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; ...
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"POSIWID" - 5 new articles

  1. Data and the Genome
  2. Algorithmic Intuition - Gaydar
  3. ChatGPT and the Defecating Duck
  4. The Mad Hatter Works Out
  5. Delayed Success - Evolution
  6. More Recent Articles

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.

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.



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




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.



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.


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.

 


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)

   

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