Tag Archives: Jacob Brogan

Machine learning, neural networks, and knitting

In a recent (Tuesday, March 6, 2018) live stream ‘conversation’ (‘Science in Canada; Investing in Canadian Innovation’ now published on YouTube) between Canadian Prime Minister, Justin Trudeau, and US science communicator, Bill Nye, at the University of Ottawa, they discussed, amongst many other topics, what AI (artificial intelligence) can and can’t do. They seemed to agree that AI can’t be creative, i.e., write poetry, create works of art, make jokes, etc. A conclusion which is both (in my opinion) true and not true.

There are times when I think the joke may be on us (humans). Take for example this March 6, 2018 story by Alexis Madrigal for The Atlantic magazine (Note: Links have been removed),

SkyKnit: How an AI Took Over an Adult Knitting Community

Ribald knitters teamed up with a neural-network creator to generate new types of tentacled, cozy shapes.

Janelle Shane is a humorist [Note: She describes herself as a “Research Scientist in optics. Plays with neural networks. …” in her Twitter bio.] who creates and mines her material from neural networks, the form of machine learning that has come to dominate the field of artificial intelligence over the last half-decade.

Perhaps you’ve seen the candy-heart slogans she generated for Valentine’s Day: DEAR ME, MY MY, LOVE BOT, CUTE KISS, MY BEAR, and LOVE BUN.

Or her new paint-color names: Parp Green, Shy Bather, Farty Red, and Bull Cream.

Or her neural-net-generated Halloween costumes: Punk Tree, Disco Monster, Spartan Gandalf, Starfleet Shark, and A Masked Box.

Her latest project, still ongoing, pushes the joke into a new, physical realm. Prodded by a knitter on the knitting forum Ravelry, Shane trained a type of neural network on a series of over 500 sets of knitting instructions. Then, she generated new instructions, which members of the Ravelry community have actually attempted to knit.

“The knitting project has been a particularly fun one so far just because it ended up being a dialogue between this computer program and these knitters that went over my head in a lot of ways,” Shane told me. “The computer would spit out a whole bunch of instructions that I couldn’t read and the knitters would say, this is the funniest thing I’ve ever read.”

It appears that the project evolved,

The human-machine collaboration created configurations of yarn that you probably wouldn’t give to your in-laws for Christmas, but they were interesting. The user citikas was the first to post a try at one of the earliest patterns, “reverss shawl.” It was strange, but it did have some charisma.

Shane nicknamed the whole effort “Project Hilarious Disaster.” The community called it SkyKnit.

I’m not sure what’s meant by “community” as mentioned in the previous excerpt. Are we talking about humans only, AI only, or both humans and AI?

Here’s some of what underlies Skyknit (Note: Links have been removed),

The different networks all attempt to model the data they’ve been fed by tuning a vast, funky flowchart. After you’ve created a statistical model that describes your real data, you can also roll the dice and generate new, never-before-seen data of the same kind.

How this works—like, the math behind it—is very hard to visualize because values inside the model can have hundreds of dimensions and we are humble three-dimensional creatures moving through time. But as the neural-network enthusiast Robin Sloan puts it, “So what? It turns out imaginary spaces are useful even if you can’t, in fact, imagine them.”

Out of that ferment, a new kind of art has emerged. Its practitioners use neural networks not to attain practical results, but to see what’s lurking in the these vast, opaque systems. What did the machines learn about the world as they attempted to understand the data they’d been fed? Famously, Google released DeepDream, which produced trippy visualizations that also demonstrated how that type of neural network processed the textures and objects in its source imagery.

Madrigal’s article is well worth reading if you have the time. You can also supplement Madrigal’s piece with an August 9, 2017 article about Janelle Shane’s algorithmic experiments by Jacob Brogan for slate.com.

I found some SkyKnit examples on Ravelry including this one from the Dollybird Workshop,

© Chatelaine

SkyKnit fancy addite rifopshent
by SkyKnit
Published in
Dollybird Workshop
SkyKnit
Craft
Knitting
Category
Stitch pattern
Published
February 2018
Suggested yarn
Yarn weight
Fingering (14 wpi) ?
Gauge
24 stitches and 30 rows = 4 inches
in stockinette stitch
Needle size
US 4 – 3.5 mm

written-pattern

This pattern is available as a free Ravelry download

SkyKnit is a type of machine learning algorithm called an artificial neural network. Its creator, Janelle Shane of AIweirdness.com, gave it 88,000 lines of knitting instructions from Stitch-Maps.com and Ravelry, and it taught itself how to make new patterns. Join the discussion!

SkyKnit seems to have created something that has paralell columns, and is reversible. Perhaps a scarf?

Test-knitting & image courtesy of Chatelaine

Patterns may include notes from testknitters; yarn, needles, and gauge are totally at your discretion.

About the designer
SkyKnit’s favorites include lace, tentacles, and totally not the elimination of the human race.
For more information, see: http://aiweirdness.com/

Shane’s website, aiweirdness.com, is where she posts musings such as this (from a March 2, [?] 2018 posting), Note: A link has been removed,

If you’ve been on the internet today, you’ve probably interacted with a neural network. They’re a type of machine learning algorithm that’s used for everything from language translation to finance modeling. One of their specialties is image recognition. Several companies – including Google, Microsoft, IBM, and Facebook – have their own algorithms for labeling photos. But image recognition algorithms can make really bizarre mistakes.

image

Microsoft Azure’s computer vision API [application programming interface] added the above caption and tags. But there are no sheep in the image of above. None. I zoomed all the way in and inspected every speck.

….

I have become quite interested in Shane’s self descriptions such as this one from the aiweirdness.com website,

Portrait/Logo

About

I train neural networks, a type of machine learning algorithm, to write unintentional humor as they struggle to imitate human datasets. Well, I intend the humor. The neural networks are just doing their best to understand what’s going on. Currently located on the occupied land of the Arapahoe Nation.
https://wandering.shop/@janellecshane

As for the joke being on us, I can’t help remembering the Facebook bots that developed their own language (Facebotlish), and were featured in my June 30, 2017 posting, There’s a certain eerieness to it all, which seems an appropriate response in a year celebrating the 200th anniversary of Mary Shelley’s 1818 book, Frankenstein; or, the Modern Prometheus. I’m closing with a video clip from the 1931 movie,

Happy Weekend!

Health technology and the Canadian Broadcasting Corporation’s (CBC) two-tier health system ‘Viewpoint’

There’s a lot of talk and handwringing about Canada’s health care system, which ebbs and flows in almost predictable cycles. Jesse Hirsh in a May 16, 2017 ‘Viewpoints’ segment (an occasional series run as part the of the CBC’s [Canadian Broadcasting Corporation] flagship, daily news programme, The National) dared to reframe the discussion as one about technology and ‘those who get it’  [the technologically literate] and ‘those who don’t’,  a state Hirsh described as being illiterate as you can see and hear in the following video.

I don’t know about you but I’m getting tired of being called illiterate when I don’t know something. To be illiterate means you can’t read and write and as it turns out I do both of those things on a daily basis (sometimes even in two languages). Despite my efforts, I’m ignorant about any number of things and those numbers keep increasing day by day. BTW, Is there anyone who isn’t having trouble keeping up?

Moving on from my rhetorical question, Hirsh has a point about the tech divide and about the need for discussion. It’s a point that hadn’t occurred to me (although I think he’s taking it in the wrong direction). In fact, this business of a tech divide already exists if you consider that people who live in rural environments and need the latest lifesaving techniques or complex procedures or access to highly specialized experts have to travel to urban centres. I gather that Hirsh feels that this divide isn’t necessarily going to be an urban/rural split so much as an issue of how technically literate you and your doctor are.  That’s intriguing but then his argumentation gets muddled. Confusingly, he seems to be suggesting that the key to the split is your access (not your technical literacy) to artificial intelligence (AI) and algorithms (presumably he’s referring to big data and data analytics). I expect access will come down more to money than technological literacy.

For example, money is likely to be a key issue when you consider his big pitch is for access to IBM’s Watson computer. (My Feb. 28, 2011 posting titled: Engineering, entertainment, IBM’s Watson, and product placement focuses largely on Watson, its winning appearances on the US television game show, Jeopardy, and its subsequent adoption into the University of Maryland’s School of Medicine in a project to bring Watson into the examining room with patients.)

Hirsh’s choice of IBM’s Watson is particularly interesting for a number of reasons. (1) Presumably there are companies other than IBM in this sector. Why do they not rate a mention?  (2) Given the current situation with IBM and the Canadian federal government’s introduction of the Phoenix payroll system (a PeopleSoft product customized by IBM), which is  a failure of monumental proportions (a Feb. 23, 2017 article by David Reevely for the Ottawa Citizen and a May 25, 2017 article by Jordan Press for the National Post), there may be a little hesitation, if not downright resistance, to a large scale implementation of any IBM product or service, regardless of where the blame lies. (3) Hirsh notes on the home page for his eponymous website,

I’m presently spending time at the IBM Innovation Space in Toronto Canada, investigating the impact of artificial intelligence and cognitive computing on all sectors and industries.

Yes, it would seem he has some sort of relationship with IBM not referenced in his Viewpoints segment on The National. Also, his description of the relationship isn’t especially illuminating but perhaps it.s this? (from the IBM Innovation Space  – Toronto Incubator Application webpage),

Our incubator

The IBM Innovation Space is a Toronto-based incubator that provides startups with a collaborative space to innovate and disrupt the market. Our goal is to provide you with the tools needed to take your idea to the next level, introduce you to the right networks and help you acquire new clients. Our unique approach, specifically around client engagement, positions your company for optimal growth and revenue at an accelerated pace.

OUR SERVICES

IBM Bluemix
IBM Global Entrepreneur
Softlayer – an IBM Company
Watson

Startups partnered with the IBM Innovation Space can receive up to $120,000 in IBM credits at no charge for up to 12 months through the Global Entrepreneurship Program (GEP). These credits can be used in our products such our IBM Bluemix developer platform, Softlayer cloud services, and our world-renowned IBM Watson ‘cognitive thinking’ APIs. We provide you with enterprise grade technology to meet your clients’ needs, large or small.

Collaborative workspace in the heart of Downtown Toronto
Mentorship opportunities available with leading experts
Access to large clients to scale your startup quickly and effectively
Weekly programming ranging from guest speakers to collaborative activities
Help with funding and access to local VCs and investors​

Final comments

While I have some issues with Hirsh’s presentation, I agree that we should be discussing the issues around increased automation of our health care system. A friend of mine’s husband is a doctor and according to him those prescriptions and orders you get when leaving the hospital? They are not made up by a doctor so much as they are spit up by a computer based on the data that the doctors and nurses have supplied.

GIGO, bias, and de-skilling

Leaving aside the wonders that Hirsh describes, there’s an oldish saying in the computer business, garbage in/garbage out (gigo). At its simplest, who’s going to catch a mistake? (There are lots of mistakes made in hospitals and other health care settings.)

There are also issues around the quality of research. Are all the research papers included in the data used by the algorithms going to be considered equal? There’s more than one case where a piece of problematic research has been accepted uncritically, even if it get through peer review, and subsequently cited many times over. One of the ways to measure impact, i.e., importance, is to track the number of citations. There’s also the matter of where the research is published. A ‘high impact’ journal, such as Nature, Science, or Cell, automatically gives a piece of research a boost.

There are other kinds of bias as well. Increasingly, there’s discussion about algorithms being biased and about how machine learning (AI) can become biased. (See my May 24, 2017 posting: Machine learning programs learn bias, which highlights the issues and cites other FrogHeart posts on that and other related topics.)

These problems are to a large extent already present. Doctors have biases and research can be wrong and it can take a long time before there are corrections. However, the advent of an automated health diagnosis and treatment system is likely to exacerbate the problems. For example, if you don’t agree with your doctor’s diagnosis or treatment, you can search other opinions. What happens when your diagnosis and treatment have become data? Will the system give you another opinion? Who will you talk to? The doctor who got an answer from ‘Watson”? Is she or he going to debate Watson? Are you?

This leads to another issue and that’s automated systems getting more credit than they deserve. Futurists such as Hirsh tend to underestimate people and overestimate the positive impact that automation will have. A computer, data analystics, or an AI system are tools not gods. You’ll have as much luck petitioning one of those tools as you would Zeus.

The unasked question is how will your doctor or other health professional gain experience and skills if they never have to practice the basic, boring aspects of health care (asking questions for a history, reading medical journals to keep up with the research, etc.) and leave them to the computers? There had to be  a reason for calling it a medical ‘practice’.

There are definitely going to be advantages to these technological innovations but thoughtful adoption of these practices (pun intended) should be our goal.

Who owns your data?

Another issue which is increasingly making itself felt is ownership of data. Jacob Brogan has written a provocative May 23, 2017 piece for slate.com asking that question about the data Ancestry.com gathers for DNA testing (Note: Links have been removed),

AncestryDNA’s pitch to consumers is simple enough. For $99 (US), the company will analyze a sample of your saliva and then send back information about your “ethnic mix.” While that promise may be scientifically dubious, it’s a relatively clear-cut proposal. Some, however, worry that the service might raise significant privacy concerns.

After surveying AncestryDNA’s terms and conditions, consumer protection attorney Joel Winston found a few issues that troubled him. As he noted in a Medium post last week, the agreement asserts that it grants the company “a perpetual, royalty-free, world-wide, transferable license to use your DNA.” (The actual clause is considerably longer.) According to Winston, “With this single contractual provision, customers are granting Ancestry.com the broadest possible rights to own and exploit their genetic information.”

Winston also noted a handful of other issues that further complicate the question of ownership. Since we share much of our DNA with our relatives, he warned, “Even if you’ve never used Ancestry.com, but one of your genetic relatives has, the company may already own identifiable portions of your DNA.” [emphasis mine] Theoretically, that means information about your genetic makeup could make its way into the hands of insurers or other interested parties, whether or not you’ve sent the company your spit. (Maryam Zaringhalam explored some related risks in a recent Slate article.) Further, Winston notes that Ancestry’s customers waive their legal rights, meaning that they cannot sue the company if their information gets used against them in some way.

Over the weekend, Eric Heath, Ancestry’s chief privacy officer, responded to these concerns on the company’s own site. He claims that the transferable license is necessary for the company to provide its customers with the service that they’re paying for: “We need that license in order to move your data through our systems, render it around the globe, and to provide you with the results of our analysis work.” In other words, it allows them to send genetic samples to labs (Ancestry uses outside vendors), store the resulting data on servers, and furnish the company’s customers with the results of the study they’ve requested.

Speaking to me over the phone, Heath suggested that this license was akin to the ones that companies such as YouTube employ when users upload original content. It grants them the right to shift that data around and manipulate it in various ways, but isn’t an assertion of ownership. “We have committed to our users that their DNA data is theirs. They own their DNA,” he said.

I’m glad to see the company’s representatives are open to discussion and, later in the article, you’ll see there’ve already been some changes made. Still, there is no guarantee that the situation won’t again change, for ill this time.

What data do they have and what can they do with it?

It’s not everybody who thinks data collection and data analytics constitute problems. While some people might balk at the thought of their genetic data being traded around and possibly used against them, e.g., while hunting for a job, or turned into a source of revenue, there tends to be a more laissez-faire attitude to other types of data. Andrew MacLeod’s May 24, 2017 article for thetyee.ca highlights political implications and privacy issues (Note: Links have been removed),

After a small Victoria [British Columbia, Canada] company played an outsized role in the Brexit vote, government information and privacy watchdogs in British Columbia and Britain have been consulting each other about the use of social media to target voters based on their personal data.

The U.K.’s information commissioner, Elizabeth Denham [Note: Denham was formerly B.C.’s Office of the Information and Privacy Commissioner], announced last week [May 17, 2017] that she is launching an investigation into “the use of data analytics for political purposes.”

The investigation will look at whether political parties or advocacy groups are gathering personal information from Facebook and other social media and using it to target individuals with messages, Denham said.

B.C.’s Office of the Information and Privacy Commissioner confirmed it has been contacted by Denham.

Macleod’s March 6, 2017 article for thetyee.ca provides more details about the company’s role (note: Links have been removed),

The “tiny” and “secretive” British Columbia technology company [AggregateIQ; AIQ] that played a key role in the Brexit referendum was until recently listed as the Canadian office of a much larger firm that has 25 years of experience using behavioural research to shape public opinion around the world.

The larger firm, SCL Group, says it has worked to influence election outcomes in 19 countries. Its associated company in the U.S., Cambridge Analytica, has worked on a wide range of campaigns, including Donald Trump’s presidential bid.

In late February [2017], the Telegraph reported that campaign disclosures showed that Vote Leave campaigners had spent £3.5 million — about C$5.75 million [emphasis mine] — with a company called AggregateIQ, run by CEO Zack Massingham in downtown Victoria.

That was more than the Leave side paid any other company or individual during the campaign and about 40 per cent of its spending ahead of the June referendum that saw Britons narrowly vote to exit the European Union.

According to media reports, Aggregate develops advertising to be used on sites including Facebook, Twitter and YouTube, then targets messages to audiences who are likely to be receptive.

The Telegraph story described Victoria as “provincial” and “picturesque” and AggregateIQ as “secretive” and “low-profile.”

Canadian media also expressed surprise at AggregateIQ’s outsized role in the Brexit vote.

The Globe and Mail’s Paul Waldie wrote “It’s quite a coup for Mr. Massingham, who has only been involved in politics for six years and started AggregateIQ in 2013.”

Victoria Times Colonist columnist Jack Knox wrote “If you have never heard of AIQ, join the club.”

The Victoria company, however, appears to be connected to the much larger SCL Group, which describes itself on its website as “the global leader in data-driven communications.”

In the United States it works through related company Cambridge Analytica and has been involved in elections since 2012. Politico reported in 2015 that the firm was working on Ted Cruz’s presidential primary campaign.

And NBC and other media outlets reported that the Trump campaign paid Cambridge Analytica millions to crunch data on 230 million U.S. adults, using information from loyalty cards, club and gym memberships and charity donations [emphasis mine] to predict how an individual might vote and to shape targeted political messages.

That’s quite a chunk of change and I don’t believe that gym memberships, charity donations, etc. were the only sources of information (in the US, there’s voter registration, credit card information, and more) but the list did raise my eyebrows. It would seem we are under surveillance at all times, even in the gym.

In any event, I hope that Hirsh’s call for discussion is successful and that the discussion includes more critical thinking about the implications of Hirsh’s ‘Brave New World’.

Essays on Frankenstein

Slate.com is dedicating a month (January 2017) to Frankenstein. This means there were will be one or more essays each week on one aspect or another of Frankenstein and science. These essays are one of a series of initiatives jointly supported by Slate, Arizona State University, and an organization known as New America. It gets confusing since these essays are listed as part of two initiatives:  Futurography and Future Tense.

The really odd part, as far as I’m concerned, is that there is no mention of Arizona State University’s (ASU) The Frankenstein Bicentennial Project (mentioned in my Oct. 26, 2016 posting). Perhaps they’re concerned that people will think ASU is advertising the project?

Introductions

Getting back to the essays, a Jan. 3, 2017 article by Jacob Brogan explains, by means of a ‘Question and Answer’ format article, why the book and the monster maintain popular interest after two centuries (Note: We never do find out who or how many people are supplying the answers),

OK, fine. I get that this book is important, but why are we talking about it in a series about emerging technology?

Though people still tend to weaponize it as a simple anti-scientific screed, Frankenstein, which was first published in 1818, is much richer when we read it as a complex dialogue about our relationship to innovation—both our desire for it and our fear of the changes it brings. Mary Shelley was just a teenager when she began to compose Frankenstein, but she was already grappling with our complex relationship to new forces. Almost two centuries on, the book is just as propulsive and compelling as it was when it was first published. That’s partly because it’s so thick with ambiguity—and so resistant to easy interpretation.

Is it really ambiguous? I mean, when someone calls something frankenfood, they aren’t calling it “ethically ambiguous food.”

It’s a fair point. For decades, Frankenstein has been central to discussions in and about bioethics. Perhaps most notably, it frequently crops up as a reference point in discussions of genetically modified organisms, where the prefix Franken- functions as a sort of convenient shorthand for human attempts to meddle with the natural order. Today, the most prominent flashpoint for those anxieties is probably the clustered regularly interspaced short palindromic repeats, or CRISPR, gene-editing technique [emphasis mine]. But it’s really oversimplifying to suggest Frankenstein is a cautionary tale about monkeying with life.

As we’ll see throughout this month on Futurography, it’s become a lens for looking at the unintended consequences of things like synthetic biology, animal experimentation, artificial intelligence, and maybe even social networking. Facebook, for example, has arguably taken on a life of its own, as its algorithms seem to influence the course of elections. Mark Zuckerberg, who’s sometimes been known to disavow the power of his own platform, might well be understood as a Frankensteinian figure, amplifying his creation’s monstrosity by neglecting its practical needs.

But this book is almost 200 years old! Surely the actual science in it is bad.

Shelley herself would probably be the first to admit that the science in the novel isn’t all that accurate. Early in the novel, Victor Frankenstein meets with a professor who castigates him for having read the wrong works of “natural philosophy.” Shelley’s protagonist has mostly been studying alchemical tomes and otherwise fantastical works, the sort of things that were recognized as pseudoscience, even by the standards of the day. Near the start of the novel, Frankenstein attends a lecture in which the professor declaims on the promise of modern science. He observes that where the old masters “promised impossibilities and performed nothing,” the new scientists achieve far more in part because they “promise very little; they know that metals cannot be transmuted and that the elixir of life is a chimera.”

Is it actually about bad science, though?

Not exactly, but it has been read as a story about bad scientists.

Ultimately, Frankenstein outstrips his own teachers, of course, and pulls off the very feats they derided as mere fantasy. But Shelley never seems to confuse fact and fiction, and, in fact, she largely elides any explanation of how Frankenstein pulls off the miraculous feat of animating dead tissue. We never actually get a scene of the doctor awakening his creature. The novel spends far more dwelling on the broader reverberations of that act, showing how his attempt to create one life destroys countless others. Read in this light, Frankenstein isn’t telling us that we shouldn’t try to accomplish new things, just that we should take care when we do.

This speaks to why the novel has stuck around for so long. It’s not about particular scientific accomplishments but the vagaries of scientific progress in general.

Does that make it into a warning against playing God?

It’s probably a mistake to suggest that the novel is just a critique of those who would usurp the divine mantle. Instead, you can read it as a warning about the ways that technologists fall short of their ambitions, even in their greatest moments of triumph.

Look at what happens in the novel: After bringing his creature to life, Frankenstein effectively abandons it. Later, when it entreats him to grant it the rights it thinks it deserves, he refuses. Only then—after he reneges on his responsibilities—does his creation really go bad. We all know that Frankenstein is the doctor and his creation is the monster, but to some extent it’s the doctor himself who’s made monstrous by his inability to take responsibility for what he’s wrought.

I encourage you to read Brogan’s piece in its entirety and perhaps supplement the reading. Mary Shelley has a pretty interesting history. She ran off with Percy Bysshe Shelley who was married to another woman, in 1814  at the age of seventeen years. Her parents were both well known and respected intellectuals and philosophers, William Godwin and Mary Wollstonecraft. By the time Mary Shelley wrote her book, her first baby had died and she had given birth to a second child, a boy.  Percy Shelley was to die a few years later as was her son and a third child she’d given birth to. (Her fourth child born in 1819 did survive.) I mention the births because one analysis I read suggests the novel is also a commentary on childbirth. In fact, the Frankenstein narrative has been examined from many perspectives (other than science) including feminism and LGBTQ studies.

Getting back to the science fiction end of things, the next part of the Futurography series is titled “A Cheat-Sheet Guide to Frankenstein” and that too is written by Jacob Brogan with a publication date of Jan. 3, 2017,

Key Players

Marilyn Butler: Butler, a literary critic and English professor at the University of Cambridge, authored the seminal essay “Frankenstein and Radical Science.”

Jennifer Doudna: A professor of chemistry and biology at the University of California, Berkeley, Doudna helped develop the CRISPR gene-editing technique [emphasis mine].

Stephen Jay Gould: Gould is an evolutionary biologist and has written in defense of Frankenstein’s scientific ambitions, arguing that hubris wasn’t the doctor’s true fault.

Seán Ó hÉigeartaigh: As executive director of the Center for Existential Risk at the University of Cambridge, hÉigeartaigh leads research into technologies that threaten the existience of our species.

Jim Hightower: This columnist and activist helped popularize the term frankenfood to describe genetically modified crops.

Mary Shelley: Shelley, the author of Frankenstein, helped create science fiction as we now know it.

J. Craig Venter: A leading genomic researcher, Venter has pursued a variety of human biotechnology projects.

Lingo

….

Debates

Popular Culture

Further Reading

….

‘Franken’ and CRISPR

The first essay is in a Jan. 6, 2016 article by Kay Waldman focusing on the ‘franken’ prefix (Note: links have been removed),

In a letter to the New York Times on June 2, 1992, an English professor named Paul Lewis lopped off the top of Victor Frankenstein’s surname and sewed it onto a tomato. Railing against genetically modified crops, Lewis put a new generation of natural philosophers on notice: “If they want to sell us Frankenfood, perhaps it’s time to gather the villagers, light some torches and head to the castle,” he wrote.

William Safire, in a 2000 New York Times column, tracked the creation of the franken- prefix to this moment: an academic channeling popular distrust of science by invoking the man who tried to improve upon creation and ended up disfiguring it. “There’s no telling where or how it will end,” he wrote wryly, referring to the spread of the construction. “It has enhanced the sales of the metaphysical novel that Ms. Shelley’s husband, the poet Percy Bysshe Shelley, encouraged her to write, and has not harmed sales at ‘Frank’n’Stein,’ the fast-food chain whose hot dogs and beer I find delectably inorganic.” Safire went on to quote the American Dialect Society’s Laurence Horn, who lamented that despite the ’90s flowering of frankenfruits and frankenpigs, people hadn’t used Frankensense to describe “the opposite of common sense,” as in “politicians’ motivations for a creatively stupid piece of legislation.”

A year later, however, Safire returned to franken- in dead earnest. In an op-ed for the Times avowing the ethical value of embryonic stem cell research, the columnist suggested that a White House conference on bioethics would salve the fears of Americans concerned about “the real dangers of the slippery slope to Frankenscience.”

All of this is to say that franken-, the prefix we use to talk about human efforts to interfere with nature, flips between “funny” and “scary” with ease. Like Shelley’s monster himself, an ungainly patchwork of salvaged parts, it can seem goofy until it doesn’t—until it taps into an abiding anxiety that technology raises in us, a fear of overstepping.

Waldman’s piece hints at how language can shape discussions while retaining a rather playful quality.

This series looks to be a good introduction while being a bit problematic in spots, which roughly sums up my conclusion about their ‘nano’ series in my Oct. 7, 2016 posting titled: Futurography’s nanotechnology series: a digest.

By the way, I noted the mention of CRISPR as it brought up an issue that they don’t appear to be addressing in this series (perhaps they will do this elsewhere?): intellectual property.

There’s a patent dispute over CRISPR as noted in this American Chemical Society’s Chemistry and Engineering News Jan. 9, 2017 video,

Playing God

This series on Frankenstein is taking on other contentious issues. A perennial favourite is ‘playing God’ as noted in Bina Venkataraman’s Jan. 11, 2017 essay on the topic,

Since its publication nearly 200 years ago, Shelley’s gothic novel has been read as a cautionary tale of the dangers of creation and experimentation. James Whale’s 1931 film took the message further, assigning explicitly the hubris of playing God to the mad scientist. As his monster comes to life, Dr. Frankenstein, played by Colin Clive, triumphantly exclaims: “Now I know what it feels like to be God!”

The admonition against playing God has since been ceaselessly invoked as a rhetorical bogeyman. Secular and religious, critic and journalist alike have summoned the term to deride and outright dismiss entire areas of research and technology, including stem cells, genetically modified crops, recombinant DNA, geoengineering, and gene editing. As we near the two-century commemoration of Shelley’s captivating story, we would be wise to shed this shorthand lesson—and to put this part of the Frankenstein legacy to rest in its proverbial grave.

The trouble with the term arises first from its murkiness. What exactly does it mean to play God, and why should we find it objectionable on its face? All but zealots would likely agree that it’s fine to create new forms of life through selective breeding and grafting of fruit trees, or to use in-vitro fertilization to conceive life outside the womb to aid infertile couples. No one objects when people intervene in what some deem “acts of God,” such as earthquakes, to rescue victims and provide relief. People get fully behind treating patients dying of cancer with “unnatural” solutions like chemotherapy. Most people even find it morally justified for humans to mete out decisions as to who lives or dies in the form of organ transplant lists that prize certain people’s survival over others.

So what is it—if not the imitation of a deity or the creation of life—that inspires people to invoke the idea of “playing God” to warn against, or even stop, particular technologies? A presidential commission charged in the early 1980s with studying the ethics of genetic engineering of humans, in the wake of the recombinant DNA revolution, sheds some light on underlying motivations. The commission sought to understand the concerns expressed by leaders of three major religious groups in the United States—representing Protestants, Jews, and Catholics—who had used the phrase “playing God” in a 1980 letter to President Jimmy Carter urging government oversight. Scholars from the three faiths, the commission concluded, did not see a theological reason to flat-out prohibit genetic engineering. Their concerns, it turned out, weren’t exactly moral objections to scientists acting as God. Instead, they echoed those of the secular public; namely, they feared possible negative effects from creating new human traits or new species. In other words, the religious leaders who called recombinant DNA tools “playing God” wanted precautions taken against bad consequences but did not inherently oppose the use of the technology as an act of human hubris.

She presents an interesting argument and offers this as a solution,

The lesson for contemporary science, then, is not that we should cease creating and discovering at the boundaries of current human knowledge. It’s that scientists and technologists ought to steward their inventions into society, and to more rigorously participate in public debate about their work’s social and ethical consequences. Frankenstein’s proper legacy today would be to encourage researchers to address the unsavory implications of their technologies, whether it’s the cognitive and social effects of ubiquitous smartphone use or the long-term consequences of genetically engineered organisms on ecosystems and biodiversity.

Some will undoubtedly argue that this places an undue burden on innovators. Here, again, Shelley’s novel offers a lesson. Scientists who cloister themselves as Dr. Frankenstein did—those who do not fully contemplate the consequences of their work—risk later encounters with the horror of their own inventions.

At a guess, Venkataraman seems to be assuming that if scientists communicate and make their case that the public will cease to panic with reference moralistic and other concerns. My understanding is that social scientists have found this is not the case. Someone may understand the technology quite well and still oppose it.

Frankenstein and anti-vaxxers

The Jan. 16, 2017 essay by Charles Kenny is the weakest of the lot, so far (Note: Links have been removed),

In 1780, University of Bologna physician Luigi Galvani found something peculiar: When he applied an electric current to the legs of a dead frog, they twitched. Thirty-seven years later, Mary Shelley had Galvani’s experiments in mind as she wrote her fable of Faustian overreach, wherein Dr. Victor Frankenstein plays God by reanimating flesh.

And a little less than halfway between those two dates, English physician Edward Jenner demonstrated the efficacy of a vaccine against smallpox—one of the greatest killers of the age. Given the suspicion with which Romantic thinkers like Shelley regarded scientific progress, it is no surprise that many at the time damned the procedure as against the natural order. But what is surprising is how that suspicion continues to endure, even after two centuries of spectacular successes for vaccination. This anti-vaccination stance—which now infects even the White House—demonstrates the immense harm that can be done by excessive distrust of technological advance.

Kenny employs history as a framing device. Crudely, Galvani’s experiments led to Mary Shelley’s Frankenstein which is a fable about ‘playing God’. (Kenny seems unaware there are many other readings of and perspectives on the book.) As for his statement ” … the suspicion with which Romantic thinkers like Shelley regarded scientific progress … ,” I’m not sure how he arrived at his conclusion about Romantic thinkers. According to Richard Holmes (in his book, The Age of Wonder: How the Romantic Generation Discovered the Beauty and Terror of Science), their relationship to science was more complex. Percy Bysshe Shelley ran ballooning experiments and wrote poetry about science, which included footnotes for the literature and concepts he was referencing; John Keats was a medical student prior to his establishment as a poet; and Samuel Taylor Coleridge (The Rime of the Ancient Mariner, etc.) maintained a healthy correspondence with scientists of the day sometimes influencing their research. In fact, when you analyze the matter, you realize even scientists are, on occasion, suspicious of science.

As for the anti-vaccination wars, I wish this essay had been more thoughtful. Yes, Andrew Wakefield’s research showing a link between MMR (measles, mumps, and rubella) vaccinations and autism is a sham. However, having concerns and suspicions about technology does not render you a fool who hasn’t progressed from 18th/19th Century concerns and suspicions about science and technology. For example, vaccines are being touted for all kinds of things, the latest being a possible antidote to opiate addiction (see Susan Gados’ June 28, 2016 article for ScienceNews). Are we going to be vaccinated for everything? What happens when you keep piling vaccination on top of vaccination? Instead of a debate, the discussion has devolved to: “I’m right and you’re wrong.”

For the record, I’m grateful for the vaccinations I’ve had and the diminishment of diseases that were devastating and seem to be making a comeback with this current anti-vaccination fever. That said, I think there are some important questions about vaccines.

Kenny’s essay could have been a nuanced discussion of vaccines that have clearly raised the bar for public health and some of the concerns regarding the current pursuit of yet more vaccines. Instead, he’s been quite dismissive of anyone who questions vaccination orthodoxy.

The end of this piece

There will be more essays in Slate’s Frankenstein series but I don’t have time to digest and write commentary for all of them.

Please use this piece as a critical counterpoint to some of the series and, if I’ve done my job, you’ll critique this critique. Please do let me know if you find any errors or want to add an opinion or add your own critique in the Comments of this blog.

ETA Jan. 25, 2017: Here’s the Frankenstein webspace on Slate’s Futurography which lists all the essays in this series. It’s well worth looking at the list. There are several that were not covered here.