Massive educational reform facilitated by technology

More than any other sector, education is currently poised for significant reform, of an expansionary, inclusionary, complementary nature, with the fingers of change that have long been present being gathered into inexorable industry-shifting waves. The hand of technology is the beneficial enabler.

Distance learning, and digital recording and streaming technologies have been steadily improving which has given way to a new way of connecting large worldwide audiences. What was the initial opening up of courses to online students has now turned into classrooms of huge online audiences in the range of 60,000-70,000 participants. This in turn has brought attention to the need and possibility of innovating educational methods to make material more dynamic. It may be possible to reorganize pedagogy in the new venue of the large-scale online audiences. Some ways are by communicating in real-time for both exercises and feedback loops to instructors, and by participating in dynamic exercises. This could help in making educational content more alive, experiencable, and interactive.

Behavior change through information availability and financial incentives

The presence of the big data era is increasingly difficult to ignore, but what is its influence exactly? Even if big data results in some beneficial outcomes, are humans being enslaved or empowered?

One example of behavior change through the availability of big data is personal power consumption. Home electricity consumption was reduced when individuals were able to self-monitor and obtain feedback on their resource use. There were 7-10% reductions with data and feedback [1,2], and a 32% reduction with data and feedback plus incentives [3].

It is a subtle line between the coercion of social pressure and other invisible influences and the ability to make a truly self-empowered choice whilst living in society. One answer philosophers have had to this question is that at least awareness of the issue helps. Irrespective of the source of motivations, the fact that responsibility-taking through greater awareness and access to information has been demonstrated could possibly be extended to have a similarly transformative impact on health and other sectors.

References
[1] Wood G, Newborough M. Dynamic energy-consumption indicators for domestic appliances: environment, behaviour and design. Energy and Buildings 2003 Sep;35(8);821-41.
[2] Parker DS. Pilot Evaluation of Energy Savings from Residential Energy Demand Feedback Devices. Solar Energy 2008 Jan; 13.
[3] Petersen JE, Shunturov V, Janda K, Platt G, Weinberger K. Dormitory residents reduce electricity consumption when exposed to real-time visual feedback and incentives. International Journal of Sustainability in Higher Education 2007;8(1);16-33.

Memory and empathy studies launch on crowdsourced health platform!

Two new health studies organized by DIYgenomics and collaborators have recently launched on the crowdsourcing platform Genomera. One is a memory study: Dopamine Genes and Rapid Reality Adaptation in Thinking and the other is an empathy study: Social Intelligence Genomics & Empathy-Building.

The Genomera platform boasts over 700 community members who are interested in participating in studies. While several of the approximately 30 listed studies investigate genetics as a related component of health, it is not necessary to have data from 23andMe or other consumer genomics services to join the health collaboration community and participate in studies. There are already 40 participants in the memory study and almost 20 in the empathy study.

The objective of the memory study is to see if genetic variants related to dopamine processing in the brain impact the processing of memories. The study is being conducted in conjunction with leading researchers at the Center of Cognitive Neurorehabilitation in Geneva Switzerland. The participation requirements are to complete an online Memory Filtering Task which takes approximately 40 minutes and a short Demographic Survey.

The objective of the empathy study is to confirm and extend research linking genetic profile and social intelligence, specifically whether individuals with certain genetic profiles may have a greater natural capacity for optimism and empathy, extraversion, and altruism. The participation requirement is to complete two short standardized online surveys for empathy quotient and other personality attributes. In addition, there is an optionally available Personal Virtual Coach app for empathy-building, a sort of SIRI 2.0 for mental performance optimization.

Mobile is the platform

At this moment, video-sharing is the number one growing application on the mobile platform.

Leading mobile analytics provider Flurry reports that Facebook (down approximately 25% since its recent IPO amidst lawsuits) is enjoying on average 22 minutes per day per user on the mobile platform.

This is perhaps a large number, but it hasn’t been growing as much over time as non-Facebook social networking (on average 25 minutes per day per user), photo & video sharing, music, and productivity apps on the mobile platform.

Surprisingly, only 53% of mobile apps are using analytics to measure usage. Of those, 75% use Flurry, which is currently resulting in 100,000 database calls per second and 8 petabytes of data.

Techniques for generating human dopaminergic neurons: reprogramming and differentiation

Perhaps more than any other medical field, stem cell research could have a significant and wide-reaching near-term public health impact. Cell-replacement therapies and other treatments are in currently in development for over 50 diseases.

Recent advances have been achieved in techniques for generating human neurons that could help – both through reprogramming somatic cells directly to neurons, and in differentiating pluripotent cells to neurons.

• Reprogramming is converting cells from one type to another by introducing additional genes (e.g.; transcription factors) to transform them. Recent research makes use of both canonical and novel transcription factors, and the application of growth factors, microRNAs, and small molecules. This technique is particularly vaunted as it may be possible to reprogram human adult cells such as skin cells, which are easily attainable, into any other type of needed cell, such as heart cells and neurons.
• Differentiation is the other main technique for generating neurons. In this case, human pluripotent stem cells are differentiated to neural cells with the introduction of growth factors and detailed cell-culturing processes.

Neurons and neural stem cells are of particular translational interest due to the lack of effective clinical therapies for neurodegenerative disease. While these emerging techniques are promising, some of the processes are relatively new, and the fidelity and functionality of generated neurons and neural stem cells in clinical application is yet to be confirmed.

Towards a fourth person perspective

Are the currently known perspectives, first, second, and third person, the only possible perspectives? With modern technology, it might be possible to construct a fourth person perspective, or even a fifth and sixth, that offers a new view on ourselves and different interaction possibilities with the world. One obvious means of this could be the concept of Siri 2.0, a mental performance optimization platform that reduces bias, serves as a personal virtual coach, and buffers communication.

Grounds for, and a potential understanding of a fourth person perspective may be found in philosophy. Philosophers such as Charles Pierce, Habermas, Levinas, Roarty, George Mead, and Stephen Darwall have helped to characterize salient aspects of the first, second, and third person perspectives, and this work could be examined, and extended to a fourth person perspective. Some of the most helpful elements that a fourth person perspective could afford are a different means of introspection and performative action-taking.

Big data facilitates new era of knowledge, education, and thinking

Big data and the internet continue their sweep across modern life by facilitating a new era of education, and possibly, thinking. As traditional educational institutions have become financial institutions intent on merchandizing their brands, students are finding other means of accessing educational content.

At present
Some of the newer models include MIT OpenCourseWare, the Khan Academy, Coursera, and Codecademy. These free or low-cost education services confer the direct benefit of their programs, and advantages by using the large numbers and real-time aspects of the internet to obtain and incorporate immediate feedback from growing student populations. This is leading to a better education product, and a mechanism for learning about learning.

The near future
A next stage could add course-level (rather than degree-level) accreditation and a basic algorithms interpretation layer à la Google Translate, Spell Check, and Ngram Viewer. Simple machine learning algorithms applied to large data sets could allow an expansion from quantitative testing to semantic testing (and more importantly, semantic living, in the sense of a broader intellectual life). Core knowledge elements could be identified in data corpora and reviewed for comprehension in student-produced material.

The farther future
Taken to its logical extreme, what if distance learning were to completely replace local educational institutions? Are there risks of homogenization of thought if everyone is taking the same classes from leading worldwide professors? Does personalized learning, via sommelier-assembled curricula, increase inherent biases that might otherwise be countered by institutional education? Does the U.S. need 5-10 philosophy/etc. professors at 5-10 universities per state? Clearly there are systemic aspects, and costs and benefits, of a more radical reinvention of education. These can be managed effectively through the lens of overall goals, perhaps the most important of which is extending the depth and capacity for thinking, both within individuals, and to more individuals.

Big data analysis and politics

Big data analysis is popping up in more contexts, and what better place in an election year than in politics. A ‘barcamp’ for campaign finance took place at Stanford May 19-20, 2012 where a hundred erstwhile participants quietly busied themselves in ten teams addressing different ways to apply big data and informatics to analyzing and improving the political process.

At the weekend hackathon, DataFest: Analyzing campaign finance data, participants learned some basic R, scripting, and quantitative data techniques to analyze data from websites like Influence Explorer. One project, for example, attempted to determine if House of Representatives Members who changed their vote at the last minute might have been influenced by campaign donations, or other factors obtained through data-mining techniques such as constituent demographics, ideology, and party voting record.

Key challenge of our era: health and preventive medicine

Delivering health care and keeping populations healthy is a key problem of the current era. Health expenditures currently comprise 17% of U.S. GDP and are growing; simultaneously health in the U.S. is in decline, with a new CDC report estimating that by 2030, 42% of American adults will be obese, compared to 34% today and 11% will be severely obese, compared to 6% today.

The Realization of Preventive Medicine
A key part of addressing health challenges is the realization of preventive medicine. Preventive medicine and health maintenance consist of identifying and managing conditions in the 80% of their life cycle before they become clinical, ideally avoiding clinical onset. Workable models for the execution of preventive medicine need to be developed. By definition, a broader ecosystem than the traditional medical establishment will be participating in all steps of the value chain ranging from health research to clinical delivery. More flexible regulatory models are needed that preserve the core ethical principles of the traditional models, but are geared towards the internet era and an expanded notion of health and health maintenance with a larger ecosystem of service providers and participants. The payments ecosystem needs to adapt in parallel, allowing for a wider range of payment mechanisms including out-of-pocket payments, H.S.A. dollars, patient advocacy group funding, and traditional (and increasingly diminishing) insurance payments.

Obtaining models for singularity futures thinking

The challenge is called out by science fiction writer Vernor Vinge as being related to the technological singularity, namely that any one future technology change could be so fundamental across all aspects of life that it is hard to write plausible science fiction, and more generally impacts how we think about the modern and future world. Any next node that has sufficient transformative power (e.g.; like the internet) could change things so fundamentally, globally, multi-dimensionally, and quickly that its impact would be essentially beyond cognition. Moreover, while there are some potential candidates visible for the ‘next internet’ such as smartphones, 3D printing, biotechnology, nanotechnology, and robotics, the real next node is likely to be an unforeseen discontinuity.

Comprehensive survey of thinking models
There is a paucity of models for thinking comprehensively and critically about the future in rigorous, sophisticated, justifiable, and transferable ways. A project that should be undertaken if not done so already is an examination of different models for structuring thinking from different disciplines. There is value in this at two levels: first generally in identifying, characterizing, and synthesizing different models for structuring thinking, and second in applying these models cross-disciplinarily to existing areas, and to new areas such as thinking about the future.

Eliciting explicit models for structuring thinking
The models that are used to structure thinking in different fields need to be made explicit. Practitioners immersed in fields may not be easily disposed to articulate these models. For example, it may be novel to inquire ‘What is the model for inquiry in this field?’ or even to have the concepts and vocabulary for explicating them.

Fields with models for structuring thinking
Some of the obvious fields to investigate for eliciting established models for structuring thinking are philosophy, complexity (complex adaptive systems, chaos theory, symmetry, etc.), computing (artificial intelligence, machine learning, knowledge representation, data management, etc.), systems-level disciplines (ecology, biology, cosmology, etc.), and social sciences (sociology, anthropology, economics, etc.).

The challenge of fishing structure and content from academic fields
Some of the immediate obvious barriers in accessing models for structuring thinking from academic disciplines are nomenclature and insularity. Semantic and conceptual nomenclature may prevent easy access to fields, but are largely a veneer that may be penetrated with a variety of translation techniques and concept mapping. Much more problematic is the potential lack of available suitable content in these fields. By default, many areas of academia are not externally-focused applied disciplines but rather inwardly-focused insular disciplines engaged in cataloging and interpreting the thoughts of their own ancestral brethren. The accompanying applied dimension to every field that would explicitly render the core ideas accessible, and proven and useful through deployment seems to be absent from many fields. Rather than being perceived as less pure of an exploit, the application of the central ideas and structures would seem to be a key raison d'être for these fields of knowledge.