Competing in a digital world: Four lessons from the software industry | McKinsey & Company

http://www.mckinsey.com/insights/business_technology/competing_in_a_digital_world_four_lessons_from_the_software_industry

Competing in a digital world: Four lessons from the software industry

About 20 years ago, software’s use within organizations was largely confined to big transactional systems in the data center. Now, it underpins nearly every function in every industry. Software spending has grown accordingly, jumping from 32 percent of total corporate IT investment in 1990 to almost 60 percent in 2011.1

The allure is plain. On the front end, software-enhanced products and services can lead to entirely new offerings—for example, turning an ordinary running shoe into one that also tracks your mileage. And as the surge in social technologies shows, software permits a host of new marketing and communications channels that consumers have been quick to embrace. The back-end benefits are equally compelling. Greater automation, integration, and standardization can lower cost and boost performance significantly, while social enterprise tools can facilitate collaboration and provide greater agility.

The strategic as well as operational challenge is that software is not static. Many have come to think of it like electricity—something that can be wired in and mostly forgotten about.2 But software and the processes and applications it touches are, in fact, constantly changing.

That reality introduces new competitive dynamics. Managers have to worry about competitors leapfrogging them with ever-faster cycle times, courtesy of such software-enabled techniques as rapid prototyping and real-time testing. They must also be mindful of network effects, since customers can become accustomed to working with a certain platform and be slow to switch. That can be good news for incumbents but a major barrier for those trying to break into a certain category. Another challenge is that an organization may be swimming in data but exploiting only a fraction of available information.

To effectively respond to these new dynamics, companies must begin thinking about ways to broaden their ecosystems and revenue streams while becoming more responsive and agile. These are issues that software providers have been addressing for a number of years. Given the increasing importance of software for almost every company’s performance, executives in all industries should consider how software may fundamentally change their businesses. Managers would do well to study leading software-industry players and discuss a set of questions to understand whether and how they can learn from the business and operating models that these companies employ. The answers will vary for different industries and companies, but we believe the exercise is a useful step toward making the most of large and rising software investments. (For more on a new management model already being adopted by executives, see sidebar “The right role for IT.”)

1. Moving from products to platforms

Success in the software industry has long been influenced, and often driven, by the ecosystem of developers, plug-ins, software-development kits and application-programming interfaces (APIs),3 and add-ons that drive added value and increase stickiness for products. Similarly, companies in other industries need to think expansively and include upstream suppliers as well as downstream vendors or consumers, and focus on how each part of the value chain integrates into the new platform. Many companies still stick to the business models of the past, where product development is almost exclusively an in-house activity and kept under strict control. But some, like consumer-goods giant P&G, have flung their doors open to include a wide range of partners in developing and tailoring the next big thing. Instead of “not invented here,” the mind-set is shifting to “proudly found elsewhere.” P&G, for instance, launched a “connect and develop” platform that has secured more than 1,000 partner agreements on innovation.

By opening innovation processes to outside voices, organizations not only gain a broader range of perspectives to enrich the innovation gene pool, they also gain valuable scale—more resources at a fraction of the price. And it’s not just the front end that stands to gain: greater connectivity with suppliers and buyers can be a win-win situation when it comes to managing inventory, budgeting and forecasting, allowing organizations to access better—and more—real-time data, and refining production and supply-chain processes on the spot. In a McKinsey Quarterly interview,4 Bob McDonald, P&G’s CEO, said his organization looks to increase integration with retail partners because “getting the data becomes part of the currency of the relationship.” In some cases, P&G is even using its scale “to bring state-of-the-art technology to retailers that otherwise can’t afford it.”

Question:What new opportunities are unlocked if we move from products to platforms?

  • What is our industry equivalent of an API that will encourage involvement and increased interaction across the ecosystem (including suppliers, partners, vendors, and users)?
  • How can we align the different parts of the ecosystem to adopt more points of integration?
  • Of the new value that is created with this integration, how are the gains shared across members of the ecosystem? What are the critical control points that we must own to protect our position and maximize rents?
  • How can we create a cadre of evangelists (internally and externally) to encourage the adoption of our platform?

2. Accelerating revenue by creating new business models

Software and Internet companies have developed multiple avenues to generate revenue, going beyond a simple licensing model. Companies like LinkedIn and Skype have thrived using the “freemium” model. Both cultivated a large base of users with their basic, no-cost platform, and then introduced several paid-for options, ranging from recruiting services and tiered access and networking privileges in the case of LinkedIn and landline calling in the case of Skype. They were able to tap an audience that was loyal to their brand to boost revenues. Other revenue models include using as-a-service and consumption-based pricing5 and creating new integrated services.

Innovative companies in other industries are experimenting with ways to combine products, services, and data to create entirely new businesses—often with software playing a critical role in knitting together or enabling these new models. Industries from manufacturing to consumer goods have stitched information assets into their traditional product offerings and have come away redefining the category and raising the bar for competitors. Nike took this approach with one of its shoe lines. It created Nike+, a sensor compatible with Apple iOS devices (for instance, the iPod or iPhone), to be used with its running shoes. The sensor allows the wearer to track mileage and running habits and upload data onto a Web site to manage workouts, connect with fellow runners, and share routes. The line not only launched a profitable new revenue stream but also helped boost Nike’s market share and created a community of highly engaged users.

In addition to creating new revenue streams by amping up traditional product and service offerings, organizations have been mining “exhaust data”—information that is a by-product of normal business operations—for use in developing new products. Such by-products, for instance, allow credit-card companies to monetize transactional data from cardholders by analyzing and selling these data to merchants. Similarly, Intuit is beginning to use data amassed from its QuickBooks software to provide new benchmarking and reporting services for small businesses.

Question:What business model could we borrow from the software industry to accelerate adoption?

  • How do we trade off one-time revenues (for example, a license fee or outright sale) to capture recurring subscription revenues?
  • What is the real lifetime value of our customers, and how does this change our approach to setting prices?
  • Are our internal systems able to handle these shifts? Are incentives in our organization (especially in the sales force and channels) in place to make the right trade-off?
  • What are the ancillary assets our company has (for example, brands or data), and how could we deploy them without harming our core business?

3. Accelerating cycle time and cocreating with customers

Empowered by constant connectivity, the rise of social networks, and an increasing amount of software in products, companies are seeing new options in the way they interact with customers and develop and release products. They are speeding up cycle times and shortening learning curves by testing new products or ideas with consumers using mockups, computer-generated virtual products, and simulations.

The software world was one of the first to roll out new products before all the planned features and capabilities were built. It started with a basic model, or minimum viable product,6 that customers could upgrade over the life of the product with just a few clicks. New features were introduced when ready rather than stalling the base product launch. This allowed companies to get to market faster, enable new features (or fix bugs), and improve their ability to respond to competitors’ changes. Apple launched its first iPhone, for instance, without an app store or the ability to add new applications. It added those features in a software update one year later.

Other industries are learning from this example. Many digital cameras, for instance, can receive firmware upgrades to fix bugs or enable new capabilities. But this is not just a phenomenon for digital gadgets. In early 2012, Ford released an upgrade for its Sync communications and entertainment system7 by mailing USB keys to customers eligible for an upgrade. No dealer visit is required.

Crowdsourcing is an example of cocreation: companies use social tools to engage customers or partners in solving problems, which reinforces engagement and a sense of community in the process. For instance, Coca-Cola used crowdsourcing to develop new designs for bottle crates in Germany and marketing ideas for Coke Zero in Singapore. GE has crowdsourced green business ideas under its “eco-magination” challenge. This engagement model has even been flipped, with companies like Kickstarter providing a platform for entrepreneurs to presell product ideas as a way to solicit funding based on early prototypes or ideas.

Question:What is the right way for us to engage with and learn from our customers?

  • How can we embed test-and-learn and rapid-iteration principles in our product-development process? Where else can these principles be used in our company?
  • Should we establish a beta program with consumers? How else can we collaborate with them?
  • What is too soon to ship? And how tolerant of potentially incomplete or buggy products will our customers be?
  • What cultural changes are needed in our organization to encourage it not only to listen to customers but also to give them control?
  • How much product control are we willing to give up?

4. Creating an agile organization

The three lessons above involve accelerating the clock speed of the enterprise and thinking differently about the structures across the business or boundaries with customers or users. Adopting these behaviors will require a more agile and flexible organization.

Software creation is inherently team based; as a result, the vast majority of software companies have built teamwork into their ethos. Teams assemble and reassemble based on specific projects, often resulting in flatter organizations than may be seen in other industries. To the uninitiated (and sometimes even to those in the industry), this way of working feels like barely controlled chaos. Companies that do this well depend on core organizational elements, including increased transparency, a laser-like focus on aligning culture and mind-set, and clearly defined, common goals.

In the past decade, many software organizations have built on these elements and further increased their productivity by using agile programming techniques—where teams run in sprints of two to three weeks to develop a workable prototype or new functionality. It is very different from the traditional planning and budgeting model used by many organizations. IT shops are beginning to employ agile methodologies, but often their counterparts across the business still operate with traditional models. This causes friction and slows down the process. In the future, though, it’s clear that accelerated cycles, increased transparency, and teaming outside the typical organizational boundaries (both within and outside the company) will have great impact on how executives organize and manage their teams. There are already tools ready for this challenge. Rypple, for example, is a software platform that allows companies to take a new approach to HR management and performance evaluations by using ongoing feedback, more public recognition, and social goals such as more dynamic team or individual objectives that change or evolve organically rather than through an annual top-down process.

IT and business have tended to operate as separate functions in many organizations, making it harder for those groomed in one discipline to cross over to the other. The software shift described in this article has the potential to force greater fusion in executive capabilities. In more traditional companies, IT employees will need to become business managers, while product-development and business unit leaders will need to become software savvy. A base level of software fluency will be a requirement for all levels, including upper management, in order to understand not only the core technologies but also the dynamics of working in a quick-turn, massively more connected, and digitized marketplace, in which economic value is driven increasingly by information-based services.

Question:What new organization models can we adopt from software to support a more agile, flexible business?

  • How do we create flatter and more fluid organizations?
  • How must we change our organizational processes to account for increased collaboration, transparency, and new behaviors within teams?
  • Organizationally, how should we prepare for more porous company boundaries and increased partnering or sourcing across the value chain from R&D to delivery?
  • What is the best way to incorporate new behaviors (like an increased tolerance for failure) into our corporate culture?

Almost every company is becoming a software company. By considering business and operating models pioneered by the software industry and tailoring them to their own needs, organizations can lower their costs, boost performance, and turn software into a competitive advantage.

For additional thinking, please see the following articles:

David Kirkpatrick, “Now every company is a software company,” forbes.com, November 30, 2011.

Marc Andreessen, “Why software is eating the world,” Wall Street Journal, August 20, 2011.

About the authors

Hugo Sarrazin is a director in McKinsey’s Silicon Valley office and Johnson Sikes is a consultant in the New York office.

11 Simple Concepts to Become a Better Leader

http://www.linkedin.com/today/post/article/20130128162711-15077789-11-simple-concepts-to-become-a-better-leader?trk=eml-mktg-inf-m-top13-0828-p1

11 Simple Concepts to Become a Better Leader

Being likeable will help you in your job, business, relationships, and life. I interviewed dozens of successful business leaders for my last book, to determine what made them so likeable and their companies so successful. All of the concepts are simple, and yet, perhaps in the name of revenues or the bottom line, we often lose sight of the simple things – things that not only make us human, but can actually help us become more successful. Below are the eleven most important principles to integrate to become a better leader:

1. Listening

«When people talk, listen completely. Most people never listen.» – Ernest Hemingway

Listening is the foundation of any good relationship. Great leaders listen to what their customers and prospects want and need, and they listen to the challenges those customers face. They listen to colleagues and are open to new ideas. They listen to shareholders, investors, and competitors. Here’s why the best CEO’s listen more.

2. Storytelling

«Storytelling is the most powerful way to put ideas into the world today.» -Robert McAfee Brown

After listening, leaders need to tell great stories in order to sell their products, but more important, in order to sell their ideas. Storytelling is what captivates people and drives them to take action. Whether you’re telling a story to one prospect over lunch, a boardroom full of people, or thousands of people through an online video – storytelling wins customers.

3. Authenticity

«I had no idea that being your authentic self could make me as rich as I’ve become. If I had, I’d have done it a lot earlier.» -Oprah Winfrey

Great leaders are who they say they are, and they have integrity beyond compare. Vulnerability and humility are hallmarks of the authentic leader and create a positive, attractive energy. Customers, employees, and media all want to help an authentic person to succeed. There used to be a divide between one’s public self and private self, but the social internet has blurred that line. Tomorrow’s leaders are transparent about who they are online, merging their personal and professional lives together.

4. Transparency

«As a small businessperson, you have no greater leverage than the truth.» -John Whittier

There is nowhere to hide anymore, and businesspeople who attempt to keep secrets will eventually be exposed. Openness and honesty lead to happier staff and customers and colleagues. More important, transparency makes it a lot easier to sleep at night – unworried about what you said to whom, a happier leader is a more productive one.

5. Team Playing

«Individuals play the game, but teams beat the odds.» -SEAL Team Saying

No matter how small your organization, you interact with others every day. Letting others shine, encouraging innovative ideas, practicing humility, and following other rules for working in teams will help you become a more likeable leader. You’ll need a culture of success within your organization, one that includes out-of-the-box thinking.

6. Responsiveness

«Life is 10% what happens to you and 90% how you react to it.» -Charles Swindoll

The best leaders are responsive to their customers, staff, investors, and prospects. Every stakeholder today is a potential viral sparkplug, for better or for worse, and the winning leader is one who recognizes this and insists upon a culture of responsiveness. Whether the communication is email, voice mail, a note or a tweet, responding shows you care and gives your customers and colleagues a say, allowing them to make a positive impact on the organization.

7. Adaptability

«When you’re finished changing, you’re finished.» -Ben Franklin

There has never been a faster-changing marketplace than the one we live in today. Leaders must be flexible in managing changing opportunities and challenges and nimble enough to pivot at the right moment. Stubbornness is no longer desirable to most organizations. Instead, humility and the willingness to adapt mark a great leader.

8. Passion

«The only way to do great work is to love the work you do.» -Steve Jobs

Those who love what they do don’t have to work a day in their lives. People who are able to bring passion to their business have a remarkable advantage, as that passion is contagious to customers and colleagues alike. Finding and increasing your passion will absolutely affect your bottom line.

9. Surprise and Delight

«A true leader always keeps an element of surprise up his sleeve, which others cannot grasp but which keeps his public excited and breathless.» -Charles de Gaulle

Most people like surprises in their day-to-day lives. Likeable leaders underpromise and overdeliver, assuring that customers and staff are surprised in a positive way. There are a plethora of ways to surprise without spending extra money – a smile, We all like to be delighted — surprise and delight create incredible word-of-mouth marketing opportunities.

10. Simplicity

«Less isn’t more; just enough is more.» -Milton Glaser

The world is more complex than ever before, and yet what customers often respond to best is simplicity — in design, form, and function. Taking complex projects, challenges, and ideas and distilling them to their simplest components allows customers, staff, and other stakeholders to better understand and buy into your vision. We humans all crave simplicity, and so today’s leader must be focused and deliver simplicity.

11. Gratefulness

«I would maintain that thanks are the highest form of thought, and that gratitude is happiness doubled by wonder.» -Gilbert Chesterton

Likeable leaders are ever grateful for the people who contribute to their opportunities and success. Being appreciative and saying thank you to mentors, customers, colleagues, and other stakeholders keeps leaders humble, appreciated, and well received. It also makes you feel great! Donor’s Choose studied the value of a hand-written thank-you note, and actually found donors were 38% more likely to give a 2nd time if they got a hand-written note!

The Golden Rule: Above all else, treat others as you’d like to be treated

By showing others the same courtesy you expect from them, you will gain more respect from coworkers, customers, and business partners. Holding others in high regard demonstrates your company’s likeability and motivates others to work with you. This seems so simple, as do so many of these principles — and yet many people, too concerned with making money or getting by, fail to truly adopt these key concepts.

8 Famous Quotes to Help You Embrace Fear and Achieve Success

http://www.linkedin.com/today/post/article/20130827143745-10667678-words-of-wisdom-8-famous-quotes-to-help-you-embrace-fear-and-achieve-success

“Develop success from failures. Discouragement and failure are two of the surest stepping stones to success.” – Dale Carnegie «There are only two ways to live life. One is as though nothing is a miracle. The other is as though everything is.» – Albert Einstein «Do not look for approval except for the consciousness of doing your best.» – Andrew Carnegie «The true measure of a person is how they treat someone who can do him absolutely no good.» – Samuel Johnson «You’ve got to be very careful if you don’t know where you are going because you might not get there.» – Yogi Berra “Expect more than others think possible.” – Howard Schultz «If people aren’t calling you crazy, you aren’t thinking big enough.» – Richard Branson “Never, never, never give up.” – Winston Churchill

The 7 Questions A Startup Should Answer in their Fund Raising Pitch

The 7 Questions A Startup Should Answer in their Fund Raising Pitch

http://tomtunguz.com/pitch-deck

  1. [Value prop] What is the problem and is it worth solving? Why is now the right time to solve it?
  2. [Team] Does the team have the vision and the wherewithal to build this company?
  3. [Go to market] What is the competitive angle (competitive barrier to entry and/or go-to-market) that will enable this company to succeed where others have tried and failed?
  4. [Sales effectiveness & product validation] Who does the startup sell to? Which customers have used the product and how have they received it? How much is each customer worth?
  5. [Product distribution] How does the company acquire customers cost effectively? What are the unit economics (customer acquisition cost, contribution revenue, and churn rates)?
  6. [Revenue model] Does the company have the revenue model to build a big (>$100M annual revenue) business with good margins (gross ~ 50 to 60% / net ~15 to 25%) under reasonable assumptions?
  7. [Market size] Can the market enable or bear a $100M revenue Alternatively, is this product in a quickly growing market or riding a disruptive wave?

Beware the Sirens of Management Pseudo-Science

Beware the Sirens of Management Pseudo-Science
http://blogs.hbr.org/cs/2013/08/beware_the_sirens_of_managemen.html

favicons?domain=blogs.hbr.org HARVARD BUSINESS REVIEW2 Days Ago

Beware the Sirens of Management Pseudo-Science

by Freek Vermeulen 9:00 AM August 23, 2013

Management is not an exact science, they say. And I guess most things that involve the study of human behavior cannot be. But I sometimes wonder if that is the reason — or the excuse — that the business sections at airport bookshops are so full of nonsense.

Quite often these books are written with panache. And the authors — aspiring «management thinkers» and «gurus» (never scientists) — have an excellent sense of the pulse of the business public. They are neither crooks nor charlatans; they write what they believe. But that doesn’t make their beliefs right. People can believe vigorously in voodooism, homeopathy, and creationism.

A common formula to create a best-selling business book is to start with a list of eye-catching companies that have been outperforming their peers for years. This has the added advantage of creating an aura of objectivity because the list is constructed using «objective, quantitative data.» Subsequently, the management thinker takes the list of superior companies and examines (usually in a rather less objective way) what these companies have in common. Surely — is the assumption and foregone conclusion — what these companies have in common must be a good thing, so let’s write a book about that and become rich.

In Search of Excellence and Built to Last, to name a few classic examples, followed that formula — including the getting rich bit. One piece of advice to come out of such tomes, for instance, has been to create a strong, coherent organizational culture, like most of high-performing firms studied. However, we now know from academic research that a strong culture is often the result of a period of high performance, rather than its cause. In fact, a very coherent culture can even be a precursor of what is called a competency trap, where firms get stuck in their old beliefs and ways of doing things. Not coincidentally, the list of superior companies frequently starts unravelling when the book is still at the printer’s.

Another formula is to introduce a new and fashionable management practice, such as Six Sigma, Lean, or the ancient Total Quality Management and ISO9000. The book not only describes the practice but also introduces us to the success stories of early adopters, in the form of awe-inspiring interviews and case studies.

However, nowadays, we know from academic research on such practices that in the long run they usually do not create any value, that early adopters are motivated to exaggerate their benefits, that they can stifle long-term innovationand that in the process of popularizing the practice, the original version (which might have worked for the company that developed it) becomes distorted, oversimplified, or just plain ineffectual. Most of them go out of fashion after a while, and some years later get smirkingly referred to as a fad.

But the books continue to sell, new lists of excellent companies emerge, and fads resurface. And that is perhaps no wonder, because it is only human to be susceptible to the beguiling songs of Sirens that bear the promise of prosperous times. But sometimes it makes sense to do what Odysseus instructed his men to do, when the Sirens were in sight: plug your ears with beeswax and just sail past.

Where Consciousness Comes From

Where Consciousness Comes From
http://www.gizmodo.com.au/2013/08/how-the-light-gets-out-solving-the-problem-of-consciousness/

Scientific talks can get a little dry, so I try to mix it up. I take out my giant hairy orangutan puppet, do some ventriloquism and quickly become entangled in an argument. I’ll be explaining my theory about how the brain — a biological machine — generates consciousness. Kevin, the orangutan, starts heckling me. ‘Yeah, well, I don’t have a brain. But I’m still conscious. What does that do to your theory?’

Lately, the problem of consciousness has begun to catch on in neuroscience. How does a brain generate consciousness? In the computer age, it is not hard to imagine how a computing machine might construct, store and spit out the information that ‘I am alive, I am a person, I have memories, the wind is cold, the grass is green,’ and so on. But how does a brain become aware of those propositions? The philosopher David Chalmers has claimed that the first question, how a brain computes information about itself and the surrounding world, is the ‘easy’ problem of consciousness. The second question, how a brain becomes aware of all that computed stuff, is the ‘hard’ problem.

In my laboratory at Princeton University, we are working on a specific theory of awareness and its basis in the brain. Our theory explains both the apparent awareness that we can attribute to Kevin and the direct, first-person perspective that we have on our own experience. And the easiest way to introduce it is to travel about half a billion years back in time.

In a period of rapid evolutionary expansion called the Cambrian Explosion, animal nervous systems acquired the ability to boost the most urgent incoming signals. Too much information comes in from the outside world to process it all equally, and it is useful to select the most salient data for deeper processing. Even insects and crustaceans have a basic version of this ability to focus on certain signals. Over time, though, it came under a more sophisticated kind of control — what is now called attention. Attention is a data-handling method, the brain’s way of rationing its processing resources. It has been found and studied in a lot of different animals. Mammals and birds both have it, and they diverged from a common ancestor about 350 million years ago, so attention is probably at least that old.

Attention requires control. In the modern study of robotics there is something called control theory, and it teaches us that, if a machine such as a brain is to control something, it helps to have an internal model of that thing. Think of a military general with his model armies arrayed on a map: they provide a simple but useful representation — not always perfectly accurate, but close enough to help formulate strategy. Likewise, to control its own state of attention, the brain needs a constantly updated simulation or model of that state. Like the general’s toy armies, the model will be schematic and short on detail. The brain will attribute a property to itself and that property will be a simplified proxy for attention. What exactly is that property? When it is paying attention to thing X, we know that the brain usually attributes an experience of X to itself — the property of being conscious, or aware,of something. Why? Because that attribution helps to keep track of the ever-changing focus of attention.

I call this the ‘attention schema theory’. It has a very simple idea at its heart: that consciousness is a schematic model of one’s state of attention. Early in evolution, perhaps hundreds of millions of years ago, brains evolved a specific set of computations to construct that model. At that point, ‘I am aware of X’ entered their repertoire of possible computations.

One way to think about the relationship between brain and consciousness is to break it down into two mysteries. I call them Arrow A and Arrow B. Arrow A is the mysterious route from neurons to consciousness. If I am looking at a blue sky, my brain doesn’t merely register blue as if I were a wavelength detector from Radio Shack. I am aware of the blue. Did my neurons create that feeling?

Arrow B is the mysterious route from consciousness back to the neurons. Arrow B attracts much less scholarly attention than Arrow A, but it is just as important. The most basic, measurable, quantifiable truth about consciousness is that we can conclude that we have it, couch that conclusion into language and then report it to someone else. Speech is controlled by muscles, which are controlled by neurons. Whatever consciousness is, it must have a specific, physical effect on neurons, or else we wouldn’t be able to communicate anything about it. Consciousness cannot be what is sometimes called an epiphenomenon — a floating side-product with no physical consequences — or else I wouldn’t have been able to write this article about it.

Any workable theory of consciousness must be able to account for both Arrow A and Arrow B. Most accounts, however, fail miserably at both. Suppose that consciousness is a non-physical feeling, an aura, an inner essence that arises somehow from a brain or from a special circuit in the brain. The ‘emergent consciousness’ theory is the most common assumption in the literature. But how does a brain produce the emergent, non-physical essence? And even more puzzling, once you have that essence, how can it physically alter the behaviour of neurons, such that you can say that you have it? ‘Emergent consciousness’ theories generally stake everything on Arrow A and ignore Arrow B completely.

The attention schema theory can handle both Arrow A and Arrow B. Consciousness isn’t a non-physical feeling that emerges. Instead, dedicated systems in the brain compute information. Cognitive machinery can access that information, formulate it as speech, and then report it. When a brain reports that it is conscious, it is reporting specific information computed within it. In short, Arrow A and Arrow B remain squarely in the domain of signal-processing. There is no need for anything to be transmuted into ghost material, thought about, and then transmuted back to the world of cause and effect.

What are out-of-body experiences then? One view might be that no such things exist, that charlatans invented them to fool us. Yet such experiences can be induced in the lab, as a number of scientists have now shown. The very existence of the out-of-body experience suggests that awareness is a computation and that the computation can be disrupted. Systems in the brain not only compute the information that I am aware, but also compute a spatial framework for it, a location, and a perspective. Screw up the computations, and I screw up my understanding of my own awareness.

Let’s turn now to a final — alleged — myth. One of the long-standing questions about consciousness is whether it really does anything. Is it merely an epiphenomenon, floating uselessly in our heads like the heat that rises up from the circuitry of a computer? Most of us intuitively understand it to be an active thing: it helps us to decide what to do and when. And yet, at least some of the scientific work on consciousness has proposed the opposite, counter-intuitive view: that it doesn’t really do anything at all; that it is the brain’s after-the-fact story to explain itself. We act reflexively and then make up a rationalisation.

This idea that consciousness has no leverage in the world, that it’s just a rationalisation to make us feel better about ourselves, is terribly bleak. Some people might confuse the attention schema theory with that nihilistic view. But the theory is almost exactly the opposite. It is not a theory about the uselessness or non-being of consciousness, but about its central importance. Why did an awareness of stuff evolve in the first place? Because it had a practical benefit. The function of awareness is to model one’s own attentional focus and control one’s behaviour. In this respect, the attention schema theory is in agreement with the common intuition: consciousness plays an active role in guiding our behaviour. It is not merely an aura that floats uselessly in our heads. It is a part of the executive control system.

And so, whether or not the attention schema theory turns out to be the correct scientific formulation, a successful account of consciousness will have to tell us more than how brains become aware. It will also have to show us how awareness changes us, shapes our behaviour, interconnects us, and makes us human.

This article has been excerpted with permission from Aeon Magazine. To read in its entirety, head here.

21 Suggestions for Success

21 Suggestions for Success
http://www.lifehack.org/articles/communication/21-suggestions-for-success.html

by Jill Harness

H. Jackson Brown, Jr. is an American author who has written over 30 books. Perhaps his best known work remains his 21 suggestions for success, which focuses not on monetary goals, but true happiness and contentment.

This attractive infographic version makes his suggestions for success easy to access -just print it out and hang it by your desk so you can always remember Mr. Brown’s advice whenever you need a little motivation.

While we love all of the suggestions on the list, a few of our favorite suggestions for success include:

  • Marry the right person. This one decision will determine 90% of your happiness or misery.
  • Give people more than they expect and do it cheerfully.
  • Be generous.
  • Commit yourself to constant improvement.
  • Stop blaming others. Take responsibility for every area of your life.
  • Take good care of those you love.

60940595347840448550-read.jpeg

Schneier on the Death of Privacy: «The simple answer is to blame consumers… But that argument delibe rately ignores the reality of today’s world».

The Public/Private Surveillance Partnership

Imagine the government passed a law requiring all citizens to carry a tracking device. Such a law would immediately be found unconstitutional. Yet we all carry mobile phones.

If the National Security Agency required us to notify it whenever we made a new friend, the nation would rebel. Yet we notify Facebook. If the Federal Bureau of Investigation demanded copies of all our conversations and correspondence, it would be laughed at. Yet we provide copies of our e-mail to Google, Microsoft or whoever our mail host is; we provide copies of our text messages to Verizon, AT&T and Sprint; and we provide copies of other conversations to Twitter, Facebook, LinkedIn, or whatever other site is hosting them.

The primary business model of the Internet is built on mass surveillance, and our government’s intelligence-gathering agencies have become addicted to that data. Understanding how we got here is critical to understanding how we undo the damage.

Computers and networks inherently produce data, and our constant interactions with them allow corporations to collect an enormous amount of intensely personal data about us as we go about our daily lives. Sometimes we produce this data inadvertently simply by using our phones, credit cards, computers and other devices. Sometimes we give corporations this data directly on Google, Facebook, Apple Inc.’s iCloud and so on in exchange for whatever free or cheap service we receive from the Internet in return.

The NSA is also in the business of spying on everyone, and it has realized it’s far easier to collect all the data from these corporations rather than from us directly. In some cases, the NSA asks for this data nicely. In other cases, it makes use of subtle threats or overt pressure. If that doesn’t work, it uses tools like national security letters.

The result is a corporate-government surveillance partnership, one that allows both the government and corporations to get away with things they couldn’t otherwise.

There are two types of laws in the U.S., each designed to constrain a different type of power: constitutional law, which places limitations on government, and regulatory law, which constrains corporations. Historically, these two areas have largely remained separate, but today each group has learned how to use the other’s laws to bypass their own restrictions. The government uses corporations to get around its limits, and corporations use the government to get around their limits.

This partnership manifests itself in various ways. The government uses corporations to circumvent its prohibitions against eavesdropping domestically on its citizens. Corporations rely on the government to ensure that they have unfettered use of the data they collect.

Here’s an example: It would be reasonable for our government to debate the circumstances under which corporations can collect and use our data, and to provide for protections against misuse. But if the government is using that very data for its own surveillance purposes, it has an incentive to oppose any laws to limit data collection. And because corporations see no need to give consumers any choice in this matter — because it would only reduce their profits — the market isn’t going to protect consumers, either.

Our elected officials are often supported, endorsed and funded by these corporations as well, setting up an incestuous relationship between corporations, lawmakers and the intelligence community.

The losers are us, the people, who are left with no one to stand up for our interests. Our elected government, which is supposed to be responsible to us, is not. And corporations, which in a market economy are supposed to be responsive to our needs, are not. What we have now is death to privacy — and that’s very dangerous to democracy and liberty.

The simple answer is to blame consumers, who shouldn’t use mobile phones, credit cards, banks or the Internet if they don’t want to be tracked. But that argument deliberately ignores the reality of today’s world. Everything we do involves computers, even if we’re not using them directly. And by their nature, computers produce tracking data. We can’t go back to a world where we don’t use computers, the Internet or social networking. We have no choice but to share our personal information with these corporations, because that’s how our world works today.

Curbing the power of the corporate-private surveillance partnership requires limitations on both what corporations can do with the data we choose to give them and restrictions on how and when the government can demand access to that data. Because both of these changes go against the interests of corporations and the government, we have to demand them as citizens and voters. We can lobby our government to operate more transparently — disclosing the opinions of the Foreign Intelligence Surveillance Court would be a good start — and hold our lawmakers accountable when it doesn’t. But it’s not going to be easy. There are strong interests doing their best to ensure that the steady stream of data keeps flowing.

This essay originally appeared onBloomberg.com.
http://www.bloomberg.com/news/2013-07-31/the-public-private-surveillance-partnership.html orhttp://tinyurl.com/me4bpsx

Corporations collecting data:
http://www.schneier.com/essay-324.html
http://www.schneier.com/essay-423.html
http://www.nationaljournal.com/magazine/how-america-s-top-tech-companies-created-the-surveillance-state-20130725 orhttp://tinyurl.com/mpy6tbz

Corporations cooperating with the NSA:
http://news.cnet.com/8301-13578_3-57593538-38/how-the-u.s-forces-net-firms-to-cooperate-on-surveillance/ orhttp://tinyurl.com/jw7f4ob
http://news.cnet.com/8301-13578_3-57595202-38/feds-put-heat-on-web-firms-for-master-encryption-keys orhttp://tinyurl.com/l4ztclv
http://www.newyorker.com/online/blogs/elements/2013/06/what-its-like-to-get-a-national-security-letter.html orhttp://tinyurl.com/ntd3ffe
http://news.cnet.com/8301-13578_3-57595529-38/feds-tell-web-firms-to-turn-over-user-account-passwords/ orhttp://tinyurl.com/osj2zps

How the partnership manifests itself:
http://www.bloomberg.com/news/2013-06-28/anti-hacking-bill-aiding-verizon-delayed-by-snowden-leaks.html?cmpid=yhoo orhttp://tinyurl.com/myc3gtl
http://www.bloomberg.com/news/2013-06-30/fbi-s-data-mining-needs-scrutiny-too.htmlor http://tinyurl.com/kkcyqej

Congress attempt to rein in NSA:
http://www.nytimes.com/2013/07/25/us/politics/house-defeats-effort-to-rein-in-nsa-data-gathering.html or http://tinyurl.com/msvoc7k

The death of privacy:
https://www.schneier.com/essay-418.html

Disclosing FISA opinions:
http://www.bloomberg.com/news/2013-07-09/fisa-court-missing-checks-and-balances.html or http://tinyurl.com/kevlx6c