Category Archives: science

Superconductivity with spin

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Vivid lines of light tracing a pattern reminiscent of a spinning top toy Courtesy: Harvard University

Vivid lines of light tracing a pattern reminiscent of a spinning top toy Courtesy: Harvard University

An Oct. 14, 2016 Harvard University John A. Paulson School of Engineering and Applied Sciences (SEAS) press release (also on EurekAlert) by Leah Burrows describes how scientists have discovered a way to transmit spin information through supercapacitors,

Researchers from the Harvard John A. Paulson School of Engineering and Applied Sciences (SEAS) have made a discovery that could lay the foundation for quantum superconducting devices. Their breakthrough solves one the main challenges to quantum computing: how to transmit spin information through superconducting materials.

Every electronic device — from a supercomputer to a dishwasher — works by controlling the flow of charged electrons. But electrons can carry so much more information than just charge; electrons also spin, like a gyroscope on axis.

Harnessing electron spin is really exciting for quantum information processing because not only can an electron spin up or down — one or zero — but it can also spin any direction between the two poles. Because it follows the rules of quantum mechanics, an electron can occupy all of those positions at once. Imagine the power of a computer that could calculate all of those positions simultaneously.

A whole field of applied physics, called spintronics, focuses on how to harness and measure electron spin and build spin equivalents of electronic gates and circuits.

By using superconducting materials through which electrons can move without any loss of energy, physicists hope to build quantum devices that would require significantly less power.

But there’s a problem.

According to a fundamental property of superconductivity, superconductors can’t transmit spin. Any electron pairs that pass through a superconductor will have the combined spin of zero.

In work published recently in Nature Physics, the Harvard researchers found a way to transmit spin information through superconducting materials.

“We now have a way to control the spin of the transmitted electrons in simple superconducting devices,” said Amir Yacoby, Professor of Physics and of Applied Physics at SEAS and senior author of the paper.

It’s easy to think of superconductors as particle super highways but a better analogy would be a super carpool lane as only paired electrons can move through a superconductor without resistance.

These pairs are called Cooper Pairs and they interact in a very particular way. If the way they move in relation to each other (physicists call this momentum) is symmetric, then the pair’s spin has to be asymmetric — for example, one negative and one positive for a combined spin of zero. When they travel through a conventional superconductor, Cooper Pairs’ momentum has to be zero and their orbit perfectly symmetrical.

But if you can change the momentum to asymmetric — leaning toward one direction — then the spin can be symmetric. To do that, you need the help of some exotic (aka weird) physics.

Superconducting materials can imbue non-superconducting materials with their conductive powers simply by being in close proximity. Using this principle, the researchers built a superconducting sandwich, with superconductors on the outside and mercury telluride in the middle. The atoms in mercury telluride are so heavy and the electrons move so quickly, that the rules of relativity start to apply.

“Because the atoms are so heavy, you have electrons that occupy high-speed orbits,” said Hechen Ren, coauthor of the study and graduate student at SEAS. “When an electron is moving this fast, its electric field turns into a magnetic field which then couples with the spin of the electron. This magnetic field acts on the spin and gives one spin a higher energy than another.”

So, when the Cooper Pairs hit this material, their spin begins to rotate.

“The Cooper Pairs jump into the mercury telluride and they see this strong spin orbit effect and start to couple differently,” said Ren. “The homogenous breed of zero momentum and zero combined spin is still there but now there is also a breed of pairs that gains momentum, breaking the symmetry of the orbit. The most important part of that is that the spin is now free to be something other than zero.”

The team could measure the spin at various points as the electron waves moved through the material. By using an external magnet, the researchers could tune the total spin of the pairs.

“This discovery opens up new possibilities for storing quantum information. Using the underlying physics behind this discovery provides also new possibilities for exploring the underlying nature of superconductivity in novel quantum materials,” said Yacoby.

Here’s a link to and a citation for the paper,

Controlled finite momentum pairing and spatially varying order parameter in proximitized HgTe quantum wells by Sean Hart, Hechen Ren, Michael Kosowsky, Gilad Ben-Shach, Philipp Leubner, Christoph Brüne, Hartmut Buhmann, Laurens W. Molenkamp, Bertrand I. Halperin, & Amir Yacoby. Nature Physics (2016) doi:10.1038/nphys3877 Published online 19 September 2016

This paper is behind a paywall.

Creative destruction for Canada’s fundamental science

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After receiving an ‘invitation’ from the Canadian Science Policy Centre, I wrote an opinion piece, drawing on my submission for the public consultation on Canada’s fundamental science research. It seems the invitation was more of a ‘call’ for submissions and my piece did not end up being selected for inclusion on the website. So rather than waste the piece, here it is,

Creative destruction for Canada’s fundamental science

At a time when we are dealing with the consequences of our sins and virtues, fundamental science, at heart, an exercise in imagination, can seem a waste of precious time. Pollution and climate change (sins: ill-considered uses of technology) and food security and water requirements (virtues: efforts to improve health and save more lives) would seem to demand solutions not the flights of fancy associated with basic science. After all, what does the ‘big bang’ have to do with potable water?

It’s not an unfair question despite the impatience some might feel when answering it by citing a number of practical applications which are the result of all that ‘fanciful’ or ‘blue sky’ science. The beauty and importance of the question is that it will always be asked and can never be definitively answered, rendering it a near constant goad or insurance against complacency.

In many ways Canada’s review of fundamental science (deadline for comments was Sept. 30, 2016) is not just an examination of the current funding schemes but an opportunity to introduce more ‘goads’ or ‘anti-complacency’ measures into Canada’s fundamental science efforts for a kind of ‘creative destruction’.

Introduced by economist Joseph Schumpeter, the concept is derived from Karl Marx’s work but these days is associated with disruptive, painful, and regenerative innovation of all kinds and Canadian fundamental science needs more ‘creative destruction’. There’s at least one movement in this direction (found both in Canada and internationally) which takes us beyond uncomfortable, confrontative questions and occasional funding reviews—the integration of arts and humanities as an attempt at ‘creative destruction’ of the science endeavour.

At one point in the early 2000s, Canada developed a programme where the National Research Council could get joint funding with the Canada Council for the Arts for artists to work with their scientists. It was abandoned a few years later, as a failure. But, since then, several informal attempts at combining arts, sciences, and humanities have sprung up.

For example, Curiosity Collider (founded in 2015) hosts artists and scientists presenting their art/science pieces at various events in Vancouver. Beakerhead has mashed up science, engineering, arts, and entertainment in a festival founded and held in Calgary since 2013. Toronto’s ArtSci Salon hosts events and installations for local, national, and international collaborations of artists and scientists. And, getting back to Vancouver, Anecdotal Evidence is a science storytelling series which has been appearing sporadically since 2015.

There is a tendency to dismiss these types of collaboration as a form of science outreach designed to amuse or entertain but they can be much more than that. Illustrators have taught botanists a thing or two about plants. Markus Buehler at the Massachusetts Institute of Technology has used his understanding of music to explore material science (spider’s webs). Domenico Vicinanza has sonified data from space vehicle, Voyager 1, to produce a symphony, which is also a highly compressed means of communicating data.

C. P. Snow’s ‘The Two Cultures’ (lecture and book) covered much of the same territory in 1959 noting the idea that the arts and sciences (and humanities) can and should be linked in some fashion was not new. For centuries the sciences were referred to as Natural Philosophy (humanities), albeit only chemistry and physics were considered sciences, and many universities have or had faculties of arts and sciences or colleges of arts and science (e.g., the University of Saskatchewan still has such a college).

The current art/sci or sci-art movement can be seen as more than an attempt to resuscitate a ‘golden’ period from the past. It could be a means of embedding a continuous state of regeneration or ‘creative destruction’ for fundamental science in Canada.

A computer that intuitively predicts a molecule’s chemical properties

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First, we have emotional artificial intelligence from MIT (Massachusetts Institute of Technology) with their Kismet [emotive AI] project and now we have intuitive computers according to an Oct. 14, 2016 news item on Nanowerk,

Scientists from Moscow Institute of Physics and Technology (MIPT)’s Research Center for Molecular Mechanisms of Aging and Age-Related Diseases together with Inria research center, Grenoble, France have developed a software package called Knodle to determine an atom’s hybridization, bond orders and functional groups’ annotation in molecules. The program streamlines one of the stages of developing new drugs.

An Oct. 14, 2016 Moscow Institute of Physics and Technology press release (also on EurekAlert), which originated the news item, expands on the theme,

Imagine that you were to develop a new drug. Designing a drug with predetermined properties is called drug-design. Once a drug has entered the human body, it needs to take effect on the cause of a disease. On a molecular level this is a malfunction of some proteins and their encoding genes. In drug-design these are called targets. If a drug is antiviral, it must somehow prevent the incorporation of viral DNA into human DNA. In this case the target is viral protein. The structure of the incorporating protein is known, and we also even know which area is the most important – the active site. If we insert a molecular “plug” then the viral protein will not be able to incorporate itself into the human genome and the virus will die. It boils down to this: you find the “plug” – you have your drug.

But how can we find the molecules required? Researchers use an enormous database of substances for this. There are special programs capable of finding a needle in a haystack; they use quantum chemistry approximations to predict the place and force of attraction between a molecular “plug” and a protein. However, databases only store the shape of a substance; information about atom and bond states is also needed for an accurate prediction. Determining these states is what Knodle does. With the help of the new technology, the search area can be reduced from hundreds of thousands to just a hundred. These one hundred can then be tested to find drugs such as Reltagravir – which has actively been used for HIV prevention since 2011.

From science lessons at school everyone is used to seeing organic substances as letters with sticks (substance structure), knowing that in actual fact there are no sticks. Every stick is a bond between electrons which obeys the laws of quantum chemistry. In the case of one simple molecule, like the one in the diagram [diagram follows], the experienced chemist intuitively knows the hybridizations of every atom (the number of neighboring atoms which it is connected to) and after a few hours looking at reference books, he or she can reestablish all the bonds. They can do this because they have seen hundreds and hundreds of similar substances and know that if oxygen is “sticking out like this”, it almost certainly has a double bond. In their research, Maria Kadukova, a MIPT student, and Sergei Grudinin, a researcher from Inria research center located in Grenoble, France, decided to pass on this intuition to a computer by using machine learning.

Compare “A solid hollow object with a handle, opening at the top and an elongation at the side, at the end of which there is another opening” and “A vessel for the preparation of tea”. Both of them describe a teapot rather well, but the latter is simpler and more believable. The same is true for machine learning, the best algorithm for learning is the simplest. This is why the researchers chose to use a nonlinear support vector machines (SVM), a method which has proven itself in recognizing handwritten text and images. On the input it was given the positions of neighboring atoms and on the output collected hybridization.

Good learning needs a lot of examples and the scientists did this using 7605 substances with known structures and atom states. “This is the key advantage of the program we have developed, learning from a larger database gives better predictions. Knodle is now one step ahead of similar programs: it has a margin of error of 3.9%, while for the closest competitor this figure is 4.7%”, explains Maria Kadukova. And that is not the only benefit. The software package can easily be modified for a specific problem. For example, Knodle does not currently work with substances containing metals, because those kind of substances are rather rare. But if it turns out that a drug for Alzheimer’s is much more effective if it has metal, the only thing needed to adapt the program is a database with metallic substances. We are now left to wonder what new drug will be found to treat a previously incurable disease.

Scientists from MIPT's Research Center for Molecular Mechanisms of Aging and Age-Related Diseases together with Inria research center, Grenoble, France have developed a software package called Knodle to determine an atom's hybridization, bond orders and functional groups' annotation in molecules. The program streamlines one of the stages of developing new drugs. Credit: MIPT Press Office

Scientists from MIPT’s Research Center for Molecular Mechanisms of Aging and Age-Related Diseases together with Inria research center, Grenoble, France have developed a software package called Knodle to determine an atom’s hybridization, bond orders and functional groups’ annotation in molecules. The program streamlines one of the stages of developing new drugs. Credit: MIPT Press Office

Here’s a link to and a citation for the paper,

Knodle: A Support Vector Machines-Based Automatic Perception of Organic Molecules from 3D Coordinates by Maria Kadukova and Sergei Grudinin. J. Chem. Inf. Model., 2016, 56 (8), pp 1410–1419 DOI: 10.1021/acs.jcim.5b00512 Publication Date (Web): July 13, 2016

Copyright © 2016 American Chemical Society

This paper is behind a paywall.

Monster science (a book announcement and interview)

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Helaine Becker has launched a new children’s science book incorporating monsters with science. The title, unsurprisingly, is: ‘Monster Science’. Here’s more about the book from Helaine’s Oct. 14, 2016 post on Sci/Why where she shares two reviews,

“From Frankenstein’s creation to Nessie, Becker uses the creatures of our scariest stories as a springboard for an introduction to the scientific understandings that might make such creatures possible—or impossible. In addition to man-made monsters and legendary sea creatures, she covers vampires, zombies, werewolves, and wild, humanlike creatures like Bigfoot. Chapter by chapter, she provides references from literature, film, and popular culture, including a bit of science, a bit of history, and a plentiful helping of humor. She includes numerous monster facts, suggests weapons of defense, and concludes each section with a test-yourself quiz. Science topics covered range widely: electricity, genetic engineering, “demonic diseases,” the nature of our blood and the circulatory system, the possibility of immortality, animal classification, evolution, cannibalism, optical illusions, heredity, hoaxes, and the very real profession of cryptozoology, or the search for hitherto unidentified creatures. … Kirkus

Then, there’s this one,

“A highlight of this work is its exploration of the often symbiotic relationship between culture and science; figures such as Shelley, John Polidori (The Vampyre), and filmmaker George Romero (Night of the Living Dead) merged cultural fascination with scientific development to create truly inspiring works and further public interest in science… School Library Journal

Interview with Helaine Becker

Not to be confused with ‘Interview with a vampire’, this one is not novel-length and includes a scoop about an upcoming book in 2017,

Were you surprised by anything when you were researching and/or witting the book?

I learned so much while writing Monster Science – it’s one of the reasons I enjoy writing nonfiction, especially for kids. I always turn up fascinating stuff. I was surprised to learn that werewolves were rounded up and burned at the stake, just like witches, during the period of the Inquisition. Werewolves, it turns out, were thought to be witches – usually male ones – who could shape shift.

My fave fact of all is that vampires would still have to eat their vegetables.

Did you have to leave any monsters/pop culture references/science out of the book? And, why?

Children’s books have very tight space constraints, but my research is comprehensive and complete. That means we have to pick and choose what stays in. It’s gotta be the very best! I work closely with my editors on this, and sometimes we have, shall we say, “heated” discussions.” For Monster Science, I was particularly sorry to see the fascinating back story of the mad scientist trope end up with a stake in its heart.

Did you have a favourite monster before you started? If so, has your favourite changed? Or if you didn’t have one before writing the book, have you since developed a favourite monster?

I’ve had an uneasy relationship with vampires from the age of about 7, after watching an episode of Gilligan’s Island. It featured a “humorous” dream sequence with Gilligan as the vampire. I failed to see the humor at that tender age, and was terrified out of my socks. And anyone remember the original Dark Shadows? Barnabus Collins? Yeah. That show should have never been on in the afternoon. I slept with the blankies up to my ears until my mid-thirties. (Who am I kidding? I still do!)

Are you hoping to tie this book into the Frankenstein bicentennial celebrations?

Illustrated children’s books have very long time lines from concept to finished book. I wrote Monster Science several years ago, before I had any notion of Frankenstein bicentennials. But now that we’ve arrived at this auspicious date, I’m excited! I’d love to participate in some way. I will put on my zzz zzzz zzzt thinking cap.

Where can your fans come to a reading or some other event?

I do dozens of school visits and festival events every year. Some of them might be focused on a specific book, like Monster Science, but most usually feature discussions around several of my titles. This holiday season, for example, I will be doing events around my latest picture book, a very Canadian Christmas-themed title called Deck the Halls. It’s the third in a very popular series. Anyone can drop in to the Sherway Gardens branch of Indigo Book Store [in Toronto] at noon on Sunday, Dec. 4 [2016], to take part in that.

I’ll be doing many events in association with the Forest of Reading, one of North America’s largest children’s choice award programs this spring. More than 250,000 children participate! I am honored to have two science-related books nominated this year, Worms for Breakfast: How to Feed a Zoo (Owlkids) and Everything: Space (National Geographic Kids). I will also be the keynote at the Killaloe Literary Festival in beautiful northern Ontario at the end of May. Best place to look for my latest book and schedule info is my blog, http://helainebecker.blogspot.ca/.

Is there anything you’d like to add?

For insiders only: Coming soon! Look for my upcoming picture book biography of William Playfair, the Victorian era scoundrel who single-handedly invented the field of infographics. It’s called Lines, Bars and Circles and will be published by Kids Can Press early in 2017.

Thank you, Helaine! (I usually don’t get funny interviews. It makes for a good change of pace.)

Getting back to ‘Monster Science’, you can purchase the book here.

Promoting video games for the pursuit of science

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An Oct. 6, 2016 essay by Scott Horowitz and James Bardwell for The Conversation (h/t Oct. 6, 2016 news item on Nanowerk) makes the case for more video gaming projects designed to advance science. From The Conversation’s Oct. 6, 2016 essay,

…

In Foldit, players attempt to figure out the detailed three-dimensional structure of proteins by manipulating a simulated protein displayed on their computer screen. They must observe various constraints based in the real world, such as the order of amino acids and how close to each other their biochemical properties permit them to get. In academic research, these tasks are typically performed by trained experts.

Thousands of people – with and without scientific training – play Foldit regularly. Sure, they’re having fun, but are they really contributing to science in ways experts don’t already? To answer this question – to find out how much we can learn by having nonexperts play scientific games – we recently set up a Foldit competition between gamers, undergraduate students and professional scientists. The amateur gamers did better than the professional scientists managed using their usual software.

This suggests that scientific games like Foldit can truly be valuable resources for biochemistry research while simultaneously providing enjoyable recreation. More widely, it shows the promise that crowdsourcing to gamers (or “gamesourcing”) could offer to many fields of study.

Horowitz and Bardwell (both crystallographers) created their own game,

We teach an undergraduate class that includes a section on how biochemists can determine what proteins look like.

When we gave an electron density map to our students and had them move the amino acids around with a mouse and keyboard and fold the protein into the map, students loved it – some so much they found themselves ignoring their other homework in favor of our puzzle. As the students worked on the assignment, we found the questions they raised became increasingly sophisticated, delving deeply into the underlying biochemistry of the protein.

In the end, 10 percent of the class actually managed to improve on the structure that had been previously solved by professional crystallographers. They tweaked the pieces so they fit better than the professionals had been able to. Most likely, since 60 students were working on it separately, some of them managed to fix a number of small errors that had been missed by the original crystallographers. This outcome reminded us of the game Foldit.

They then ran a competition between their students, two trained crystallographers, and some Foldit players,

We gave students a new crystallography assignment, and told them they would be competing against Foldit players to produce the best structure. We also got two trained crystallographers to compete using the software they’d be familiar with, as well as several automated software packages that crystallographers often use. The race was on!

Amateurs outdo professionals

The students attacked the assignment vigorously, as did the Foldit players. As before, the students learned how proteins are put together through shaping these protein structures by hand. Moreover, both groups appeared to take pride in their role in pioneering new science.

At the end of the competition, we analyzed all the structures from all the participants. We calculated statistics about the competing structures that told us how correct each participant was in their solution to the puzzle. The results ranged from very poor structures that didn’t fit the map at all to exemplary solutions.

The best structure came from a group of nine Foldit players who worked collaboratively to come up with a spectacular protein structure. Their structure turned out to be even better than the structures from the two trained professionals.

Students and Foldit players alike were eager to master difficult concepts because it was fun. The results they came up with gave us useful scientific results that can really improve biochemistry.

I first wrote about Foldit in an August 6, 2010 posting (scroll down about 50% of the way).

Dr. Frankenstein and competitive exclusion

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A promotional photo of Boris Karloff as Frankenstein's monster, using Jack Pierce's makeup design. Credit:: Universal Studios

A promotional photo of Boris Karloff as Frankenstein’s monster, using Jack Pierce’s makeup design. Credit:: Universal Studios

An Oct. 28, 2016 news item on phys.org provides some new insight into the ‘Frankenstein story’ and its perspective on science,

Frankenstein as we know him, the grotesque monster that was created through a weird science experiment, is actually a nameless Creature created by scientist Victor Frankenstein in Mary Shelley’s 1818 novel, “Frankenstein.” Widely considered the first work of science fiction for exploring the destructive consequences of scientific and moral transgressions, a new study published in BioScience argues that the horror of Mary Shelley’s gothic novel is rooted in a fundamental principle of biology.

The co-authors point to a pivotal scene when the Creature encounters Victor Frankenstein and requests a female companion to mitigate his loneliness. The Creature distinguishes his dietary needs from those of humans and expresses a willingness to inhabit the “wilds of South America,” suggesting distinct ecological requirements. Frankenstein concedes to this reasoning given that humans would have few competitive interactions with a pair of isolated creatures, but he then reverses his decision after considering the creatures’ reproductive potential and the probability of human extinction, a concept termed competitive exclusion. In essence, Frankenstein was saving humankind.

An Oct. 28, 2016 Dartmouth College news release (also on EurekAlert) by Amy Olson, which originated the news item, describes the co-authors and the research in more detail (Note: Links have been removed),

A study co-authored by Dartmouth’s Nathaniel Dominy casts a new light on the story of Frankenstein’s monster, who lives on in the public imagination in stories, in movies, and of course, on Halloween.

Mary Shelley’s gothic novel is rooted in a fundamental principle of biology, and its horror lies in the specter of the extinction of the human race, say Dominy, a professor of anthropology, and his coauthor, Justin Yeakel.

…

“The principle of competitive exclusion was not formally defined until the 1930s,” says Dominy. “Given Shelley’s early command of this foundational concept, we used computational tools developed by ecologists to explore if, and how quickly, an expanding population of creatures would drive humans to extinction.”

The authors developed a mathematical model based on human population densities in 1816, finding that the competitive advantages of creatures varied under different circumstances. The worst-case scenario for humans was a growing population of creatures in South America, as it was a region with fewer humans and therefore less competition for resources.

“We calculated that a founding population of two creatures could drive us to extinction in as little as 4,000 years,” says Dominy. Although the study is merely a thought experiment, it casts new light on the underlying horror of the novel: the extinction of the human race. It also has real-word implications for how we understand the biology of invasive species.

“To date, most scholars have focused on Mary Shelley’s knowledge of then-prevailing views on alchemy, physiology, and resurrection; however, the genius of Mary Shelley lies in how she combined and repackaged existing scientific debates to invent the genre of science fiction,” says Justin D. Yeakel, an Omidyar fellow at the Santa Fe Institute and an assistant professor in the School of Natural Sciences at the University of California, Merced.

“Our study adds to Mary Shelley’s legacy, by showing that her science fiction accurately anticipated fundamental concepts in ecology and evolution by many decades,” he says.

Here’s a link to and a citation for the paper,

Frankenstein and the Horrors of Competitive Exclusion by Nathaniel J. Dominy and Justin D. Yeakel.  BioScience (2016) doi: 10.1093/biosci/biw133 First published online: October 28, 2016

This paper is behind a paywall.

News from Arizona State University’s The Frankenstein Bicentennial Project

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I received a September 2016 newsletter (issued occasionally) from The Frankenstein Bicentennial Project at Arizona State University (ASU) which contained these two tidbits:

I, Artist

Bobby Zokaites converted a Roomba, a robotic vacuum, from a room cleaning device to an art-maker by removing the dust collector and vacuuming system and replacing it with a paint reservoir. Artists have been playing with robots to make art since the 1950s. This work is an extension of a genre, repurposing a readily available commercial robot.

With this project, Bobby set out to create a self-portrait of a generation, one that grew up with access to a vast amount of information and constantly bombarded by advertisements. The Roomba paintings prove that a robot can paint a reasonably complex painting, and do it differently every time; thus this version of the Turing test was successful.

As in the story of Frankenstein, this work also interrogates questions of creativity and responsibility. Is this a truly creative work of art, and if so, who is the artist; man or machine?

Both the text description and the video are from: https://www.youtube.com/watch?v=0m5ihmwPWgY

Frankenstein at 200 Exhibit

From the September 2016 newsletter (Note: Links have been removed),

Just as the creature in Frankenstein [the monster is never named in the book; its creator, however, is Victor Frankenstein] was assembled from an assortment of materials, so too is the cultural understanding of the Frankenstein myth. Now a new, interdisciplinary exhibit at ASU Libraries examines how Mary Shelley’s 200-year-old science fiction story continues to inspire, educate, and frighten 21st century audiences.

Frankenstein at 200 is open now through December 10 on the first floor of ASU’s Hayden Library in Tempe, AZ.

Here’s more from the exhibit’s webpage on the ASU website,

No work of literature has done more to shape the way people imagine science and its moral consequences than “Frankenstein;” or “The Modern Prometheus,” Mary Shelley’s enduring tale of creation and responsibility. The novel’s themes and tropes continue to resonate with contemporary audiences, influencing the way we confront emerging technologies, conceptualize the process of scientific research, and consider the ethical relationships between creators and their creations

Two hundred years after Mary Shelley imagined the story that would become “Frankenstein,” ASU Libraries is exhibiting an interdisciplinary installation that contextualizes the conditions of the original tale while exploring it’s continued importance in our technological age. Featuring work by ASU faculty and students, this exhibition includes a variety of physical and digital artifacts, original art projects and interactive elements that examine “Frankenstein’s” colossal scientific, technological, cultural and social impacts.

About the Frankenstein Bicentennial Project: Launched by Drs. David Guston and Ed Finn in 2013, the Frankenstein Bicentennial Project, is a global celebration of the bicentennial of the writing and publication of Mary Shelley’s Frankenstein, from 2016-2018. The project uses Frankenstein as a lens to examine the complex relationships between science, technology, ethics, and society. To learn more visit frankenstein.asu.edu and follow @FrankensteinASU on Twitter

There are more informational tidbits at The Frankenstein Bicentennial Project website.

Removing gender-based stereotypes from algorithms

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Most people don’t think of algorithms as having biases and stereotypes but Michael Zou in his Sept. 26, 2016 essay for The Conversation (h/t phys.org Sept. 26, 2016 news item) says different, Note: Links have been removed,

Machine learning is ubiquitous in our daily lives. Every time we talk to our smartphones, search for images or ask for restaurant recommendations, we are interacting with machine learning algorithms. They take as input large amounts of raw data, like the entire text of an encyclopedia, or the entire archives of a newspaper, and analyze the information to extract patterns that might not be visible to human analysts. But when these large data sets include social bias, the machines learn that too.

A machine learning algorithm is like a newborn baby that has been given millions of books to read without being taught the alphabet or knowing any words or grammar. The power of this type of information processing is impressive, but there is a problem. When it takes in the text data, a computer observes relationships between words based on various factors, including how often they are used together.

We can test how well the word relationships are identified by using analogy puzzles. Suppose I ask the system to complete the analogy “He is to King as She is to X.” If the system comes back with “Queen,” then we would say it is successful, because it returns the same answer a human would.

Our research group trained the system on Google News articles, and then asked it to complete a different analogy: “Man is to Computer Programmer as Woman is to X.” The answer came back: “Homemaker.”

Zou explains how a machine (algorithm) learns and then notes this,

Not only can the algorithm reflect society’s biases – demonstrating how much those biases are contained in the input data – but the system can potentially amplify gender stereotypes. Suppose I search for “computer programmer” and the search program uses a gender-biased database that associates that term more closely with a man than a woman.

The search results could come back flawed by the bias. Because “John” as a male name is more closely related to “computer programmer” than the female name “Mary” in the biased data set, the search program could evaluate John’s website as more relevant to the search than Mary’s – even if the two websites are identical except for the names and gender pronouns.

It’s true that the biased data set could actually reflect factual reality – perhaps there are more “Johns” who are programmers than there are “Marys” – and the algorithms simply capture these biases. This does not absolve the responsibility of machine learning in combating potentially harmful stereotypes. The biased results would not just repeat but could even boost the statistical bias that most programmers are male, by moving the few female programmers lower in the search results. It’s useful and important to have an alternative that’s not biased.

There is a way according to Zou that stereotypes can be removed,

Our debiasing system uses real people to identify examples of the types of connections that are appropriate (brother/sister, king/queen) and those that should be removed. Then, using these human-generated distinctions, we quantified the degree to which gender was a factor in those word choices – as opposed to, say, family relationships or words relating to royalty.

Next we told our machine-learning algorithm to remove the gender factor from the connections in the embedding. This removes the biased stereotypes without reducing the overall usefulness of the embedding.

When that is done, we found that the machine learning algorithm no longer exhibits blatant gender stereotypes. We are investigating applying related ideas to remove other types of biases in the embedding, such as racial or cultural stereotypes.

If you have time, I encourage you to read the essay in its entirety and this June 14, 2016 posting about research into algorithms and how they make decisions for you about credit, medical diagnoses, job opportunities and more.

There’s also an Oct. 24, 2016 article by Michael Light on Salon.com on the topic (Note: Links have been removed),

In a recent book that was longlisted for the National Book Award, Cathy O’Neil, a data scientist, blogger and former hedge-fund quant, details a number of flawed algorithms to which we have given incredible power — she calls them “Weapons of Math Destruction.” We have entrusted these WMDs to make important, potentially life-altering decisions, yet in many cases, they embed human race and class biases; in other cases, they don’t function at all.
Among other examples, O’Neil examines a “value-added” model New York City used to decide which teachers to fire, even though, she writes, the algorithm was useless, functioning essentially as a random number generator, arbitrarily ending careers. She looks at models put to use by judges to assign recidivism scores to inmates that ended up having a racist inclination. And she looks at how algorithms are contributing to American partisanship, allowing political operatives to target voters with information that plays to their existing biases and fears.

I recommend reading Light’s article in its entirety.

Uganda and emerging technology

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Matsiko Kahunga’s Sept. 26, 2016 piece from The Monitor (Uganda: Are We Hunter-Gatherers or a Nanotechnology Economy?) on allafrica.com provides some intriguing insight,

Our teacher of Agriculture in lower secondary school, (I can only remember his moniker: we called him Boxer) had a very intriguing definition of land, which we may today find instructive as the land question in Uganda rears its ugly head again. From his various definitions of land, what emerges is that land will mean different things to different people. Thus, to an aeropilot, land is a hard, flat surface onto which airports can be built to enable safe take off and landing; while to an equatorial forest hunter-gatherer, land is that lush green environment where fruits, berries and roots are ever in abundance and game animals plentiful. To the sedentary arable farmer, land is that medium in which crops can grow…it is useful if it can support crop life, and it is useless if it cannot support crop life.

The land question is up again. And already tempers are high and rising, building on the earlier intermittent squabbles across the country. Perhaps a simple reflection may send us rethinking our perception of land: does land mean the same thing to all Ugandans? If we are on the path to industrialisation as we ought to, does land in an industrial country carry the same meaning and importance it carries in a subsistence economy?

Kahunga then recounts this story,

A friend who recently returned from a tour of duty with a UN agency in an Asian Tiger, tells me that he lived on the 17th floor of an 81-storey skyscraper, which is basically a self-contained town: besides residential flats, the entire height of the building is punctuated by public arenas, kindergartens, shopping malls, clinics, temples, office blocks, police stations, municipal council and related services.

He then contrasts it with Seoul,

Another instructive case is Seoul, the South Korean capital. The Seoul National Capital Area houses 25 million people (as of 2012).

This is over half the population of South Korea, living on 0.6 per cent of the country’s land area, and generating 21 per cent of the country’s GDP (Leahy, 2012). Twenty five million is 73 per cent of Uganda’s population (2012 figures) or Burundi and Rwanda combined.

I am struck by the similarities between the current heated discussions about land use and density in Vancouver (Canada) and our national climate change issues and Kahunga’s depiction of Uganda’s issues,

The tokenism of ‘carbon-fund’, ‘green development’ ‘mainstreaming’…, typical of conferences will not save us. Uganda is best placed to pioneer green industrial development with not only minimal impact on the climate, but also a reversal of the current catastrophe: plastic-choked soils, drying marshlands and river beds, changing season patterns and melting Rwenzori glaciers.

And no one is safe from this pending catastrophe: rich or poor, investor or squatter, powerful or powerless . …

Thought-provoking, eh?

The Nine Dots Prize competition for creative thinking on social issues

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A new prize is being inaugurated, the $US100,000 Nine Dots Prize for creative thinking and it’s open to anyone anywhere in the world. Here’s more from an Oct. 21, 2016 article by Jane Tinkler for the Guardian (Note: Links have been removed),

In the debate over this year’s surprise award to Bob Dylan, it is easy to lose sight of the long history of prizes being used to recognise great writing (in whatever form), great research and other outstanding achievements.

The use of prizes dates back furthest in the sciences. In 1714, the British government famously offered an award of £20,000 (about £2.5 million at today’s value) to the person who could find a way of determining a ship’s longitude. British clockmaker John Harrison won the Longitude Prize and, by doing so, improved the safety of long-distance sea travel.

Prizes are now proliferating. Since 2000, more than sixty prizes of more than $100,000 (US dollars) have been created, and the field of philanthropic prize-giving is estimated to exceed £1 billion each year. Prizes are seen as ways to reward excellence, build networks, support collaboration and direct efforts towards practical and social goals. Those awarding them include philanthropists, governments and companies.

Today [Oct. 21, 2016] sees the launch of the newest kid on the prize-giving block. Drawing its name from a puzzle that can be solved only by lateral thinking, the Nine Dots prize wants to encourage creative thinking and writing that can help to tackle social problems. It is sponsored by the Kadas Prize Foundation, with the support of the Centre for Research in the Arts, Social Sciences and Humanities (CRASSH) at the University of Cambridge, and Cambridge University Press.

…

The Nine Dots prize is a hybrid of [three types of prizes]. There is a recognition [emphasis mine] aspect, but it doesn’t require an extensive back catalogue. The prize will be judged by a board of twelve renowned scholars, thinkers and writers. They will assess applications on an anonymised basis, so whoever wins will have done so not because of past work, but because of the strength of their ideas, and ability to communicate them effectively.

It is an incentive [emphasis mine] prize in that we ask applicants to respond to a defined question. The inaugural question is: “Are digital technologies making politics impossible?” [emphasis mine]. This is not proscriptive: applicants are encouraged to define what the question means to them, and to respond to that. We expect the submissions to be wildly varied. A new question will be set every two years, always with a focus on pressing issues that affect society. The prize’s disciplinary heartland lies in the social sciences, but responses from all fields, sectors and life experiences are welcome.

Finally, it is a resource [emphasis mine] prize in that it does not expect all the answers at the point of application. Applicants need to provide a 3,000-word summary of how they would approach the question. Board members will assess these, and the winner will then be invited to write their ideas up into a short, accessible book, that will be published by Cambridge University Press. A prize award of $100,000 (£82,000) will support the winner to take time out to think and write over a nine month period. The winner will also have the option of a term’s visiting fellowship at the University of Cambridge, to help with the writing process.

With this mix of elements, we hope the Nine Dots prize will encourage creative thinking about some of today’s most pressing issues. The winner’s book will be made freely accessible online; we hope it will capture the public’s imagination and spark a real debate.

The submission deadline is Jan. 31, 2017 and the winner announcement is May 2017. The winner’s book is to be published May 2018.

Good Luck! You can find out more about the prize and the contest rules on The Nine Dots Prize website.