Why Augmented Learning Collaboration (ALC)?

Problems. Challenges. Opportunities.

What is collaboration? What are “collaboration habits” and “collaboration practices”?

Let’s start with a bit of terminology and differentiate two terms that are often confused, “cooperation” and “collaboration”. Cooperation and collaboration are related concepts that involve working together towards a common goal, but there are some differences between the two.

Cooperation refers to a situation where individuals (organisms, humans, organisations, institutions…) or groups of such individuals act together in concert to achieve a shared goal, often by dividing tasks and responsibilities among themselves. In a cooperative relationship, each individual or group may have their own objectives and may work independently, but they coordinate their efforts to achieve a common outcome. (Perceived) Reciprocity favours cooperation; (perceived) free riding / asymmetric sharing of benefits deteriorates cooperation; therefore, cooperation in general is intertwined with competition and coercion (rewards and sanctions). Life, and specifically evolution, takes place through a combination of mutation, selection and cooperation (to create “higher” organisms).

Collaboration is a special form of cooperation, where humans voluntarily coordinate / combine efforts for a common purpose, which benefits each of them, but also can transcend them. Collaboration often requires a high degree of communication and planning, and individuals or groups collaborate closely to achieve a shared objective. In a collaborative relationship, each person or group brings their potentially unique skills and expertise to the table, and everyone works together in a highly integrated way. Collaboration requires joint decision-making, problem-solving, mutual accountability / commitments, satisfying outcomes for participants… and hence coordination and information exchange.

In this sense, we collaborate in all spheres of life. Certainly, we collaborate at work, where we are paid for it. But payment of effort is not indispensable for a collaboration. We also collaborate when we learn and teach; when we interact with health care professionals; when we participate in democracy; when, with friends, we prepare and enjoy a birthday party; when, with the help of teachers / trainers, we develop new competencies….

Not only the “why” of collaboration is important but also the “how”. The “quality” of collaboration depends on how the process is orchestrated in terms of many factors: group size (2, 3 to 5, 6 to 15, dozens, hundreds, thousands, millions…?); structure (structured versus informal?); organisation (flat or organisation in subgroups?); order of exchanges (sequence, parallel, hybrid…?); timing (short versus long time span / horizon?); pace (slow versus fast?); sharing of contributions (synchronous versus asynchronous?); privacy (nominative versus anonymous versus untraceable?); group stability (short versus medium-term versus long-term life span?); incentives & sanctions (what do people when they collaborate actively / respect the rules of the game, or do not?); traceability / memory (are some of all results archived?); transparency (are rules and modalities of contribution transparent? how are commitments formalised?); supporting means (which means / and tools are used or not to facilitate collaboration); physical / visual presence (are people in the same room or interacting remotely? do they see and / or hear each other?); social proximity / trust / mistrust (how far do participants in the collaboration trust each other?); the diversity of the group (are participants complementary or homogeneous? do they share sufficient common references to be able to collaborate effectively?); affiliation / domination / bias and group type (impact of social / organisational status such boss versus expert versus underling…; types such command group, task group, functional group, interest group, group of friends; majorities versus minorities…?); conflict potential (is the collaboration conflict prone? does it try to resolve a conflict…?); personalities (for example, introvert versus extrovert?);  risks and consequences of failure (what are the risks and their consequences for the group and / or its members?); dependence on outside factors and information (how far is the group influenced by what happens outside of the group? how far does it receive information and send information to third parties? how does this interaction take place? ...);...

All these factors, and perhaps many more, significantly affect collaboration dynamics: how participants communicate and interact; participate and engage; how they make decisions; how cohesive the group will be; how “deep” its collaboration can be; how motivating the collaboration is for participants… They are not only important in isolation, but even more so in their interaction. Most importantly, for many collaborative undertakings, the factors and their combinations change throughout the life span of the collaboration. Often a shorter collaboration (e.g., the organisation of a party) is embedded in a larger event (a group of friends in regular contact and helping each other) It is useful to view a collaboration as a complex flow of togetherness, combining and mixing different forms of collaboration. The structure of this combination and mix, and its evolution over time, are critical for the individual and collective success of the collaboration.

Individual collaboration habits and collective collaboration practices are essential, as they embed lessons learnt in the past, they reduce the amount of time and energy to obtain the expected results (instead of “reinventing the wheel” each time), they can lead to “better” collaboration, as we reapply best practices discovered in the past. However, bad habits and poor practices can be very counter-productive. Such practices typically “emerge” from repeating past actions, albeit without enough scrutiny and critical sense. Bad collaboration practices transpire in all domains – unproductive work which wastes goodwill; students who do not learn effectively from their teachers; politicians who do not interact effectively with their constituency; inter-disciplinary research with does not overcome barriers of mutual incomprehension… Collaboration habits and practices often make the difference between success and failure.

The increasing societal complexity raises the bar for collaboration

The world changes and evolves more and more rapidly, creating permanently both challenges and opportunities. We must cope with ever increasing levels of complexity and in particular uncertainty. In such a context collaboration becomes increasingly important to address dynamically the resulting situations. But in turn collaboration also becomes itself more complex.

A larger group with more roles and responsibilities, a longer duration of the collaboration, a bigger number of tasks, events, competencies, … will induce more uncertainty, more diverse perspectives, more need for interdisciplinary collaboration (which is (naturally more difficult as the shared basis of participants is smaller). It will require more sophisticated forms of commitment and trust, the need for continuous learning and adaptation, more complex processes.

All this increases the overhead associated with collaboration. And this overhead creates costs, delays and often is a (very) severe drag on the quality collaboration. Reducing that overhead entirely changes how we collaborate. To take a few analogies: just think of the difference between travelling from Paris to Rome by foot versus in a safe horse carriage versus by car versus by plane versus by … Or between writing a document on a parchment sent by a horse-riding courier, versus creating a manuscript with a typewriter and then sending them by the post, updating it, sending it back… versus writing it on a computer and then sending it by email, annotating it and send it back versus collaborative editing versus… These changes are not just incremental, they change deeply how we collaborate.

Digital technologies – we need to start coping with complexity

New digital and social technologies have been emerging over the past centuries, and at an increasing pace over the past decades, to facilitate collaboration. Our current digital collaboration tools privilege informal exchange which can severely handicap group intelligence.

Today there are many hundreds of software tools to support collaboration – email, messaging, team and project management, date schedulers, meeting management, workflows, forms, knowledge management, electronic signature, whiteboards, videoconferences, blockchains… And even so, we do not really have progressed when it comes to collaborating more intelligently, more effectively, more efficiently, more inclusively, more pleasantly, safer.

We read endless useless messages, which, ideally, we should not have received. We chase inputs, confirmations, results… just to know what has been done or not; scheduling meetings that some participants better never attend; producing information that is forgotten before one week passes by… And despite hard work, we seem to progress at a snail's pace. And when it comes to collaborating across different organisations, we are back to the most basic tools…

Collaborations often are not sufficiently inclusive. Many people are not really included in the outcome of collaborative undertakings; they have the impression that their input and competence are not valued and that they could contribute much more.

Often, we repeat collaboration mistakes and do not to learn from them. Often ineffective collaboration carries sterile competition and useless coercion with it. We think that democracy is just about voting every few years, and that often it does not make a difference and that nothing changes. We still learn as in old times. Private health and public health are still terribly disconnected.

Since ever we favour informal exchange – talking and chatting. According to global historian Yuval Noah Harari, language was invented to gossip. We have essentially kept these habits for our face-to-face meetings and have extended these habits to our digital collaboration. Often “natural” communication is however deeply biased and ineffective. When we talk, contributions are collected sequentially and not in parallel. Also, it is uneasy to progress stepwise and in a focused way towards common purposes. The typical real-time applications for this purpose – notably email, chat and videoconference create a lot of noise and render cumbersome even simple tasks such as finding a common date.

This does not mean that we do not also practice structured interactions with the corresponding digital tools: we fill forms; we vote online; we use business process management applications. These applications tend to focus on form-based data collection and / or application specific rigid interactions. There are simple tools such a list fillers (e.g., a la Google Keep) or finding a common date (Doodle, Calendly etc.), template-based electronic whiteboards, e.g., for brainstorming (such as Mural, Miro or Klaxoon). And collaboration platforms such as Teams or Slack have integrated / connected to simple polling and form filling apps. Information collection is often rigidly set by specific “solutions” which collect biased inputs. The current solutions are functionally poor and inadequate for many purposes.

Some platforms, such as Trello and Asana, focus on project / team management. They presuppose a fixed structure of collaboration flows. They are relatively rigid and become difficult to maintain and use as soon as users try to go beyond a few standard processes. Also, they require a significant amount of learning.

As they focus on micromanagement, logically these tools do not differentiate the roles of participants: is somebody the initiator / leader of a collaborative flow? A participant? A simple observer? This induces that it is also not possible to differentiate the information that people receive by their role, and hence to organise work by levels of focus and importance: That increases the cognitive overload of the “hyperactive hive” of myriads of messages floating back and forth, and by consequence reducing the complexity and quality of the collaborative work we are able to cope with.

The more tools we use, the more fragmented our collaborations seem to be. Our digital tools often reinforce our bad practices rather than helping us to overcome them. And the problems related to data protection have made this even worse: on one hand, the collection of data is not sufficiently hampered to collect treasures of information about us, which are then used to inundate us with even more information; on the other hand, we are hampered by well-intentioned data protection regulations, which stop us from overcoming the intrinsic ever/growing complexities in fields such as personal and public health. We spend more and more time in front of screens but somehow seem to get less and less out of it, in terms of tangible impacts.

In summary, the digital tools developed during the past (+/-) 50 years have increased the speed of collaboration, but they also have dramatically raised the “noise” level, and perhaps even worse, they have fragmented collaboration to a point, where we quite often tend to shy away from the intrinsic complexity of collaboration, sometimes nearly at any price, to avoid the cognitive overload and the mental stress of having to weed through all this information. This fragmentation makes it practically very difficult to manage complexity effectively. This vastly increases the waste of time and resources involved in collaboration, increases inertia and slows things down… and thus greatly reduces the potential of our collaborative undertakings and the individual and collective benefits we get from collaboration.

What about the impressive Artificial Intelligence (AI) tools coming up? So-called “Large Language Models” (LLM, e.g., OpenAI’s ChatGPT, Google’s Bard, Baidu’s Ernie, and Facebook’s LLaMA…) are right now attracting enormous attention. They are touted as the biggest innovation after (or before) the steam engine. These tools deeply change how we collaborate, as a lot of time- and resource-intensive jobs can be largely subcontracted to virtual agents. But there are also rapidly mounting concerns. These programs easily “hallucinate” (make up content) and can be deliberately steered to produce massively “fake news”. They tend to reinforce conventional wisdom, as they are created from scouting existing content and weighting “probable” associations. They carry a range of risks; perhaps the most important one is to lose control over our understanding of the world and the decisions we take, individually and collectively. As with many previous outstanding technologies, LLM offer great potential for changing how we collaborate. But they will also increase complexity. They will require even more sophisticated ways of using our collective human intelligence, e.g., to better understand reality, to differentiate real from fake news, to create effective mixes of human and artificial intelligence, rather than to “simplify” things by getting rid of the humans.

Augmented Learning Collaboration (ALC) is a comprehensive systemic and holistic attempt to address the above challenges, and to convert them into shining opportunities.

Two illustrative examples


Bloomberg quotes a study by the University of North Carolina, indicating that companies (from all industries) waste about 25 000 USD per year per employee just because of attendance to non-critical meetings, i.e., meetings which participants would better not attend. The researchers recommend coping with this problem by better preparing meetings; notably, they suggest ahead of a meeting, to collect and prioritise the questions to be answered at the meeting, so that participants can decide if they need to attend, can just contribute their input without attending, or just ignore it. Also let’s remember that many meetings are regular and involve the same group of (potential) participants; the key topics are often conditioned by what happened at earlier meetings.

But now let us just take stock of the practical implications of this recommendation and visualise the communications needed for this preparation, so that participants can safely decide if and how they attend. We must conclude that this will create a lot of additional overhead. This kind of “friction” creates a lot of inertia when it comes to changing practices or habits.

At SymPlace we have calculated that companies using our future tools, which focus on reducing this overhead, could save between 5% and 10% of their total salary costs! Suddenly meetings would not only waste all this overhead, but would involve the right group of participants, who will have prepared before the meeting, combining slow and fast interactions: These meetings will involve less people, be shorter, be more effective and be more fun. And then things become even better: once we allow for tools that reduce overhead, the possibility of new practices emerges, allowing for more collective intelligence, more inclusion, alternating more rapidly through a savvy combination of individual and group thinking, slow and fast, asynchronous and real-time exchanges… An entirely new way emerges of working together, of deciding together, of having fun together, of socialising….

In the near future, SymPlace will especially focus on this application domain.

Patient – Doctor relation

A common scenario: after a few days with persistent headaches and diarrhoea, Lucy, a patient, gets an appointment two days later, through a scheduling system with her very busy general practitioner (GP). GP diagnoses a flu, prescribes a drug, DPX, for 10 days; he makes a note in Lucy's medical record. Lucy buys DPX, goes home; after two days she does not feel better but worse. Lucy stops taking DPX, but two days later feels even worse. She resigns herself that her GP “certainly” cannot help her. This story highlights: lack of therapeutic compliance (a major health problem affecting 30% of prescriptions), absence of feedback to GP (who will not learn), risks to the patient’s health, potential pharmacological or pandemic risks, which are not detected, perhaps a missed opportunity for progressing medical research, higher medical costs downstream, economic impacts of patients not going to work…

Ideally, the GP would follow up with her.his patient to check how things are going. But that would increase dramatically the workload of the GP. Again, the core problem is one of overhead…

SymPlace is currently involved in an attempt to launch a European research project to cope exactly with this problem… and the resulting opportunities: closing the loop would allow GPs to better adapt to the evolving health situation of their patients, and better know them.

And at the same time vastly progress medical research, pharmacovigilance, pandemic watch, preventive medicine…

Healthcare is one the major application domains, SymPlace will go after in the medium- to long-term, in cooperation with business partners.