Esko Kilpi on Interactive Value Creation

The art of interaction, the design of digital and the science of social complexity

Tag: Learning

The changing system of skills and responsibilities

We have so far followed a very crude pyramid-like classification in work: skilled work was what highly educated individuals would do. Semi-skilled work was possible for trained people. Unspecified labor was what almost everybody could do after onboarding. This classification of work led to the unintended consequence that the most economical design of mass-era organizations reduces the amount of skilled work and increases the amount of less-skilled work, thus reducing costs. A bigger problem than low-skilled people is the low-skilled occupations we have created.

Classification of work as different bundles of skills and responsibility has been very easy to grasp and easy to follow in compensation schemes. More skills and/or more responsibility — more pay. Managers, who are responsible people, are given responsibilities — and higher wages. Workers are given less demanding tasks, less responsibility — and lower wages. The argument behind is a circular, self-fulfilling prophecy. People who are not made responsible tend to avoid responsibilities and therefore never become responsible. Skilled people acquire more skills because of the higher cognitive demands of their work. Less-skilled work roles give less opportunities for learning, leading in fact to a slow but certain de-skilling. This is something we see in many industries today. The phenomena and the causes of the problem become the same.

The organizational system of skills and responsibilities has been made on the assumption that all that has to be done can be known and managed with efficiency and insight. In mass-production, work corresponds mainly with what has been planned and budgeted. But today, in more contextual problem solving, work corresponds mainly with complex engagements with the customers.

The focus changes from generic skills to contextual presence, empathy and interaction.

The most modern definition of work is “an exchange in which the participants benefit from the interaction”. Interestingly, cooperation is also described as “an exchange in which the participants benefit from the interaction”.

The technological environment of work has changed fundamentally, but we haven’t yet developed a new mode of economic space design, neither have we escaped the pull of the traditional industrial system. Our relations at work are still asymmetrical involving status differences based on systems of responsibility and systems of skills. This inbuilt systemic fault generates increasing social distance and inequality, as we have now seen.

Due to the variety of contexts people work in, work requires interpretation, exploration and negotiation. The interpreter with the best situational awareness is the worker, working together with the customer, not a manager. The relations are built on symmetry.

What defines most problems today is that they are not isolated and independent. To solve them, a person has to think not only about what he believes the right answer is, but also about what other people think the right answers might be. Work, then, is exploration both what comes to defining the problems and finding the solutions. Again, the relations need to be based on symmetry.

Most decision makers are still unaware of the implications of the complex, responsive properties of the world we live in. Enterprises are not organized to facilitate interactions, only the actions of parts taken separately. Even more, compensation structures normally reward improving the actions of parts, not their interactions. This is why conventional jobs are increasingly inhibiting flexibility and contextual responses to new problem definitions or new technological solutions to old problems.

To succeed in the new economic spaces we need symmetric relationships, open assets and very open organizations.

When customers are identified as individuals in different use contexts, also the sales process is in fact a joint process of solving problems. You and your customer necessarily then become cooperators. You are together trying to solve the customer’s problem in a way that both satisfies the customer and ensures a profit for you. The industrial make-and-sell model required (explicit) skills as we still know them. The decisive thing was your individual knowledge and individual education. Today, in new economic spaces you work more from your presence and network than your skills. Work is interaction.

The really big objective of digital transformation is to reconfigure agency in a way that brings these relationships into the center. Success today is increasingly a result of skillful presence: it is about empathy and interaction. Through new technologies and ubiquitous connectivity, we have totally new opportunities for participation and communication in the new economic spaces

These economic spaces are about interdependent individuals and groups defining and solving problems in shared contexts utilizing smart contracts.

Individuals competing on job markets may be one of the historic mistakes we have inherited from the early industrial era. It made sense a very long time ago but now we should think differently.

Interaction creates capability beyond individuals. Cooperative performance can be more than what could ever be predicted just by looking at the performance of the parties involved. It is not about individual skills any more. Skills, performance and resilience are emergent properties of cooperative interaction. They are not attributable to any individuals. Higher performance is more a result from the quality of interaction than the quantity of training and education.

Networks provide problem-solving capability that results directly from the richness of communication and the amount of connectivity. What happens in interaction between the parts creates a reality that cannot be seen in the parts or even seen in all of the parts.

This is why it does not make sense any more to talk about skill levels and just managers being responsible. Either you are present in a relevant way or not. Neither can responsibility be somewhere else. You can only be present and contribute if you are response able.

Credits Nick Hanauer and Katri Saarikivi

Work is solving problems and learning is answering questions

Studies predict that nearly half of all jobs and over 70% of low-skill jobs could be susceptible to computerization over the next two decades. Our chances of creating work for human beings in this new, demanding environment will be very limited if old and unjustified assumptions about what people can or can’t do are not examined. If we continue to assume that some people are born intelligent, while most are not, and continue to see intelligence as a fixed, personal possession, the options for large-scale systemic changes will be few.

If, on the other hand, we were to visit recent findings of neurosciences, relational psychology and computational social science, we would see intelligence as something more fluid. Then a whole different set of opportunities would become visible. Perhaps a bigger problem than low-skilled people would be the low-skilled occupations we have created.

There is a misunderstanding of the relationship between “nature” and “nurture” as causes of our intelligence. In most cases, genes do not establish limits that determine the space for personal growth. Recent scientific findings show that everyday life plays a role in defining how and when the genes themselves are expressed in us. Genes, the nature, take their cues from nurture. Environmental influences can be less reversible than genetic ones.

There is another argument than the science of genes about whether intelligence is fixed or can be expandable. Many people tend to think that they live their life with a fixed-capacity. Some people think differently. They have a growth mindset, as Stanford professor Carol Dweck calls it. They think that minds are like bodies: people come in different shapes and sizes, but everyone can benefit from exercise.

Individuals who believe that they can grow, tend to enjoy challenges. They like pushing themselves because they think that struggling leads to something good. People who think that their minds are fixed often see challenges as a threat to their imagined level of ability. They don’t like having to try new things, or making mistakes, because they interpret that as evidence of inadequacy.

These mindsets come from the way people around us respond to our successes and failures. Belief systems are contagious. If, over an extended period of time, people are treated as if they are intelligent, they actually become more so. The opposite can also be true.

Success in life has been seen governed by two concepts: skills and effort; how bright you are and how hard you work. Recently, researchers have claimed that there is a third and decisive concept. It is the practice of lifelong curiosity: “knowing what to do when you don’t know what to do” as Piaget put it.

The collective intelligence of our societies depends on the tools that augment human intelligence. We should welcome the fact that people today are smarter in large measure because they have invented and use smarter tools. Making tools is what human beings have always done. The interactions between tools and human minds are so complex that it is very hard to try to draw a line between humans and technology. Neither is it a zero-sum game where the human brain is losing to technological intelligence, but as technology changes, people and what people do, are necessarily changed.

To benefit from technology, we need resourcefulness. It means to be constantly looking for new tools with which to augment our intelligence. It also means new services: if you have a smartphone in your pocket, you should have an easy access to education in your pocket. Smarter and smarter tools surround us, but if we don’t want to learn the new practices and take up the new roles that the new technologies make possible, they might as well not be there. It is sometimes not easy, because the challenge with new technologies is, what is called “functional fixedness”, our inability to see more than the most obvious use cases.

There is more to being intelligent than using the latest technologies; how we interact with others is a crucial element of how smart we are in practice. Intelligence is social and arises in communities and communication. The world has never been a more networked place, and yet schools and workplaces still focus on individuals. That needs to change.

Human behavior is learned in relations. Our brains are wired to notice and imitate others. Computational social science has proved that behavior can be caught like a disease merely by being exposed to other people. Perhaps you can catch intelligence from others the same way? Learning and also non-learning can be found in communication. It is not that people are intelligent and then socially aware. Social intelligence is not a separate type of intelligence. All intelligence emerges from the efforts of the community.

Work starts from problems and learning starts from questions. Work is creating value and learning is creating knowledge. Both work and learning require the same things: interaction and engagement.

Scientists have discovered that learning is learnable. With the help of modern tools, we can create ways for very large numbers of people to become learners. But learning itself has changed, it is not first acquiring skills and then utilizing those skills at work. Post-industrial work is learning. It is figuring out how to solve a particular problem and then scaling up the solution in a reflective and iterative way — both with technology and with other people.

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The Internet of Things

Industrial era enterprises viewed customers through the lens of a fairly uniform set of features, leading to customers being seen as having relatively uniform needs. But even commodity products are always a bundle of use contexts, buying patterns, complementary goods and delivery options. Just because a product is a commodity doesn’t mean that customers can’t be diverse in the ways they use the product.

All use cases are somewhat the same and somewhat different. This means that different customers and processes use products that are manufactured in the same way, with the same product features, differently. It is contextual. Customers and the way products are used, are today understood to be active contributors to value creation. The word “consumption” really means value creation, not value destruction. Companies don’t create value for customers, the way the products are used creates value, more value or less value.

The parties explicitly or implicitly “help each other to help each other”. Value creation is a process of interaction. As the goal is to create more value together, a critically important element would be to implant context aware intelligence and interaction capability to a product.

The Internet of Things refers to embedded computing power and networking capability of the physical objects through the use of sensors, microprocessors and software that can collect, actuate and transmit data about the products and their environment. The gathered data can then be analyzed to optimize, develop and design products, processes and customer services. IoT is often about two new digital “layers” for all products: (1) an algorithmic layer and (2) a network layer.

The algorithmic layer “teaches” the customer and the product itself to create more value in a context-aware way, and accordingly teaches the maker the product to develop. As a result, the customer’s need set is expanded beyond the pre-set physical features of the offering. This changes the conceptual definition of the product and it becomes more complex. The more complex the product, the more opportunities there are for the maker to learn something that will later make a difference.

From a marketing standpoint, when a customer teaches the firm behind the product how she uses the product, what she wants or how she wants it, the customer and the firm are also cooperating on the sale of a product, changing the industrial approach to sales and marketing. The marketing and sales departments used to be the customer’s proxy, with the exclusive role of interpreting changing customer needs. Internet-based business necessarily transforms the marketing function and sales specialists by formally integrating the customer use case into every part of the organization. Thus the customer of tomorrow interacts with, and should influence, every process of the maker through the connected, intelligent products.

In the age of the Internet of Things, all products are software products. The value of the code, computing power and connectivity, may determine the value potential of a product more than the physical product itself. The effectiveness of an offering is related to how well it packages the learning from past activities, other use cases and from other similar products and how it increases the users options for value creation through network connections in the present. The offering actuates data via algorithmic smartness and through live presence (in the Internet). Connectivity also enables some functions of the product to exist outside the physical product in the product system, the cloud.

A product or a service should today be pictured as a node in a network with links to supplementary services and complementary features surrounding the product. The task today is to visualize the product in the broadest sense possible.

Visualizing these connections changes the strategic opportunity space dramatically. The study of isolated parts offers little help in understanding how connected parts work in combination and what emerges as the result of network connections. Every link and relationship serves as a model for what might be possible in the future. What new relational technologies are making possible for manufacturing industries is a much, much richer repertoire of business opportunities than what we were used to in a traditional industrial firm.

The ability to create value in a remarkably more efficient and resource-wise way corresponds to possibilities for interaction with relevant actors, information and products. If interdependent links are few, poor, or constraining, the activity and value potential will be limited.

The Internet of Things and technological intelligence in general, create transformative opportunities for more efficient and more sustainable, resource-wise, practices and also higher margins!

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Thank you Rafael Ramirez

More on the subject: Ford’s OpenXC. Bosch. Kari A. Hintikka (In Finnish)

Social business and the changing theory of management

A manager recently voiced his concerns: “Most employees prefer being told what to do. They are willing to accept being treated like children in exchange for reduced stress. They are also willing to obey authority in exchange for job security.” That is the way we have seen it: managers inspire, motivate, and control employees, who need to be inspired, motivated, and controlled. These dynamics create the system of management and justify its continuation.

If we want to meet the challenges of the post-industrial world, this relationship needs to change. The workers changing their role is often seen as a matter of the extent to which the managers are willing to allow it and give up responsibility. In reality it is as much a matter of how much the workers are willing to develop their (management) capacity and take more and wider responsibility.

The dysfunctional relationship between managers and employees creates a self-fulfilling prophecy and a systemic failure in creative, knowledge-based work. What is tragic is that neither side normally understands the predictability of what is going on. The pattern is a mutually reinforcing self-destructive process that manifests itself as a steady decline in the authority of management and productivity of work.

A few researchers have started to dispute the assumption that the present system of management is a fact of life that will always be with us. It may be time for us to question whether the recent problems created by bad management are isolated and should be tolerated. Or to ask whether the fault is in the system itself and not in individual managers?

Luckily, management theory and practice are slowly starting to catch up with the dramatic changes brought about by the loosely coupled, modular nature of creative work and the ideals of social business.

A social business does not behave in the way our dominant management thinking assumes. What is it, then, that has changed?

Organizations are always assemblies of interacting people. The reason for an organization to exist is to simplify, support, and enrich interaction.

At present, there are three types of organizational cultures depending on the type of management and the alternative mechanisms for the coordination of tasks. The different task interdependencies accordingly place different and increasing burdens on our communication practices .

I call these the administrative culture, the industrial culture and the creative, social culture.

The administrative culture, which is found in most governmental organizations is about function-specific independent activities. Two functions or tasks are independent if it is believed that they don’t affect each other. The most important communication exists between the employer and the employee, the manager and the worker. The principle is that the execution of two independent tasks does not require communication between the tasks. The architecture consists of black boxes that are not coupled directly, but in an indirect way by higher-level managers, who coordinate the work. Work as interaction is mainly communication between hierarchical levels.

The industrial culture of process-based organizations is about dependent and sequential activities. Manufacturing work is about dependent tasks. Being dependent means that the output of one task is the input of another. The reverse cannot normally take place. In sequential dependence, those performing the following task must comply with the constraints imposed by the execution of the preceding task. Since the process architecture is typically quite clear, management coordination is mostly about measuring and controlling whether the execution conforms to the planned requirements. The architecture consists of tightly coupled tasks and predetermined, repeating activities. Work as interaction is a sequential process with one-way signals.

A creative, social culture is different. It is about loose couplings and modularity, about interdependent people and interdependent tasks. Two people/tasks are interdependent if they affect each another mutually and in parallel. Interdependent tasks call for peer-level responsiveness and coordination by mutual adjustments, not coordination by an outside party such as a manager.

Most of the information that is relevant will be discovered and created during the execution of the task, not before. As a result it is not always possible for a manager and a worker to agree on a coherent approach in advance. Nor is it normally possible to follow a predetermined process map.

The basic unit of corporate information in creative, social work is not content in the form of documents but interaction in the form of conversations. Knowledge is perpetually constructed in interaction. Work as interaction is complex, situational communication between loosely connected nodes of the network! The structure of work resembles the structure of Internet.

The three cultures and corresponding architectures differ in the degree to which their components are loosely or tightly coupled. Coupling is a measure of the degree to which communication between the components is fixed or not. In most creative work, and always in a social business, any node in the network should be able to communicate with any other node on the basis of contextual interdependence and creative participative engagement.

As organizations want to be more creative and social, the focus of management theory should shift towards understanding participative, self-organizing responsibility and the equality of peers. It is a systemic change, much more than just kicking out the bad managers and inviting new, better managers in. It is not about hierarchies vs. networks, but about how all people want to be present and how all people want to communicate in a way that was earlier reserved only for the people we called managers.

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Eric Brynjolfsson video on TED. Steven Johnson video on peer networks. Gary Hamel interview.

Communication and cognition

Economic growth is about value added. In manufacturing adding value was a transformation process from physical raw materials to physical goods. Economic growth is still today about value added. The difference is that the generic, homogeneous raw materials of the industrial era are now unique ideas and the transformation process is an iterative, interactive, non-linear movement, rather than a linear, sequential chain of acts.

The worlds of manufacturing-based added value and creativity-based added value require very different skills. Before the Internet and smart devices, most professional occupations required individual competencies that in most cases had accumulated over years. This experience base, often called tacit knowledge, was used to retrieve answers from memory and to independently solve situations arising at work. Knowledge was situated in the individual. In order to help individuals cope with the challenges of everyday life, individual competencies needed to be developed. This is why our whole education system is still based on independent individuals learning and, as a consequence,  knowing.

The cognitive load of work has increased as a result of manufacturing giving way to creative, knowledge-intensive work. The content of work is changing from repetitive practices to contextual, creative practices. This makes the individual experience base, by default, too narrow a starting point for efficient work. Experiences can be a huge asset but experiences can also be a liability, creating recurrence where there should be novelty and innovation.

Creative work is not performed by independent individuals but by interdependent people in interaction. A new way to understanding work and competencies is unfolding: knowledge that used to be understood as the internal property of an individual is seen as networked communication. This requires us to learn new ways of talking about education and competencies. What is also needed is to unlearn the reductionist organizing principles of industrial work. Work is communication and the network is the amplifier of creativity.

People have always networked. Scholars depended largely on correspondence networks for the exchange of ideas before the time of the universities. These communities, known as the “Republic of Letters” were the social media of the era, following the communication patterns of today astonishingly closely. The better-networked scientist was often the better scientist. The better-networked worker is today usually the better worker. The better-networked student in the future is always the better student.

The main difference from the time of the Republic of Letters is the efficiency of our tools for communication, meaning thinking together. A “man of letters” may today be a man of tweets, blog posts and Facebook, but the principle is the same: the size and quality of the network matters. What matters even more than the network, is networking, the way we are present and interact. It is time to acknowledge the inherently creative commons nature of thinking, creativity and economic growth.

Life is a temporal pattern of emotional and intellectual interaction. We are our interaction.

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Noam Chomsky interview.

Emergence and self-organization

Many people say that open source software developers have the most efficient ecosystems for learning that have ever existed. What is it, then, that is so special about the way developers do things? Is there something that could act as a model for the future of work, or the future of education?

What takes place in open source projects is typically not the result of choices made by a few (powerful) people that others blindly implement. Instead, what emerges is the consequence of the choices of all involved in the whole interconnected network, “the connective“, as Stowe Boyd puts it. What happens does not follow exactly a plan or a design, what happens emerges. It is about the hard to understand process of self-organization.

We still don’t quite understand what emergence and self-organization mean. The problem is that we believe that the unit of work is the independent individual. Self-organization is then thought to mean that individuals organize themselves without the direction of others. People think that it is a form of empowerment, or a do-whatever-you-like environment, in which anybody can choose freely what to do. But connected people can never simply do what they like. Cooperating individuals are not, and cannot be, independent. People are interdependent.  Interdependence means that individuals constrain and enable each other all the time. What happens, happens always in interaction and as a result of interaction.

According to the present approach to management, planning and enactment of the plans are two separate domains that follow a linear causality from plans to actions. From the perspective of open source development, organizational outcomes explicitly emerge in a way that is never just determined by a few people, but arises in the ongoing local interaction of all the people taking part. For example GitHub “encourages individuals to fix things and own those fixes just as much as they own the projects they start”.

What emerges is, paradoxically, predictable and unpredictable, knowable and unknowable at the same time. This does not mean dismissing planning, or management, as pointless, but means that the future always contains surprises that the managers cannot control. The future cannot be predicted just by looking at the plans.

Emergence is often understood as things which just happen and there is nothing we can do about it. But emergence means the exact opposite. The patterns that emerge do so precisely because of what everybody is doing, and not doing. It is what many, many local interactions produce. This is what self-organization means. Each of us is forming plans and making decisions about our next steps all the time. “What each of us does affects others and what they do affects each of us.”

No one can step outside this interaction to design interaction for others.

An organization is not a whole consisting of parts, but an emergent pattern in time that is formed in those local interactions. It is a movement that cannot be understood just by looking at the parts. The time of reductionism as a sense-making mechanism is over.

What we can learn from the open source ecosystems is that organizational sustainability requires the same kind of learning that these software developers already practice: “All work and learning is open and public, leaving tracks that others can follow. Doing and learning mean the same thing.”

The biggest change in thinking that is now needed is that the unit of work and learning is not the independent individual, but interdependent people in interaction.

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Thank you David Weinberger, Ken Gergen, Ralph Stacey and Doug Griffin

More on the subject: the GitHub generation, Sugata Mitra. Video: “Knowledge in a MOOC” Steve Denning on complexity. The mundanity of excellence.

The core of the social business

We are in the midst of a shift from the industrial system of supply and demand to social, co-production models. The customer is now seen as being directly and actively involved in the key moments of value creation as opposed to passively consuming value. There are profound implications that result from this change of thinking. Products and services are not reproducible as such any more. Solutions are by default contextual and personalized, but they can be starting points for someone else to create value.

Creative, connected learning is at the core of the social business.

It is not learning related to meeting the requirements set by someone else, but learning that is motivated and expressed through personal, situational needs. As a result, a new meaning of education and learning is emerging.

Business, more than government, is driving the changes in education that are required for the knowledge-based economy. The government-run education systems are lagging behind the transformation in learning that is evolving outside schools. Businesses are even coming to bear the primary responsibility for the kind of education and learning that is necessary for a country to remain competitive in the future.

Gutenberg’s printing press broke the monopoly of the church on what was taught and by whom. Today’s social technologies are doing the same to schools and universities. The learners decide what is taught and by whom. The new technologies are perhaps not making teachers and schools obsolete, but are definitively redefining their roles and breaking local monopolies.

A learning business is not the same as the learning organization made popular by Peter Senge and many others. It is not about systems thinking, or learning how to use technologies and data.

A learning business is one that leverages the economic value of knowledge.

Producing more value than is used is the characteristic of productivity. True learning businesses must therefore be teaching businesses. This means communicating to customers the additional value of learning in the context of the services and products offered. Learners are teachers and teachers are learners. Creating learning connections is more valuable than creating learning content.

Inside an organization, all people must take responsibility for information and communication. Each person needs to take responsibility for his or her own active contribution. Everyone needs to learn to ask three questions continuously. What information do I need? What information do I owe others? With whom should I communicate?

Each level of management and each process step is a relay. That was OK when the speed of learning was not an issue. It was also OK that businesses were hierarchy-based, because transparency was not possible. In a learning business each relay means cutting the potential for learning in half and doubling the noise. Hierarchy used to speed things up, now it slows down.

The most important principle of a social, learning business is to build the organization around information and communication instead of around a hierarchy.

There is a debate going on that focuses on the distinction between ethical and practical education. There are people who emphasize moral values and those who underline the practical reasons for education. There are voices that are concerned that business-driven learning would mean less moral and ethical education than under government-led learning. But there are also people who stress that in order for any business to thrive in the new economy, it needs to show a new, intense and honest interest in values and sustainable ethics. Some people I know inside the church have been surprised that leading corporations dedicate more time to education about values than they, or schools do.

We have moved to a new economy, but we have yet to develop a new educational paradigm.

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Andrew Ng on the importance of universal access to education. Clayton Christensen on disrupting the education industry. Joi Ito on formal vs. informal education. Clay Shirky on social reading. Paul Graham: “Large organizations will start to do worse now because for the first time in history they are no longer getting the best people

The future of ICT?

Industrial work clearly determined the tasks that had to be done. The machine and the ways to work with the machine were given. People served the machine. Workers did not need to be concerned and feel responsible for the results. They just did what they were told.

Knowledge work is very different. The first thing for a knowledge worker is to try to answer these questions:  What am I here for? What is my responsibility? What should I achieve? What should I do next? Key questions for a knowledge worker have to do with how to do things and what tools to use. This time, the machines, the tools, need to serve the worker. It is, in fact, a change from only following instructions to also writing the instructions.

Historians claim that the invention of the printing press led to a society of readers, not a society of writers despite the huge potential of the new technology. Access to printing presses was a much, much harder and more expensive thing than access to books. Broadcasting systems such as radio and television continued the same pattern. People were not active producers, but passive receivers.

Computer literacy or the idea of being a digital native still often follow the same model. In practice it means the capability to use the given tools of a modern workplace – or a modern home. But literacy to just use, to be the consumer of, the technologies and the programs is not what we need. The perspective of the consumer/user was the perspective of the industrial age. Success meant learning how to behave in the way the machine needed you to behave.

That should not be the goal today.

As a result of Internet-based ICT we have learned how to speak and how to listen; we have learned how to write and how to read. But in the digital world, it is not enough if we know how to use the programs, if we don’t know how to make them.

We are typically always one step behind what technology can offer. We can now participate actively through tweets, status updates and profile pages, but the thing to remember is that somebody else has made the programs that make it possible. And often the real goal of that somebody is to create a new advertising model. Nothing wrong with that.

The underlying capability of the knowledge era is programming, not reading or writing. It is a change from using things to making things. Creating things for yourself and sharing them.

I have met many people who think that programming is a kind of a modern version of a working-class skill. It can well be outsourced to some far-away, poor nation while we here do higher value things. Nothing could be further from the truth, more wrong, and more dangerous for us. Today the code is the main domain of creativity and innovations. It is a new language. Writing code is the number one high leverage activity in a creative, digital society.

The primary capability of the knowledge era is not using computers, but programming computers. It is not using software, but writing software.

Mitch Resnick talks about the new challenge: “After people have learned to read they can read to learn. And after people have learned to code, they can code to learn.”

It is time for a human response to technology.

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Thank you Mika Okkola

More on the subject: On software productivity. The Finnish ICT 2015 report. How to start learning programming. Codecademy. Linda Liukas. The Estonian approach. On GitHub. On data democracy.

Thoughts on work, productivity and change

Everybody seems to “know” that the only way a worker can produce more and be more productive is by working longer hours or by working harder.

This has led to the view that the key management responsibility is for the performance of the people. This, however, is too narrow a definition. The way we should think today is that the key responsibility is for the application and performance of knowledge.

The industrial firm is a conservative institution. It tries to maintain stability and often tries to maintain the problems that it was originally the solution to. But the organization of post-industrial society is a disruptor and reformer because its function is to put new knowledge to work – which means to learn. It must be organized for constant change because to learn means to change. It must be prepared for the systematic abandonment of the established and the familiar.

The task today is asking: “If we did not do this already, would we go into it knowing what we know now and knowing what technologies and new tools have become available?” If the answer is “No”, the next question to ask is: “How could we plan abandonment rather than try to prolong the life of outdated practices?”

Workers in industrial-age firms were used to and comfortable with the rules that limited the scope for their initiative. The burden of decision making, with the need to communicate and gather costly information, was minimized. Furthermore, by narrowing the scope of decision making and action, the learning requirements for workers and consumers were limited, reducing the transaction costs and related expenditures. In part, the efficiency-enhancing contribution of mass-production was derived from these lower learning costs.

In contrast to consumers being content with limited choice, today more and more offerings are made specifically according to the unique requirements of the individual customers. For workers and customers the burden of gaining the information needed for such tasks is creating an entirely different environment from that of the industrial era.

The knowledge economy could more appropriately be called a learning economy because creative learning becomes the fundamental entrepreneurial activity. Learning that is not industrial in today’s sense of acquiring pre-set information, earning credentials or passing tests, but from the perspective that learning is the foundation for creative action and innovation. Learning to meet the situational needs of value creation better cannot take place outside that context. Learning cannot be a separate domain outside the practice of work. Neither can it be something with beginnings and ends.

Our present formal training systems are neither designed for networked, life-long progression nor designed for situation-specific just-in-time problem solving. Perhaps the worst thing is that they are not accessible to all learners at all times.

The competitive edge of learning comes from the ability to connect with new information and people as and when they are needed. As such, it is not what is already known that gives the creative edge so much as the ability to co-solve problems that require learning on the spot. In increasingly complex environments the curricula for the new just-in-time learning cannot be known and designed beforehand. Needs and solutions emerge situationally in interaction. Learning is more and more about connecting and interacting in wide area networks. This is why the post-capitalistic society and the post-industrial firm have to be decentralized. The nodes of the network organization must be close to customers, close to new technologies, close to changes in society, close to things that matter.

Learning is emerging shifts in the patterns of human networking, interaction and action. Learning is the emerging transformation of inseparable individual and collective identities. Learning, then, does not mean the cumulative growth of knowledge but occurs as shifts in meaning and is simultaneously individual and social.

Productivity is not about doing more but about learning more.

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