They are already here

As a chunk of investments go down the drain seeking extra-terrestrials, drug resistant bacteria that cause two million illnesses and 23 thousand deaths in the US alone (1), have gotten little attention. These true extra-terrestrials, who got here hitching a ride on an asteroid, have been powerful and robust over a few billion years. They have transformed the planet, oxygenated it and prepared it for larger organisms, that would fall prey to them. They could dance in unison, divide and multiply and evolve in short horizons, aided by almost countless experiments. They will create organisms that could walk and eat, to satisfy their every whim, with an intelligent control system, that "advanced life," calls the microbiome. They could trigger feelings, switch their occupants' brain on and off, get them to eat what they would like and even decide on an expiry date for the host. Such is the power of the single cell organism, they have dominated the blue planet since their arrival, perhaps by chance.

ET is already here and they have been for over four billion years. As the greatest scientists fear, they are indeed more intelligent as they have not only designed an environment for themselves but also populated it with organisms they could control for their own benefit. As the chemists seek soil from far and wide to conquer the fully optimized machines they could only observe under a microscope, as the pharmaceutical companies run away from declining economics of third world diseases, as the NIH struggles to figure out how to advance thoughts and action, as the foundations that proclaim to lift humanity from disease and strife stop at mosquito nets and commercials, the single cell organism organizes further to consolidate control.

The worst idea of human history is the thought that they are "advanced."

(1) http://esciencenews.com/articles/2016/09/09/how.fight.drug.resistant.bacteria

The fifth force

Recent research from the University of California, Irvine, (1) speculates on the existence of the fifth fundamental force field, apart from gravitation, electromagnetism and the weak and strong nuclear forces. This is possibly in a newer direction that counters the tendency of contemporary physicists to spawn yet another "fundamental particle", anytime they do not understand a phenomenon. Speculating on the existence of a newer force, at the very least, shows some creativity in high energy physics, resting on the laurels of their recent discovery of the God particle, in the noise generated in Geneva.

It appears that we are in a stalemate. Physics, dominated by technicians, has been running amok, plunking billions down the tunnel, proving particles of fantasy. It appears that few are asking if proving fantastic particles is advancing the field in any way. Recently, the engineers hung mirrors to measure gravity waves to the tune of the diameter of a proton to prove two black holes merged nearly a billion years ago. Could somebody prove otherwise? Physics has reached a plateau, in which physicists can prove anything with the help of engineers.

Since we have over hundred "fundamental particles," already, perhaps defining a new "fundamental force field," is in a better direction.

(1) http://esciencenews.com/articles/2016/08/15/uci.physicists.confirm.possible.discovery.fifth.force.nature

Deeper learning

Recently, statistical and mathematical techniques that have been tried and abandoned decades ago to teach computers to be smarter, have surfaced again with better sounding names. With nearly zero cost computing power in the cloud, some companies have been plunging head first into the deep abyss. Deep learning is stylish - some even try "deep mind," in an attempt to replicate the complex human. What the younger scientists may not know is that most of what they have found, has been known for a long time and one should not take advancements, due to only the recent availability of cheap computing power and memory, as "ground-breaking." Disappointments may be in store for those, highly optimistic of "solving," human intelligence. The convergence of Neuroscience and Computer Science is a welcome trend, but a dose of realism may be apt medicine for those modeling the mind, downloading the brain and possibly curing physical death.

Even since she stood up in the African Savannah, a few hundred thousand years ago, the human has been puzzled by her own mind. She searched the skies, climbed mountains and dived into the oceans, seeking the object, she could not herself define. The theory of consciousness has eluded her, for what she was seeking obviously interfered with the tools she was using. It was the ultimate prize. If she could understand herself, then, a whole new world could open up. The body can be separated from the mind, and the latter then could be rendered immortal. The mind could be replicated and networked and perpetuated across space and time. She could create and capture imagination at will. She could solve problems of infinite complexity, travel into interstellar space or even to another universe. If only, she could understand the mind and concoct a theory of consciousness. But alas. it is not to be. Whatever one calls it, the "neural network," has failed to show signs of consciousness. Yet another technology is substantially sub-optimized by engineers and scientists, most comfortable with deterministic answers to complex questions.

Ignorance is highly scalable in the presence of infinite computing power.

Biology meets computing

The ease of biological manipulation by chemical means has held life sciences companies back for over a century from exploring the system, that is equally receptive to electromagnetic interventions. Recent news that GSK has partnered with Alphabet to advance the field of bioelectronics is encouraging. The idea is to impart electrical signals to neurons by micro implants to cure chronic diseases. Although it is a profitable path to pursue, some caution may be in order.

There is a long history of engineering experts attempting prescriptive interventions on biological systems with an expectation of deterministic outcomes. Humans are generally good in engineering and traditional computing but biological systems do not behave in such a predictable fashion. Their engineering competence comes from selection, in which simple tools based on Newtonian Physics let them survive the harsh environment they were in for nearly hundred thousand years. The modern game is distinctly different and it is unlikely that they possess the skills to fast track with the hardware they have built up. With "Artificial Intelligence," soaking up the air waves, it is important for technology giants to bias toward humility. As projects such as "death cure," so slow to come to fruition so as to annoy the technologists behind it, perhaps getting not too excited about curing diabetes through neuron stimulation is a good idea. After all, nature took four billion years to get here, albeit, it was without a computer farm that soaks up a high share of the world electricity production. Competing with nature is likely to take a bit more than that.

The convergence of biology and computing is unavoidable. However, it is unlikely to be advanced by those with stagnant notions of either field.

Cognitive monopoly

Major discontinuities in human history have often led to monopoly positions in subsequent markets, driven by winner takes all characteristics. In the modern economy - automobiles, airplanes and computers certainly fit this view. In the case of the internet, invented by tax payer investments, attempts by a few to monopolize the flow of electrons, have been averted thus far. But "Net neutrality," is not something that rent seeking behemoths are likely to accept in the long run, even if they did not pay for it.

The nascent wave - machine cognition - has the monopolists scrambling to get the upper hand. In this wave, capital, as measured by megaflops and terabytes, has a significant advantage. The leaders, plush with computing power, seem to believe that there is nothing that may challenge their positions. Their expectations of technology acceleration appear optimistic but nonetheless we appear to be progressing at an interesting enough trajectory. Although many, including the world's leading scientist, are worried about runaway artificial intelligence, one could argue that there are more prosaic worries for the 7 billion around the world.

Monopolies generally destroy societal value. Even those with a charitable frame, acquire the disease of "God complex," as the money begins to flow in. Humans are simple, driven by ego and an objective function, either biased toward basic necessities or irrational attributes that are difficult to tease out. Contemporary humans can be easily classified by intuition, without even the need for the simplest of algorithms - Nearest neighbors - into those with access to information and those who do not. Politicians and policy makers have been perplexed by the fact that such a simple segmentation scheme seems to work in every part of the world population from countries to counties and cities. Cognition monopolists will make it infinitely worse.

Can Mathematics be monopolized? The simple answer is yes. In a regime of brute force over highly available computing power for a few, answers could be found by the blind and the dumb. Perhaps, there is still hope for the rest as we have seen this movie before.

Small step toward bigger hype

Recent research from the University of Liverpool (1) suggests a method by which computers could learn languages by semantic representation and similarity look-ups. Although this may be in the right direction, it is important to remember that most of the work in teaching computers language or even fancy tricks, is not in the realm of "artificial intelligence," but rather they belong to the age old and somewhat archaic notion of expert systems. Computer giants, while solving grand problems such as Chess, Jeopardy, Go and self driving cars, seem to have forgotten that rules based expert systems have been around from the inception of computers, much before some of these companies were founded. The fact that faster hardware can churn larger set of rules quicker is not advancing intelligence but it is certainly helping efficient computing.

Engineering schools appear to still teach ideas that are already obsolete. Programming languages have been frozen in time, with prescriptive syntax and rigid control flow. Today's high level languages are certainly practical and immensely capable of producing inferior applications. Even those who could have "swiftly," assembled knowledge from previous attempts seem to have concocted together a compiler that borrows from the worst that have gone before it. As they proclaim "3 billion devices already run it," every hour an update is pushed or conduct conferences around the globe dotting and netting, the behemoths don't seem to understand that their technologies have inherent limitations.

Computer scientists, locked behind ivy walls, are given skills that the world does not need anymore.

(1) http://esciencenews.com/articles/2016/05/06/teaching.computers.understand.human.languages

Nutritional genetics

Research from Indiana University (1) speculates that physical traits could be substantially impacted by food. The adage that "you are what you eat," appears to work at a deeper genetic level. In low complexity biological systems, such as ants and bees, variation in food at the larvae stage seems to explain specialization at the genetic level. If true, this has implications beyond what has been observed.

Food, a complex external chemical, has to be metabolized, utilized and purged by biological systems routinely. Although it is clear that available energy content and processing efficiency will depend on the variation and complexity in inputs, the idea that food could cause genetic specialization is fascinating. More importantly, this may lead to better design of food to favorably impact physical and mental conditions, the latter possibly holding higher promise for humans.

Ancient cultures and medicines have routinely relied on food as the primary way to remedy tactical issues. The Indiana research may provide a path to propel this idea into more systematic and planned impacts.

(1) http://esciencenews.com/articles/2016/05/12/you.are.what.you.eat.iu.biologists.map.genetic.pathways.nutrition.based.species.traits

No safety net

Recent research from Johns Hopkins (1) suggests there are over a quarter of a million deaths in the US per year due to medical errors. It is a sobering observation that future generations will look back on with anguish and perhaps, incredibility.  At the height of technology, we are slipping, not because of lack of know-how, but rather, lack of application. One preventable death is too much and the fact that medical errors are the third leading cause of death in the US, is immensely troubling.

Unfortunately, technology does not solve problems. Bigger data and faster computers are likely irrelevant if they cannot fundamentally influence decision processes and allow information flow to enhance decision quality. It is not about precision - there is no such thing - but a systematic use of all available information at the point of decision. Further, the human brain, with its inherent limitations, is unable to minimize downside risk in a regime of high utilization and volatility. A loss of life, a traumatic and life changing event for any healthcare provider, looms high but the environment simply does not allow anything more than what is tactically possible. The lack of a safety net below cascading, complex and error-prone processes suggest the need for a sudden and impactful change that most technology companies are unable to help with.

It is high time that healthcare embraced practical applications of available technologies to improve patient health and welfare.

(1) http://esciencenews.com/articles/2016/05/04/study.suggests.medical.errors.now.third.leading.cause.death.us

Biological storage

Recent news (1) that University of Washington researchers have successfully stored and retrieved data using DNA molecules is exciting. As the world accumulates data - already many tens of millions of gigabytes, growing at an alarming rate, storage capacity and efficiency are becoming top priorities in computing. With material sciences still lagging and computer scientists clinging to the Silicon status-quo, it is important that the field takes a biological direction. After all, nature has coded and retrieved complex information for ever. Using the same mechanism is likely a few orders of magnitude more efficient than what is currently available.

DNA, the most important biological breakthrough over four billion years, has been almost incomprehensible for humans, arguably, the best product of evolution. Lately, however, they have been able to understand it a bit better. Although some argues that the human genome map is the end game, it is likely that it is just a humble beginning. The multi factorial flexibility afforded by the DNA molecule may allow newer ways to store binary data, making it akin to the other belated innovation - quantum computing. Here, thus far, research focused on mechanistic attempts to force fit the idea into the Silicon matrix. Taking a biological route, perhaps aided by the best functioning quantum computer, the human brain, may be a more profitable path.

Biology could accelerate lagging innovation in material sciences and computer science.

(1) http://esciencenews.com/articles/2016/04/07/uw.team.stores.digital.images.dna.and.retrieves.them.perfectly

Hole in the soul

The super-void, that presented itself in the background radiation, sporting a size of close to two billion light years, has baffled scientists. A few years after its discovery, no reasonable explanation is forthcoming. The standard model, that most still pin their research on, has shown so many cracks that scientists who adhere to it are beginning to look like economists, who have similar difficulty letting go of established theories. Hunting in the particle forest, either to propose new ones or to prove the hypothesized ones indeed exist, has been the favorite past-time of physicists. Recently, they even measured the reverberation of gravity waves, generated by an event over billion years ago, to the tune of the diameter of a proton. Now, it is nearly impossible to disprove anything in Physics.

Biologists and chemists are in the same spot. Technology is advancing so fast that scientists are running out of hypotheses to prove. There are so many engineers and technologists, pumped out by the elite educational institutions around the world, who stand ready to prove anything in science. We are fast approaching a regime of dearth of ideas and an oversupply of proofs. Is this what was envisioned a few decades ago by visionary scientists, who predicted a future in which there would be nothing more to prove. If so, it would be bleak, indeed.

Creating hypotheses, a skill that was left undernourished for a few decades, may need to be brought back.

Return to hardware

Hardware design has been losing luster for many decades in the world of computers. Software has been riding high, partly aided by hype and partly due to the younger crowd plunging deep into apps to make a quick buck and associated fame. Monopolies have been created on inferior operating
systems and office automation, while those who are opposed to it have been chasing public domain noise. Even educational institutions, following the latest ephemeral trends, with half lives of runway fashions, have been churning out courses with little utility for the future. Some have been putting content on-line and others still want students to toil under fluorescent lighting on wooden desks, while picking up the skills of the future.

Computer science has gone astray. Humans, susceptible to incrementalism, have been chasing false dreams on antiquated frameworks. Just as their predecessors, modern humans always attempt to scale inferior performance by massive parallel processing. They stack circuits ever closer and they network computers ever larger in an attempt to squeeze out performance, Meanwhile, software companies, hungry for speed and scope have created clouds of silicon that appear to suck up most of the production capacity in energy. Data have been accumulating in warehouses, some never to see the light of day and others, creating havoc and panic in complex organizations. Economists often worry about bubbles, for some are not so sanguine about rationality but technologists never dream of a software bubble as they presuppose such conditions.

It's time to leave synthesized voices, fake artificial intelligence and bleak games behind and return to hardware. Without two orders of performance improvement, there are very few apps that would move humanity and that can only come from practical quantum computing. Notwithstanding the much anticipated version X of existing operating systems and mobile phones, without innovation in hardware, humans will swim in a sea of mediocrity for ever. There are glimmers of hope, however. Recent news that larger quantum circuits could be built in more direct ways (1) is encouraging.

Educational institutions have an obligation to move society to the future and not just following trends that will fill up class rooms - physical or virtual.


(1) http://esciencenews.com/articles/2016/03/26/unlocking.gates.quantum.computing

Innovative Life Sciences

Recent research (1) that shows Graphene could be utilized to interact with neurons open up a new avenue for research and practice to cure cognitive disabilities and possibly treat CNS diseases. More importantly, this is a profitable direction for biosciences to accelerate innovation. From the moment humans figured out they could impact the system by the ingestion of chemicals, they have been focused singularly on that. The system, however, is clearly electromagnetochemical, providing plenty of opportunities for more elegant interventions without multifactorial and unpredictable long term effects. Chemistry, has plateaued and life sciences companies with a vision of the future, have to move in a direction they are uncomfortable with.

Such an innovative departure in life sciences will take new leadership and a collaboration with emerging ideas and technologies. The impact will be far reaching - possibly replacing chemicals as the only non-invasive intervention. Medical education has to consider robotics, precision electronics and even high energy physics. Computer science and information science have to become integral to diagnosis and treatment. The meaning of intervention has to change - with impacts on the brain and the body simultaneously for optimum effect. In a regime of subdued bugs, unable to threaten the mighty human, it is going to be a battle against the body and the mind. Here, chemicals fail.

Innovation in life sciences will not come from incremental improvements to existing therapies, it will come from embracing hitherto unknown intervention modalities.

(1) http://esciencenews.com/articles/2016/01/29/graphene.shown.safely.interact.with.neurons.brain

Data science blindspot

Recent research from MIT that claims their "data science machine," does better than humans in predictive models is symptomatic of the blind spots affecting data scientists - both the human and non-human variety. Automation of data analytics is not new - some have been doing it for many decades. Feature selection and model building can certainly be optimized and that is old news. The problem remains to be how such "analytics," ultimately add value to the enterprise. This is not a "data science problem," - it is a business and economics problem.

Investments taken by companies into technologies that claim to be able to read massive amounts of data quickly in an effort to create intelligence are unlikely to have positive returns for their owners. Information technology companies, who have a tendency to formulate problems as primarily computation problems, mostly destroy value for companies. Sure, it is an easy way to sell hardware and databases, but it has very little impact on ultimate decisions that affect companies. What is needed here is a combination of domain knowledge and analytics - something the powerpoint gurus or propeller heads cannot deliver themselves. Real insights sit above such theatrics and they are not easily accessible for decision-makers in companies.

Just as the previous "information technology waves," called "Enterprise Resource Planning" and "Business Intelligence," the latest craze is likely to destroy at least as much value in the economy, if it is not rescued from academics seeking to write papers and technology companies trying to sell their wares. The acid test of utility for any "emerging technology," is tangible shareholder value. 

Machines do not learn!

Artificial Intelligence is fashionable again, aided by cheap computing and cheaper memory, computer behemoths have been diving head first into the abyss. It has happened before, albeit, with much limited computing power. Just as in the previous iteration in the 80s, the current excitement may die down in a few years. Simulated machine voice and jeopardy are easier problems to solve but finding a cure for cancer is a lot harder. Similarly, churning through limitless text - “search”, is a mechanistic process but “curing death” is not. Soon, hopefully, the “leaders” will realize the naked truth – machines do not learn and that the “singularity” they envision is many centuries away.

Machines have captured the human imagination from the start. When they trained animals to drive farm equipment many thousands of years ago, they understood how machines could be built and powered to enhance productivity. More recently, the silicon chip, a conventional and mechanistic processor, has raised their ambitions to a level that may not be realistic. In the initial going, it was focused on productivity, very similar to farm equipment but now some believe their machines can learn. If so, this is a departure for humans from sustenance to imagination, from mediocrity to advancement, from tactics to strategy. But alas, machines do not learn!

“Machine learning,” a term used too liberally by information technology and consulting firms, may need further definition. One can clearly demonstrate machines do not learn by themselves and if so, we are back to using machines to enhance productivity – a posture humans have been in for ten thousand years.

ET’s very large SUV

Recent discovery of an object by NASA’s Kepler telescope around a star, some 1500 light years away that cannot be explained by typical exoplanet properties, has raised speculation that it may be an artificial structure, created by advanced intelligence to garner energy from the star. A simpler explanation, such as a fragmented comet could be more valid, but certainly less interesting. Astrophysics, quickly degrading into bedtime stories of fancy, may yet have a long way to sink in conventionalism, before it could make a contribution.

Humans, seeking intelligence elsewhere, with attributes similar to theirs, seem to forget that their own experiences clearly show that intelligence is a network process. The mighty bacterium, able to dance with billions in unison, appears much more intelligent as a system than humans could ever be. By substantially increasing the diversity and the probability of favorable mutations at the micro-level, the system is able to evolve and adapt faster in a universe that appears hostile in every direction. Harnessing energy in such systems will be an internal process and may not require structure-building or star-domination, only phenomena humans are able to understand fully. Granted, finding such intelligence will remain outside human capabilities for the foreseeable future, if not for ever.

The recent fervor in seeking extra-terrestrials, is symptomatic of the limited understanding of humans of the formation, development and propagation of intelligence.

Training Schrödinger’s Cat

A recent article in Nature describes a possible break-through in quantum computing. Engineers at the University of New South Wales seem to have built a quantum logic gate in Silicon, possibly opening up a pathway toward practical quantum computing in Silicon based processors. In theory, the technology could turn conventional bits into quantum bits, allowing traditional chip architectures to morph into those supporting quantum computing.

This is good news. As many philosophers worry about singularity, for no apparent reason, creative engineers have been moving the goal posts closer to practical quantum computing. It is a technology discontinuity, something if shown to be practical, could substantially change the economic prospects of a whole generation, currently stuck in a plateau of no innovation. They are beginning to realize that calling a phone 6, 7, 18 or 6S is not really innovation – it is packaging. They are realizing that creating fake computer generated voices in marketing announcing Sherlock Holmes and Watson, is not really innovation, it is bad sales technique. They are realizing that skipping version 9 and going straight to 10 is not innovation, it is a cheap gimmick. They are realizing that names that are difficult to pronounce are not really technologies but ways to siphon money out of companies who want to jump on the latest band wagons.

The next discontinuity is not in software – it is in hardware. Unfortunately, world's largest hardware companies do not seem to understand it and the world is now replete with incompetent software companies – creating operating systems, applications, "artificial intelligence" and databases – with no innovation content.

Fusion, it is here (almost)

Ever since a brilliant member of the Homo Erectus produced fire for the first time nearly 2 Million years ago, their descendents have been trying to tame and use energy optimally. More recently, humans have been getting smarter with alternatives to wood burning, including fossil fuels, biofuels, nuclear energy, hydro, solar, wind and tidal. For many decades now, it has been obvious to many that most of these are inelegant solutions to the energy problem.

Burning hydrocarbons, albeit easy to do, has possible long term negative effects on the environment and biofuels take more energy than they produce. Nuclear fission, often fails to account for the costs associated with the storage of waste materials, with half lives exceeding 50,000 years. Solar, the darling of environmentalists, is not economical – in all varieties, photoelectric and concentrating-solar and it is an industry propped-up by subsidies, devised by politicians looking for brownie points. Hydro power has displaced massive populations across the world, with long term deleterious effects on the ecosystem. Finally, tidal and wind, better understood by public, show low efficiency and they are pushed by “green companies,” who make turbines for profits.

The energy problem is far from being solved. Lately, however, there are glimpses of hope – Lockheed, Alpha Energy and National Ignition Facility – to mention a few, seem to be making great strides to taming fusion. Ever since humans understood how stars worked, it should have been obvious that there is only one avenue to pursue to solve energy. Better late than never.

Fusion could lead to zero cost energy and that will make most tactical problems that consume humanity currently, utterly irrelevant.

Selective Bayesian Updating

Confirmation and conformation biases, symptoms of a disease that is eating into science and technology, have wrecked havoc in many areas including pharmaceutical research, astrophysics, finance, healthcare and policy, just to name a few. It appears that participants in these areas, utilize a novel mathematical technique – Selective Bayesian Updating (SBU). It is not just that data are fine tuned to prove the hypothesis but even in cases where it could not be proved, the posteriors remain the same for subsequent experiments.

Take Search for Extra-terrestrial Intelligence (SETI) as an example. It has been speculated that oceans that could support life exist in many icy and rocky remnants within the solar system – Titan, Europa and even the outcast, Pluto. Suppose the missions to these objects reveal no signs of life, will NASA and SETI use Selective Bayesian Updating for the probability of ET? Recent excitement around Kepler 452B, the most “Earth-like” planet ever found in the Milky Way, has led SETI to focus their instruments in that region. Suppose we find no signals of value, will the posterior probability of the existence of ET, remain the same? This is very convenient for those involved in the research. It is the ultimate free lunch in science – a negative result has no change in the posterior probability of the hypothesis being correct.

In pharmaceutical research, it has been shown that the efficacy of marketed drugs decline over time. This is a curious phenomenon as cutting edge research coupled with a vigilant regulator, the FDA, are unlikely to let marginal drugs into market. Was Selective Bayesian Updating deployed in the many experiments that led to the approval of the drug? Patients and providers, perhaps, are less susceptible to this problem and normal updating over a period of time, may be revealing the truth.

Selective Bayesian Updating, a disease that is substantially slowing the innovation slope in science and technology, could be treatable.

Light chip

Recent research from the University of Utah seems to get closer to silicon photonics and faster light based processors, many orders better than conventional products. Splitting light has always been easy but Utah engineers have accomplished it with beam splitters of a mere 2.4 microns of size. This may propel us out of the ongoing rat race of packing silicon ever closer on conventional chips for less interesting performance improvements.

Moore’s law, held sacred by technologists and used by exponential curve plotting, singularity seeking intellectuals, for stupid predictions, may have done significant damage to the psyche of innovation in electronics. Humans, grand optimizers of their limited life horizons, always fall into the trap of incrementally improving what is available. They appear to be satisfied with metrics that double over long horizons – such as years and this is in stark contrast to their keen awareness of limited time. With less than a thousand months of life span, a metric that doubles every 18 months appears so much less interesting than one that explodes by a few orders of magnitude in the same horizon. More importantly, doubling computing power in 18 months with no perceptible impact on existing applications is a waste of time.

It is time to throw out processes that grow within the same orders of magnitude every year – they will certainly employ people, but they will not make any difference to humanity.

The cost of thinking

A recent article from MIT (1) argues that consumers’ decision processes in the retail arena, replete with confusing choices and an overabundance of brands, are dominated by an “indexing strategy.” To reach a decision, consumers may be indexing (or utilizing a bundle of proxies to compare) rather than conducting an exhaustive search as such an optimization process could have high cognitive costs. If true, this finding has implications for companies in the retail arena for product design, promotions, delivery and pricing.

First, it opens up a dimension in the psyche of the consumer, that makes analyzing decisions more complex for the observer (retailer) even though it simplifies the process for the consumer. In a world of a large number of close substitutes for any product or service, a consumer with a preference for minimizing cognitive cost, will only consider a subset of products, that is not necessarily obvious to the retailer. As the consumer “indexes” against an unknown subset of substitutes, she will likely consider all aspects of comparability – as the simplified process allows her to do so, in the comfort of an already reduced cognitive cost. Ironically, these attributes may include both physical and virtual aspects – with differing weights, making it very difficult for the retailer to define “competition,” in a world of interacting product definitions.

Second, status-quo strategies that may include price discounting, bundling and couponing, may have a longer lasting effect on the “indexing strategy,” followed by the consumer. Such tactics by the retailer could move the brand away or closer to the indexing bundle, used by the consumer. Although the impact of such strategies on the near term decisions of the consumer is ambiguous, it does increase the complexity of optimizing such strategies. And, finally, retailers who have a rigid view as to “who their competition is,” may find themselves drifting – as the consumer preferences and retailing tactics may enroll or remove them from the proxy bundles considered by the consumer.

Retailers may have to move away from long held views on the competitive landscape and tactics that may have brought customers to their doorstep in the past. Flexible and dynamic strategies in design, delivery and pricing may be needed to win the consumer indexing game.

(1) The brain in the supermarket, Published: Friday, March 27, 2015 - 11:33 in Mathematics & Economics, Science News

http://esciencenews.com/articles/2015/03/27/the.brain.supermarket