AI and Politics

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Source: AI, machine learning and marketing: a brave new world,  http://www.thedrum.com/profile/news/265498/ai-machine-learning-and-marketing-brave-new-wor

At the end of last week I attended a presentation about Economy 4.0 and Artificial Intelligence (AI). Idea is that all the expected improvements in services and products, the Internet of Things (IoT) depends on the intelligence of the communication of out machines.

Most of the simple repetitive tasks are already computerized; replacing workers either by smart software, or by robots. The next step, which is taken rapidly, are learning algorithms. Learning by algorithms can be described as repeating processes, games or tasks, evaluating the results and adapting the reaction to the initial input. This repetition had to be accompanied by human input, to distinguish right and wrong outcomes. Yet, the last generation algorithms can even learn from other algorithms. By computerizing simple task, so is the expectation, labour productivity will increase by 40%.

The learning process requires lots of data on inputs, procedures and desired outcomes. Therefore, Big Data is of importance and is one of the functions of the IoT to generate and analyze data. The idea is to generate so much data that every task becomes simple and repetitive. In the (nearby) future, all task will become divided in simple repetitive tasks. The presenters sketched a future in which people can enjoy a 24/7 economy where interactions are real-time, but with a robot, who can help you based on your emotional pattern, earlier request, request of similar identities and communication with other AI’s in both your and its own network.

In my view, if something is possible, in time it will be realized. However, this is true for positive and negative developments. So four remarks with respect to the Economy 4.0-future:

  • The underlying models of the algorithms determine the validity of the outcomes of the analyzes and actions. For example, criminal profiling depends on the correctness of the relationship between the chosen profiles and the probability of criminal behaviour. Another example is the fact that advertisements on Facebook and websites are determined by past behaviour. boyd and Crawford (2012) cite Bollier: “As a large mass of raw information, Big Data is not self-explanatory”.
    Often the remark is heard that after the buy of a pair of sneakers, or in my case a casserole, the algorithms for some time will offer us the same sneakers and casseroles. Learning, then, takes the form of changing the advertisements after I placed a new buy on the internet. A less sympathetic feature is the fact that if you have looked for airline tickets, the price increases with each visit to the website. Some people even reserve one computer for looking and another one for buying! The Financial Times recently asked attention for “The algorithms that seduce our children“: “The tech industry is under scrutiny for how its algorithms manipulate adults but little attention has been paid to how algorithms seduce children, who are far more susceptible than their parents. Children often lack the self-control or even the means to change the channel“.

    hook

    Illustration reproduced with permission of Pâté pateontoast.co.uk

  • An implicit assumption in the Big Data approach is that every task can be divided in simple tasks which can be described by an algorithm, simplifying complex activities in sets of computerized tasks. Activities which are to complex today can be solved by gathering more data. Yet, as someone remarked: finding a needle in a haystack is not made simpler by adding more and more hay to the stack.

boyd and Crawford (2012) compare the influence of Big Data with the assembly line of Ford, stating: “[..] the specialized tools of Big Data also have their own inbuilt limitations and restrictions. For example, Twitter and Facebook are examples of Big Data sources that offer very poor archiving and search functions. Consequently, researchers are much more likely to focus on something in the present or immediate past – tracking reactions to an election, TV finale, or natural disaster – because of the sheer difficulty or impossibility of accessing older data“. Kate Metzler argues that academics in social sciences either lack the access to Big Data or the capabilities for Big Data analyses. According to her, the digital age will result in a division between in company researchers and academic researchers, resulting in a majority of research aimed at selling more, and a minority of research trying to understand social processes and outcomes.

  • The gathering of data also raises issues about privacy and ownership of the data. If my behaviour is recorded by some home device, which learns to make expectations on my personal life: raising the temperature after 5, ordering pizza if I’m not home at 7; it is uncomfortable to know that this data is shared with some anonymous IT-workers in Silicon Valley. Especially when firms, but also government agencies, will use this data to forecast my behaviour and use this knowledge to influence my decisions.
    To quote boyd and Crawford (2012): “Just because it is accessible does not make it ethical”. Arguments for such actions are often found in “it is convenient for you….”, “it is only to help….”, of “it is for your/the national safety……”. Next to privacy and unwanted influences, data on your behaviour, on and of the web, is worth money. The firms pay the data collecting firms money for the data you have given them. An old internet proverb states that if you don’t pay for the product, you become the product; often followed by the remark that you agreed with the user agreements. Yet, without agreeing with a long list of conditions, you can’t use Facebook, web browsers or other ICT-applications, used for modern communication. So if I want to keep communicating with my family in our WhatsApp group, I cannot state that I agree with conditions 1 – 10, but not with 11 -121. Yet, I still think that there should be some discussion on the ownership of data on myself, or at least have a say in the way it is used and by whom.
  • The emergency of Economy 4.0 will cause serious disturbances, even if the algorithms are right, the needle is found and agreement is arrived. As the Austrian economists as Mises and Hayek already showed around the start of the last century, changes in the real economy take time. When workers become obsolete, this will result in unemployment, losses in income and human capital, with real effects. In that sense, Economy 4.0 can increase inequality and social instability.

Economy 4.0 can influence our lives in positive and negative ways. It is expected to increase the ease of use of several appliances, increase quality of life through self-learning and communicating between different machines and applications, mechanization of dirty and tedious work. On the other side, it gives the opportunity for firms, governments and others to influence our behavior in an undesirable way, can give rise to wrong or socially unacceptable decisions, for example by supporting biases etcetera.

These (potential) developments ask for a Public Management 4.0; not only in the sense that government agencies apply the new technologies, but in a way that supports the positive sides of AI and IoT, and suppresses the negative sides.

To do so, governments have to leading in the knowledge of the underlying technologies, but also make the usage of these technologies transparent. Why is a loan denied, what kind of commercials are financed by whom? And in extreme cases, governments should be able to pass laws, forbidding some kinds of usage of the Economy 4.0 technologies.

Next to direct interferences in the negative sides of the technological possibilities, is the obligation to educate the new generations in the do’s and don’ts. So they (we?) know when we are manipulated, know that ‘fake news’ exists, but also see that it requires some effort to make a distinction between good and bad.

Much is possible, much will be positive, but to enjoy the advantages of the AI/IoT developments, society has to defend itself against the negative aspects.

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Openness, lessons from innovation for education

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In two seminal papers, Dahlander and Gann (2010) and Huizingh (2011) try to define openness as used in open innovation.  Here, I try to use these definitions of openness in describing openness in education, drawing some lessons for both sectors.

Definitions on openness in innovation

Although Huizingh (2011) bases its definitions on Dahlander and Gann (2010), it is easier to start with his distinction between the innovation process and the innovation outcome. Openness in terms of the process is determined by the amount of knowledge which is obtained externally, or developed internally. The openness of the outcome is determined by the fact if the resulting process or product is proprietary or made freely available for external partners.

Innovation process: Innovation outcome:  
  Closed Open
Closed Closed Innovation: proprietary innovation developed inhouse. Public Innovation: the outcome is available for others, whereas the innovation was developed inhouse.
Open Private Open Innovation: a proprietary innovation, developed with the input of external partners. Open Source Innovation: both the development as the result of the innovation are open.

Source: Huizingh (2011, p. 3)

Closed innovation is the traditional way innovations were developed. The aim of public innovation often is the development of a standard. For example, by making the PC the standard in computing during the 80’s, IBM could control part of the market for personal computers.

Another way to divide open innovation is to make a distinction between inbound and outbound innovation. In the definition of Huizingh (2011, p. 4): Inbound open innovation refers to internal use of external knowledge, while outbound open innovation refers to external exploitation of internal knowledge. Dahlander and Gann (2010) combined these types with the question whether there is money involved or not.

  Inbound Innovation Outbound Innovation
Pecuniary Acquiring Selling
Non-pecuniary Sourcing Revealing

Source: Dahlander and Gann (2010, p. 702)

Revealing seems to be used to attract collaboration, especially in situations without strong IPR regimes. It also resembles Public Innovation of Huizing (2011), in aiming to set a market standard. Sourcing refers to the absorption of external available knowledge to create new products and services. The literature suggests an inverted U-shaped curve: searching for external knowledge will be profitable up to a certain level, after which the “over-search” will become more costly than profitable.

There seems to be a paradox in openness: as Huizingh (2011) states, companies perform more inbound than outbound activities (which recently confirmed by studies of the open innovation network, http://oi-net.eu/), yet inbound activities of one organization should generate reciprocal outbound effects from other organizations?

Openness in education

As we noted elsewhere (De Langen, 2013), there are a lot of definitions of openness in education. Openness in the sense of free to obtain (MOOCs), free to use (OER) or the absence of entry barriers (Open Universities).

If we define the process as a measure of openness of the process, leading to the product, we can distinguish between free to access, free to use or even collaboration in design and production. The outcome is the education, the course or the program. Traditional education is mostly distributed in a closed form: it is exclusively for students of the institution. Traditional education is often designed and developed by a single teacher, by an internal group of teachers (both examples of closed process) and in some cases with developers outside of the own institution (often subsidy-led) or the usage of open resources and MOOCs. The Open Outcome-side describes the production of open educational products and services. The closed production of open outcomes are typically of the production of MOOCs. A situation of open production and open outcomes is found in situations where communities both develop and use educational resources. For example in the case of knowledge bases and portals, developed and exploited by communities of fellow teachers; two examples are MERLOT and FEmTechNet.

Educational process: Educational outcome:  
  Closed Open
Closed Closed Education: traditional education with an one-to-one relationship between students and teachers. Free to use: the outcome (courses, programs) are open to use, but the teaching/developing process is closed. We can distinguish different regimes:

a.       Traditional education without fees, as in large parts of Europe is practice; Open Universities

b.      MOOCs, where the product is free, but the process of developing the course is proprietary.

c.       Certain forms of Open Access, in the sense that the production process belongs to the researchers (holding the copyrights, sometimes having to pay a fee), whereas the published research results are free for the public.

Open Use of free: the use of free (open) resources to develop educational resources for traditional institutions; for example Lumen Learning offers to teach educators to use OER to develop courses and programs for usage within traditional institutions. Open Education: Open educational resources, DOCCs, communities of practice and alike.

If we look into the role of money in (open) education, than is the pecuniary side of the inbound knowledge acquisition the fact that most teachers use standard textbooks, produced and sold in a for-profit-business model by publishers. Of course, in traditional education teaching is one of the courses of income, however there are more opportunities. For example,

  Inbound education Outbound education
Pecuniary Acquiring textbooks and materials. Selling knowledge, texts and competences.
Non-pecuniary Sourcing: collaborating to acquire knowledge and resources. Revealing: collaborating to supply knowledge, competences and resources.

Another model

Another way to categorize education is based on Yunus et al. (2010). In their view, organizations optimize either financial profit or social value. On the other dimension, they distinguish the way organizations are financed: either they have to earn back the invested capital, or they don’t. In this last case, another organization will supply the funds necessary for the long term survival of the organization. Traditional HEI’s were placed either in the Not-for-profit category for public education; or in the For-profit-category for private educational firms. Interesting are those organizations (websites, portals, knowledge bases ect.) which resulted in the past years, as result of inter-organizational collaborations, subsidies or individual initiatives.

Financial Profit Maximization
No recovery of Not sustainable in the long term For profit organizations Repayment of
Invested capital

(depending on external funds)

(Traditional) Not-for-profit organizations Social businesses Invested capital

(self-sustainable)

Social Profit Maximization

Next to the educational knowledge and competences, their survival will depend on the capability to generate funds to reimburse the capital used in the production and exploitation of open education.

Literature

Dahlander, L., & Gann, D. M. (2010). How open is innovation?. Research policy, 39(6), 699-709.

De Langen, F. H. T. (2013). Strategies for sustainable business models for open educational resources. The International Review of Research in Open and Distributed Learning, 14(2), 53-66.

Huizingh, E. K. (2011). Open innovation: State of the art and future perspectives. Technovation, 31(1), 2-9.

Open Innovation in European industries (2015), study for the European Commission, http://oi-net.eu/.

Yunus, M., Moingeon, B., & Lehman-Ortega, L. (2010). Building social business models: lessons from the Grameen experience. Long Range Planning, 43, 308-325.

A Business Model for a research and education

Recently, I was asked to suggest a business model for a research and education center. Some organizations aimed to work together in the field of innovation and regional knowledge sharing. Aim is to make the center sustainable in the sense of Yunus et al. (2010). They describe Social Businesses as an organization which aims to earn enough to renew the invested capital combined with social profit maximization: At the same time as trying to achieve their social objective, social businesses need to recover their full costs so they can be self-sustainable.

 

Already several earning models of the kind Rappa describes at his website were discussed, however, a business model involves more than only an earning potential. So starting out with the assumption that in research each question is unique, this defines n=1. The methods of academic research may be more or less modeled in a stage model, each query will need different data bases, different academic specialties and competences.

The same applies for education. Taking aside learning styles and other contextual  factors, the group of intended learners will have specific work and practice related needs.

This suggest that at the input side r=g, a network organization is needed to meet the demand of the customers. The business model has to take the r=1-n=g philosophy of Prahalad (and others) into account. Central questions are

  1. how the network organization can attracted the necessary resources to organize the activities needed to fulfill the unique demands of the customers?
  2. How to organize the earning model to make the center self-sustainable as a social business.

Education and research as a network organization

Note that in a network organization there are two sets of key resources and key activities as mentioned in the Osterwalder-Pigneur business canvas: firstly the resources and activities aimed at fulfilling the needs of the customer, the realization of the value offering. These factors have to be found in the relationships which make up the network of the organization. The key resources and activities within the organization have to do with setting the conditions necessary to activate the former external resources and activities. The internal resources and activities as relationship management, ‘the black books’ and communication and organizational skills are the core competences of the network organization. Money is often an important persuading factor, but reputation, knowledge sharing and strategic issues can also convince organizations to work together in a network setting.

A business model for an education and research network organization

The assumption is that the main customers of such a model are other organizations, having specific research questions, wanting to school their employees. The aim of the network organization is to match demand by organizing its partners into a relevant supply.

The actual business model is inspired by a model some colleagues of mine had developed some years ago for a HEI. It consists of different layers, each aimed at a specific audience, but building on each other.

The major difference between the layers is its amount of openness and the facilities offered. The first layer consists of free information, free courses, OER and research rapports. This layer offers free products and services for interested parties. The only restriction is that one has to register with an real email-address. There are several potential sources of income in such a case:

  1. Selling marketing space to third parties
  2. Internal subsidies because of the marketing of other products and services
  3. External subsidies because of the dissemination of knowledge
  4. Analyzes and sales of data on potential customers; email addresses ect.

In terms of Rappa’s earning models this is a combination of the advertising and the infomediary model. In Rappa’s taxonomy, the Freemium model of Anderson (giving away something for free; earning an income by offering additional services or products) is part of the advertising model.

In the second layer (registered) visitors find a supply of standardized service and products, for example courses based on existing courses of the participants, workshops and alike. Interested parties can either participate or buy products on a pay-as-you-go base, or –in the case of changing offerings- take a subscription. The utility model assumes the first case, whereas the subscription model differs from the description here as they assume the subscriber also to be a member of the network.

Here, I would label the participants of the last two layers as members. Members of the third layer become part of the community in the sense that they can freely use courses and existing research. Furthermore, they can participate in discussions and influence the direction of new research and the educational course of the center. This level can be compared with a regular student at a HEI, who has pays a yearly fee and is during that year free to use all the facilities and courses at the institute.

Of course, for specific studies or custom made courses and other on-demand the subscribing member has to pay an additional fee. The fourth layer consists of the full participants, the suppliers of services and products supplied in the three other layers. New full participants should pay a fee reimbursing the others for the initial investment costs, getting the right to promote and sell their own products and services within the center.

Open Education                                          – free (registered) entry–                                             Open Access
Courses                                                                  – pay as you go –                                                                 Studies
Programs and custom made courses          – community I –                                                Original research
(New) Producers                                                 – community II –                                               Founding fathers

 

Overall, such a center will act as a broker between the participating organizations and individuals or organizations seeking the products and services on offer. In the brokerage model, income is earned by charging a commission or a fee either based on actual transactions or as part of a general agreement. Yet, at each level data is generated which could be used to create value for (potential) customers and partners, again creating income. Another additional source of income could be regional and national subsidies as governments often stimulate geographical collaboration.

Changes are that an actual implementation of such a model will require some adjustments, for example the privacy regulations with respect to adjustments to the gathering and usage of data are strict; in a world of ever falling government budgets, subsidies may be small or non-existent.

Still, a business model which generates income through its communities can afford to sustain Open Education and Open Access (research), which in itself will not be sustainable.

It would, therefore, be interesting to see if an institute or center build on these principles would be self-sustainable in the sense of Yunus et al (2010), combining a social goal (Open Education, Open Access), while at the same time covering the full costs.

 

Literatuur

Yunus, M., Moingeon, B., & Lehman‐Ortega, L. (2010). Building social business models: lessons from the Grameen experience, Long Range Planning, 43, 308‐325

 

Open Education, efficiency, collaboration and management

Ben Janssen, a former colleague who started his own consultancy on change and (open) education, and myself discussed several experiences we have with open educational resources and alike.

In this context he made an interesting remark, as Ben often does. In his view, Open Education is not only a public good, but can also be used as a communication channel. As he stated:

“in my work as an external consultant I often find that departments within an organization are working on the same projects, starting the same pilots and the same programs”.

Even over organizations he sees the same phenomena: organizations who work on the same projects without knowing what happens a stone throw away.

By opening up, organizations make this kind of information available for potential partners. In the same sense as commercial organizations try to innovate through openness and collaboration, offering knowledge and materials invites others to collaborate and improve on the original resources. Yet, as in open innovation, organizations should do so from their own strength: giving away your core competences is bad business, even when you’re not in business.

So opening up education in this way offers the possibility to share programs, or as Wiley (2014) argues, developing competence profiles and the accompanying programs, techniques and assessments.

By offering open competence programs, more institutions can develop new experiments based on these programs, improve and change the programs, which will feed back in the education of the original developers. This line of thought opens an interesting question: What is the core competence, resource, program or technique of a specific educational institution? What is the distinctive characteristic which distinguishes one HEI from another?

There is also a dangerous side to these possibilities. We know that both governments as boards of HEI’s have seen Open Educational Resources, MOOCs and other open educational materials as a way to reduce teaching costs. It causes a paradox: using OER can decrease teaching costs, producing OER will increase costs of the organization. The sensible management decision will be to demand that people use OER in their teachings, forbidding them to produce free materials for others.

In the ’70s of the former century, this was called the innovation paradox and used to explain why the national level of innovation will be below its potential level. Cure for this paradox is a good system of IP’s, so the inventing firm can also secure the income of the innovation.

This remedy is of course impossible in a system which is built on openness. Protecting OER with IP-rights would remove the essence of sharing.

So accepting that:

  1. the production of OER is costly in the sense of hours spend;;
  2. there is none or little incentive for an individual organization or department to offer free materials and programs in isolation;

    and assuming:

  3. that open education will increase efficiency (lower overall costs of education) and,
  4. increase effectivity (best materials will be used, freeing resources for additional teaching and teaching materials),

there has to be an external force redistributing income over the producers and users of OER.

This could be an internal authority, for example the board of the HEI, which can stimulate the development and use of the same supporting courses (for example, the development of an open course on statistics for non-mathematical studies; developed by the intern mathematical department). The development costs can be earned back as usage outside the own department is rewarded by additional funding by the board.

On a national level, government agencies could reward the supply and use of open courses by subsidizing the suppliers, without punishing the users by cutting back there teaching funds (which in itself is not a challenge for the HEI’s, but more for the politicians to resist the temptation to save money on the education budget).

Yet, by reading each other signals in the sense that organizations will open-up non-core courses; collaboration in these fields can make education more efficient and effective. As Janssen said, collaboration needs communication.

Specialised teachers can provide free courses for non-specialist students, freeing sources to develop better and more courses, flipping the class room and freeing students from uninteresting class room lectures.

A win-win situation could be possible if we would agree to communicate our “weaknesses”, offering our “strengths” to our colleagues.

Literature

Wiley, D., (2014), The Open Education Infrastructure, and Why We Must Build It, July 15, 2014, http://opencontent.org/blog/archives/3410, accessed December 18, 2014

A Business Model for a research and education

Recently, I was asked to suggest a business model for a research and education center. Some organizations aimed to work together in the field of innovation and regional knowledge sharing. Aim is to make the center sustainable in the sense of Yunus et al. (2010). They describe Social Businesses as an organization which aims to earn enough to renew the invested capital combined with social profit maximization: At the same time as trying to achieve their social objective, social businesses need to recover their full costs so they can be self-sustainable.

Already several earning models of the kind Rappa describes at his website were discussed, however, a business model involves more than only an earning potential. So starting out with the assumption that in research each question is unique, this defines n=1. The methods of academic research may be more or less modeled in a stage model, each query will need different data bases, different academic specialties and competences.

The same applies for education. Taking aside learning styles and other contextual  factors, the group of intended learners will have specific work and practice related needs.

This suggest that at the input side r=g, a network organization is needed to meet the demand of the customers. The business model has to take the r=1-n=g philosophy of Prahalad (and others) into account. Central questions are

  1. how the network organization can attracted the necessary resources to organize the activities  needed to fulfill the unique demands of the customers?
  2. How to organize the earning model to make the center self-sustainable as a social business.

Education and research as a network organization

Note that in a network organization there are two sets of key resources and key activities as mentioned in the Osterwalder-Pigneur business canvas: firstly the resources and activities aimed at fulfilling the needs of the customer, the realization of the value offering. These factors have to be found in the relationships which make up the network of the organization. The key resources and activities within the organization have to do with setting the conditions necessary to activate the former external resources and activities. The internal resources and activities as relationship management, ‘the black books’ and communication and organizational skills are the core competences of the network organization. Money is often an important persuading factor, but reputation, knowledge sharing and strategic issues can also convince organizations to work together in a network setting.

A business model for an education and research network organization

The assumption is that the main customers of such a model are other organizations, having specific research questions, wanting to school their employees. The aim of the network organization is to match demand by organizing its partners into a relevant supply.

The actual business model is inspired by a model some colleagues of mine had developed some years ago for a HEI. It consists of different layers, each aimed at a specific audience, but building on each other.

The major difference between the layers is its amount of openness and the facilities offered. The first layer consists of free information, free courses, OER and research rapports. This layer offers free products and services for interested parties. The only restriction is that one has to register with an real email-address. There are several potential sources of income in such a case:

  1. Selling marketing space to third parties
  2. Internal subsidies because of the marketing of other products and services
  3. External subsidies because of the dissemination of knowledge
  4. Analyzes and sales of data on potential customers; email addresses ect.

In terms of Rappa’s earning models this is a combination of the advertising and the infomediary model. In Rappa’s taxonomy, the Freemium model of Anderson (giving away something for free; earning an income by offering additional services or products) is part of the advertising model.

In the second layer (registered) visitors find a supply of standardized service and products, for example courses based on existing courses of the participants, workshops and alike. Interested parties can either participate or buy products on a pay-as-you-go base, or –in the case of changing offerings- take a subscription. The utility model assumes the first case, whereas the subscription model differs from the description here as they assume the subscriber also to be a member of the network.

Here, I would label the participants of the last two layers as members. Members of the third layer become part of the community in the sense that they can freely use courses and existing research. Furthermore, they can participate in discussions and influence the direction of new research and the educational course of the center. This level can be compared with a regular student at a HEI, who has pays a yearly fee and is during that year free to use all the facilities and courses at the institute.

Of course, for specific studies or custom made courses and other on-demand the subscribing member has to pay an additional fee. The fourth layer consists of the full participants, the suppliers of services and products supplied in the three other layers. New full participants should pay a fee reimbursing the others for the initial investment costs, getting the right to promote and sell their own products and services within the center.

Open Education                                   – free (registered) entry–                   Open Access
Courses                                                     – pay as you go –                                 Studies
Programs and custom made courses          – community I –                   Original research
(New) Producers                                           – community II –                   Founding fathers

Overall, such a center will act as a broker between the participating organizations and individuals or organizations seeking the products and services on offer. In the brokerage model, income is earned by charging a commission or a fee either based on actual transactions or as part of a general agreement. Yet, at each level data is generated which could be used to create value for (potential) customers and partners, again creating income. Another additional source of income could be regional and national subsidies as governments often stimulate geographical collaboration.

Changes are that an actual implementation of such a model will require some adjustments, for example the privacy regulations with respect to adjustments to the gathering and usage of data are strict; in a world of ever falling government budgets, subsidies may be small or non-existent.

Still, a business model which generates income through its communities can afford to sustain Open Education and Open Access (research), which in itself will not be sustainable.

It would, therefore, be interesting to see if an institute or center build on these principles would be self-sustainable in the sense of Yunus et al (2010), combining a social goal (Open Education, Open Access), while at the same time covering the full costs.

http://www.opencoffeeoss.nl/open-coffee/

Source: http://www.opencoffeeoss.nl/open-coffee/

Literatuur

Yunus, M., Moingeon, B., & Lehman‐Ortega, L. (2010). Building social business models: lessons from the Grameen experience, Long Range Planning, 43, 308‐325

It has to be Open: The Lau last performance at PinkPop

Not-for–profit organizations and customers: trying to solve the puzzle

Lately, I gave a lecture on shareholders, using Mitchell et al. (1997) Toward a theory of stakeholder identification and salience: defining the principle of who and what really counts. In this paper, they try to describe an instrument which can be used by managers to identify the stakeholders and their relative importance.

This is important, because given any organization, the whole world (and perhaps the whole universe) can be seen as some kind of an stakeholder. So it is important to order your stakeholders one a scale between very urgent towards ignore. However, the order in the stakeholders is not given, but dynamic. If time changes, positions and influence can change.

The dimensions Mitchell et al. (1997) use are:

  • Power: ..a party to a relationship has power, to the extent it has or can gain access to coercive, utilitarian, or normative means, to impose its will in the relationship… (p. 865)
  • Legitimacy: …”a generalized perception or assumption that the actions of an entity are desirable, proper, or appropriate within some socially constructed system of norms, values, beliefs, and definitions”.. (quoting                Suchman, 1995, p.866)
  • Urgency: .. time sensitivity is necessary, it is not sufficient to identify a stakeholder’s claim or “manager relationship” as urgent. In addition, the stakeholder must view its claim on the firm or its relationship with the firm as critical or highly important. …. (p.867)

 

 

So shareholders are the ultimate dominant stakeholders (having power to change the policy of the firm and having a legitimate claim to do so). However, when there is an idea that present management is making large mistakes, they will want to change management fast and they become definitive stakeholders.

The same will happen when an environmental pressure group, who have legitimate claims and a sense of urgency (dependent stakeholders) acquire political support; becoming powerful and so definitive stakeholders.

Customers have a legitimate claim on the firm. Next, they have a discreet power, if they get a sense of urgency, a customer’s strike will force the firm to act in a desirable way.

By determining the strategy of a not-for –profit organization (whether an NGO or an educational organization) it is often not possible to determine a customer, an individual or group who pays for the service or product offered. Stakeholder analyzes can help to answer the question: For who are we doing what we do? What is our value-offering to whom?

For example, education has several goals, depending on the individual or group you ask. If we take the four kinds of “aspirations” of Christensen et al (2011, 1) and combine them with the stakeholders who have an interest in these goals, we get the following combination:

Goal Stakeholder(s)
1. Maximize human potential StudentEmployers
2. Facilitate a vibrant participative democracy in which we have an informed electorate that is capable of not being “spun” by self-interested leaders GovernmentSociety 
3. Hone the skills, capabilities and attitudes that will help our economy remain prosperous and economically competitive GovernmentEmployersStudents
4. Nurture the understanding that people can see things differently-and that these differences merit respect rather than persecution GovernmentSociety

 

Christensen et al. (2011) furthermore point out that education is used as a sort of magic cure, for several societal problems (ranging from poverty towards anti-terrorism). Budgets, regrettably, do not  rise in the same amount as requests do.

Society at large is too big and not specific enough to be anything else than a discretionary or demanding stakeholder. Employers can be divided into two categories; as part of the society, defining certain legitimate demands on the competencies of students, but without power. Another group is a real customer, paying institutions to organize refresher courses and alike. In that case, they have both the power and the legitimate to influence (this kind of) education: becoming dominant stakeholders.

Governments and other financiers are also dominant stakeholders which goals should be taken seriously into account. As described above, goals are added to the original goals as society changes, but budgets overall remain the same adding budget control as an additional goal.

Students want to learn, to further their career, to increase their social skills. They want to learn the right things in the right way. This makes them legitimate stakeholders with some sense of urgency. However, question is how much power they have? In most educational systems, students pay fees, but not enough to reimburse costs. So who determines which are the right things to learn? Governments finance the major part of educational programs, but often based on the number of students, certificates and awarded degrees. Yet, academic teaching is supposed to be founded in academic research, which is financed by governments and corporations. So indirect these determine the content of the programs.

The goals of Christensen et al. (2011) concentrates on the external stakeholders. Of course employers (teachers but also administrative personnel) are important stakeholders. Employment means not only income, but also (hopefully) a meaningful work environment.

It is interesting to see what happens when the stakeholders’ aims differ.

For example, students campaign for free education: Free education is not just about the money. It’s about the working conditions of those who make our education possible, and about democratising and liberating our institutions and the curriculum; funding vocational and further education, living grants and childcare that allows women to freely access learning.

In the Netherlands, students and teachers occupy part of the University of Amsterdam protesting against a perceived reduction in quality of teaching and too little democracy.

It is the Board of the HEI’s who have to unite or compromise the different conflicting goals of the diverse stakeholders. Power and urgency fight for influence.

 

I don’t think that this blog solves the puzzle of the role of “customers” or stakeholders in education. Most teachers I know will say that they teach because of the students. However, as seen above, it is important to realize that funding partners will influence our institutional targets. As far as these coincide with the personal goals of the teachers and students, this will be reinforcing; however when they conflict, it becomes interesting.


 

 

 

Professor R. Edward Freeman speaks about the role of business in society: Purpose of business is not maximizing profit for shareholders, but is about changing the world!


 

 

Literature:

Christensen, C., M. Horn and C. Johnson (2011) Disrupting Class, McGraw Hill, New York

Mitchell R., B. Agle, D. Wood (1997) Toward a Theory of Stakeholder Identification and Salience: Defining the Principle of Who and What Really Counts, The Academy of Management Review, Vol. 22, No. 4 (Oct., 1997), pp. 853-886

Osterwalder, A., Y. Pigneur (2010), Business Model Generation: A Handbook for Visionaries, Game Changers, and Challengers, John Wiley and Sons Ltd, Augustus 2010

Articles on budget cuts:

http://www.msnbc.com/msnbc/gop-governors-want-higher-education-cuts-recoup-budget-shortfalls

http://www.cbpp.org/cms/?fa=view&id=4011

http://eacea.ec.europa.eu/education/eurydice/documents/facts_and_figures/National_Budgets.pdf

 

Internet, sharing and openness; lessons from e-commerce

At the beginning of the century, the influence of the Internet on business really took off. This induced managers and scientists to reflect on the role of the Internet on the way we do business. One of the major changes was the openness and sharing. Another influence is the increasing competition. Because information flows “openly”, the possibility to compare prices, quality and other characteristics increases beyond the geographical proximity.

Education is only beginning to feel the influence of both trends. The High Level Group on the Modernisation of Higher Education has published a new rapport on the New Modes of Learning and Teaching in Higher Education. In this report, the importance of technological progress for the widening of access of HE is stressed. As they state “Online technologies provide opportunities to learn anywhere, any time and from anyone”. Non-traditional learners have access to new forms of learning which will increase lifelong learning and ongoing professionalization.

In a world were global politics become more complex and worldwide manual labour has become a commodity, both European democracy and Europe’s competitive position require an ever increasing education of its population. Creativity and smart solutions have to take the place of mass production; not only the designers and developers have to be high educated, the average labour force also has to scale up. Another interesting observation is that “The goal should be to ensure that all publicly funded education resources are openly available”. This is not only a support of the Open Educational Resources-movement, but can be interpreted broader: education should be free as mostly all public educational institutes are mainly funded by the government.

Tony Bates (2014) concludes his review of Moocs with the observation, that “[A]t some point, institutions will need to develop a clearer, more consistent strategy for open learning, in terms of how it can best be provided, how it calibrates with formal learning, and how open learning can be accommodated within the fiscal constraints of the institution, and then where MOOCs might fit with the strategy”.

When we look into different sectors, where openness plays a role, we can distinguish:

– Open as in free to use, re-use and distribute: the open source movement in the sector of Information Technology. In general there are two different approaches. Communities develop free software, whereas companies are allowed to use the free software to sell specialized adaptations (only making the customers pay for the added value). In the other case, firms give away software or products to earn money with additions to these products and services (freemium, ranging from WinZip to razors).

– open as in open access in the publishing sector, where costs are shifted from users (readers) towards producers (researchers, writers); the intermediate firms keep the same or more income. Often open access is motivated by the fact that most research is funded by public funds, so it should be freely available for the public. Publishers are then compensated for their costs by authors’ fees.

– open as in free to participate, as the Internet opens the possibility for the public to participate in journalism or quality control. Furthermore firms use customers to improve their products and develop new products and services; labeled co-creation.

– open as in open innovation, the process whereby firms ‘spin-in’  ideas and inventions of others and ‘spin-out’ ideas and inventions which do not fit into the business models of the firm, especially in the industrial sectors. IP-rights are essential as they make it possible to trade inventions which can or will not be used internally. By selling and buying inventions, the efficiency and size of innovations in society will increase. Technology increases the possibilities for innovation on a small scale. Sharing of knowledge and resources is a major force behind the MakersMovement, in which small inventors design, prototype and -eventually- distribute their innovative products or services (see Anderson, 2012).

Wiley (2014) – in his discussion on Moocs – defines openness in education as the transition of ‘open entry’ (in the sense of no entry demands from the Open Universities) towards ‘open licenses’, as in Open Educational Resources (OER), towards a possible  ‘open educational infrastructure’.

The Open Educational Resources movement strives to generate educational resources, which are shared for free (although often developed using subsidies of national governments and private institutions).  Moocs are a part of this development, but where the majority of OER is aimed at teachers, Moocs are developed for usage by learners, opening up participation.

Moocs are also, more then OER, examples of the ‘give-part sell-part’ approach to openness. In the regulations of several Mooc-platforms, we see explicit remarks about the earning potential of alternative usage of the Moocs: licensing, assessment and certification but also use a HRM-instrument and corporate universities.

This definition of openness is consistent with the 5-components model for open education (5COE) of Mulder and Janssen [2013]. This model analyses the different activities of (open) education and it is possible to un-bundle these into three components on the supply side and two on the demand side.

On the supply side they distinguish:

  1. Open educational resources (OER)
  2. Open learning services (OLS): online and virtual activities which are available either free or for payment, including assessments, exams and communities.
  3. Open teaching efforts (OTE): all supporting activities as teaching, ict-support and other roles in (distance) teaching; these activities will generally not be free.

On the demand side they describe the following two components:

  1. Open to learners’ needs (OLN): open education should be free in the sense of time, space and tempo; however, it should also be affordable for everyone.
  2. Open to employability & capabilities development (OEC): education should be open towards new and changing demands from society and the labour market, but also promote critical thinking, creativity and personal growth.

Christensen et al. (2014) uses a similar approach to forecast a more disruptive development with respect to the (American) educational sector. Distance education, the competence based approach, the existence of high quality, accredited open educational materials offers commercial firms the opportunity to enter the educational sector, aiming at low cost segments and non-consumers (of existing education). According to them, it is only a matter of time before the last bastion of the traditional mixture of academic research and education, the accreditation organizations, will fall. So unbundling education at an organizational level could result in unbundling at a sectorial or national level and a new division between open en exclusive forms of education.

Most educational programs are not financed by their students, but subsidized by governments, churches or private enterprises. Depending on the fee, the financial barriers of participation in education are substantial to non-exsting. Contrary to the (average) openness in finances, most institutions have entry barriers in terms of quality requirements. Only the Open Universities (yet not all, and not for all programs) accept all students without a formal qualification. So, although open access in a financial way exists in some European countries, where the majority of the costs is shifted from the individual towards the collective. Yet open participation is even rarer due to qualitative restrictions for non-degree learners. This is an explanation why Moocs have attracted so much attention: it is the change for many not formally qualified learners to follow relevant academic courses.

Open innovation is based on collaboration, based on trust or contracts and on bought knowledge. HEI’s have a long tradition on working together on research projects. Yet, it seems that in the field of education, both developing and exploiting courses and programs, collaboration is less common. Still, there are large opportunities to exploit the Long Tail of Education. In Anderson’s long tail, the Internet combines two factors. The distribution and marketing costs of digital materials is approaching zero, so it’s only production costs which determine the price; furthermore is it possible to reach out to more people than locally interested. In the music business this means that a Celtic classical ensemble can distribute its music towards a global public covering costs, whereas in the traditional music industry this was only possible for hits. In education, this means that it should be possible for small audience courses to survive, provided that the teachers work together and share resources.

The success of Open Innovation depends on the right attitude. It requires a realization that the organization has to absorb external knowledge and has the competence to do so. It also requires an awareness of the strengths of the organization, as the external knowledge has to be complementary with the existing knowledge and competencies. External knowledge can destruct the existing business model and help to build a new one, but only when the competencies are available to transform the knowledge in an actual business model.

This means that opening up the supply side of the educational business model, we should ask ourselves questions like:

  1. What are our strengths and weaknesses, in the services we provide towards our students, our financiers and society?
  2. Which external knowledge can lessen our weaknesses and how do we acquire this knowledge? Are collaborations possible?
  3. How do we exploit and enlarge our strengths? Can the be of use in the collaborations to lessen the weaknesses?

For example, specific knowledge could be used to develop online courses which are taught to both our own students as students of other institutes for a fee. Even the expertise to develop online courses itself could be used to make excellent external knowledge available for our own students, by seeking combinations of our excellence in online teaching, combined with the knowledge of research institutes.

So opening up on the supply side may be a case of showing the possibilities of win-win situations by combining the strengths (or weaknesses) of the different institutions involved. Opening up on the demand side, from teacher/institution to student is perhaps both simpler and more difficult. As shown above, an Open Access-model requires a shift of costs from the users towards the producers. The simple solution is the removal of all fees for students and a full government funding of the HEI’s. This can be resisted on ideological grounds. For example, the British government finances students through loans, so they will choose the HEI’js best fitted for them, challenging HEI’js to improve their education in such a way that most students chose for them. If this is a good model to improve educational quality and the knowledge level in the economy can be discussed, however, it is one of the used models.

The second barrier to openness depicted above is the use of qualitative entry demands. Of course, there are formal restrictions on entry, but institutions are often more strict than legally required. For example, in the Netherlands, the entry demands for students with a vocational degree when entering a university are very high. That is not only because they lack research competencies, or the knowledge of specific academic subjects, but also because educational institutions in the Netherlands strive for the best students. The flexible part of their budgets depends on the success ratios of students and the amount of degrees awarded. By discouraging the lesser students, success ratios will be enhanced and for every student the “degree bonus” will be received.

Openness will increase experimentation, which will lead to a certain amount of failure. Not every (open) invention becomes a sustainable innovation and not every individual starting an academic program will become a successful student. Yet, without experimentation no successes too!

Remaining question of course is who is going to pick up the bill of the students’  “free lunch”?

Live BC – Before College / AD – After Degree according to 9GAG http://9gag.com/gag/aRPPPxM?ref=fbp

Literature:

Anderson , C., (2014) Makers: The New Industrial Revolution, Crown Business

Bates, T. (2014), A review of MOOCs and their assessment tools,  http://www.tonybates.ca/2014/11/08/a-review-of-moocs-and-their-assessment-tools/  , accessed November 2014

European Commission (2014), Report to the European Commission on New modes of learning and teaching in higher education, October 2014, ISBN 978-92-79-39789-9, doi:10.2766/81897,  http://ec.europa.eu/education/library/reports/modernisation_en.pdf , accessed November 2014

Mulder, F.,  B. Janssen (2013, in Dutch) Open (het) onderwijs, Surf Trendrapport, http://www.surf.nl/en/knowledge-and-innovation/knowledge-base/2013/trend-report-open-educational-resources-2013.html (accessed October 2014);
English version: https://www.surf.nl/en/knowledge-and-innovation/knowledge-base/2013/trend-report-open-educational-resources-2013.html

Wiley, D. (2014) The MOOC Misstep and the Open Education Infrastructure, September 18, retrieved September 30,  2014, http://opencontent.org/blog/archives/3557

Wiley, D.,  (2014), The Open Education Infrastructure, and Why We Must Build It, July 15, 2014, http://opencontent.org/blog/archives/3410 , accessed December 18, 2014