Data and the Genome

The word data comes from the Latin meaning that which is given. So one might think it is entirely appropriate to use the word for our DNA, given to us by our parents, thanks to millions of years of evolution. DNA is often described as a genetic code; the word code either refers to the way biological information is represented in the molecular structure of chromosomes, or to the way these chromosomes can be understood as a set of instructions for building a biological entity. Watson and Crick used the word code in their 1953 Nature article.

However, when people talk about the human genome, they are often referring to a non-biological representation in some artificial datastore. In other words, given by biology to data science.

Shannon E French objects to talking about data stored on DNA like it’s some kind of memory stick, and Abeba Birhane sees this as part of the current trend that is so determined to present AI as human-like at all costs, describing humans in machinic terms has become normalised.

Elsewhere, Abeba Birhane is known for her strong critique of AI. As well as important ethical issues (algorithmic bias, digital colonialism, accountability, exploitation/expropriation), she has also raised concerns about the false promise of AI hype.

we have arrived at peak AI hype accompanied by minimal critical thinking

— Abeba Birhane (@Abebab) June 12, 2022

But describing humans (or other biological entities) in machinic terms, or treating them as instruments. is far older than AI. When we replace animals with technical devices (canaries. carrier pigeons, horses), the substitution implies that the animals had been treated as devices, the replacement often justified by the argument that technical devices are cheaper, more efficient, or more reliable, or don't require regular breaks - or are simply more modern. Conversely, when scientists try to repurpose DNA as a data storage mechanism, this also seems to mean treating biology in instrumental terms.

But arguably what is stored or encoded in the DNA - whether in its original biological manifestation or more recent exercises in bioengineering - is still data, regardless of how or for whom it is used.

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Abeba Birhane, Atoosa Kasirzadeh, David Leslie and Sandra Wachter, Science in the age of large language models (Nature Reviews Physics, Volume 5, May 2023, 277–280)

Abeba Birhane and Deborah Raji, ChatGPT, Galactica and the Progress Trap (Wired, 9 December 2022)

Grace Browne, AI is steeped in Big Tech's 'Digital Colonialism' (Wired, 25 May 2023)

J.D. Watson and F.H.C. Crick, Genetical Implications of the Structure of Deoxyribonucleic Acid (Nature, 30 May 1953)

Related posts: Naive Epistemology (July 2020), Limitations of Machine Learning (July 2020), Mapping out the entire world of objects (July 2020), Lie Detectors at Airports (April 2022), Algorithmic Intuition (November 2023)

Algorithmic Intuition - Gaydar

When my friend A was still going out with women, other friends would sometimes ask if he was gay. An intuitive ability to guess the sexuality of other people is known as gaydar. There have been studies that appear to provide evidence that both humans and computers possess such an ability, although the reliability of this evidence has been challenged. For example, some of these studies have relied on images posted on dating sites, but images that have been crafted and selected for dating purposes may already reflect how a person of a given sexuality wishes to present thenselves in that specific context, and may not reflect how the person looks in other contexts.

The latest study claims to assess sexuality from brain waves. This has been criticized as gross and irresponsible (Rae Walker) and as unscientific (Ababa Birhane). Continuing a debate that had started with other methods of algorithmic gaydar.

More generally, there is considerable disquiet about computers attempting to segment people in this way. For a start, there are many parts of the world where homosexuality doesn't only lead to social disapproval and harassment, but also criminal penalties and sanctions. Even though the algorithms may be inaccurate, they might be used to discriminate against people, or trigger homophobic actions. Whether someone actually is gay or is a false positive is almost beside the point here, either way the algorithmic gaydar may result in individual suffering.

Furthermore, these algorithm appears to want to colonize aspects of subjectivity, of the subject's identity.

• WyssBernard: I’m not going accept a machine determination as to what I identify as. ?¿
• Abeba Birhane: just let people be or let people identify their own sexuality

In an interview with the editor of Wired, Yuval Noah Harari wonders whether an algorithm might have guessed he was gay before he realised it himself. And if an algorithm had been the source of this wisdom about himself, would this not have been incredibly deflating for the ego?

And Lawrence Scott describes how his Facebook timeline started to be invaded by images of attractive men, suggesting that the algorithm had somehow profiled him as being particularly susceptible to these images.

to be continued

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Isobel Cockerell, Facial recognition systems decide your gender for you. Activists say it needs to stop (Codastory, 12 April 2021)

Isobel Cockerell, Researchers say their AI can detect sexuality. Critics say it’s dangerous (Codastory, 13 July 2023)

Lawrence Scott, Hell is Ourselves (The New Atlantis #68, Spring 2022, pp. 65-72)

Nicholas Thompson, When Tech Knows You Better Than You Know Yourself (Wired, 4 October 2018)

Wikipedia: Gaydar

ChatGPT and the Defecating Duck

For dog owners, the intelligence of dogs shows itself (among other things) in their ability to learn tricks. For cat owners, the intelligence of cats shows itself (among other things) in their disdain for learning tricks. 

When Alan Turing conceived of a way to tell computers and humans apart, now known as the Turing Test, he called it the Imitation Game. His first example was to ask a computer to write poetry - specifically a sonnet on the subject of the Forth Bridge. And his idea of a plausible answer for the computer was to say: Count me out on this one. I never could write poetry.

No doubt many people have tested ChatGPT with exactly the same question. When Jessica Riskin tried it, she was not impressed by its efforts. She found Turing’s imaginary machine’s answer (Turing imitating a machine imitating a human) infinitely more persuasive (as indicator of intelligence) than ChatGPT’s. Turing’s imagined intelligent machine gives off an unmistakable aura of individual personhood, even of charm.

An earlier article by Professor Riskin described a mechanical automaton that attracted large admiring crowds in 18th century Paris. This was a generative pretrained transformer in the shape of a duck, which appeared to convert pellets of food into pellets of excrement. The inventor is careful to say that he wants to show, not just a machine, but a process. But he is equally careful to say that this process is only a partial imitation.

Whereas ChatGPT's bad imitation of poetry is real shit.

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Jessica Riskin, The Defecating Duck, or, The Ambiguous Origins of Artifical Life (Critical Enquiry, 2003)

Jessica Riskin, A Sort of Buzzing Inside My Head (New York Review of Books, 25 June 2023)

Alan Turing, Computing Machinery and Intelligence (Mind 1950)

The Mad Hatter Works Out

An interesting exchange on Twitter between the mainstream media and the owner of Twitter, which came to my attention via @RMac18 and @karaswisher.

Over a year ago, an American professor wrote a column on MSNBC noting a trend of far right groups using fitness chat groups to recruit and radicalize young men. 

One of the co-founders of Open AI (yes, him) chose to interpret this as asserting that you're a nazi if you work out. There are several possible interpretations of this tweet.

The most unlikely explanation is that a person with a good STEM education and (supposedly) a high IQ has committed a serious error in elementary logic. As in some cats are grey therefore all grey objects are cats.

A slightly more plausible explanation is that the tweet was produced on their behalf by a large language model (LLM), operating a symmetric bi-logic (Matte-Blanco) rather than conforming to classical logic. In the dream world of the unconscious, or in the hallucinations of chat algorithms, the idea that all grey objects are cats might seem perfectly reasonable.

You might just as well say, added the Dormouse, who seemed to be talking in his sleep, that I breathe when I sleep is the same thing as I sleep when I breathe! It is the same thing with you, said the Hatter.

However, the most likely explanation is that the message was deliberately designed to flout logical validity in order to generate the desired affective response - simultaneously appealing to audience A and provoking audience B. (I guess I must be in audience B.) Chasing clicks, as @zsk suggests elsewhere.

Many of the responses adopt similarly dodgy logic, including those that observe (ad hominem) that there are some fat and flabby people on the far right.

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Arwa Mahdawi, Why is EM borrowing insults from white supremacists? (Guardian, 11 July 2023)

Cynthia Miller-Idriss, Hate in the Homeland: The New Global Far Right (Princeton University Press, 2020)

Cynthia Miller-Idriss, Pandemic fitness trends have gone extreme — literally (MSNBC, 22 March 2022)

For more on LLM and Matte-Blanco, see my post From Chat GPT to Infinite Sets (May 2023)

Delayed Success - Evolution

Andreas Wagner notes the long time that elapsed between the first appearance of grass and its ecological dominance. He argues that delayed success holds a profound truth about new life forms.

Evolution works across enormous timespans. Regarding humans as the pinnacle of evolution only works if you forget this.

During the COVID-19 pandemic, some people offered predictions about where and in what form the virus would end up, without considering the fact that everything would change and mutate many times before anything ended up anywhere. And some people thought that we didn't need to worry about the less efficient or effective variants, because they would eventually disappear.

It is said that a Chinese leader (perhaps Mao Zedong or Zhou Enlai), when asked about revolutionary action in France, opined that it was too early to tell, and this quote is often understood to refer to the French revolution two hundred years earlier. Even if this actually referred to the much more recent events of the 1960s, the story accords with the belief that the Chinese government is able to take a much longer view of such matters than democratically elected governments can.

But even a few thousand years of Chinese history is nothing at all in evolutionary timescales.

 

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Andreas Wagner, Sleeping beauties: the evolutionary innovations that wait millions of years to come good (Guardian, 18 April 2023)

Related posts: Rates of Evolution (September 2007), Explaining Natural Selection (January 2021)

What Does A Patent Say?

There is a narrative about accelerating technological change, which appears to be supported by an increasing volume of patent activity. I have expressed my doubts about this metric in previous posts.

• Death of Software (November 2004)
  
• Evolution or Revolution (May 2006)
• Rates of Evolution (September 2007)
• Hedgehog Innovation (February 2023)

In their latest book, Ariel Ezrachi and Maurice Stucke also call out the unreliability of this metric.

The number of patents is also an imperfect measure of innovation. ... no correlation between the number of patents in a technological field and the annual performance improvement of that field ... The number of patents does not reflect how disruptive the patented innovation is or whether it's toxic or beneficial. ... Furthermore, patent numbers do not account for the Tech Barons' distorting the innovation paths and monopolizing knowledge. Ezrachi and Stucke p 150

Although despite this caveat, they appear to take the metric seriously when evaluating cities on their support for innovation pp 208-211, p268 n30.

They also suggest a further twist.

It should be noted that not all patents have been transformed into products and services. Some of the technologies may have been developed but not necessarily implemented, Still, they offer a valuable indication as to the assets a company is trying to secure and the direction in which its technology is heading. p238 n1

This is supported by a newspaper article by Sahil Chinoy, which includes a quote from law professor Jason M Schultz.

A patent portfolio is a map of how a company thinks about where its technology is going.

Tech watchers have often interpreted patent applications in this way. In my post Guardian Angel (May 2008), I discussed a patent application that attracted a lot of attention at the time, both because of its content and because of some of the people involved. (Bill Gates obviously, who else?)

But with all respect to Professor Schultz, that's not actually the purpose of a patent. The primary purpose of a patent is not to enable the inventor to exploit something, it is to prevent anyone else freely exploiting it. 

(The purpose of the patent system may be to reward inventors and encourage invention, but that's an entirely different question.)

As reported by Dani Deahl and Sarah Perez, Amazon took out a patent to prevent people doing in Amazon shops exactly what Amazon had always encouraged them to do in everyone else's shops! See my post on Showrooming and Multi-sided Markets (December 2012, updated June 2017). 

And in some cases, a patent is just staking a precautionary claim to an invention that is not currently viable, to make sure nobody else can profit from it.

Obviously this kind of patent game is not the only method used by Tech Barons to suppress innovation that is inconvenient to them, and Ezrachi and Stucke document many others. Sometimes it just means taking over an inconvenient service and shutting it down, as eBay did with decide.com. See my post Predictive Analytics for the Smart Consumer (April 2014).

Meanwhile, if the Tech Barons actually wanted to do something totally devious and evil, do you really think they would submit a patent application for the world to see?

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Sahil Chinoy, What 7 Creepy Patents Reveal About Facebook (New York Times, 21 June 2018) subscribers only

Dani Deahl, Amazon granted a patent that prevents in-store shoppers from online price checking (The Verge, 15 June 2017)

Ariel Ezrachi and Maurice Stucke, How Big-Tech Barons Smash Innovation and how to strike back (New York: Harper, 2022)

Sarah Perez, Amazon, now a physical retailer too, is granted an anti-showrooming patent (TechCrunch, 16 June 2017) 

Related post: How soon might humans be replaced at work (November 2015)

Who Codes Whom?

@daily_barbarian (Geoff Shullenberger) describes René Girard as politically ambivalent.

He codes as right-wing in his insistence on the necessity of social order, but as left-wing in his insistence that any such order is founded on violence.

When I ask who is doing the coding here, and for what purpose, he replies 

People of all sorts who encounter his work and attempt to place it in the conventional categories. I’ve seen many on the left use the first point to call him a reactionary, and some on the right use the second to call him naïve about power.

Quite so. But the fact that other people don't know how to categorize Girard doesn't imply any contradiction or ambivalence on his part. What it does show is that the conventional categories (rightwing, leftwing) are becoming increasingly muddled. (There are several other arguments for moving away from this conventional way of framing politics - for example recent work by Latour.)

But what I want to talk about here is the elision. Instead of people of all sorts code him ..., we get simply he codes. As if Girard is somehow responsible for his own classification.

Classification is a political act, but categories are often treated as objective facts rather than subjective opinions (Bowker & Star). Hence my question about who and why. 

One domain in which the act of coding hasn't always received sufficient attention is in data and intelligence, but this is now changing thanks to great work by @abebab and others. See links to my other posts below.

And in the political domain, commentators are increasingly willing to challenge the coding that underpins certain alleged social facts. See for example Global Media Literacy. And those wishing to politicize the COVID pandemic can find more than enough complexity in the coding of health and pharma data that might support any given measure. (Politicizing such matters is not necessarily a bad thing, but it is itself a political choice.)

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Anon, Opinion: Beware the data on American right-wing violence (Global Media Literacy, 23 May 2022)

Geoffrey Bowker and Susan Leigh Star, Sorting Things Out (MIT Press 1999)

Related posts: Framing a riot (August 2011), Limitations of Machine Learning (July 2020), Mapping out the entire world of objects (July 2020), Near Miss (April 2021), Purpose of Shame (April 2022)

The Dogs of WWW

@kkomaitis and @j2bryson discuss the anniversary of the New Yorker cartoon On the Internet nobody knows you're a dog.

Obviously this is no longer true. Konstantinos Komaitis raises the important topic of surveillance capitalism and government snooping. There is more than enough data to know how many dogs you have, what you call them, how often you take them for walks, which other dogs and dog-owners you meet in the park, and how much you spend on dog-food and veterinary bills.

Joanna Bryson also raises the topic of deep fakes. Does this mean that some of those cute dogs we see on the Internet don't even exist? Or perhaps shifting our understanding as what counts as existing?

 

The title of this post is a reference to the words Shakespeare gives to Mark Antony:

Cry Havoc!, and let slip the dogs of war.

In its original meaning, crying havoc is a signal for looting and plunder. On the internet, this would include stealing your data and stealing your identity. 

In its article on the dogs of war, Wikipedia reproduces a Punch cartoon from 1876, showing Russia threatening war against Turkey in revenge for its losses in the Crimean War twenty years previously. Isn't history interesting?

Wikipedia: On the Internet nobody knows you're a dog, The Dogs of War, Crimean War (1853-1856), Russo-Turkish War (1877–1878)

The Government Inspector

Around £550 million has been spent on purpose-built facilities to conduct post-Brexit checks. Most of this money came from UK taxpayers, with the remainder being covered by local authorities and other organizations. However, following a recent change in policy by the UK government, these facilities will no longer be required.

The one in Portsmouth cost £25 million. It is designed specifically for government inspections, nothing else, Mike Sellers, director of Portsmouth International Port, told the Guardian. The cheapest option would be to demolish it.

The Government Inspector was an 1836 play by Nikolai Gogol, described by Wikipedia as a comedy of errors, satirizing human greed, stupidity, and the extensive political corruption of Imperial Russia.

The main character, Khlestakov, personifies irresponsibility, light-mindedness, and absence of measure. Remind you of anyone?

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Joanna Partridge, Portsmouth’s £25m border post stands empty after minister’s imports U-turn (The Guardian, 5 July 2022)

Wikipedia: The Government Inspector

Progress Bar

There are algorithms whose primary purpose appears to be to generate affect - for example, to reduce the anxiety of those waiting. For example, the progress bar that is displayed when something is loading or downloading. Other examples include indicators at bus stops, on railway platforms or next to lifts, showing either the current location or the expected time of arrival.

Sometimes these indicators misbehave. The progress bar suddenly jumps from 60% to 90% and then gets stuck. One moment the bus is five minutes away, the next moment it is seven minutes away. These glitches reveal that the indicators are not unmediated truth but fictions functioning as truth.

The algorithm of the progress bar depends not only on the code generating it but the cultural calculus of waiting itself, on a user seeking feedback from the system, and on the opportunity - increasingly capitalized on - to show the user other messages, entertainments or advertising during the waiting phase. Finn p34

Jason Farman compares these indicators with earlier symbols, such as the spinning cursor, which provided no such feedback.

These symbols keep us from seeing how the system is actually working; we’re not given a behind-the-scenes view of how the process is actually progressing, so we are kept at arm’s length, spinning or twiddling our thumbs as we wait. Farman

In other contexts, such as digital games, progress bars are designed to motivate the players.

Feedback is a system that tells players how close they are to achieving a goal and can come from points, levels, a score or a progress bar; this provides motivation to keep playing. Pulos quoting McGonigal, 2011, p. 21

And if the progress bar gets stuck on 99%, what then? In her PhD thesis, Kate Starbird discusses a meme that circulated on Twitter during the 2011 political uprising in Egypt, with progress bars showing variations of installing freedom and uninstalling dictator, in some cases linked to messages encouraging patience and/or persistence.

As things turned out, President Mubarak was uninstalled, but many of the protesters were unhappy with subsequent events, and there was a further uprising in 2013. So how much progress has Egypt made in installing freedom and democracy? Unfortunately, democracy isn't something that was uploaded to the cloud by the ancient Greeks, just waiting to be downloaded into any country with sufficient memory.

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Jason Farman, Delayed Response (Yale University Press 2018). Extract: Spinning in Place

Ed Finn, What Algorithms Want (MIT Press 2017)

McGonigal, J. (2011). Reality is broken: Why games make us better and how they can change the world. New York, NY: Penguin Press

Alexis Pulos, FARMING AND FIGHTING AS PRACTICE AND PEDAGOGY: A PROCEDURAL FIELD ANALYSIS OF DIGITAL GAMES (University of New Mexico, PhD thesis 2013). https://digitalrepository.unm.edu/cj_etds/45

Kate Starbird, Crowdwork, Crisis and Convergence: How the Connected Crowd Organizes Information duringMass Disruption Events (Atlas Institute, PhD thesis 2012)

Wikipedia: Progress Bar, Progress Indicator, 2011 Egyptian revolution