One of many interesting things about the history of punch needle is its origin. The beginnings of this form of rug hooking date back to the 15th century when it was first referred to as "punch stitch." Back then, it was mainly used for the embellishment of religious clothing. Sailors while on long voyages used to wile the time away punching these miniature rugs, and it became a hobby for seafaring men. Appeal for this form of rug hooking began to dwindle in the late 1800's, but recently there has been a resurgence and a keen spark of interest in this fascinating pastime. It began as a yarn craft, and remains a yarn craft for most punchers, though some yarns look more like embroidery floss in a finished design. Fine gauge acrylic, lusters and polyester yarns are used extensively for Punch Needle Stitchery and look very delicate when finished. These yarns are also easier to use without constant re-threading. Punch needle embroidery is often referred to as thread painting, since it can be used to depict scenes, not unlike an oil painting. This technique and its variants are known as Punch, Punch Embroidery, Punch Needle Embroidery, Russian Embroidery and Bunka. Although these terms are not the same, they do use the same tool, a punch needle. The basic concept is simple; you punch the yarn through a fabric with a hollow pencil shaped needle, and it leaves tufted loops of yarn over top of the fabric. Punch Needle is more closely related to hook rug than embroidery, but the application and end product are better described as embroideries than rugs. Punch needle is a rapidly growing revival. It's quick, easy, and seems to be the latest needle craze! You can start a punch needle project in the afternoon and be finished with it by evening. Take the next step by becoming a part of history making a contribution to the history of punch needle.
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‘Phrenology’ has an old-fashioned ring to it. It sounds like it belongs in a history book, filed somewhere between bloodletting and velocipedes. We’d like to think that judging people’s worth based on the size and shape of their skull is a practice that’s well behind us. However, phrenology is once again rearing its lumpy head. In recent years, machine-learning algorithms have promised governments and private companies the power to glean all sorts of information from people’s appearance. Several startups now claim to be able to use artificial intelligence (AI) to help employers detect the personality traits of job candidates based on their facial expressions. In China, the government has pioneered the use of surveillance cameras that identify and track ethnic minorities. Meanwhile, reports have emerged of schools installing camera systems that automatically sanction children for not paying attention, based on facial movements and microexpressions such as eyebrow twitches. Perhaps most notoriously, a few years ago, AI researchers Xiaolin Wu and Xi Zhang claimed to have trained an algorithm to identify criminals based on the shape of their faces, with an accuracy of 89.5%. They didn’t go so far as to endorse some of the ideas about physiognomy and character that circulated in the 19th century, notably from the work of the Italian criminologist Cesare Lombroso: that criminals are underevolved, subhuman beasts, recognizable from their sloping foreheads and hawk-like noses.
However, the recent study’s seemingly high-tech attempt to pick out facial features associated with criminality borrows directly from the ‘photographic composite method’ developed by the Victorian jack-of-all-trades Francis Galton - which involved overlaying the faces of multiple people in a certain category to find the features indicative of qualities like health, disease, beauty, and criminality. Technology commentators have panned these facial-recognition technologies as ‘literal phrenology’; they’ve also linked it to eugenics, the pseudoscience of improving the human race by encouraging people deemed the fittest to reproduce. In some cases, the explicit goal of these technologies is to deny opportunities to those deemed unfit; in others, it might not be the goal, but it’s a predictable result. Yet when we dismiss algorithms by labeling them as phrenology, what exactly is the problem we’re trying to point out? Are we saying that these methods are scientifically flawed and that they don’t really work - or are we saying that it’s morally wrong to use them regardless?
There is a long and tangled history to the way ‘phrenology’ has been used as a withering insult. Philosophical and scientific criticisms of the endeavor have always been intertwined, though their entanglement has changed over time. In the 19th century, phrenology’s detractors objected to the fact that phrenology attempted to pinpoint the location of different mental functions in different parts of the brain - a move that was seen as heretical, since it called into question Christian ideas about the unity of the soul. Interestingly, though, trying to discover a person’s character and intellect based on the size and shape of their head wasn’t perceived as a serious moral issue. Today, by contrast, the idea of localizing mental functions is fairly uncontroversial. Scientists might no longer think that destructiveness is seated above the right ear, but the notion that cognitive functions can be localized in particular brain circuits is a standard assumption in mainstream neuroscience. Read: How do you build a pet-friendly gadget?
Phrenology had its share of empirical criticism in the 19th century, too. Debates raged about which functions resided where, and whether skull measurements were a reliable way of determining what’s going on in the brain. The most influential empirical criticism of old phrenology, though, came from the French physician Jean Pierre Flourens’s studies based on damaging the brains of rabbits and pigeons - from which he concluded that mental functions are distributed, rather than localized. The fact that phrenology was rejected for reasons that most contemporary observers would no longer accept makes it only more difficult to figure out what we’re targeting when we use ‘phrenology’ as a slur today. Both ‘old’ and ‘new’ phrenology have been critiqued for their sloppy methods. In the recent AI study of criminality, the data were taken from two very different sources: mugshots of convicts, versus pictures from work websites for nonconvicts. That fact alone could account for the algorithm’s ability to detect a difference between the groups.