“On Intelligence”

I recently listened to an audiobook format of Jeff Hawkins’ 2004 book “On Intelligence.” In this essay I will try to review some of the key concepts from the book. In a future essay I will relate these concepts directly to holistic tracking and awareness.

Jeff Hawkins has focused much of his life on understanding computers, the human brain, and searching for an overarching theory of intelligence. In his book titled “On Intelligence,” he presents such a theory, supports it with research, and explains how this theory can help design truly intelligent machines.  Hawkins does a great job of explaining the fundamental differences between computers and brains and the reasons why the most advanced computers of today still cannot do certain tasks that a three year old human does with ease.

Some of the key arguments that Hawkins makes can be summarized as follows:

1. Behavior is not the best way to measure intelligence.
2. The type of intelligence that he is looking at is an aspect of the neocortex (the most recently evolved part of the brain).
3. The main function of the neocortex and the basis of intelligence are memory and prediction.
4. Intelligent machines should be built by using the principles of the neocortex otherwise it will be difficult to make them truly intelligent.

Hawkins’ first point is that intelligence should not be measured by behavior such as the classic test of artificial intelligence called the Turing Test. Many aspects of having intelligence do not require action and behavior by itself can be very misleading. Instead, Hawkins’ is interested in the type of intelligence that humans take for granted but that has been very difficult to achieve in computer programs and robots. He is interested in how humans understand the world around us, learn patterns, and make meaningful predictions effortlessly without getting bogged down in millions of calculations.

Hawkins focuses almost exclusively on the most recent part of the brain known as the neocortex. While I might normally criticize this reductionism I feel that he justifies his focus and it works with his narrow definition of intelligence. One of the most interesting points he makes about the neocortex is the uniformity of it in appearance and structure. Hawkins’ cites the work of neuroscientist Vernon Mountcastle as pointing to the simple yet overlooked possibility that all of the neocortex is performing the same basic operation. He calls this the “single cortical algorithm.” This structure is seemingly redundant yet extremely flexible and functional. Unlike computers, it allows us to take incomplete information, recognize patterns, classify experience hierarchically, think creatively through analogy, learn language, and make useful predictions. Unlike a pre-programmed computer or robot this cortical architecture is specifically set up to learn, adapt, and function in an unknown and novel environment.

The single cortical algorithm does four main things:
1. It stores sequences of patterns
2. It recalls patterns in an auto-associative way
3. It stores patterns in invariant forms
4. It organizes stored patterns in a hierarchy

“Prediction is not just one of the things your brain does. It is the primary function of the neocortex, and the foundation of intelligence. The cortex is an organ of prediction.”  I must admit I was very stoked with how Jeff Hawkin’s emphasized the primacy of pattern recognition, memory, and prediction in his book. These are three attributes central to much of what I do and this framework has a lot of useful applications especially in tracking and awareness. In our daily life our brain is constantly making predictions about the world around us. These predictions are based upon patterns that we have learned through experience and store in our memory. As a child you learn how different objects respond to your touch, you store these experiences as patterns, and by the time you are an adult you unconsciously make predictions about how much force is necessary to push open a door. When everything goes according to subconscious predictions the tendency is not to notice. However, if something does not meet your prediction it is quickly brought to your conscious attention. If the door is rigged to be heavier you will notice because your prediction about how much force is necessary to open it will not match up.

In the last part of his book Jeff Hawkins explains the steps necessary to create intelligent machines based on the single neocortical algorithm and he delves into some of the ethics surrounding this field. As a non-computer scientist I still found this part of the book easy to understand and extremely interesting. His arguments were compelling and gave me a much better understanding of the hurdles faced by artificial intelligence. It also helped me broaden my conceptions of AI beyond the influence of Hollywood and popular media. It is amazing how the popular imagination and the worldview of the industrial age have had such a huge influence on the trajectory of AI research.

Overall, I truly enjoyed this book. It was thought-provoking, well-argued, and I look forward to synthesizing the key ideas and incorporating them into my approach.

For more information on Jeff Hawkins:
http://en.wikipedia.org/wiki/Jeff_Hawkins

Knowledge as an obstacle to learning

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With today’s omnipresent media it seems that the average person knows more than ever before in human history. Google searches, wikipedia articles, and countless online news sites make huge amounts of information available. This information bombards the modern person from all directions: TV screens at gas stations and checkout lines, 24 hour news channels, magazines, shared articles on Facebook, DIY websites, and Youtube tutorials. How often do people quote some bit of information that they “know” but they have no idea where the information even came from?

 
I have been wondering about this phenomenon for a while and I have become more and more critical of the whole idea of “knowing.” These days I try really hard not to recite bits of information that I’m not sure about, where the source is forgotten, or at least I put a strong disclaimer on what I spout. For those who are interested there is a field of philosophy that deals with knowledge, how it is acquired, and how it influences belief, certainty, and the concept of truth. This branch of philosophy is called epistemology and is worth some reading. For a basic article see: http://en.wikipedia.org/wiki/Epistemology

 
Lately, I have been leaning towards the idea that “knowing” or knowledge is one of the major obstacles preventing learning. This phenomenon is easily observed in young children who are the masters of learning. They constantly ask unusual questions and make novel connections when young. This flow of novel thinking is essential to how children learn about the world around them. Unfortunately, this type of thinking is often pruned out and paved over with “knowledge” in the process of socialization. I’m frequently saddened by how adults respond to the often keen and always worthy questions of children. The first possibility and perhaps the most common is for adults to ignore or not notice a child’s question. They might reject the question outright or not take it seriously. If they do provide an answer for the child it often is an answer that shuts off the child’s line of inquiry. Once the child “knows” this answer, often misinformation, they are much less likely to pursue the matter further. They think that they know. Following is an example of this unfortunate stifling of the learning process.

 

I was once visiting the Arizona Sonora Desert Museum, an impressive center with diverse animals and plants in well made exhibits. At the enclosure for the desert bighorn sheep I was watching the adult male of the herd repeatedly bashing his head against a large palm tree. From the sizable dent in the tree it was evident that the ram did this on a regular basis. A large group of people stood milling around the exhibit and I could only imagine the pent up stress and boredom of such a creature. Just then, a little girl asked out loud, “Does that hurt it when it hits its head like that?” It seemed to me like a legitimate question rooted in a feeling of empathy for another creature. However, the girls mom seemed to think it was a stupid question and answered quickly without a second thought, “Of course not. Haven’t you seen them bashing heads all day long on TV?”

 

The mother’s answer is based on “knowledge of the the world” that she has acquired over  the years of her life (apparently much of this from watching TV). She may have seen bits of documentaries about bighorn sheep where the males ram into each other during the mating season. Even more likely she saw this behavior in a popular beer commercial that ran during a Superbowl. From this she assumed that since this is normal behavior for them that it probably doesn’t hurt. She also expressed a high degree of certainty about her “knowledge” in her response to her daughter. She did not add any modifiers or maybes. She did not admit her own lack of an answer to the question.

Chances are that bighorn rams have lots of anatomical features that mitigate the potential damage of their intense head-on impacts. Chances are that the male we were watching was not causing too much damage to himself by ramming the palm tree. However, the point is that we will probably never know if he was experiencing pain. More importantly, the girl’s question is totally valid and a perfect entree into a fascinating line of inquiry that could open many doors of learning. Let me create an alternative scenario where an adult did not insultingly answer the question in a way that stifled a potential learning experience:

At the bighorn sheep exhibit the adult male repeatedly bashed his head against the palm tree in the corner. A large dent in the trunk showed that this was a regular behavior. Just then a little girl asked out loud, “Mommy, does that hurt him when he bangs his head like that?” A thoughtful moment passed before the woman answered, “ I’m not sure honey, how could we find that out?” Instantly, more neurons are firing in the girl’s brain, more connections are being made, and she is forced to think creatively. She recalls her own experiences of pain while also searching her memory for examples of other animals experiencing pain. “ I know that some animals can feel pain, remember that injured horse we saw?” The question hangs in the air before she continues, “But how can we know what they are feeling if we can’t talk to them?”

It is easy to imagine all the possible lessons that could stem from the girl’s original question. Maybe this conversation will lead her to become a behavioral biologist or inspire her to study the neuroscience of pain. Unfortunately, all it takes is an unthoughtful and self-assured answer in the wrong tone of voice from an adult to stifle the learning opportunity. This scenario can also happen between adults, in a whole community, or within the microcosm of our own mind. I think we must be careful of this tendency if we truly want to learn. For true learning is a process, a way of seeing and thinking, it is not the mere accumulation of bits of information.

Be always wary of knowledge and answers; seek instead the power of good questions and child-like curiosity.

For more info on the wonderful Arizona Sonora Desert Museum see here: http://www.desertmuseum.org/