mondora is a software services company and a benefit corporation. They care about how their software products are being crafted and used, considering how both people and planet are impacted. For example, they track the paper (and trees) that are saved in the use of their application that allows banks to easily keep digital records.

mondora role models creating benefit for the world and its workers

Their social impact extends beyond outward acts, mondora proposes to change how work is done in Italy by demonstrating a way of working where employees may choose to be as remote as they like and have flexible hours. mondora believes in creating value for their community of workers as well as the world.

mondora was founded with these values in 2002. As they grew from 10 to 60 employees in the last 7 years, they evolved their ways of working to better fulfill their purpose. They have developed a culture of openness and transparency and a flatter organisational hierarchy. They have implemented tools, such as Loomio, so that anyone can share their ideas and everyone decides together.

Loomio helps move discussions to clear outcomes and action

Kirsten Ruffoni, mondora’s Benefit Officer, spoke to a number of the obstacles mondora was facing prior to adopting Loomio. She shared how, “discussions would occur but nothing would happen”. With people working remotely and on flexible hours, it was “hard to move conversation to conclusion”, and, generally, “hard to keep a conversation going as you always run into different people at the office”.

Kirsten reported that they’ve come a long way in this regards, and Loomio has played a role. “Decisions that used to take months now take a week”, Kirsten told me. mondora takes full advantage of the variety of voting and decision tools that Loomio offers, and appreciates not losing messages on Slack and—unlike email—having the ability to indicate deadlines to increase accountability.

Kirsten described a challenging decision that was made on Loomio: making the salaries of mondora transparent to everyone in the company. The CEO had some reservations, but decided to use Loomio to consult everyone in the company. After the input—unanimously in favor—the CEO decided to trust the group and implement the policy. Not only did nothing bad happen, but they were able to do something really positive in the eyes of everyone in their company. They identified, and fixed, a pay gap between women and men, establishing equal pay for equal work. Kirsten commented, “Loomio makes it easier to voice our opinions in front of our boss”. Using asynchronous decision-making tools can make it easier to have thoughtful conversations and hard decisions, whether the team is remote or meeting regularly in person.

Loomio supports collaboration between organisations and across teams

mondora has also been using Loomio to bring customers into the design process to produce better results and strengthen relationships. They involve customers in the process as early as possible and establish open communication between their customer and every person on the team.

Beyond supporting internal communication and decision-making, Loomio allows mondora to invite guest users into specific threads or groups; mondora uses this to improve their interactions with investors and university researchers. According to Kirsten, Loomio supported mondora to “get information they weren’t expecting from stakeholders.”

After acquisition by TeamSystem, a larger IT company, mondora has introduced Loomio as a decision-making tool within TeamSystem’s R&D department.

In their efforts to better the world and cultivate employee happiness, mondora is leading Italy and others into a future of work where there is a new model of employment—a “new employee” where all workers can fully participate with flexibility, remote work, and effective communication and decision-making. mondora leverages Loomio to get better outcomes with less time and effort, supporting every employee to fully participate in all aspects of the business and to deepen their interactions with customers. Want to create more benefit in the world? Look to mondora as a valuable example.

By John Gieryn at Loomio, read the original post here.

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Collins is a sociologist. In his book “Artifictional Intelligence – Against Humanity’s Surrender to Computers”, out today from Polity, Collins does many interesting things. To begin with, he argues what qualifies him to have an opinion on AI.

Collins is a sociologist of science at the School of Social Sciences, Cardiff University, Wales, and a Fellow of the British Academy. Part of his expertise is dealing with human scientific expertise, and therefore, intelligence.

It sounds plausible that figuring out what constitutes human intelligence would be a good start to figure out artificial intelligence, and Collins does a great job at it.

The impossibility claims

The gist of Collins’ argument, and the reason he wrote the book, is to warn against what he sees as a real danger of trusting AI to the point of surrendering critical thinking, and entrusting AI with more than what we really should. This is summarized by his 2 “impossibility claims”:

1. No computer will be fluent in natural language, pass a severe Turing test and have full human-like intelligence unless it is fully embedded in normal human society.

2. No computer will be fully embedded in normal human society as a result of incremental progress based on current techniques.

There is quite some work to back up those claims of course, and this is what Collins does throughout the 10 Chapters of his book. Before we embark on this kind of meta-journey of summarizing his approach, however, it might be good to start with some definitions.

The Turing test is a test designed to categorize “real” AI. At its core, it seems simple: a human tester is supposed to interact with an AI candidate in a conversational manner. If the human cannot distinguish the AI candidate from a human, then the AI has passed the Turing test and is said to display real human-like intelligence.

The Singularity is the hypothesis that the appearance of “real” artificial intelligence will lead to artificial superintelligence, bringing unforeseen consequences and unfathomable changes to human civilization. Views on the Singularity are typically polarized, seeing the evolution of AI as either ending human suffering and cares or ending humanity altogether.

This is actually a good starting point for Collins to ponder on the anthropomorphizing of AI. Why, Collins asks, do we assume that AIs would want the same things that humans want, such as dominance and affluence, and thus pose a threat to humanity?

This is a far-reaching question. It serves as a starting point to ask more questions about humanity, such as why people are, or are seen as, individualistic, how do people learn, and what is the role of society in learning.

Social Science

Science, and learning, argues Collins, do not happen in a monotonous, but rather in a modulated way. What this means is that rather than seeing knowledge acquisition as looking to uncover and unlock a set of predefined eternal truths, or rules, the way it progresses is also dependent on interpretation and social cues. It is, in other words, subject to co-production.

This applies, to begin with, to the directions knowledge acquisition will take. A society for which witches are a part of the mainstream discourse, for example, will have very different priorities than one in which symptomatic medicine is the norm.

But it also applies to the way observations, and data, are interpreted. This is a fundamental aspect of science, according to Collins: the data is *always* out there. Our capacity for collecting them may fluctuate with technical progress, but it is the ability to interpret them that really constitutes intelligence, and that does have a social aspect.

Collins leverages his experience from social embedding as practiced in sociology to support his view. When dealing with a hitherto unknown and incomprehensible social group, a scholar would not be able to understand its communication unless s/he is in some way embedded in it.

All knowledge is social, according to Collins. Image: biznology

Collins argues for the central position on language in intelligence, and ties it to social embedding. It would not be possible, he says, to understand a language simply by statistical analysis. Not only would that miss all the subtle cues of non-verbal communication, but, as opposed to games such as Go or chess that have been mastered by computers, language is open-ended and ever-evolving.

Collins also introduces the concept of interactional expertise, and substantiates it based on his own experience over a long period of time with a group of physicists working in the field of gravitational waves.

Even though he never will be an expert who produces knowledge in the field, Collins has been able to master the topics and the language of the group over time. This has not only gotten him to be accepted as a member of the community, but has also enabled him to pass a blind test.

A blind test is similar to a Turing test: a judge, who is a practising member of the community, was unable to distinguish Collins, a non-practising member, from another practising member, based on their answers to domain specific questions. Collins argues this would never have been possible had he not been embedded in the community, and this is the core of the support for his first impossibility claim.

Top-down or Bottom-up?

As for the second impossibility claim, it has to do with the way AI works. Collins has one chapter dedicated to the currently prevalent technique in AI called Deep Learning. He explains how Deep Learning works in an approachable way, which boils down to pattern recognition based on a big enough and good enough body of precedents.

The fact that there are more data (digitized precedents) and more computing power (thanks to Moore’s Law) today is what has enabled this technique to work. It’s not really new, as it has been around for decades, it’s just that we did not have enough data and processing power to make it work reliably and fast enough up until now.

In the spirit of investigating the principal, not the technicalities behind this approach, Collins concedes some points to its proponents. First, he assumes technical capacity will not slow down and soon reach the point of being able to use all human communication in transcribed form.

Second, he accepts a simplified model of the human brain as used by Ray Kurzweil, one of AIs more prominent proponents. According to this model, the human brain is composed of a large number of pattern recognition elements. So all intelligence boils down to is advanced pattern recognition, or bottom-up discovery of pre-existing patterns.

Top-down, or bottom-up? Image: Organizational Physics

Collins argues however that although pattern recognition is a necessary precondition for intelligence, it is not sufficient. Patterns alone do not equal knowledge, there needs to be some meaning attached to them, and for this language and social context is required. Language and social context are top-down constructs.

Collins, therefore, introduices an extended model of the human brain, in which additional inputs are processed, coming from social context. This, in fact, is related to another approach in AI, labeled symbolic AI. In this top-down approach, instead on relying exclusively on pattern recognition, the idea is to encode all available knowledge in a set of facts and rules.

Collins admits that his second impossibility claim is weaker than the first one. The reason is that technical capacity may reach a point that enables us to encode all available knowledge, even tacit one, a task that seems out of reach today. But then again, many things that are commonplace today seemed out of reach yesterday.

In fact, the combination of bottom-up and top-down approaches to intelligence that Collins stands behind, is what many AI experts stand for as well. The most promising path to AI will not be Deep Learning alone, but a combination of Deep Learning and symbolic AI. To his credit, Collins is open-minded about this, has had very interesting conversations with leading experts in the field, and incorporated them in the book.

Technical understanding and Ideology

There are many more interesting details that could not possibly fit in a book review: Collins’ definition of 6 levels of AI, the fractal model of knowledge, exploring what an effective Turing test would be, and more.

The book is a tour de force of epistemology for the masses: easy to follow, and yet precise and well-informed. Collins tiptoes his way around philosophy and science, from Plato to Wittgestein to AI pioneers, in a coherent way.

He also touches issues such as the roots of capitalism or what is driving human behavior, although he seems to have made a conscious choice of not going into them, possibly in the spirit of not derailing the conversation or perhaps alienating readers. In any case, his book will not only make AI approachable, but will also make you think on a variety of topics.

And, in the end, it does achieve what it set out to do. It gives a vivid warning against the Surrender, which should be about technical understanding, but perhaps even more so about ideology.

Collins, Harry M. (2018). Artifictional Intelligence: Against Humanity’s Surrender to Computers. Cambridge, UK; Malden, Massachusetts: Polity. ISBN 9781509504121.

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The organization of work and of the production of goods and services is experiencing profound changes that may strongly alter the way we work and the future of work itself.

Cooperative employment tends to be more sustainable in time, suffer less income inequality, tends to be characterized by a better distribution between rural and urban areas, and enjoy a higher level of satisfaction and self-identity than the average. Cooperatives are also a large laboratory experimenting innovative and sustainable forms of work and work relations within the enterprise with continuous creativity and innovation. Almost a century-old model of work organisation based on worker ownership is proving its remarkable modernity to adapt to new challenges when work and working conditions are threatened.

The strategic paper analyses four challenges contributing to the transformation of work, present and future:

• technological change and the knowledge economy
• change in demographic, societal and environmental trends
• globalization and de-industrialization
• working conditions, inequality and social protection

How do industrial and service cooperatives react to these challenges? What are the most recent innovative cooperative models, based on worker ownership, being established in response? CICOPA’s strategic paper on the Future of Work attempts to answer to those questions and address recommendations to policy makers in that field.

• Download the report in PDF: The Future of Work: Where do Industrial and Service Cooperatives Stand?
• Opinion: “Cooperatives and the Future of Work”
• News: How can cooperatives in the platform economy shape the future of work?

The post The Future of Work Where do Industrial and Service Cooperatives Stand? appeared first on P2P Foundation.

Bart Grugeon Plana: After the breakthrough of the internet, Yochai Benkler, a law professor at Harvard University, quickly understood that new online forms of collaboration such as Wikipedia or Linux responded to a completely new economic logic. Specializing in the digital culture of the networked society, Benkler worked on a coherent economic vision that guides us beyond the old opposition between state and markets.

According to Benkler, we may be at the beginning of a global cultural revolution that can bring about massive disruption. “Private property, patents and the free market are not the only ways to organize a society efficiently, as the neoliberal ideology wants us to believe,” Benkler says. “The commons offers us the most coherent alternative today to the dead end of the last 40 years of neoliberalism.”

Bart Grugeon Plana: In the political debate today, it seems that world leaders fall back to an old discussion whether it is the free market with its invisible hand that organizes the economy best or the state with its cumbersome administration. You urge to step beyond this old paradigm.

Yochai Benkler, law professor at Harvard University: Both sides in this discussion start from an assumption that is generally accepted but fundamentally wrong, namely that people are rational beings who pursue their own interests. Our entire economic model is based on this outdated view on humanity that goes back to the ideas of Thomas Hobbes and Adam Smith, philosophers from the 17th and 18th centuries. My position is that we have to review our entire economic system from top to bottom and rewrite it according to new rules. Research of the past decades in social sciences, biology, anthropology, genetics, and psychology shows that people tend to collaborate much more than we have assumed for a long time. So it comes down to designing systems that bring out these human values.

Many existing social and economic systems — hierarchical company structures, but also many educational systems and legal systems — start from this very negative image of man. To motivate people, they use mechanisms of control, by incorporating incentives that punish or reward. However, people feel much more motivated when they live in a system based on compromise, with a clear communication culture and where people work towards shared objectives. In other words, organizations that know how to stimulate our feelings of generosity and cooperation, are much more efficient than organizations that assume that we are only driven by self-interest.

This can work within a company or an organization, but how can you apply that to the macro economy?

Over the past decade, the internet has seen new forms of creative production that hasn’t been driven by a market nor organized by the state. Open-source software such as Linux, the online encyclopedia Wikipedia, the Creative Commons licenses, various social media, and numerous online forms of cooperation have created a new culture of cooperation that ten years ago would have been considered impossible by most. They are not a marginal phenomenon, but they are the avant-garde of new social and economic tendencies. It is a new form of production that is not based on private property and patents, but on loose and voluntary cooperation between individuals who are connected worldwide. It is a form of the commons adapted to the 21st century — it is the digital commons.

What is so revolutionary about it?

Just take the example of the Creative Commons license: It is a license that allows knowledge and information to be shared under certain conditions without the author having to be paid for it. It is a very flexible system that considers knowledge as a commons, that others can use and build on. This is a fundamentally different approach than the philosophy behind private copyrights. It proves that collective management of knowledge and information is not only possible, but that it is also more efficient and leads to much more creativity than when it is “locked up” in private licenses.

In the discussion whether the economy should be organized by the state or by the markets, certainly after the fall of communism, there was a widespread belief that models starting from a collective organization necessarily led to inefficiency and tragedy, because everyone would just save their own skin. This analysis has been the responsibility for the deregulation and privatization of the economy since then, the consequences of which have been known since 2008.

The new culture of global cooperation opens up a whole new window of possibilities. The commons offer us today a coherent alternative to the neoliberal ideology, which proves to be a dead end. After all, how far can privatization go? Trump and Brexit prove where it leads to.

Image by Bart Grugeon Plana

The commons is a model for collective management, which is mainly associated with natural resources. How can this be applied to the extremely complex modern economy?

The commons are centuries old, but as an intellectual tradition it was mainly substantiated and deepened by Elinor Östrom, winner of the Nobel Prize in Economics. Over the past decades the commons have gained a new dimension through the movement of open source software and the whole culture of the Digital Commons. Östrom demonstrated on the basis of hundreds of studies that citizens can come together to manage their infrastructures and resources, often in agreement with the government, in a way that is both sustainable ecologically and economically. Commons are capable of integrating the diversity, knowledge, and wealth of the local community into the decision-making processes. They take into account the complexity of human motivations and commitments, while market logic reduces everything to a price, and is insensitive to values, or to motivations that are not inspired by profit. Östrom showed that the commons management model is superior in terms of efficiency and sustainability to models that fall back on a strong government — read: socialism or communism, or on markets and their price mechanism.

Examples of commons in the modern economy include the management model of the Wi-Fi spectrum, for example, in addition to the previously mentioned digital commons. Unlike the FM-AM radio frequencies that require user licenses, everyone is free to use the Wi-Fi spectrum, respecting certain rules, and place a router anywhere. This openness and flexibility is unusual in the telecommunications sector. It has made Wi-Fi an indispensable technology in the most advanced sectors of the economy, such as hospitals, logistics centers, or smart electricity grids.

In the academic, cultural, musical, and information world knowledge or information is increasingly treated as a commons, and freely shared. Musicians no longer derive their income from the copyright of music, but from concerts. Academic and non-fiction authors publish their works more often under Creative Commons licenses because they earn their living by teaching, consultancy, or through research funds. A similar shift also takes place in journalism.

An essential feature of the commons management model is that all members of the “common” have access to the “use” of goods or services, and that it is jointly agreed how access to those goods and services is organized. Market logic has a completely different starting point. Does this mean that markets and commons are not compatible?

Commons are the basis of every economic system. Without open access to knowledge and information, to roads, to public spaces in the cities, to public services and to communication, a society can not be organized. The markets also depend on open access to the commons to be able to exist, even though they try again and again to privatize the commons. There is a fundamental misconception about the commons. It is the essential building block of every open society. But commons and markets can coexist.

If today it is mainstream to think that a company should maximize its financial returns in order to maximize it shareholder value, it isn’t a fact of nature, it’s a product of 40 years of neoliberal politics and law intended to serve a very narrow part of the society. Wikipedia shows that people have very diverse motivations to voluntarily contribute to this global common good that creates value for the entire world community. The examples of the digital commons can inspire to set up similar projects in real economy, as happens with various digital platforms in the emerging collaborative economy.

A society that puts the commons at the center, recognizing the importance of protecting them and contributing to them, allows different economic forms of organization to co-exist, both commons and market logic, private and public, profit-oriented and non-profit-making. In this mixture, it is possible that the economy as a whole is oriented towards being socially embedded, being about the people who generate the economic activities, and who can have very different motivations and commitments. The belief that the economy would be driven by an abstract ideal of profit-oriented markets is no more than a construction of neoliberal ideology.

You seem very optimistic about the future of the commons?

I was more optimistic ten years ago than I am today. The commons are so central to the organization of a diverse economy that they must be expanded and protected in as many sectors of the economy as possible. There are many inspiring examples of self-organization according to the commons model, but it is clear that their growth will not happen automatically. Political choices will have to be made to restructure the economy beyond market logic. Regulation is necessary, with a resolute attitude towards economic concentration, and with a supportive legislative framework for commons, cooperatives and various cooperation models.

At the same time, more people need to make money with business models that build on a commons logic. The movement around “platform cooperativism” is a very interesting evolution. It develops new models of cooperatives that operate through digital platforms and that work together in global networks. They offer a counterweight to the business models of digital platforms such as Uber and Airbnb, which apply the market logic to the digital economy.

This brings us to the complex debate about future of work.

In the context of increasing automation, there is a need for a broader discussion that can see “money” and “work” as separate from each other, because the motivations to “work” can be very diverse. A general basic income is an opportunity to build a more flexible system that makes these various motivations possible, but also a shorter working week is an option.

We are facing an enormous task and we do not have a detailed manual that shows us the way. However, the current economic crisis and the declining acceptance of austerity means that the circumstances are favorable to experiment with new forms of organization.

When Wikipedia began to grow, it was told that it “only works in practice, because in theory it’s a total mess.” I believe, however, that today we have a theoretical framework that allows us to build a better life together without subjecting ourselves to the same framework that gave us oligarchic capitalism. The commons is the only genuine alternative today that allows us to build a truly participatory economic production system. The commons can cause a global cultural revolution.

This piece has been edited for length and clarity.

Photo by Ratchanee @ Gatoon

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