Bias and Payoff

A random piece generated the following:

We know but try not to believe that it is impossible to erase bias in anything created by a human, as human bias is inevitable. Some engineers (social, civil, name your kind) will offer to detect bias and correct for it article by article, act by act. Yet, to solve for evidence of bias in how people choose articles, or acts or words or deeds, is to solve for a math problem without first clustering a set of laws or hypotheses that pertain to the problem at large, i.e. without encompassing the problem holistically.

The only way to control for bias in anthropomorphic products is to have a series of anti/corrective procedures, fading into multiplicity, perhaps somewhat like solving for the value of pi. The right way to run that ‘evidence of bias and correction for it’ experiment would be  to solve for both hypothesis and application problems simultaneously. Otherwise, the solution to problems would be equivalent to examining already-biased data and piling up evidence of certain degrees of bias without looking at why those biases exist.

The missing problem — in the whole field of machine learning, deep learning, AI and cognitive manipulation of political-economic populations, socio-political power and attribute-signalling furore — is why, given a choice (and not just between yes/no, such as in business or consumer choice models, or controlled experiments) individuals and groups choose one way and for one type of eventual result rather than others.

The calculation of outcome is not quite as cerebral as in chess. And people often choose to keep or return to homeostasis, i.e. to maintain what keeps them happy and fulfilled or to engineer outcomes in the common world that would bring them (as preferred group, not just one participating group) the lost homeostasis. Rarely do people choose for an outcome not yet imagined, and rarely are they willing to follow along without cognitive pictures of what the future will look like.

Bias is linked to payoff; ethically, it is impossible to remove human bias as long as we cannot solve the gnarls of human motivation.

It would perhaps be more desirable and fruitful to control for bias and payoff rather than attempt to remove the bias at all (even by cancelling out a negative with a positive). The calculation of payoff and satisfaction is a long derivation, and only a long game will ensure evidence that stands up to scrutiny as well as means to manage that evidence.

The real game in the digital world now is the vast experiment of controlled human emotion and behavior, which can be played by anyone who wants to ‘make an impact’ in the worlds linked up to social media, but are especially visible and truly formidable as platforms under names such as Google and Facebook. Data-driven regimes are perfect for both (1) convincing digitally docile populations to believe in the veracity of small steps and changes and choices as narrated within the framework of justice (righting wrongs, reversing damage) outcomes, and (2) gradually manipulating them to think and believe in digitally calculable ways. The Panopticon meets The Foundation trilogy.

Facing Violence

In a week during which several deaths have been recorded in India – in each, the perpetrators belonged to a social group who did not wish to enter an economic or social contract with individuals from another social group perceived as simultaneously inferior and locally oppressive, and wherein each symbolic action (words, raising the national flag on Republic Day) was the offensive trigger for violent retaliation (Chandan in Kasganj, Manjunath in Bangalore, Ankit in Delhi) – I connect the news to an incident I witnessed in Kolkata.

On Jan 28th, 2018, late at night in Kolkata, India, I observed three women being threatened with violent communal retaliation by an Uber driver because one of these women questioned the driver’s peremptory ride cancellation after the car was loaded and the trip had started. The driver told them to get out, physically intimidated them, declared he would block their street departure location with his car all night, and if the women didn’t shut up he would bring people back from Kidderpore. (The driver obviously guessed enough about his passengers to threaten them with violence from a different religious community). All this under the benign and smiling presence of local traffic policemen, who blamed the women because they couldn’t detain the driver.

Violence becomes real when it is personal. Up close, it is also a large emotion, inciting us to large actions. If we have learned to exteriorize and blame all our misfortunes on the ‘Other’ and its deliberate malice (person, group, entity, event), we enter the justificatory realm of virtuous scapegoating.

If I say my city has changed in 20 years, I will likely be called a bigoted bhakt or worse in India, a vile Islamophobe in the U.S., and a Modi-moron in my old discursive academic world (which told me to leave since I was an un-progressive settler colonial anyway). My good interlocutors will throw Ayodhya, Kashmir, NE India and Trump at me (lumped under an imagined category in their heads that they mis-read from Anglophone media; they still ask, ‘You speak Hindu?’ To which I say I don’t).

In that accusatory and reformist narrative, women such as these in the Uber tale are collateral damage in the necessary revolution of the world and the righting of historical wrongs.

In my reasoning, retaliatory justice is short-sighted and unpardonable, especially when supported by history shortened to 500 years. Violence, no matter how ‘halal,’  neither purifies nor resolves.

And yet this is how the world begins to burn again. I invite you to think on this article:

The PhotoBooth app on iPad tells you in childlike ways how the user’s face can be distorted and changed. The world is the same. How we see distorts what we see.