have a picture of the device online already! Who would have really thought 5 years ago that information about something like this could not only be readily available but that organizations, such as the police, would be on the front lines of providing it. we no longer need to wait for the evening newscast or the paper the next day to get informed.

And as I finish this, the Twitter feed states that the downtown streets have been reopened.

Disruptive technology seldom is accurately described during its disruptive period

Apple’s “history of lousy first reviews”
[Via Edible Apple]

From the original Mac to the iMac to the iPod and even the iPhone, early reviews of revolutionary products tend to evoke a lot of negative reactions. The Week takes us back in time and examines what reviewers have historically thought about Apple’s latest and greatest creations.

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The problem with so many new, disruptive technologies is that most people do not understand them. Let me pull back a little bit to discuss how innovations are accepted by a community, using the model proposed by Everett Rogers.


diffusion

The majority of people do not change, do not take up new things, very rapidly. They like to stick with what they know.

A small group do accept new things very fast. These so called innovators are the ones that almost always make up the tech community.

Read any tech blog and you’ll see all sorts of stuff regarding the coolest new toys. They know in detail just why a new product is worthy, usually because it is the best, fastest, newest.

Now, to get new technology out of the hands of the innovators and into the majority requires the work of early adopters. These act as filters, helping move innovations that can make a real difference to the majority, out of the hungry hands of the innovators.

These people are pretty special because, for all sorts of reasons, the majority just will not listen to the innovators. They are too disruptive. They might listen to the early adopters because this group seems to know how to mediate between the two groups that often fail to communicate at all.

Now, the people who write about high tech are usually of two types (and this holds for any writing about rapidly changing technologies). They either write for the innovators, providing insights into the newest. Or they write for the majority, providing a comfortable view of how the rapid churn of the new can be ‘controlled’.

To really be successful, a technology needs to move out from the innovators to the majority. But who will write about this? Those that cater to the innovators will not because the technology that is usually being moved is ‘old hat.’ That is who their audience is.These writers always tell us how there are faster things with more memory that can do the same thing. “My hand-built PC is able to do three times as much for half the price.”

And what about those who cater to the majority? Well, they are usually skeptical of anything new. That is who their audience is. So this disruptive technology is often viewed in the same way as any other – something to be feared and watched carefully. “This computer is really slow and will never replace the speed of a mainframe.”

If you look at the criticisms of Apple products over the years, especially the ones that have been shown by history to be flat out wrong, you see they fall into one of these two bins.

What Apple has done, more than most other companies, is act first to move technologies and ideas out of the hands of the innovators, into the land of the majority. This does not mean they have to be the most innovative or always have the best ideas. What they have been successful at is becoming the premier company of transitioning technology. They filter out the technology, finding the best ones to move out to the majority.

Few companies are able to do this even once. The fact that Apple has done this in multiple product categories is amazing.

And, just as early adopters are usually the opinion and thought leaders of a community, so Apple is watched to see what will become the new paradigm for the majority. This explains why keynotes given by Steve Jobs can bring down the internet.

Most pundits and commenters on Apple, and on any disruptive technology, will continue to get it wrong. Few people are able to effectively, and accurately, discuss the views of the early adopter segment. I think that might be because to do that requires someone who can simultaneously understand both the views of the innovator cohort and the majority. These people seem to be pretty rare and can probably find a more lucrative livelihood than writing for a magazine. Perhaps working for Apple.

Creating collaboration

group by Arenamontanus

How John Chambers Learned to Collaborate at Cisco
[Via HarvardBusiness.org]

In 2001, as the dot.com boom turned to bust, CEO John Chambers of Cisco saw a massive $460 billion of Cisco’s overall stock market value evaporate before his eyes. Game over? Not really. At that moment, Chambers started a reinvention of the company — from a “cowboy” mentality where people worked in silos to a collaborative approach. It has paid off so far. Revenues are up 90% since 2002, while profit margins are up to 20.8% from 16.3%. And Chambers earned the #4 spot on our best-performing CEO ranking, published last month by Harvard Business Review. Not bad.

Chambers created the following 5 pillars to drive collaboration, an approach we can all learn from. These amount to what I call disciplined collaboration in my book Collaboration: focus on business value, tear down barriers, and create a new organization architecture. (Full disclosure: last autumn I met with the top 50 leadership team at Cisco to discuss collaboration; the information here is all from public sources, however).

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The five pillars are these:

1. Change leadership style.

2. Change incentives.

3. Change the structure.

4. Change how you work.

5. Use new social media tools.

These are all hallmarks of systems thinking. No more top-down thinking. Make people want to collaborate. The structure needs to map human social networks. Bring multiple points of view to examine the problem.

But it also uses things like constraints and goals to keep on track. It uses diffused leadership rather than central but makes sure there are ways to give the successful groups their rewards.

It also includes selecting for people who want this sort of structure. Luckily, the ones who thrive here are exactly the types who will produce success.

Read about the development of the Mac to get an idea of what these people are like. And also see what happened when a typical hierarchical manager was put in charge. Order and proper respect for authority was more important than success.

Apple made a mistake by putting these people into a silo type of management structure after the Mac came out. Many of the developers of the Mac were gone in less than 18 months, including the founder of the company, Steve Jobs.

The structure that Cisco built for collaboration can produce wonderful things. But its requirements need to be understood and supported by management in order to succeed.

Disruption rather than deviancy

path by notsogoodphotography

Why every team needs a deviant.
[Via Creativity Central]

Most of us in the creativity brainstorming world are professional deviants.

We don’t typically use the term deviant, preferring the less harsh term gadfly. Or in a politically correct world, idea catalyst.

But deviant is good enough for J. Richard Hackman, the Edgar Pierce Professor of Social and Organizational Psychology at Harvard University and leading expert on teams. Hackman has spent his career exploring and questioning — the wisdom of teams.

In a recent interview with Diane Coutu called “Why Teams Don’t Work” he talks about why every team needs a deviant.

Coutu: “If teams need to stay together to achieve the best performance, how do you prevent them from becoming complacent?”

Hackman: “This is where what I call the deviant comes in. Every team needs a deviant, someone who can help the team by challenging the tendency to want too much homogeneity, which can stifle creativity and learning.

Deviants are the ones who stand back and say, “Well wait a minute, why are we even doing this at all?” What if we looked at the thing backwards or turned it inside out?” That’s when people say, “Oh, no, no, no, that’s ridiculous” and so the discussion about what’s ridiculous comes up…the deviant opens up more ideas and that gives you a lot more originality.

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I view these types more as disruptors than deviants. They look at things differently, bring in novel ideas from outside the group and generally disrupt the ‘easy flow’ of a strong team. They look to stretch or beak some of the constraints that we use, in order to make sure we really need them.They are often disliked by the rest of the group and will simply shut up if not provided even a little support.

And that is what most teams do, shut them up. Shunning is usually the main approach. The disruptors then quickly understand and stop disrupting. The inability to support any disruption, often because it may seem almost insubordinate, leads to the failure of many teams.

But, even a little support will go a long way. Some useful facilitation of disruptors, allowing their ideas to be brought out and examined, can have a huge effect on the general creativity of the group. Good managers need to realize this because, as has been shown in many studies, the people that act as useful filters for this sort of disruptive information, the ones that help the community adopt these disruptive ideas, are often the ones that are viewed as thought leaders in the organization and on the track to greater things.

Unfortunately, at the moment, few organizations properly recognize the disruptor. Maybe that will change.



The difference between the creative and the commonplace

tufte by BruceTurner

Edward Tufte Presidential Appointment
[Via Daring Fireball]

President Obama has appointed Edward Tufte to the Recovery Independent Advisory Panel, “whose job is to track and explain $787 billion in recovery stimulus funds”. Outstanding.

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This is pretty cool. Tufte is one of my favorite people, not only for his highly original books on data presentation but also for his sheer force of personality. He is one of the most entertaining, enlightening speakers I have ever heard.

I attended one of his workshops in Seattle probably close to 20 years ago. There was an interchange that has stuck with me ever since, because it so succinctly illustrates the divide between truly original, innovative change and the typical corporate response.

Tufte was discussing the different interfaces between the Mac OS and Windows. After going through a lot of the pluses he saw in the Mac and a lot of the minuses in Windows, he stated that the Mac looked like it had been created by one or a small group of people with a single purpose, a single view of how the information should be presented, while Windows looked like it had been done by a committee.

He then said that all the best presentations were this way – a single point of view forcefully pushed onto everyone. Someone in the audience then asked but what happens if your single point of view turns out to be wrong, to not work.

Tufte replied, simply, “You should be fired.” You could almost audibly hear the intake of everyone’s breath. That is exactly what they feared and why they would always want to retreat into committee decisions – they can’t be fired if the committee made the decision. FUD is what drives most people.

The creative, the innovative do not really fear failure, often because they are adaptable enough to ‘route around the damage’ quickly enough. They do not usually doubt the mission they are on and are certainly not uncertain about the effects. Read about the development of the Mac. They were going to change the world, no doubt about it. While you can see that there really was a focus of vision, there are also lots of ‘failures’ that had to be fixed. The key was to fail quickly, leaving time to find success.

And permitting committed individuals to find their own way to success rather than rely on committees to fix them.

Committees very seldom fail quickly, since failure is the thing they fear the most. They would rather succeed carefully than perhaps fail spectacularly. And they very seldom produce revolutionary change.

Single viewpoint, change the world, rapidly overcome obstacles, adaptable. All characteristics of successful change. They do not fear spectacular failure because the fruits of success will be so sweet.


Getting at data

Four Ways of Looking at Twitter
[Via HarvardBusiness.org]

Data visualization is cool. It’s also becoming ever more useful, as the vibrant online community of data visualizers (programmers, designers, artists, and statisticians — sometimes all in one person) grows and the tools to execute their visions improve.

Jeff Clark is part of this community. He, like many data visualization enthusiasts, fell into it after being inspired by pioneer Martin Wattenberg‘s landmark treemap that visualized the stock market.

Clark’s latest work shows much promise. He’s built four engines that visualize that giant pile of data known as Twitter. All four basically search words used in tweets, then look for relationships to other words or to other Tweeters. They function in almost real time.

“Twitter is an obvious data source for lots of text information,” says Clark. “It’s actually proven to be a great playground for testing out data visualization ideas.” Clark readily admits not all the visualizations are the product of his design genius. It’s his programming skills that allow him to build engines that drive the visualizations. “I spend a fair amount of time looking at what’s out there. I’ll take what someone did visually and use a different data source. Twitter Spectrum was based on things people search for on Google. Chris Harrison did interesting work that looks really great and I thought, I can do something like that that’s based on live data. So I brought it to Twitter.”

His tools are definitely early stages, but even now, it’s easy to imagine where they could be taken.

Take TwitterVenn. You enter three search terms and the app returns a venn diagram showing frequency of use of each term and frequency of overlap of the terms in a single tweet. As a bonus, it shows a small word map of the most common terms related to each search term; tweets per day for each term by itself and each combination of terms; and a recent tweet. I entered “apple, google, microsoft.” Here’s what a got:

twittervenn.jpg

Right away I see Apple tweets are dominating, not surprisingly. But notice the high frequency of unexpected words like “win” “free” and “capacitive” used with the term “apple.” That suggests marketing (spam?) of apple products via Twitter, i.e. “Win a free iPad…”.

I was shocked at the relative infrequency of “google” tweets. In fact there were on average more tweets that included both “microsoft” and “google” than ones that just mentioned “google.”

[More]

Social media sites provide a way to not only map human networks but also to get a good idea of what the conversations are about. Here we can see not only how many tweets are discussing apple, microsoft and goggle but the combinations of each.

Now, the really interesting question is how ti really get at the data, how to examine it in order to discover really amazing things. This post examines ways to visually present the data.

Visuals – those will be some of the key revolutionary approaches that allow us to take complex data and put it into terms we can understand. These are some nice begining points.

An interesting juxtaposition

data by blprnt_van

Reaching Agreement On The Public Domain For Science
[Via Common Knowledge]

Photo outside the Panton Arms pub in Cambridge, UK, licensed to the public under Creative Commons Attribution-ShareAlike by jwyg (Jonathan Gray).

Today marked the public announcement of a set of principles on how to treat data, from a legal context, in the sciences. Called the Panton Principles, they were negotiated over the summer between myself, Rufus Pollock, Cameron Neylon, and Peter Murray-Rust. If you’re too busy to read them directly, here’s the gist: publicly funded science data should be in the public domain, full stop.

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and this

BBC News – Science damaged by climate row says NAS chief Cicerone
[Via BBC News | Science/Nature]

Leading scientists say that the recent controversies surrounding climate research have damaged the image of science as a whole.

President of the US National Academy of Sciences, Ralph Cicerone, said scandals including the “climategate” e-mail row had eroded public trust in scientists.

[snip]

He said that this crisis of public confidence should be a wake-up call for researchers, and that the world had now “entered an era in which people expected more transparency”.

“People expect us to do things more in the public light and we just have to get used to that,” he said. “Just as science itself improves and self-corrects, I think our processes have to improve and self-correct.”

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It is important for Federally funded research to be in the public domain. But, Universities, who hope to license the results of this research, and corporations, who will not as likely commercialize a product if they can not lock up the IP, Both of these considerations must be accounted for if we want to translate basic research into therapies or products for people.

So, as the Principles seem to indicate, most of this open data should happen AFTER publication, so this would give the proper organizations to make sure they have any IP issues dealt with.

But what about unpublished data? What about old lab notebooks? The problem supposedly seen now has nothing to do with data that was published. It has to do with emails between scientists. Is this relevant data that should be made public for any government funded research?

Who determines which data are relevant or not?

And what about a researcher’s time? More time in front of the public, more time filling out FOIs, more time not doing research in the first place.

The scientific world is headed this way but how will researcher’s adjust? There will have to be much better training of effectively communicating science to a much wider audience than most scientists are now comfortable with.


Filters lead us to wisdom

filters by aslakr
[2b2k] Clay Shirky, info overload, and when filters increase the size of what’s filtered
[Via Joho the Blog]

Clay Shirky’s masterful talk at the Web 2.0 Expo in NYC last September — “It’s not information overload. It’s filter failure” — makes crucial points and makes them beautifully. [Clay explains in greater detail in this two part CJR interview: 1 2]

So I’ve been writing about information overload in the context of our traditional strategy for knowing. Clay traces information overload to the 15th century, but others have taken it back earlier than that, and there’s even a quotation from Seneca (4 BCE) that can be pressed into service: “What is the point of having countless books and libraries whose titles the owner could scarcely read through in his whole lifetime? That mass of books burdens the student without instructing…” I’m sure Clay would agree that if we take “information overload” as meaning the sense that there’s too much for any one individual to know, we can push the date back even further.

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David Weinberger has been one of my touchstones ever since I read The Cluetrain Manifesto. I cried when I read that book because it so simply rendered what I had achingly been trying to conceptualize.

Dealing with information glut today leverages an old way of doing things in a new way. It uses synthesis rather than analysis. Analysis gave us the industrial revolution. Breaking the complex down into small understandable bits allowed us to create the assembly line that could put together our greatest creations, such as the Space Shuttle, with more than 2.5 million parts.

Yet a single O-ring can destroy the whole thing.

Synthesis brings together facts, allows us to see them in new ways. But to attack the really complex problems of today, we need to utilize synthesis from a wide range of viewpoints, all providing their own filter. As with the story of the 5 blind men and the elephant, no one person has all the information. But a synthesis of everyone’s information provides a reasonable approximation.

David discusses this view:

A traditional filter in its strongest sense removes materials: It filters out the penny dreadful novels so that they don’t make it onto the shelves of your local library, or it filters out the crazy letters written in crayon so they don’t make it into your local newspaper. Filtering now does not remove materials. Everything is still a few clicks away. The new filtering reduces the number of clicks for some pages, while leaving everything else the same number of clicks away. Granted, that is an overly-optimistic way of putting it: Being the millionth result listed by a Google search makes it many millions of times harder to find that page than the ones that make it onto Google’s front page. Nevertheless, it’s still much much easier to access that millionth-listed page than it is to access a book that didn’t make it through the publishing system’s editorial filters.

It is through synthesis that new technologies allow us to deal with information glut. And this synthesis necessarily involves human social networks. Because humans are exquisitely positioned to filter out noise and find the signal.

I’ve discussed the DIKW model. Data simply exists. Information happens when humans interact with the data. Transformation of information, both tacit and explicit, produces knowledge, which is the ability to make a decision, to take an action. Often that action is to start the cycle again, generating more data and so on.

This can be quite analytical in approach as we try to understand something. But the final link in the cycle, wisdom, is the ability to make the RIGHT decision. This necessarily require synthesis.

New technologies allow us to deal with much more data than before, generate more information and produce more knowledge. However, without synthetic approaches that bring together a wide range of human knowledge, we will not gain the wisdom we need.

Luckily, the same technologies that produce so much data also provide us with the tools to leverage our interaction with knowledge. If we create useful social structures, ones that properly synthesize the knowledge, that employ human social networks that act as great filters, then we can more rapidly compete the DIKW cycle and take the correct actions.




Information into action

Online Activism: The Movie – Ten Tactics for Info Activism
[Via Beth’s Blog: How Nonprofits Can Use Social Media]

Activists around the world are using social media tools to make change. A new 50- minute documentary film called “10 Tactics for Turning Information into Action” is a guide to how best to use take advantage of the power of these tools and avoid hidden dangers. The site and film include inspiring info-activism stories from around the world, a set of cards with tool tips and advice. The project comes from Tactical Technology, inspired their info-activism camp in India.

The film is being shown in 35 countries, showcasing the experiences of 25 human rights advocates from around the globe who have masterfully incorporated tools like Twitter and Facebook to take on governments and corporations.   The film also covers the security and privacy issues faced by human rights activists.

[More]

In today’s world, the huge amount of information makes it impossible for one or a few people to quickly examine a complex situation and begin to formulate a successful response. It requires a knowledge of social interactions as well as an appreciation for systems thinking.

These ten tactics fit right in the sweet spot of systems approaches and social interactions. There ned to be good facts and information. There need to be great stories and an understanding of policy. Here are the ten (there are more but ten is such a great number):

The Ten Tactics

1. Mobilise People

2. Witness and Record

3. Visualise Your Message

4. Amplify Personal Stories

5. Just Add Humour

6. Investigate and Expose

7. How to Use Complex Data

8. Use Collective Intelligence

9. Let People Ask the Questions

10. Manage Your Contacts

These tactics can be incorporated into several strategies for systems thinking to produce some powerful solutions to complex problems.

My model is the bacterium. It does not know where a food source is, yet moves quite rapidly towards it. Bacteria, such as E. coil, have no eyes or nose. How does it find the sugar, or other nutrient it needs? It is called chemotaxis and is actually a very simple solution to a complex problem.

E. coli has a few flagella to propel itself. When they all rotate counter-clockwise, they work together and move the bacterium forward. This is called swimming. When they rotate clockwise, the bundle of flagella breaks apart and the bacterium rotates in a random fashion called tumbling. Here is an example:

The combination of these two behaviors allows the bacterium to move towards a food source. As long as the concentration of the attractant is increasing the bacterium swims. If it gets off track, and the concentration begins declining, it tumbles, eventually picking a new, random direction to swim. No attractant, more tumbling. More attractant, swimming.

This actually results in a very efficient method to move to, or away, from things.

When the bacterium fails to successfully follow the correct path, it makes corrections to see if a better path arises. If these corrections fail, more tumbling until it succeeds. It has a process for dealing with failure that inevitably leads to success.

Same with systems approaches. Intermediate evaluations, rapid failure, path to success. Incorporate the ten tactics into these strategies and you are well on your way.


More than a change in latitude. A change in afftitude

margaritaville by Ed Bierman
We cannot problem solve our way into fundamental change, or transformation
[Via Gurteen Knowledge-Log]

By David Gurteen

Whenever I run my Knowledge Cafe Masterclasses, a few people always have a serious problem with the fact that when run in its “pure form” there are no tangible outcomes of a Knowledge Cafe.

There are plenty of intangible ones, such as a better understanding of the issue, a better understanding of ones own views, a better understanding of others perspectives, improved relationships and genuine engagement and motivation to pursue the subject but no outcomes in the form of a decision or a consensus or a to-do list.

I and many others don’t have a problem with this — the intangibles are worthy outcomes. And then I recently came across this quote from Peter Block in an online booklet of his entited Civic Engagement and theRestoration of Community: Changing the Nature of the Conversation

My belief is that the way we create conversations that overcome the fragmented nature of our communities is what creates an alternative future.

This can be a difficult stance to take for we have a deeply held belief that the way to make a difference in the world is to define problems and needs and then recommend actions to solve those needs.

We are all problem solvers, action oriented and results minded. It is illegal in this culture to leave a meeting without a to-do list.

We want measurable outcomes and we want them now.

What is hard to grasp is that it is this very mindset which prevents anything fundamental from changing.

We cannot problem solve our way into fundamental change, or transformation.

This is not an argument against problem solving; it is an intention to shift the context and language within which problem solving takes place.

Authentic transformation is about a shift in context and a shift in language and conversation. It is about changing our idea of what constitutes action.

So another intangible I should add to my list: “a shift in context and in language and conversation that changes our idea of what constitutes action.”

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I do not usually include an entire post but this one has so many important points. There are intangible benefits when these changes are made that may eventually lead to tangible benefits. But, most likely, those benefits will be a series of actions that would be wildly different than expected.

This is the paradox of a paradigm shift. People on either side live in completely different contextual worlds and are completely unable to explain their worldview to the other. One example – mimeograph machines. This used to be the only inexpensive way that multiple copies of a test could be produced for schools. There was an entire process developed for creating the stencils for the test, etc. It resulted in a ‘wax’ copy of the test that was used to print off the copies. With the appearance of copiers, the mimeograph disappeared from regular use. Now most young people have no idea of what a mimeograph is.

Thus when they watch National Lampoon’s Animal House, they just do not understand the whole scene with the two characters rifling through the trash bin to find the stencil. They have no personal knowledge of what a stencil is or why having one would be useful for cheating on a test.

Transformation presents a similar division between what was and what is. But those organizations that can effectively learn how to move information around more effectively, who can harness human social networks in order to solve complex problems, will be more successful.

They may just have a hard time explaining it to those organizations still on the other side.