Google Scholar: Use it

As we enter the final phase of research, a common dilemma is finding sources for thought that are not blogs, news articles. The following exercise is designed to increase the authoritative appearance of your research. To be an authority in research, you must show that you know the field.

In the next week, please use Google Scholar: — for ONE hour at least, searching for terms in your domain. Insert useful results into Zotero & post the results (a list of citations and quotations) on the blog.

The results provided there are pre-filtered: they represent research style writing. For university purposes, inclusion of results from these network searches can increase the credibility of your writing. Studying the style of results that exist in your subject area can also be useful as models for how-to write or structure and organize an essay.

Example paragraph from a scientific article. Note how it contains support for every statement.

While the categorization, interpretation and identification of faces from conspecifics is likely a consequence of the social life, which may have resulted in neural specialization for faces [11], it is a further challenge to achieve at least some of these abilities with faces of heterospecifics. The configuration of the face, the underlying facial muscles and the resulting expressions are more or less different from the own, depending on how taxonomically distant the other species is [12,13]. Nevertheless, a variety of animals have been shown to be able to identify and categorize faces and also emotions of heterospecifics (e.g. macaques [14], sheep [15], horses [16]). Several investigations on con- and heterospecific face processing suggest learned aspects in the information transfer and speed (c.f. face expertise, [1722]). Hereby individuals are able to recognize and discriminate best between faces similar to those that are most often seen in the environment. For instance, the influence of individual experience with the other species was shown for urban living birds like magpies [23] and pigeons [24]. Especially early exposure to faces facilitates the ability of face discrimination [25,26]. Although some individuals are able to learn about heterospecific faces also later in life (e.g. chimpanzees [27], rhesus macaques [28]), they will not reach the same high level of competence [12,21]. It remains an open question, however, whether the improved abilities to read faces due to early life exposure are caused solely by an acquired early sensitivity for faces (innate mechanisms) or simply by the larger amount of experience (learned responses).

Barber, Anjuli L. A., Dania Randi, Corsin A. Müller, and Ludwig Huber. “The Processing of Human Emotional Faces by Pet and Lab Dogs: Evidence for Lateralization and Experience Effects.” PLOS ONE 11, no. 4 (April 13, 2016): e0152393. doi:10.1371/journal.pone.0152393.

Or note how in the prologue from 

Hayles, N. Katherine. How We Became Posthuman: Virtual Bodies in Cybernetics, Literature, and Informatics. Chicago, Ill: University of Chicago Press, 1999. — Hayles weaves story with concrete reference.
You are alone in the room, except for two computer terminals flickering in the dim light. You use the terminals to communicate with two entities in another room, whom you cannot see. Relying solely on their responses to your questions, you must decide which is the man, which the woman. Or, in another version of the famous “imitation game” proposed by Alan Turing in his classic 1950 paper “Computer Machinery and Intelligence,” you use the responses to decide which is the human, which the machine.1 One of the entities wants to help you guess correctly. His/her/its best strategy, Turing suggested, may be to answer your questions truthfully. The other entity wants to mislead you. He/she/it will try to reproduce through the words that appear on your terminal the characteristics of the other entity. Your job is to pose questions that can distinguish verbal performance from embodied reality. If you cannot tell the intelligent machine from the intelligent human, your failure proves, Turing argued, that machines can think.

Tortoises, Neural Nets and Cybernetics

Neural nets are currently the most hyped format for artificial intelligence. What are they? Basically they are an attempt to emulate a brain by building a mathematical pattern recognition process with a network of nodes. Neural nets underlie many recent image and speech recognition and generation advances.


The contemporary neural net resurgence is often traced to Geoffrey Hinton whose work gave rise to convolutional neural networks. Convolution is mathematical treatment of matrices of values; but it can also be understood as simple feature extraction since it’s been used in image processing to find outlines and edges. What the neural nets do (at a very simple level) is find those edges, compare the similarity of those edges in data, then cluster the edges that are similar, apply the filter again, repeat. Essentially building a weighted graph: lines between nodes in a network, thick lines have more weight suggesting connection. Treating any data in this way gives rise to surprising insights. For examples the sentiment or emotion in language can be extracted (for more info: here’s a very brief review I wrote of Socher’s 2014 sentiment treebank).

Recently Google DeepMind labs succeeded in beating a Go master.

And the conceptual roots of these neural nets arises from cybernetics, the idea of a feedback loop, Frank Rosenblatt ( in 1957 proposed single-layer perceptrons which were expanded into multi-layer perceptrons which became neural nets), Gregory Bateson (difference that makes a difference), Grey Walter (early robotic homeostatic machines with sensors and simple feedback elicting complex behavior, see video below), Warren McCulloch and Walter Pitts (synaptic inhibition within networks), W Ross Ashby (information theory), Norbert Weiner and the Macy conferences.

258px-Wiener_Norbert_Cybernetics_or_the_Control_and_Communication_in_the_Animal_and_the_Machine (1)Margeret Boden (whose exhaustive Mind as Machine 2 volume history of cognitive science is the canonical reference for 20th century cybernetic history; at 1452 pages with 134 pages of references, it includes references to all of the major figures) wrote:

Grey Walter’s intriguing tortoises, despite their valve technology and clumsiness, were early versions of what would much later be called Vehicles,38 autonomous agents, situated robots, or animats. They illustrated the emergence of relatively complex motor behaviour—analogous to positive and negative tropisms, goal seeking, perception, learning, and even sociability—out of simple responses guided and stabilized by negative feedback.


Electronic Superhighway (2016-1966) at Whitechapel Gallery

“The exhibition title is taken from a term coined in 1974 by South Korean video art pioneer Nam June Paik, who foresaw the potential of global connections through technology.” – Exhibit website

“The show—featuring over 100 works by 70 artists—is curated by Omar Kholeif, who flips chronology on its head.” – Review by ArsElectronica

Robin Dunbar: Social Brain Hypothesis (SBH)

Social networks seem to suggest that suddenly due to the internet we can have many friends; more friends means more support. Research suggests the opposite.

Anthropologist Robin Dunbar’s Social Brain Hypothesis (SBH) establishes a “quantitative relationship between group size and brain size”. In other words, our cognitive architecture (brain, body, heart, pores, etc…) limits the number of deep friendships (3-15 people) we can develop simultaneously. We are evolutionary creatures adapted for small clusters (villages of 150-200) immersed in an augmented networked situation.

In 1996, Dunbar wrote an excellent readable book Grooming Gossip and the Evolution of Language which argued that human language was actually a tool for power dynamics between tribe members, thus an aspect of social hierarchy; and that human community sizes are regulated by neocortex size. In 2016 his recently-published research concerns friendships in the era of Facebook; his results confirm his contention that:

…there is a cognitive constraint on the size of social networks that even the communication advantages of online media are unable to overcome…

This limit is thought to arise from a combination of a cognitive constraint (the product of the relationship with neocortex size known as the social brain hypothesis (SBH) [18,23]) and a time constraint associated with the costs of servicing relationships [24,25].

Who would support you in crisis? For many years sociologists have referred to a core support group as a grief/bereavement network; it follows a network typology/topology (which means it has the shape and form of a physical network and obeys similar dynamics). Dunbar distinguishes between “support clique (friends on whom you would depend for emotional/social support in times of crisis) and sympathy group (close friends).” Average is 4.1 for support clique and 13.6 for sympathy group. Dunbar’s research also finds that women have more friends than men, young people have more online friends, and teenagers have much smaller offline communities than adults.

His primary conclusion:

We can only interact coherently with a very small number of other people (about three, in fact) at any one time [40,41]. It seems that even in an online environment, the focus of our attention is still limited in this way.

Dunbar, Prof. Robin. 1997. Grooming, Gossip, and the Evolution of Language. Harvard University Press.

Dunbar, R. I. M. 2009. “The Social Brain Hypothesis and Its Implications for Social Evolution.” Annals of Human Biology 36 (5): 562–72. doi:10.1080/03014460902960289.

Traumawein (2014), Campbell & Huff: Psycho (2011) & Gannis: In Search of … (2013)

Since September 2014, the Traumawein Product Store uses the Traumawein Product Algorithm to select and repurpose (without authorisation) Tweets and Facebook status updates through POD (print-on-demand) portals like CafePress, Zazzle, Pikistore or Printalloverme.

Post Digital is the conscious decision to dispense a final, physical product with respect to integrate latest conditions of digital media. Just like the printed book, the product (or object) is a freezing of time and information as a means and way to consider reflection”

A ‘traditional-media book’ published by Traumawein is Mimi Campbell and Jason Huff’s rendition of American Psycho, a book written

“by sending the entire text of Bret Easton Ellis’ American Psycho between two GMail accounts page by page. We saved the relational ads for each page and added them back into the text as footnotes. In total, we collected over 800 relevant ads for the book. The constellations of footnoted ads throughout these pages retell the story of American Psycho in absence of the original text.”

The authors speak of this as a blurry portrait of an algorithm. It repurposes serial killing as ubiquitous corporate power; and networks as identity visceration.

Network evisceration of identity, coding death, defining entities through algorithms, haunts Carla Gannis’ existential In Search Of (Self Portrait Study 01 for \ˈgü-gəl\e Results Project) a video made by

“searching string phrases on Google and publishing them on social networks, primarily twitter, as a way to share a textual snapshot of my thoughts relative to the hive mind that exists within my Googlesphere”  

The leviathan rising from Milton’s lake, subconscious bearer of light and darkness, is now the network-platform A.I., drenched in our identities, bearing both scandals and a smear of erased relevance. It comes with a warranty, demanding we sign an EULA before we read ourselves.


Céleste Boursier-Mougenot

Boursier-Mougenot originally trained not as an artist but as a musician, at the Conservatory for Music in Nice. His time as composer for the avant-garde Pascal Rambert theatre company, from 1985 to 1994, pushed his work into more experimental realms. Starting in the early 1990s, he began to stage sound installations in art galleries, venues where his ideas for compositions could unfold over long stretches of time.

Zebra finches exemplify a stochastic system: living untamed integrated into a sculptural-sonic process, they satirize and question the uniqueness of human creativity. Flocks are networks governed by simple rules. Melodic improvisation is part randomization, part social: an activity that emphasizes the human capacity to project meanings onto patterns, to discern structure within sets.

Very Nervous System (1982-1991) by David Rokeby

Very Nervous System was the third generation of interactive sound installations which I have created. In these systems, I use video cameras, image processors, computers, synthesizers and a sound system to create a space in which the movements of one’s body create sound and/or music.

The body is implicated as a map within the sensor field. Motion invokes music. Essentially this instrument provokes the user to explore how the sensors map gesture to make music: in this way dance becomes an exploration of an esoteric exterior system whose contours only slowly (if ever) become known.

I created the work for many reasons, but perhaps the most pervasive reason was a simple impulse towards contrariness. The computer as a medium is strongly biased. And so my impulse while using the computer was to work solidly against these biases. Because the computer is purely logical, the language of interaction should strive to be intuitive. Because the computer removes you from your body, the body should be strongly engaged. Because the computer’s activity takes place on the tiny playing fields of integrated circuits, the encounter with the computer should take place in human-scaled physical space. Because the computer is objective and disinterested, the experience should be intimate.