Why great ideas are opposed? How do we learn? And why the Cloud will change every aspect of how we live bringing about more computing intelligence than ever perceived

In ~2005, I was doing a bit of research on algorithms with an ambition to build a mobile personal assistant. I theorized that a virtual assistant coupled with the power of web search using schematized data can help reduce complexities we face as humans as a bi-product of the ever increasing information availability. A set of specialized inter-communicating software agents mimicking human-experts in diverse fields could collaborate to share information in their subsequent areas of knowledge would potentially bring about group intelligence (this paper from Princeton explains a few of the concepts). The cloud as we know it today was not quite there yet.

I was focused on borrowing concepts from biological systems. It couldn't be more obvious to me at the time that in computing and software design, we base much of our approaches on already existing natural systems and algorithms. Even today (only a decade later), we continue to observe more and more traditional aspects of our lives move into virtual ones – consider Aviation or Facebook as an elaborate broader examples.

One of the most interesting concepts I stumbled upon at the time was that of schema (plural schemata or schemas). Schemata help us store information in categories and define the relationships between things. It’s a framework that represents the world around us allowing for easier absorption of new knowledge. Schemata are the reason why we learn slowly in the beginning and yet get incrementally better at doing things after repeating them because we reinforce elements in our schema. It is also why, we start to teach our children with the basics first and then later we add more abstract concepts. However, it is also the reason why we’re very stubborn and once we manage to find some beliefs to cling on to, they are very difficult to modify.

A schema is a living entity that gets modified with each new piece of knowledge acquired. It constitutes our cognitive learning abilities. Schematic learning uses previously learned ideas, concepts to understand and simplify new learning. Schemata have a huge influence in determining how new information is processed and how long it is retained. These Schemata guide encoding, organization, and retrieval of information (Ormrod, 2004). They are a closely connected set of ideas that are related to a specific events or objects. They are developed through a person’s experience with objects, people, and events in the world. In addition they are emphasized or de-emphasized through a system of feedback based on experience. People store experiences and associate them with words - A word alone is less meaningful unless it is contextualized with some background information or an event.

As humans, we’re seeking to formulate an understanding of the world around us and build a structure which allows us to feel a certain level of comfort and security – we want to feel that we know something. We also despise changing this complex mental model and the more elaborate the model is, the harder it is to modify or break down. Consider why cultures norms are so ingrained into our thoughts and habits. We learn by taking in new information, but we first check against our schema (i.e. experiences) to understand where this new knowledge might fit. It helps us make sense of the world around us. Most situations do not require complex thought when using schema. It’s a simple input-output scenario; we simply do a fast computation and retrieve from existing structures (the sub-conscience) whether the information already exists or if there is something similar to it. In the cases when the information is new, we try to classify it somehow into existing structures. We run into trouble a bit when the new knowledge contradicts our internal structures/beliefs. It confuses us as we get faced with the fact that it doesn't fit anywhere and may require us having to re-structure. This is time consuming, requires energy and requires lowering our self-esteem in order to accept it. Thus, new and contradictory concepts are hard to accept. Consider why new paradigms and ideas are initially ridiculed if not violently opposed at first. “The earth is not flat!!!?” – The list is infinite.

New knowledge and information are in endless conflict with the concept of security and self-esteem – it’s an incessant battle. The more complex and sturdy our schema is, the harder it is to change it because it threatens out self-worth, confidence and our very sense of security. It defeats the Maslow hierarchy of needs.

Consider children with virtually no schemata in place and their ability to absorb new knowledge. Although, there are many other variables allowing children to be like sponges, schemata coupled with their yet-to-be-developed self-esteem and sense of security makes them ripe for super-human learning capability.

In psychology, general intelligence is classified into fluid intelligence which is the biologically crystallized intelligence which is the ability to accumulate knowledge through life experiences and utilize previously acquired knowledge. Not much can be done about the first type, but the latter is where we excel and this is where software has not yet ventured.

predetermined reasoning capacity and

Civilization started with classifying and organizing information. This produced refined knowledge and wisdom. The internet broke the barrier of location and time and allowed for the genesis of new types of information. Search engines facilitated the information retrieval and transformed our lives. Our software began to exhibit small pockets of intelligence mimicking human-like cognition. In the 1980’s a chess powered computer game was a marvel to observe. The

evolution of this intelligence began to increase with software complexity. However, there was a limit – one related to storage.

Historically, software had plenty of pre-programmed reasoning ability built-in, but made fewer strides on learning to extend its crystallized intelligence – This was primarily a centralization and permanency challenge. In other words, the potential for stored schemata were simply not possible since crystallized intelligence could not be permanent to build one.

When you consider stand-alone personal computing devices, you can imagine that it is hard to acquire this type of crystallized intelligence when software is fragmented across devices. With the cloud center stage, we have reached a very interesting milestone in technology where once decentralized systems can now accumulate intelligence in a centralized manner. Ironically, the cloud solves a dual challenge. The first is the retention one allowing the preservation in the form of an individual crystallized intelligence. The second is the possibility of mimicking the behavior and intelligence of communities. The result is likely to be unlike anything we’re ever known simply because the internet collapse all borders and allows for this massive global humankind-schema to be born.

So what do you think is possible?