Augmented Learning Collaboration (ALC) transforms Health / Quality of Life

ALC has the potential of deeply transforming health, reducing therapeutic non-observance, improving prevention, enrichening medical research, strengthening pharmacovigilance...

Health & Quality of Life are another critical global public good, in the making, of humanity. The relationship between patients and health professionals, and more generally the health system, can be seen as collaborative undertaking. CoViD catalysed and highlighted a situation where cracks in public health systems all over the world is about developing and leveraging this cooperation for the dignity of everybody and the solidarity of us all.

In the medium- to long-term, typically over the next decade, ALC could very significantly progress in public and individual health. It could dramatically reduce therapeutic non-compliance. More generally it opens the opportunity of complex coaching combining social assistance, professional counselling, psychological guidance and health coaching, thus enabling a holistic approach to quality of life. It could help to coordinate healthcare activities at micro-, meso- and macro-level. It could improve prevention, holistic approaches to quality of life and health, spanning from young to old age. And it could contribute to make public health more sustainable, notably as patients are empowered to take better care of their health (especially prevention) and their therapies, and as healthcare professionals can focus on added value rather than spending much time on menial activities, which can be “subcontracted” to symBots and the “guided patient” and / or her.his relatives. This opens entirely new perspectives on the quality of life of dependent people and the chronically ill.

Some examples of future symBots and symFlos:

  • Circular long-term patient-centred symFlos could connect patients with healthcare professionals, and especially their general practitioners, to support new collaborative practices and habits whereby patients would be guided / coached through treatments, would provide feedback on prescriptions (where they followed or not? which was the result?). SymBots would embody in their “genotype” the knowledge about medical protocols. Thus, it could identify situations where human health specialists need to participate and / or an emergency situation would appear, and indirectly, reduce the number of situations where they are a priori less needed.
  • Different pathologies and treatments would correspond to different symFlo templates structuring the symFlo according to the milestones in the therapy.
  • Circular symFlos, supported by digital ledgers, running from patients to public health systems, especially by involving bots in the symFlos, would come handily to alert and / or monitor emerging individual and collective health risks such as pandemics, and / or regularly update clinical trial data for drugs.
  • Voluntarily shared patient data, made traceable, anonymous and monetizable for participating volunteers, could, after providing added value through machine learning and data sciences, provide invaluable longitudinal knowledge for health research purposes and personalised health services.
  • SymBots would detect weak signals for epidemics and / or monitor spreading of epidemics, and to collect systematically feedback on drug usage.
  • SymCommunities would provide effective support for health education and coaching, both between patient-experts and between medical doctors and patients. It would become possible to test advice and feedback.
  • Positive health management, e.g., for personalised nutrition and exercise, could be significantly strengthened.

In another conversation with ChatGPT, independently of the above examples, came up with its own ideas; after some iterations in our discussion, we arrived at the following:

ChatGPT: Here's a structured list that merges the different ideas and examples of Augmented Learning Collaboration (ALC) in the context of health, emphasizing inter-human collaboration and illustrating new social practices:

Collaborative Health Challenges SymFlo:

  • Organize health challenges or competitions within communities or workplaces.
  • Foster inter-human collaboration and teamwork to achieve common health goals.
  • Utilize a symBot to facilitate team formation, track progress, and provide support.

Peer Mentorship and Support SymBot:

  • Connect individuals with similar health conditions or experiences.
  • Promote peer mentorship, advice sharing, and emotional support.
  • Facilitate inter-human collaboration, mutual learning, and encouragement.

Health Research Crowdsourcing SymFlo:

  • Engage patients, caregivers, and citizen scientists in collaborative health research.
  • Crowdsource data collection, sharing of experiences, and contribution to research projects.
  • Utilize a symBot to coordinate data collection, curate research questions, and facilitate knowledge dissemination.

Co-creation of Personalized Treatment Plans SymBot:

  • Enable collaborative decision-making in personalized treatment plans.
  • Involve healthcare providers and patients in shared decision-making processes.
  • Foster inter-human collaboration, patient empowerment, and customized healthcare strategies.

Community Health Forums SymFlo:

  • Establish virtual forums or social platforms for community health discussions.
  • Encourage open dialogues, sharing of local health information, and collective problem-solving.
  • Utilize a symBot as a central hub for moderation, resource provision, and fostering collaboration.

Interdisciplinary Healthcare Teams SymBot:

  • Support inter-human collaboration among diverse healthcare professionals.
  • Facilitate communication, information sharing, and task delegation within interdisciplinary teams.
  • Enhance collaboration, care coordination, and patient outcomes.

Health Education Co-creation SymFlo:

  • Foster collaborative development of health education materials and programs.
  • Encourage inter-human collaboration in curriculum design and content creation.
  • Utilize a symBot to facilitate resource sharing, feedback exchange, and collective improvement.

Inversely, the application domain “Health” presents specific challenges for ALC, which are most relevant for many other application domains. Privacy-by-design is an aspect which SymPlace gives special importance, and which is addressed through its partnership with Refinio. Another key aspect is the interaction of VPAs with symBots, and the interaction between symBots, which allow users to share their data in a controlled way with data ecosystems, and then, inversely, to benefit through customised therapies and guidance, from customised knowledge generated through machine learning technology and data sciences based on big data.

Also, Health is a highly relevant application domain of ALC in the sense that micro-, meso- and macro-collaboration interact in complex ways, which directly affect effectiveness (and hence quality of life), efficiency (and hence economics) and innovation (new practices, new treatments…). Some ideas, of how this can play out, are sketched in a discussion with ChatGPT, in one of the annexes of this White Paper. The interaction between “micro”, “meso” and “macro” plays out in all application domains, such as for instance:

  • Business: global versus local versus individual
  • Education: educational policies versus schools and competence communities versus individual learning and teaching
  • Politics, democracy and governance: global geopolitics versus national politics versus regional politics versus local politics versus individual citizen living in society and participating in politics

We will get back to this later in the FAQ on transforming politics, democracy and governance.