Money Laundering for Bias

19 December 2020

It’s terrifying to choose an area of study for your PhD research – what if it turns out to be a dead end in a year? That thought is inescapable as I start (in earnest) studying the Linguistic Intergroup Bias.

At this critical juncture in my research (and life), I’m glad I found this talk by Maciej Ceglowski. It might seem overtly simplistic, but I appreciate its sentiment, and find it useful to keep in mind when studying bias from a computational perspective:

Instead of relying on algorithms, which we can be accused of manipulating for our benefit, we have turned to machine learning, an ingenious way of disclaiming responsibility for anything. Machine learning is like money laundering for bias. It’s a clean, mathematical apparatus that gives the status quo the aura of logical inevitability. The numbers don’t lie.


False Friends

3 November 2020

pardés in Hebrew:

  1. orchard, grove, fruit garden

paradesi in Tamil:

  1. Foreigner, stranger … 2. Sojourner, pilgrim, traveller;

What the latter definition leaves out is that paradesi is almost always used as a derogatory word. Are the two words cognates? The Hebrew word’s roots are Proto-Iranian as the etymology describes, while the Tamil word is probably derived from Sanskrit. Proto-Iranian and Sanskrit are both theorized to have developed from Proto-Indo-European. They are probably false friends — true cognates with different meanings due to semantic change.

My interest in these two words began when I learned about the Paradesi Jews of India — is it an accident that a word with negative connotations ties back to people who faced persecution and antisemitism? Maybe, but the sad truth today is that few people in Chennai are aware of its Jewish past. History is the story of people - many stories are tragic but deserve to be remembered.


Don't Make Me Talk

31 October 2020

John Siracusa in episode 19 of his pre-eminent podcast Hypercritical:

What were the earliest mass-market PC interfaces like?…they were like conversations…you’d tell it what to do, it gives information back to you…That was the basic paradigm until the Macintosh…What it gave you was not a conversation, but a thing…you could poke the thing and see how it reacts…it worked like a physical object

I really liked the comparison of early command-prompt user interfaces to conversations. It struck me that today’s AI assistants (Alexa, Google Assistant, Siri) are all based around having conversations. If these systems ever approached anything close to human intelligence and common-sense, perhaps having a conversation is the best way to interact with AI. But I wonder if there is a better interface to interact with AI? What’s the next leap from conversational AI? Perhaps Augmented Reality is the answer — artificial intelligence dispersed in our lived reality, giving us glancable information and the illusion of a physical object we can interact with. I wonder if this is why Apple is so bullish on AR as well.

Or maybe the best way to interact with artificial intelligence is the same way we interact with other people — using conversations.


Stop Using MTurk

15 September 2020

Why now? My thought process was simple: My research output thus far has been based on underpaid labour. Do I want that to continue?

For me, the answer is no, hence why I’m going to stop using MTurk. Perhaps there are alternatives that are fair to workers, that lead to good wages and job security. Linguistic data is important, and more so when it comes from a diverse population. But I don’t think paying miniscule amounts of money to obtain it is something to be proud of. We can do better.

Update

I’ve been thinking more about this topic after a research seminar discussion – would ensuring that workers get paid atleast $10 per hour fix the problem? It certainly ensures that they get paid a decent wage by you. A few requesters making the decision to pay more(and advertising their decision) isn’t going to make the median wage go up, nor does it do much to fix the numerous other issues with how the platform treats workers. It does help in a small way, and its the least evil thing you can do on the platform.


Ongoing Genocide

15 August 2020

Howard Zinn in A People’s History of the United States (emphasis mine):

One can lie outright about the past. Or one can omit facts which might lead to unacceptable conclusions. Morison does neither. He refuses to lie about Columbus. He does not omit the story of mass murder; indeed he describes it with the harshest word one can use: genocide.

This passage, and especially the last line, made an unusual impression on me when I first read it, and still does. Perhaps it’s the fact that one word needs to do so much work. How can one word possibly convey the magnitude of death, destruction, and suffering? On the other hand, genocide, along with words like racist, do seem to work. Those in power (and the privileged) seem more upset over being labelled racist, or being accused of genocide, than the crimes themselves.

I was reminded of the passage when reading a report describing the forced labour of Uyghurs in China, which used the term — cultural genocide (or ethnocide) to describe the Chinese government’s practises. Words matter, and the crimes against Kashmiris and Dalits need to be called for what they are, regularly and loudly.

Can the decades of military occupation of Kashmir, and the torture and killing of Kashmiris be captured by these words? Or the centuries of discrimination and persecution directed at the Dalit community? Calling these crimes for what they truly are — ongoing genocide, may not be adequate to describe the extent of the horrors that the people have experienced, nor the generational trauma, but it is a good start.