Processing Education

We should change our education system to take advantage of how are brains are designed to process information by utilizing current technology. Humans are unique in our thought process, we recognize patterns in information better than any other animal or technology. We should teach humans to better use this ability rather than teaching rote memorization. We should change the education system to teach us to learn to think rather than teaching the details of subject matter.

At one time in history, information had to be integrated by an individual in a sequential fashion, using memory to carry information from one book or experience to something observed in another book or experience; the details mattered.  But now, with massive digital stores of fact available, it is possible to put information together based on affinities that are discovered through automated searches and machine processing.  This changes everything.  While it doesn’t render memorization completely obsolete, it emphasizes our need to be able to recognize patterns in order to extract meaning from collections of information.

Think about the pre- and post-internet age. What percentage of the population had the knowledge of a certain topic like Greek mythology? Before the internet, an instructor was required to teach these topics. However, with the internet, more people are exposed to any given topic thus, more people know about it. There is increased access to Greek mythology, for example, so that each person does not have to learn it in class, but could learn it on their own without an instructor.

One possibility would be to teach everything through problem based learning – teach the students how to learn rather than teaching them the information. Teaching through problem-based learning does not reduce the amount of information students are taught, but actually increases it. When students are taught to ask questions about a topic, they are able to research the details (on the internet, etc), find patterns in the information, and deduce the answers. Despite not having lectures and they would be learning how to follow a process to teach themselves.

Accordingly, learning needs to emphasize an ability to develop patterns of recognition, as opposed to memorizing facts.  Machines bring together large bodies of information; it is the role of an intelligent person to put together that information into meaningful understanding by assimilating the patterns. The implications for modalities of education are huge.  A lecturer who teaches facts is largely outmoded, since the set of facts can often be gleaned from simple web searches.  It is the interpretation of the facts that are accessed, by means of recognizing patterns in some generalized and approximate fashion that needs to be sharpened for young and old alike.

Advertisements

Mitigating the Threat of Asteroids

The survival of the human race is a serious matter.  The United Nations recently drafted a resolution that recommends including the creation of an International Asteroid Warning Group to help protect society from Near Earth Objects.  The resolution will most likely be adopted.  Though a small step for the UN, this could be a large move for humanity.  It is laudable and further technical and political measures should be considered.

Early this year, a meteor exploded above Chelyabinsk, Russia injuring 1,000 people due to the resulting shock wave.  The warning systems we have in place did not detect the asteroid.  Luckily, there were no deaths but these rare events have become a wake up call for professional and amateur astronomers.

The threat posed by Near Earth Objects (NEO) is real.  An asteroid detected in 1997, 1997XF11, will bypass Earth in 2028 but would likely wipe out life on the planet if it collided with Earth’s atmosphere.  It is estimated that there are roughly one million asteroids within the Sun’s orbit, 10,000 of which are being tracked by NASA.  Small asteroids collide with the planet regularly.  Most burn up in the atmosphere.  The few that make it through vary in size, composition, and angle of entrance.  Early warning systems are the best approach to prepare for a collision, thus enabling time to deflect the object or evacuate the impact zone.  For instance, under the new plan the “UN Committee on the Peaceful Uses of Outer Space will monitor detections and help plan a deflection campaign if that is necessary.”

The realization and acceptance by scientists of the inevitability of a collision with Earth is not new.  The probability of another asteroid striking Earth is 100%; there is no uncertainty in this calculation.  The uncertainty exists in determining when such a significant collision will occur. The product of the probability of collision in any given year and the effect on society of the collision is a calculation fraught with high degrees of uncertainty because it depends on many parameters: diameter, composition, density, velocity, and angle of impact of the asteroid, as well as the timing, population density at the location of impact, and local infrastructure of society.

Despite this difficulty, it is widely accepted in scientific communities today that the risk of doing nothing is unacceptable.  The cost-benefit analysis, though noisy, is clearly in favor of protecting human life.  It begs the question: Do we ensure the survival of future generations by making investments now?  And the more difficult question: If so, how many resources should be devoted to these endeavors?

Today we have advanced technologies to sense, collect, store, analyze, and predict these projectiles on massive scales.  For example, RF and laser radar technology, big data analytics, modeling and simulation software, commercial launch capabilities, and autonomous systems have advanced rapidly in recent years.  This past June NASA launched a grand challenge to gather ideas to mitigate the threat of asteroids, including bold ideas such as solar sails and gravity tractors.

Communicating the science of asteroid physics is also critical to enable policy implementation.  Hollywood movies like Armageddon might be entertaining, but in the end they do little to educate the public due to the fact that they come from fiction-based Hollywood and are bursting with technology flaws.  Rational, vetted analysis based on rigorous scientific research presented in widely understandable language is the only way to make political headway.

The international support to plan for space rock collision is promising.  Private space companies, groups such as the Association of Space Explorers, B612 Foundation, The Lifeboat Foundation, international organizations, and government agencies should partner to confront this task together.  With greater collaboration, testing, information sharing, and mock impact scenarios in place we can ensure that we are dedicating resources to a worthy cause.

The ability to predict rare events such as an asteroid collision is achievable and our human ingenuity will ensure this.  In order for our government to fulfill its responsibility to protect its citizens, more federally sponsored research needs to be conducted on asteroid collision mitigating science and technologies.  Surely, it is a worthy endeavor of human activity to protect the human race and ensure its longevity.  Given that the world spends roughly $1.75 trillion annually defending ourselves against one another, wouldn’t it be wise to spend a few billion a year to defend ourselves from true external, existential, space-based threats.

Big Data and the Scientific Method

The first in a series of three articles on the implications and challenges in Big Data.

The term “Big Data” suggests that the concept, however defined, is a Big Deal.  However, the concept of collecting, storing, and analyzing large volumes of data in ways that were not possible some years ago, is both older and bigger than the concept that people ascribe to “Big Data.”

The ability to store and retrieve data, and to convert data into information, is an essential aspect of being human.  The development of language, and oral tradition, is perhaps the most profound development in human history.  No one is quite sure when this happened; speech may have occurred a hundred thousand years ago, or maybe earlier.  Certainly by 50,000 years ago, speech had established in what we now view as the human race.  The ability to transmit to others information derived from observations and experience, as well as to successive generations, through words within the construct of a language, completely changed the nature of what human beings could accomplish.  Transmission of information supplementing genetic transmission is an evolutionary leap that redefined the meaning of “human.”

Subsequent advances in information transmission in the history of human existence came slowly at first, and then with increasing frequency.  Around 30,000 years ago, writing was invented, first as a way of recording accounts (numbers), and then through recordings in cave paintings and other markings. Later (perhaps only 5,000 years ago) written language representing words and ideas appeared in various forms, permitting the recording of history, and development and transmission of cultures and religion, in large volumes of written material, rather than merely through oral traditions.  Development of writing instruments and paper was important.  In more modern times, a huge advance occurred with the development of the printing press, which permitted mass production of written material, and the democratization of information.  Arguably, the invention of the printing press enabled the Reformation, and the Peace of Westphalia that established the notion of the nation-state separate from the local customs and religion.  Further democratization occurred with the development of pamphlets and newspapers, and the total amount of stored data greatly increased with the development of photography and then videography.  The twentieth century saw the development of computers, microelectronics, personal computers, and digital communication devices. Each advance profoundly changed humanity’s interaction with data, and how we assemble, store, and transmit information.

With the further development of microprocessors and digital storage media, another profound change has occurred.  What are we to make of the fact that in the year 1993, estimates are that 3% of the world’s data was stored digitally, but that by 2007, 94% of all recorded data was digital[i] (and undoubtedly an even higher percentage by 2013)?  The figures may be dwarfed by imagery and video, but it is clear that there has been a sea-change in the sensing, recording, and retrieval of data, from analog forms to digital representations.  And while this transformation is occurring, the sheer volume of data has been growing, at a rate that is at least exponential.  With new high capacity disks, RAID storage systems, flash memory and solid state drives, and now readily available cloud storage, the opportunity to keep and maintain data from all events and activities in people’s lives has become feasible.  The same researchers that observe the role reversal of digital data in storage also estimate that there has been an exponential increase in the amount of data since 1986 with a compounded annual growth rate of 25%.[ii]

The impact of this rapid transformation is, we assert, as profound as any of the historical revolutions that changed humankind’s interaction with information, on par with the invention of language.  Big Data grossly understates how big a deal is the transformation to massive digital recording.

One of the principle impacts of this change is the method by which we, as a human race, extract information and develop theories to explain phenomena.  The scientific method has served mankind well for centuries: An iterative process of observation, hypothesis, devising of tests, and refinement and/or validation. The development of modeling and simulation capabilities with massive computer processing power allows for greater use of computational models in the testing phase of the scientific method.  But an even greater modification to the scientific method is afforded by the existence of massive stores of digital recording of sensor data.  Instead of using a few observations and developing hypotheses based on human intuition, it is now possible to comb through massive amounts of observed data, and to develop hypotheses based on computed correlations.

For example, throughout history, marketers attempted to convince people to buy things based on good guesses as to what might persuade them.  Now, online advertisers can observe trails of “clicks” and observe patterns of purchases, to far more easily deduce persuasive patterns.  This is the basis of many commercial endeavors that use internet and web tracking.

But scientific discovery can also make use of massive data stores to develop better theories of natural phenomena. Cosmological observations, for example, have enabled us to deduce the presence of planets circling distant stars, based on analysis of patterns of intensity data.  Medical data, including statistics over sequenced DNA data, is permitting us to identify genetic causes of certain diseases.  Image processing of data gathered from particle accelerators (in particular, the Large Hadron Collider) yields massive amounts of information that has allowed scientists to deduce the existence of the Higgs boson.

And while scientific inquiry has been transformed, the analysis of the sociology of humans has been unleashed through the collection of large amounts of data of nearly every human on the planet.  Of course, there are significant concerns about individual privacy, but since data is being collected by companies and authorities of all of our transactions, locations of our devices, and health and status of our machines, soon it will be possible to track the movements and behavior of just about every human being.  The potential to understand human behavior as a function of stimulus and history is both stunning and frightening.  If the data is anonymized and analyzed statistically, then great good can come from the analysis.  If the data is used to discover and “target” individuals, then there are more sinister possibilities.

In any case, the modification to the scientific method, whether for marketing, science, or sociology, goes deeper than just the amount of data being observed.  Instead of having to intuit relationships between observable variables, computer analysis can now look at groups of variables, sometimes correlated across multiple data bases, to look for statistical relationships (a form of correlation) between the variables.  Algorithmic methods can be used to look for constraints that indicate a statistical relationship between observables.  The formulation can be extended to account for “noise” in the observed data by allowing for approximate relationships, and also can be extended for the case of variables that can take on discrete values (as opposed to continuous numerical values).

The change is the ability to analyze by algorithmic means large amounts of data, collected using “big data” techniques that store massive amounts of data in cloud-based disks, or on individual flash drives in home laptops, or in massive government databases.  Whereas until recently, discovery and analysis progressed largely through empirical means, dependent on an analyst’s ability to intuit relationships in data that is sparse, rare, and displayed through analog means, we can now use computer programs to cull massive amounts of data to suggest relationships in variables that might never have been viewed by humans.  Empirical testing and laborious search can become automated analysis through massive databases to suggest relationships that can be used to far more rapidly develop hypotheses of causality and models to describe behavior.

In a quiet revolution, sitting in the midst of a change that takes a few years masks the momentousness of the event in the course of human history.  This massive bulk of digital data, and the information derived from it, can be shared with societies throughout the world, and with generations to come.  Not all of the changes will be good.  It is often said that information is power, and with an ability to extract and share information derived from automated means, concentrations of power are indeed possible.  Already, political parties use massive databases to perform fundraising and campaigning.  Perhaps knowing and understanding human behavior too well will threaten individual choice and independence.  From influencing what we buy to dictating for whom we vote, our very selves might become predictions based on correlations of variables.

Lurking behind the development of “big data” analytics is a transformation comparable to the invention of language, in terms of the ability to transform the meaning of being human.  And yet, the opportunities and challenges afforded by a new way of deducing information from observations, now become massive digital observations, can reasonably be called a revolution in human means of executing a scientific method of understanding phenomena.

While our ability to record data and to analyze massive databases are exploding, and while scientists and analysts develop new skills at executing automated data analysis tasks in place of intuition and empirical searches, the question arises:  Are we getting prepared to accept the implications and consequences of this massive revolution in the way humankind handles data?  Preparations might imply new policies, new rights, and new approaches to sharing of information.  Most likely, these policy and procedural reforms will be enacted post-facto as consequences of the big data revolution unfold.  But since at least some of the directions and implications are apparent now, it would make sense to implement policies now that steer the use of data analytics toward the development of knowledge that is beneficial, or at least not harmful, to mankind as a whole.