History of discussion about singularity

Vernor Vinge, a science fiction writer, first wrote about the vision of technological singularity and coined the term in 1993. He wrote, "Within thirty years, we will have the technological means to create superhuman intelligence. Shortly after, the human era will be ended."
Ray Kurzweil, inventor and futurist, is a fervid proponent of technological singularity. Kurzweil predicts the timeline of singularity as follows:

• By 2019, a $1000 PC will have the computing power of the human brain. It will be capable of performing 20 million billion calculations.
• By 2029, a $1K PC will be a thousand times more powerful than the human brain; the human brain itself will be successfully reverse engineered.
• 2045 is singularity: machines will have surpassed humans in intelligence and in fact will have created next-generation robots even smarter than themselves. We should either merge with our creations or step out of their way. Immortality!
• By 2055, $1K of computing power will equal the processing power of all the humans on the planet.

In 2011, Ray Kurzweil sponsored a movie/documentary about singularity, titled "Transcendent Man," which has been screened in five major cities in the U.S., as well as London. In December 2012, Kurzweil was hired by Google as a director of engineering to "work on new projects involving machine learning and language processing."
In 2000, Bill Joy, a well known computer scientist and the primary figure behind the BSD operating system (on which MacOS was built on) and the widely used Java programming language, joined this discussion. In a Wired magazine article, "Why the future doesn’t need us," Joy declared, in what some have described as a "neo-Luddite" position, that he was convinced that growing advances in genetic engineering and nanotechnology would pose severe risks to humanity.

Arguments and counterarguments about the feasibility of singularity

Proponents of singularity often cite Moore’s law to support their claim. Moore’s law states, crudely, that the capacity of computer chips doubles every two years. That is, the speed and capability of computers grows at an exponential speed. Such an exponential growth is a powerful enabler. Consider the series 1,2,4,8,16,32… The small increments in the beginning may be misleading about the overall speed of the series’ growth. The 20th element in this series would be 1 million. The 266th element in this series is 1080, which is more than the number of atoms in the universe.
Proponents of singularity argue that thanks to this exponential growth, the processing powers of computers will reach such high levels in the next few decades that it will be possible to simulate the human brain in high fidelity. The workings of each neuron in the brain will be simulated in real time, achieving a full simulation of the brain. At that point, the computer will essentially have the equivalent of human intelligence. In the succeeding years, with the increase in capacity, the computer intelligence will be several folds ahead of human intelligence.
Opponents of the feasibility of singularity cite that exponential growth is hard to sustain. Exponential growth is seen in the beginning of a series, but then due to limitations/adversities, most series will level off and stay constant. An example of this is the population of rabbits. Initially, the increase is exponential; however, due to scarcity of food sources and an abundance of predators, the population stabilizes around a constant. Therefore, opponents of singularity argue that the exponential progress of computer processing speeds will similarly hit a brick wall. At the chip level, physical issues such as heating will make exponential speedup unsustainable. At the cluster level, latency, consistency, and scalability issues will also prevent exponential growth.
Underlying all of Kurzweil’s ideas regarding the progress of technology and the singularity is the Law of Accelerating Returns. This Law states that technological progress occurs exponentially instead of linearly, meaning that each new advancement enables several higher advancements instead of just one higher advancement, and, concordantly, every year brings more useful inventions and discoveries than were made in the last. The first generation artificial intelligence (AI) approaches failed, but simulating a human brain may work if we know the workings of the brain in excruciating detail. As a promising development, recently, “deep learning” and “deep neural networks” technologies achieved great success in image and speech recognition tasks.
However, the opponents of singularity like to point out that the workings of the brain as a whole are still a big mystery. We have information about the rough mechanism of how a neuron works. An excited neuron can transmit a signal to a neighboring neuron through its synapses. But, there is no clear explanation about how thought occurs from this process. Brain-scanning techniques are improving, as they are based on computers, but the brain may throw us more complex surprises as we learn more about it.
In fact, much of the brain power comes about through organic materials, and the very low-level analog physical interactions between these materials. These physical phenomena could be close to impossible to model/simulate in a digital environment. Henry Markram, lead researcher of the "Blue Brain Project" for simulating mammal brains at the molecular level, has stated that "it is not [their] goal to build an intelligent neural network." He claimed, “[That would] be very difficult because, in the brain, every molecule is a powerful computer and we would need to simulate the structure and function of trillions upon trillions of molecules as well as all the rules that govern how they interact. You would literally need computers that are trillions of times bigger and faster than anything existing today."
Another relevant question is whether we can develop the parallel processing architectures needed to support the parallel processing that goes on in the brain. The brain uses far more parallel processing than exists in most classical computing designs.
Even if a computer successfully simulates the human brain, whether such a computer design will be “scalable” to two times, ten times, or even one hundred times the brain’s normal power is an unknown; for the human brain’s computation power may be inherently unscalable. Also, if a computer models the human brain, human emotions would also be modeled. Would the resulting computer be stable? As it scales up, would it become existential and suicidal, or perhaps become an arrogant killer?

The aftermath of singularity

Several questions are raised about the aftermath of singularity. Can a downloaded personality replace the spirit? How does this equate to living forever? Singularity promises are similar to claiming that you can live forever by cloning yourself. One copy dies, but another digital copy survives. But it is clear that the copies are different entities.
And it is also clear that this is not true immortality. If we stretch singularity’s approach to immortality a little further, we can argue that humans can achieve immortality through their work or art. And to this idea Woody Allen provided the best response: "I don’t want to achieve immortality through my work. I want to achieve it by not dying."

References

• Vernor Vinge, “The Coming Technological Singularity: How to Survive in the Post-Human Era”, 1993, available from https://www-rohan.sdsu.edu/faculty/vinge/misc/singularity.html
• Ray Kurzweil, ”The singularity is near: When humans transcend biology”, Penguin books, 2005.
• Bill Joy, “Why the future doesn’t need us”, Wired 8 (04), 2000.  
• Henry Markram, “The blue brain project”, Nature Reviews Neuroscience, 7 (2), 153–160, 2006.

Cost-benefit analysis of piracy

To begin, I want to analyze piracy free from any ethical or normative judgments. Piracy is an act, and like any other act, it has costs and benefits. A utility calculation or a cost-benefit analysis shows that the material benefits far outweigh the minimal material costs of piracy. Entertainment media usually has a monetary price that must be paid in order to consume it, like buying tickets to watch a movie at the theater. On the other hand, given that the individual possesses the technical knowledge, the individual can receive the same entertainment for free if he chooses to pirate the media instead of buying it. While some individuals who pirate are caught and do pay fees, the probability of these negative consequences are very small. Given no other external factors, this cost-benefit analysis indicates that the materialistic benefits outweigh the materialistic costs.

Additionally, from a behavioral perspective, piracy makes sense. When a person commits piracy, they are immediately presented with the benefit of entertainment or utility. The behavior is immediately rewarded and reinforced. The costs are not immediately evident, and can be easily overlooked, because the probability of being caught and punished for pirating is very small. In contrast to the act of physically stealing the DVD of a movie, the act of illegally downloading the movie is much less risky and only entails the seemingly innocent pressing of buttons. When contemplating whether to physically steal another DVD of a movie, the person would weigh whether the entertainment benefit is really worth suffering the stress and energy as well as the high risk of being caught and punished by the law. When contemplating whether to illegally download a movie, the person would only need to weigh whether the entertainment benefit is greater than pressing some buttons. With such low risks and such immediate gratification, the behavior of piracy is easily engrained.

This cost-benefit analysis in a vacuum free from any external forces like ethics, morality, and religion sufficiently shows why piracy is so prevalent. It is easy and rewarding. However, people do not live in a vacuum.

The ethical factor

If piracy is theft, then it is unethical, immoral, and wrong. And it is indeed theft. All digital media whether film, music, ebooks, or games are products of another’s hard work. Just like a farmer’s crops or an author’s book, digital media would not exist but for the producer. Thus, similarly, the producer has taken ownership of digital media by production. Modern copyright and digital rights laws are evidence of this societal norm. So, if it is wrong, why do some people pirate digital media anyway?

When a person is given the choice between paying for the entertainment and consuming it for free, ethical principles clash with desire. In order to resolve cognitive dissonance, the discomfort caused by the clash of conflicting inner-beliefs, individuals will attempt to justify their actions and alter their beliefs (1). In the case of piracy, an individual might conclude that the producers of the entertainment media are already wealthy and do not need more money. Alternatively, the individual may decide that his financial circumstances do not allow him to pay for the products, forcing him to illegally obtain them. Ultimately, these justifications allow the individual to live more comfortably with their decision to pirate the product.

Justifying piracy

In addition to common justifications for any other ethical violations, piracy has a unique justification due to the unique nature of digital media. This unique justification is that the illegal downloading of digital media does not harm the producer, because it does not represent a loss of revenue for the producer of the game, movie, or song. Given the digital nature of entertainment media, a pirated copy of a game does not directly mean a loss of revenue equal to the price of the game. For example, when an item in the physical world, such as a watch, is stolen from a store, the store loses money that is equal to the sum of the cost of the watch and the profit from the sale of the watch. If the thief had not stolen the watch, the store could have sold it to someone else. In contrast, when an individual obtains a pirated copy of a digital media, the ability of the producer to sell a copy of the digital media to someone else is not inhibited in anyway. In other words, the benefits or entertainment experienced by the individual who chooses to pirate does not result in a loss for the producer. Those who have this justification would then conclude that piracy only has positive consequences.

This justification, unique to digital products, has two main deficiencies. First, piracy can lead to loss of revenue to the producer if a person who would have otherwise purchased the product chooses to pirate it. Aggregating all the individual acts of piracy can lead to a cumulative loss of revenue of many millions of dollars. Second, loss of revenue is not the only reason piracy is immoral. The primary reason why piracy is unethical is because it constitutes a taking of another property, violating another’s fundamental property rights. If a producer chooses to share its property with only those who pay for it, then the taking of that property without paying for it is a violation of fundamental property rights. An independent showing of damage or loss of revenue is not necessary to prove its wrongness.

Habit

Another possible explanation for the prevalence of piracy is habit. Once an individual has committed piracy, despite ethical prescriptive to the contrary, the individual experiences the benefits and joys of that piece of entertainment. As previously mentioned, this immediate reward can lead to a cycle that constantly reinforces the behavior until it has become habitual. The case study of the video game, Proun, can provide some insight.

Proun, a low budget game, was released under the pay-what-you-want pricing method which allows consumers to legally obtain the product at whatever price they decide to pay including for zero dollars. In other words, people could legally get the game for free from the developer’s official website. Essentially, the developer removed monetary concerns from the utility calculation. According to the released statistics, approximately 40% of used copies were pirated (2). Individuals chose to pirate the game, despite being able to obtain the game legally for free.

The implication of the Proun case study is that price may not be the sole determinant for pirating behavior. A possible explanation for the observed pirating behavior could be that obtaining entertainment media through illegal means has become habitual to a significant portion of the population. Due to the low risks associated with piracy, individuals who have chosen to pirate media experience no consequences that would deter their actions, making piracy their normal means of acquiring any form of software, irrelevant of whether or not the software is free. In other words, habitual piracy has become legitimate in their eyes. After the initial act, the individual no longer considers the ethicality of their actions. Every subsequent act merely reinforces the habit.

References

1. See also Yerli, Selnur Hatice. “Cognitive Dissonance and the Psychology of Sin.” The Fountain 80, March-April 2011.
2. van Dongen, Joost. “Proun sales data revealed: Proun is a big success! Pay What You Want is not!.” <http://joostdevblog.blogspot.com/2011/10/proun-is-big-success-pay-what-you-want.html>

According to a study by researchers of the Human Footprint Project [1], humans have influenced 83% of the earth’s surface. The study is based on four factors: population, travel routes, land use, and lights. One of the findings of the study shows that an average American is responsible for more carbon emissions in one year, than a person in Tanzania in a lifetime. This significant difference is certainly related to the average lifespan, income, culture, and climate. However, do any of us have the rights to disturb the environment more than others? Are we consuming something that doesn’t belong to us, and leaving an unsustainable environment for future generations? To answer these questions, it is imperative that we understand and acknowledge exactly what we have inherited, what we are responsible for, and what we will leave to future generations.

Our influence on the earth and environment in a general sense is not limited to the consumption of goods. One of the most influential yet less-visible traces is the footprint we leave in the digital environment. There are active or passive traces left in a digital environment by personal activity. An active trace is left when personal information is released by a person himself, whereas a passive trace (digital shadow) is left when personal data is collected during personal activity. These traces, also known as digital footprints, can spread very quickly and may reach to millions in a very short time. One can leave digital traces by simply visiting a website, sending a blog post, or posting a photo or message to a friend’s website.

Our digital traces affect the environment in many ways. Every trace takes our time to generate it and for others to read it. It consumes storage and network resources on the server that increase the costs, power usage, and eventually our carbon footprint, or the total greenhouse gas emissions. We need to seek a balance in our use of digital media in order to utilize the benefits efficiently and to minimize our consumption of time and other resources.

Have you ever wondered “how often a person leaves digital traces behind every day?” or “how much of our privacy are we sharing with others?” A recent study reveals some figures about the size of the digital universe as 281 billion gigabytes (GB) for 2008 and 1.8 billion terabytes for 2011 [2]. The digital trace generated by the average person on a daily basis was about 45 GB in 2008. This includes private information such as emails, photos, VOIP calls, and instant messages.

How about passive digital traces we leave behind by credit card purchases, bank accounts, phone records, web searches, general backup data, medical and hospital records, surveillance cameras, and so on? There are more passive traces collected than our active digital traces, which provide more personal information.

As of 2006, there were over 1 billion Visa credit cards worldwide and counting [3]. Credit cards give a lot of private information about a person: stores we prefer, movies we watch, places we travel, books we read, prescriptions we take, rent and utility fees we pay; mainly our lifestyle is hidden in our credit card statements. It might contain a lot of details we want to keep private. We can easily learn a lot about our social life just by analyzing one of our credit card statements.

Web searches provide more insightful information about a person. 113 billion web searches were conducted in July 2009, a 41 percent increase compared to 2008 [4]. Besides all the information we leave with our credit card, web searches may show things we have not actually done. They contain information about our future plans, such as travel, job search, health related issues, meetings, and education. Websites can provide smarter search results and personalized advertisements according to our search habits. Search engines even know how fast we type or process information, our typos, languages we speak, how smart we search, and even our physical location from the IP address.

Today many cars have GPS (Global Positioning System) capabilities and smart phones have GPS sensors. GPS devices can show our exact location anywhere in the world, provide turn-by-turn instructions from one location to another, provide a list of nearby stores, and warn us about traffic problems. A recent market research [5] estimates that the mobile location technology market that crosses the US will be $75 billion by 2013 with growing usage of GPS capabilities in automobiles and consumer electronics. Beside all the benefits, GPS devices leave an important digital trace behind, our exact location, which can be stored for later use or tracked by third parties.

Even if a person doesn’t have a GPS sensor with him, there are cameras all around the city that can help capture one’s location. We can see cameras inside and outside of the banks, stores, traffic lights, and even closed-circuit TV (CCTV) surveillance cameras in some cities. The total number of CCTV cameras in England is 4.2 million, or one for every 14 people according to an estimate. According to Scotland Yard, one crime per 1,000 CCTV cameras is solved in a year [6].

The number of smart phones increased 13.9 percent worldwide, compared to 2007, and reached 139 million in 2008 [7]. Many smart phones have real-time video streaming capabilities and are widely used. Users upload hundreds of thousands of videos per day to YouTube about themselves or people around them. Considering that there are thousands of video sharing websites like YouTube, sharing videos on these websites lies at the center of important privacy concerns. There are websites to share videos, photos, music, location, blog posts, and personal updates. With the rise of the micro-blogging trend, we can see real-time updates about a person on websites like Twitter. This allows us to track every minute of a person’s life.

Social networking is a new way of communication. Many websites provide tools to build online communities of people, who want to share and learn interests and activities of others. We can build our friend list and share photos, videos, and updates about our life. According to Nielsen Online’s report on Internet usage in June 2009 [8], users spent an average of 4 hours and 39 minutes during June on one of the most famous social networking sites, Facebook, which has 87 million visitors. Normally these websites provide privacy settings to limit who can access our friend list, photos, or other information. Since most of the people don’t refuse friend requests, it is very easy to be added as a friend and get access to all the private information of people we do not even know. Once we get accepted by a person as a friend, it gets easier to be accepted as friend by his/her friends, since we have mutual friends. These connections increase our friend list exponentially.

I had known about this process for some time, so I wanted to confirm it myself by setting up an account with fake information and identity on Facebook in 2008. I selected a college and input random personal information to my profile. I visited some group pages on Facebook and joined them. Then Facebook started to offer possible friend lists that have common interests with me. I started to make random friend requests to many users on these lists. In one day, I had around a hundred friends in my list that I don’t know personally. As a friend on their list, I have access to all information they share with others. Most of the users are using default settings and are not aware of privacy issues. Even if we are careful about all these settings and our privacy, our information is accessible by website managers. Digital traces left by users are valuable commercial assets for companies, and most of them share or sell this information to third party companies which provide online advertisements, products, and services.

There is a positive side of these digital traces. Websites provide better recommendation of products and services, targeted advertisements, smarter search results, and personal news. Entertainment businesses can provide appropriate suggestions by using location services. However, erasing our digital traces is difficult or even impossible in some cases. To protect our privacy and identity, it is essential that we are aware of places our personal information is stored. It is the responsibility of websites to protect user’s data. However, it will be a good start to be aware as users of our traces on the digital universe and to share personal information carefully.

With various effects on our natural and social environment, digital traces are one of the most influential and yet less known by-products of consumption. It is an important responsibility for us to decide how we affect our environment, how we spend our time, and what we are going to leave to future generations. With all the unique values given to humans, we need to learn to make meaningful contributions and carry more responsibility for our actions, especially in the digital world where boundaries are unlimited.

Acknowledgment: This article is produced either in part or a whole at MERGEOUS [9], an online article and project development service for authors and publishers dedicated to the advancement of technologies in the merging realm of science and religion.

Halil I. Demir is an internet entrepreneur and freelance writer.

References

1. Wildlife Conservation Society [http://www.wcs.org/humanfootprint]
2. EMC Report, “The Diverse and Exploding Digital Universe,” 2008.
3. Visa USA Internal Statistics, Q4 2006.
4. ComScore Press Release, August 31, 2009.
5. RNCOS Market Research Report, “World GPS Market Forecast to 2013,” April 2009.
6. Telegraph, 24 Aug 2009.
7. Gartner Press Release, Worldwide Smartphone Sales, Mart 2009.
8. Nielsen Online’s Report, June 2009.
9. Mergeous [http://www.mergeous.com]

Human beings are visually-oriented in their daily life; they use the sense of sight more than any of the other senses with which they have been endowed. The modern understanding of human vision and the underlining principles were only discovered in the past couple centuries. The nineteenth and twentieth centuries witnessed the development of photographic and digital imaging camera systems, which partially mimic human visual systems. We will open a small window on the history of human vision and camera systems, and try to compare today’s state-of-the-art cameras with the human visual system, focusing mainly on solid-state image sensors, or camera chips, and the image-sensing element of the human visual system, the eye.

History of human vision

Human vision has been the subject of conflicting interpretations since ancient times. Many ancient physicians and philosophers believed in the theory of extramission, or the active eye. According to this theory, the eye perceives objects by emanating light and seizing objects with its rays. It was in medieval Islamic culture that research on human vision and optics developed into a system similar to the modern theory of vision. Among others, Ibn Al-Haytham (Alhazen) (965-1040 A.D.), a Muslim physicist, astronomer, and mathematician in the tenth century, played a great part in this field by promoting the intromission theory which states that vision only occurs because of light rays entering the eye. Ibn Al-Haytham founded physiological optics, which distinguished the functioning of the eye from the behavior of light. On the other hand, ten centuries after Ibn Al-Haytham, Winer et al. (2002) have found recent evidence that as many as 50% of American college students believe in the extramission theory.1

Although the fundamental features, anatomy, and physiology of the eye were documented by Galen (129–200 A.D.), an ancient Greek physician, in the second century A.D., it was Kepler, a close reader of Ibn Al-Haytham, who offered the first theory of the retinal image and the correct operation of the eye in 1604. He proclaimed, “Therefore vision occurs through a picture of the visible things on the white, concave surface of the retina.” Progress came slowly after Kepler, because little was known about the nervous system until the nineteenth century, and only recently have scientists acquired a more knowledge about how the brain apprehends the retinal image. But many questions still elude us.

History of the camera

In parallel with curiosity about human vision, human beings have also tried to mimic human vision by capturing images of objects with instruments. Around 1000 A.D., Ibn Al-Haytham, also known as the father of modern optics, invented the pinhole camera,2 and explained why the image was upside down. It was Johannes Kepler who further suggested the use of a lens to improve the pinhole camera in the 1600s. Capturing an image on a photographic plate was first achieved in the early 1800s. Consequently, photographic cameras began to be mass-marketed in the twentieth century. The photographic equipment with which we are all familiar today, such as the 35mm camera, flash bulb, Polaroid camera, and the point-and-shoot auto focus camera, all were developed in the twentieth century. The invention of the camera as we know it today paved the way for other technologies, including the moving image capture, and, later, the digital camera, in which electronic image-capture devices were used. In 1972, chemically processing an image onto photographic paper no longer became the sole destination of an image, because the first filmless electronic camera was patented by Texas Instruments Corporation. Filmless electronic cameras were made possible with the invention of solid-state image-capture devices called charge coupled devices (CCD) and metal-oxide-semiconductor (MOS) image sensors in the late 1960s. Since the invention of solid-state imagers, people have become more visually stimulated and oriented than ever before in history.

A comparison of camera chips and the human eye

The technological advancements of solid-state image-capture camera chip design and manufacturing during the past twenty-five years has made digital imaging more affordable and accessible to the general public. These advancements have become more visible to consumers in mobile products, particularly in cellular phones, in which there are still and video-camera functions. Although digital cameras are easily available today, the state-of-the-art image sensor chips used in these cameras exhibit a performance gap when compared with the capabilities of the human eye. How good these image sensor chips are today when compared to our eyes is a question that will be elaborated on.

It is possible to compare the capabilities of the human eye and state-of-the-art image sensor chips used in cellular phones or in mainstream PC and digital still cameras. It is also possible to compare the capabilities of the human visual system, including the eyes, the optic nerve, the visual cortex, etc. with a digital camera system which includes optics, image-capture and signal-processing chips and other camera apparatuses. The capabilities include ability to see different colors (spectral response), photo-element (pixel) characteristics (size, density, distribution), light sensitivity, light-intensity response range, functionality and operation modes, and signal processing capabilities.

Spectral response

A single light-sensing element in a solid-state image sensor is called a pixel. In the human eye it is called the photoreceptor. Both elements convert impinging light or photons into electrical signals. The human eye sees in the so-called visible spectrum, between 380nm (blue) and 750 nm (red), and utilizes two kinds of photoreceptors on the retina; rods and cones. The cones are used for color and daylight vision. Rods are responsible for night vision. There are three types of cone photoreceptors on the retina that contain different types of photosensitive pigments. The three types of cones are L, M, and S, and they have pigments that respond best to wavelengths of light that are long or red (peak at 564 nm), medium or green (peak at 534 nm), and short or blue (peak at 420 nm), respectively. The rods (R) are most sensitive at a wavelength of approximately 498 nm (green), as seen in Figure 1.3 Image sensor pixels in digital cameras mimic the photoreceptors in the human eye for color vision. They utilize three kinds of color filters (red, green, blue) on top of each pixel to convert light rays into electrical signals in different visible spectrums. Unlike the cones in the human eye, camera pixels and color filters can be designed to cover wide spectrums that are not visible to the human eye, for instance, the x-ray, ultraviolet, and infrared spectrums. In the category of spectral response range, camera pixels exhibit greater flexibility than those of the photoreceptors of the human eye. On the other hand, interestingly enough, the eyesight that humans possess has similar spectral characteristics as the sun. The solar light emission peaks in the visible spectrum as seen in Figure 2.4

Figure 1. Spectral absorption curves of the short (S), medium (M), and long (L) wavelength pigments in human cone and rod cells.3

Figure 2. The daylight solar spectral power distribution on earth.4

Pixel and array size

The size of pixels in today’s modern digital cameras is getting closer to the size of the photoreceptors in human eye. The typical human eye contains an average of 130 million photoreceptors. The diameter of the rods and cones varies between 1.0m and 8.0m, depending on their location on the retina.5 Today’s state-of-the-art image sensor chips contain 10 to 30 million pixels. Each pixel can be as small as 1.4m in diameter. To date there has been no image sensor that is 1.4m pixel in size or more than 8 million pixels. However, the human being has been equipped with photoreceptors that are as small as 1.0m and has more than 100 million photoreceptors; and this is since the beginning of existence. It is also estimated that the resolution of the human eye is equivalent to an imager sensor chip of 576 million pixels with a 120 degree field of view.6 Thus we still have a long way to go in improving the image-sensor pixel and array sizes used in cameras if we are to match the human eye.

Pixel distribution and formation

In the human eye the photoreceptor size and densities change, depending on their location on the retina. For example, no rods exist on the focus center of the eye, which is called the fovea. Color vision photoreceptors, which total only 10% of the eye’s photoreceptors, are located mostly on the fovea. There is an irregular distribution of photoreceptors which is unique for every human being, like a fingerprint. Yet, we all see things the same, such as colors (with the exception of people who are colorblind). In camera chips, however, pixels are arrayed regularly, in two-dimensions. As the image-processing techniques and algorithms used in camera systems are linear and do not closely mimic the signal processing that exists in the human visual system, regularly arrayed pixels are required.

Light sensitivity and response range

Although the pixel sizes in image-sensor chips are approaching the size of the photoreceptors in the human eye, camera systems are not yet close to being able to match performance in terms of light sensitivity and response range. The human visual system and photoreceptors can easily adapt to very dim and bright light, with a light-intensity response range of ten billion to one (1010:1).7 This response range goes from light conditions on a bright sunny day to dim night vision. Typically, a conventional consumer camera pixel has a light intensity response range of one thousand to one (103:1).8 In a camera system, details of a captured scene are either concealed in the dark regions or washed out by the bright light, depending on the exposure settings of the system. Thus, one could say that the human visual system works ten million times (107) more efficiently than that of consumer cameras in terms of transferring scenes into images.

Operation principle

In terms of operation principles, the photoreceptors in the human eye convert light rays into electrical signals with extremely rapid electro-chemical reactions which can detect a single photon. Typically, in the image sensor pixel of a digital camera the photoelectric effect is used to convert impinging photons into electrical charges. Electrical charges are collected and stored in each pixel during the exposure period. Collected electric charges in each pixel are amplified and converted into digital ones (logic-1) and zeros (logic-0) during image readout before the image is sent to higher processing elements, such as a personal computer, digital-still or video camera. It is possible for a single photon-counting camera to be developed. However, very special and larger pixel sizes and extra apparatuses are required to build such a camera system. Thus, we could say that it is almost impossible to build imaging pixels that have the capability and dimensions of the photoreceptors of the human eye with today’s state-of-the-art technology.

Signal processing capabilities

The captured image in the human eye is preprocessed before it is sent to the visual cortex of the brain. This preprocessing consists of a data reduction operation in which nothing is lost, with a compression ratio of 130 to 1, as only 1 million optic nerves leave each eye carrying the information from 130 million photoreceptors. This compression allows the brain to process information at a rate of 25 to 150 scenes or frames per second. Typically, every pixel in an image sensor chip is first transferred to higher processing units. A data compression method is either carried out with some loss of details in the image or the compression is never used. The transfer of frames in camera chips typically takes place sequentially, reducing the speed of the image-capture operation or frame rate. Different techniques are used to maintain a capture rate of, at most, 25 frames-per-second in camera chips. With today’s technology, image sensors that have a capture rate of one million frames per second have been proposed and can be manufactured for scientific applications.

The inherent inefficiencies of image-capture in today’s image-sensor chips are hidden by employing the limitations of the human eye. For example, solid-state image sensors have always been produced with row or column-vice uncanny stripes which are easily picked up by the human eye. However, psycho-visual experiments have shown that the human eye can only detect contrasts between two adjacent gray lines when the difference is greater than 0.5%. Thus, if a camera chip is designed to have a column to column or row to row contrast of less than 0.5%, these odd stripes would not be visible.

Conclusion

Humans are visually oriented and without a doubt, our eyes are considered to be our primary source of information. It is obvious that the human visual system is extremely complex and this complexity has fascinated human beings throughout history. Yet, the underlining principles and basic functions of human vision and the eye have only been discovered during the last two centuries. These discoveries have led research in how to mimic these functions, which has resulted in moving and still-photographic and camera equipment, and the image sensors chips used in digital cameras today. Even though human beings are only taking baby steps in fully mimicking the human eye, curiosity and scientific inquiry allows us to discover functions and features of the eye and the visual pathways that will increase our knowledge and help us to build better pixels and image sensor chips.

References

1. Winer, G. A., Cottrell, J. E., Gregg, V., Fournier, J. S., & Bica, L. A., “Fundamentally misunderstanding visual perception: Adults’ beliefs in visual emissions.” American Psychologist, 57, 417-424, 2002.

2. Ertan Salik, “Pinhole Cameras, Imaging, and The Eye” The Fountain Magazine, Issue 54, pp. 30-33, April – June 2006.

3. URL: http://en.wikipedia.org/wiki/Image:Cone-response.png

4. URL: http://www.handprint.com/HP/WCL/color3.html

5. Stefan Winkler, Digital Video Quality – Vision Models and Metrics, John-Wiley & Sons, Ltd., 2005.

6. URL: http://www.clarkvision.com/imagedetail/eye-resolution.html

7. R.C. Gonzalez and R.E. Woods, Digital Image Processing, Addison-Wesley, 1993.

8. M. Schanz, et al., “A high-dynamic-range CMOS image sensor for automotive applications”, IEEE Journal of Solid-State Circuits, vol. 35, no. 7, pp.932-938, July 2000.

I would like to focus briefly on the twentieth century in terms of technological innovations and their impact on the human soul. The Industrial Revolution radically changed our traditional lifestyle. Modern technology engendered many improvements in such areas as production and transportation. These changes were reflected in the literature and art of the period as well.

Views of Technology

In 1909, for instance, the Italian writer Marinetti published The Manifesto of Futurism, a great example of how intellectuals were affected by technology. He states that the world’s magnificence has been enriched by this new beauty, the beauty of speed: We stand on the last promontory of the centuries! Why should we look back? What we want is to break down the mysterious doors of the impossible. Time and space died yesterday. We already live in the absolute, because we have created eternal, omnipresent speed. We will destroy the museums, libraries, academies of every kind, will fight moralism, feminism, every opportunistic or utilitarian cowardice.(1)

This approach is very understandable, because its adherents assumed that modern technology would provide opportunities they had never experienced. The prospects of technology amazed them. But looking back, we see that technology shaped a new type of people who are dependent on machines. Producing tools and making money became cornerstones of modern life. These views threaten cultural values and traditional relationships among people who feel alone in these technologically separated environments. We ask: How much do machines dominate humanity, and why do people feel so deeply abandoned?

We can look at two perspectives from that period. The first is technology as a magical and wonderful creation, promoted by Marinetti and other futurists. The other is characterized by people like Charlie Chaplain who, in one of his movies, shows a worker who screws bolts every day as eventually starting to see everything as a bolt. This is the worst effect of twentieth-century technology: People have begun to feel like machines or parts of machines.

Do people need and deserve more than this? Of course, they do.

The latest version of modern technology is cyberspace, a place where people can find all sorts of information. Locating information and sharing experiences is easier than ever before. The Internet, for example, has become the information superhighway on which people can find almost everything. The Internet and other technological tools have helped create the expression being digital, which refers to people who use a lot of technology. Is this the illusion of technological globalization(2) or electronic democracy will be the end of participatory democracy?(3) Even though this digital medium provides a new source of information, we have not figured out how best to use it or what information to trust on it.

Issues

At this point, we must learn how to use modern technology and regulate information, because we cannot ignore them. These scientific and technological advances will play important roles in future developments. Science and technology in and of themselves are not the problem, nor have they ever been. The real problem is that science and technology are developed, deployed, and controlled by the predatory system of pancapitalism. The mainstream development of knowledge and technology is guided by increased efficiency in militarized production of violence and/or by potential corporate profits in civilian markets.(4)

There is another significant point here: Modern technology has been trying to create a cyberbody. In the future, scientists will be able to produce digital flesh to enhance our abilities. So here is the problem we have to solve: People who have these enhancements installed may begin to wonder if they are humans or robots. We already have seen that people can adjust their bodies in many ways: laser surgery to correct their vision, or synthetic material to replace their teeth.

Cyberfeminism focusing on women’s role in cyberculture is another interesting example of changing the human body. This already has caused some problems. The challenge here is rather how to combine the recognition of postmodern embodiment with resistance to relativism and a free fall into cynicism.(5)

Technology has limited privacy. When we are born, we get a birth certificate that quickly goes online. Educational files, social security files, insurance files, criminal files, consumption files, and so on are all in cyberspace. The Internet has become an on-line marketplace and is continuing to grow.

On the other hand, even though we are so connected, our social relationships with others have fallen apart. Every relationship between teachers and students, buyers and sellers, parents and children, for example, will be changed radically in the next few decades.

The most important question is how can we find a good balance that gives happiness and hope for both our bodies and our souls? We are not just bodies that need to eat, sleep, and rest, among other things; our souls must be nourished. In this technological age, this has led to a conflict”the crisis of modernity”between religious and metaphysical ideas. Nietzsche said that God was dead. Of course he was wrong, because he, like other philosophers, could not have realized that spiritual needs would become so important in modern times.

Today, we still are seeking for something to feed modern society’s spiritual hunger. We will have to find or build a way of thinking that will include metaphysical ideas, scientific innovations, and religious thought. After that, we will be able to put ourselves in a place where people can regulate their spiritual and physical needs. Otherwise, we will never feel that we are free

Footnotes

1. F. T. Marinetti, The Manifesto of Futurism, Le Figaro (February 20, 1909).
2. Steve Gibson, www.kk.kau.se/mct/MCTO199/steve/ right.html.
3. An Interview with Paul Virilio, www.nettime.org/ nettime.w3archive/199904/msgn00456.html.
4. Critical Arts Ensemble Staff, Critical Art Ensemble, The Flesh Machine: Cyborgs, Designer Babies, and New Eugenic Consciousness (Autonomedia: 1998), 7-8.
5. Rosi Braidotti, Cyberfeminism with a Difference, www.let.ruu.nl/womens_studies/library.html.