Microcommunication: high-valence minicontent bursts

Micro is not just for microformats, hardware miniaturization, microexpressions, micropractices, and political microtargeting, it can be a concept and a platform. One use is in the new concept of microcommunications.

Microcommunications are very small communications, possibly carrying a burst of high-valence content, emotional or otherwise. Conceptually, the next node smaller than tweets, microcommunications are ultra-lightweight, where no response is required but could be two-way chatted. One reason that microcommunications are more light-weight is because they are coming from a personified virtual coach as opposed to a real person. An example of microcommunications is in Figure 1, light-weight SMS messages from a Siri-2.0-like personal virtual coach used in the DIYgenomics Social Intelligence Genomics & Empathy-Building study.

Microcommunications from the empathy-building module are displayed. A range of other applications are currently in design, modules for developing and enhancing mindsets of leadership, charisma, motivation, influence, and gratitude.

Figure 1. Empathy-building Microcommunications from your Personal Virtual Coach. (Source: DIYgenomics Social Intelligence Genomics & Empathy-Building Study)

The Infovizzy Social Layer

In the current era of big data, it is increasingly expected that there be some way to visualize data in a readily consumable infographic. Figure 1 shows one such example, for the social networking site, LinkedIn, with the infographic web service provided by LinkedIn Maps. The nodes in the social networking fabric are other individuals.

Figure 1. Infographic of One Person’s LinkedIn Relationships.

Looking at the figure, some of the aspects to notice are that this person is interacting in different kinds of communities. One of the kinds of communities is clusters that have some high degree of central linkage (the pink and green clusters on the right). Another kind of community is those where the connected people are themselves more broadly linked (the majority of the fabric, around the name box). The farther away communities in the infographic are separated by time (graduate school), and distance (different geographical continents).

However, all of this could be misleading, because the algorithms applied to execute the visualization might not be the most accurate mapping of the relationships with this person and these communities in real life. Also the visualization has an inherent relativism that may result in bias. The infographic is indicative of this person’s relationships in those communities, not conclusive information about the communities themselves.

This kind of infovizzy display could be extended as a digital anthropology tool for viewing the overlaid networks of whole communities. More complete inferences could then be made regarding the closeness and closedness, expansivity, density, breadth, volume, fluidity, and connectedness of different communities. Time lapse analysis could show how and how fast communities grow and fade, especially assessing which kinds of new elements come into communities to sustain and broaden them. Performance metrics for the quality of output of communities could be developed, where relevant.

Supercomputing: 16 petaflops, schmetaflops?

Supercomputing advances continue to exponentiate – the world’s best machine (IBM’s Sequoia - BlueGene/Q installed in the U.S. at LLNL) currently has 16 petaflops of raw compute capability.

Figure 1. Data Source: Top 500 Supercomputing Sites

As shown in Figure 1, the curve has been popping – up from 2 to 16 petaflops in just two years! However for all its massivity, supercomputing remains a linear endeavor. While the average contemporary supercomputer has much greater than human-level capability in raw compute power, it cannot think, which is to say pattern-match and respond in new situations, and solve general rather than special-purpose problems.

For the future of intelligence and cognitive computing, the three-way horse race continues between enhancing biological human cognition, reverse-engineering and simulating the human brain in software, and hybrids of these two.

The ‘So What’ Interface – a Prescriptive Layer

When we see a calendar, we know what the information means, and readily map this to potential action-taking. This is not as clear with data displayed from the new era of the Health Internet of Things - the increasingly ubiquitous information climate of consumer biophysical monitoring and quantified self-tracking that surrounds us.

So far the main focus has been on Apple-y/iOS-y design and data visualization in health data streams such as 23andMe genomic data, Fitbit data, the Eatery food diary summarization data, or EKG data tracking across a smartphone screen when held up to the chest. However, we are all still scratching our heads as to what to do as a result of seeing the information.

The Prescriptive Interface
A whole new conceptual category of ‘what to do with this data’ needs to be articulated, named, and implemented – an intuitively-apparent prescriptive layer of suggested action-taking as a result of viewing the data. The two biggest challenges are first, these data streams are only nascently available and therefore meaning has not yet been determined in many cases, and second, there is little effort in determining and implementing a core set of principles for behavior influence and ambient suggestioning. Having these challenges solved could help constitute what is missing in the health data streams but not the calendar – knowing what the information means and what action to take as a result.

The Rapid Approach of the Health Internet of Things

The efforts of the eHealth movement have been quietly gathering steam for the last five years and are finally fulminating into what could be a significant transformation in the management of health and health care. The most encouraging sign of change is that it consists of not just the usual shiny new technology solutions, but more importantly, structural changes in the public health system:

The 80% slim-down of the doctor’s office visit…

• Telemedicine reimbursement: As of March 2011, only 12 states offered reimbursement for telemedicine services (e.g.; telephone, email, video consultation), and at lower rates than in-office visits. Now more payers and states are starting to approve telemedicine reimbursement, which could be a huge cost savings for the industry as it is estimated that 70% of physician consultations could be handled by phone.

• Majority of diagnosis is straightforward: It is estimated that in 18/20 cases (per Singularity University FutureMed), diagnosis is straightforward, and could be accomplished via telemedicine.

• Trend to higher deductible plans: many programs are underway to transfer employees to higher-deductible plans which both reduces costs and puts more of an emphasis on preventive medicine.

Significant progress could be made with these structural changes acting in concert with the new generation of healthtech tools in areas such as:

• Health sensors, examples: continuous glucose monitoring patches, EEG sensors, ambient assisted living
  

• Quantified self-tracking devices, examples: Fitbit, Zeo sleep tracking, Body Media, Pebble Watch, Nike Fuel Band, Basis Watch

• mHealth (mobile health) apps, examples: The Eatery, MoodPanda, Map My Run, Cardio Trainer

Refocusing on the customer to improve startup failure rates

Even when startups have a seemingly good idea, high-powered team, funding, and marketing, most fail. Instead of accepting this as normal (a badge of courage and a ‘fail early, fail fast’ mentality), many people have started to question this, and congruently with Silicon Valley’s problem-solving mindset, try to solve the high rate of startup failures.

It is not that startups fail to build products and services, it is that they fail to build products and services that anyone WANTS.

Focusing on the customer and their needs, first, last, and at every step of the way, is suggested as the answer for creating startups that are far less likely to fail. One advent in tools to help develop and stay in the customer-centric mindset is the ‘canvas’ concept. The canvas is a large paper with the quadrants of the business model set forth, and teams populate the quadrants with content written on post-its which can be dynamically updated as ideas change and assumptions are validated. Some examples are the Lean Startup Machine Canvas and Business Model Canvas.

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.