Algorithm, Analog Computing, Art, Automata, Bacteria, Biological Computation, Biology, Cybernetics, Deep Learning

Beyond design: cybernetics, biological computers and hylozoism (Pickering 2008)

Analog Computing, Bio hacking, Biological Computation, Biology, Biometrics, Brain, Cybernetics, DNA, Science

Mind-controlled transgene expression by a wireless-powered optogenetic designer cell implant

“Mammalian synthetic biology has significantly advanced the design of gene switches that are responsive to traceless cues such as light, gas and radio waves, complex gene circuits, including oscillators, cancer-killing gene classifiers and programmable biocomputers, as well as prosthetic gene networks that provide treatment strategies for gouty arthritis, diabetes and obesity. Akin to synthetic biology promoting prosthetic gene networks for the treatment of metabolic disorders, cybernetics advances the design of functional man–machine interfaces in which brain–computer interfaces (BCI) process brain waves to control electromechanical prostheses, such as bionic extremities and even wheel chairs. The advent of synthetic optogenetic devices that use power-controlled, light-adjustable therapeutic interventions18 will enable the merging of synthetic biology with cybernetics to allow brain waves to remotely control the transgene expression and cellular behaviour in a wireless manner.”


Art, Biology, Cybernetics, ecology, History, music theory, systems theory

communication +1, 3(1): Afterlives of Systems (2014) (pdf)


“Under the impression of today’s global crisis and the rise of ecological thinking, confronted with smart, ubiquitous technosystems and the impression of interconnectedness, there appears a new urge to excavate the remnants of the past. The articles of this issue suggest that in order to understand present technologies, we need to account the systems thinking that fostered their emergence, and that we cannot gain insight into the afterlives of systems without exploring their technologies.

The nine contributions ask how these debates and affective states survive and live on in today’s discussions of media ecologies, environmentalism, object-oriented philosophies, computer simulations, performative art, and communication technologies. In this sense, they take the renaissance of systems thinking in the late 20th and early 21st Century as an effect of various system crisis and explore new media technologies as stabilizing ‘cures’ against the dystopian future scenarios that emerged after World War II. The articles of this issue suggest that in order to understand present technologies, we need to account the systems thinking that fostered their emergence, and that we cannot gain insight into the afterlives of systems without exploring their technologies.”

AI, Algorithm, Automata, Biological Computation, Code, Cybernetics, Deep Learning, Emergence, Man/Machine, Neural Networks, Robots, Science, Social intelligence, Society

Can a robot be too nice?

“Designing artificial entities perfectly groomed to meet our emotional needs has an obvious appeal, like creating the exact right person for a job from thin air. But it’s also not hard to imagine the problems that might arise in a world where we’re constantly dealing with robots calibrated to treat us, on an interpersonal level, exactly the way we want. We might start to prefer the company of robots to that of other, less perfectly optimized humans. We might react against them, hungry for some of the normal friction of human relations. As Lanier worried, we might start to see the lines blur, and become convinced that machines—which in some ways are vastly inferior to us, and in other ways vastly superior—are actually our equals.”


AI, Algorithm, Biometrics, Brain, Capitalism, Cybernetics, Economy, Education, Emergence, Ethics, Man/Machine, Robots, Science, Social intelligence, Society

Will You Lose Your Job To a Robot?

“The biggest exception will be jobs that depend upon empathy as a core capacity — schoolteacher, personal service worker, nurse. These jobs are often those traditionally performed by women. One of the bigger social questions of the mid-late 2020s will be the role of men in this world.” — Jamais Cascio, technology writer and futurist


Algorithm, Analog Computing, Brain, Code, Cybernetics, Download, History, Interface, Logic, Mathematics, Memory

From Memex to Hypertext: Vannevar Bush and the Mind’s Machine (1991)

“Vannevar Bush, the engineer who designed the world’s most powerful analog computer, envisioned the development of a new kind of computing machine he called Memex. For many computer and information scientists, Bush’s Memex has been the prototype for a machine to help people think. This volume, which the editors have divided into sections on the creation, extension, and legacy of the Memex, combines seven essays by Bush with eleven others by others that set his ideas within a variety of contexts. The essays by Bush range chronologically from the early “The Inscrutable Thirties” (1933), “Memorandum Regarding Memex” (1941), and “As We May Think” (1945), to “Memex II” (1959), “Science Pauses” (1967), “Memex Revisited” (1967), and a passage from “Of Inventions and Inventors” (1970). Bush’s essays are surrounded by four chapters that place his changing plans for the Memex within his career and within information technology before digital computing. The contributors include Larry Owens, Colin Burke, Douglas C. Engelbart, Theodor H. Nelson, Linda C. Smith, Norman Meyrowitz, Tim Oren, Gregory Crane, and Randall H. Trigg.”

Memex animation


AI, Algorithm, Automata, Biological Computation, Brain, Code, Cybernetics, Deep Learning, Logic, Man/Machine, Mathematics, Neural Networks, Science, Social intelligence

Neural Networks and Deep Learning

“Will we understand how such intelligent networks work? Perhaps the networks will be opaque to us, with weights and biases we don’t understand, because they’ve been learned automatically. In the early days of AI research people hoped that the effort to build an AI would also help us understand the principles behind intelligence and, maybe, the functioning of the human brain. But perhaps the outcome will be that we end up understanding neither the brain nor how artificial intelligence works!”