Analysis Tech

The overlay bias

I’m not very fond of some highly popular pieces of writing (I won’t name them because I’m nervous about backlash from authors and/or their supporters) because a part of their popularity is undeniably rooted in technological ‘solutions’ that asymmetrically promote work published in the solution’s country of origin.

My favourite example is Pocket, the app that allows users to save copies of articles to read later, offline if required. Not long ago, Pocket introduced an extension for the Google Chrome browser (which counts hundreds of millions of users) such that every time you opened a new tab, it would show you three articles lots of other Pocket users have read and liked. It’s fairly brainless, ergo presumably non-malicious, and you’d expect the results to be distributed equally from among magazines, journals, etc. published around the world.

However, nine times out of ten – but often more – I’d find articles by NYT, The Atlantic, The Baffler, etc. there. I was reluctant to blame Pocket at first, considering their algorithm seemed too simple, but then I realised Pocket was just the last in a long line of other apps and algorithms that simply amplified existing biases.

Before Pocket, for example, there might have been Twitter, Facebook or some other platform that allowed stories from some domains (,, etc.) to persist for longer on users’ feeds because they were more easily perceived to be legitimate than articles from other sources, say, a Venezuelan newspaper, a Kenyan blog, a Pakistani magazine or a Vietnamese journal. Or there might have been Nuzzle, which auto-compiles a digest of articles that others your friends on the social media have shared most – likely unmindful of the fact that people quite often share headlines, or domains they’d like to be known to be reading, instead of the articles themselves.

This is a social magnification like the biological magnification in nature, whereby toxic substances pile up in greater quantities in the gizzards of animals higher up in the food chain. Here, perceptions of legitimacy and quality accumulate in greater quantities in the feeds and timelines of people who consume, or even glance through, the most information. And this way, a general consciousness of what’s considered desirable erects itself without anything drastic, with just the more fleeting and mindless actions of millions of people, into a giant wheel of information distribution that constantly feeds itself its own momentum.

As the wheel turns, and The Atlantic publishes an article, it doesn’t just publish a good article that draws hundreds of thousands of readers. It also rides a wheel set in motion by American readers, American companies, American developers, American interests and American dollars, with a dollop of historical imperialism, that quietly but surely brings the world a good article plus a good-natured reminder that The Atlantic is good and that readers needn’t go looking for anything else because The Atlantic has them covered.

As I wondered in 2017, and still do: “Will my peers in India have been farther along in their careers had there been an equally influential Indian for-publishers tech stack?” Then again, how much is one more amplifier, Pocket or anything else, going to change?

I went into this tirade because of this Twitter thread, which describes a similar issue with arXiv – the popular preprint repo for physical sciences, computer science and applied mathematics papers (don’t @ me to quibble over arXiv’s actual remit). As the tweeter Jia-Bin Huang writes, the manuscripts that were uploaded last – i.e. most recently – to arXiv are displayed on top of the output stack, and what’s displayed on top of the stack gets more citations and readership.

This is a very simple algorithm, quite like Pocket’s algorithm, but in both cases they’re algorithms overlaid on existing bias-amplifying architectures. In a sense, they’re akin to the people who might stand by and watch a lynching, neither egging the perpetrators on nor stopping them. If the metaphor is brutal, remember that the effects on any publication or scientist that can’t infiltrate or ‘hack’ social biases are brutal as well. While their contents and their ideas might deserve international readership, these publications and scientists will need to spend more – energy, resources, effort – to grab international attention again and again.

The example Jia-Bin Huang cites is of scientists in Asia, who – unlike their American counterparts – can’t upload a paper on arXiv just before the deadline so that their papers sit on top of the stack because 2 pm in New York is 3 am in Taipei.

As some replies to the thread indicated, the people maintaining arXiv can easily solve the problem by waiting for the deadline to pass, then randomising the order of papers displayed in its email blast – but as Jia-Bin Huang notes, doing that would mean negating the just-in-time advantage that arXiv’s American users enjoy. So here we are.

It isn’t hard to see how we can extend the same suggestion to the world’s Pockets and Nuzzles. Pick your millions of users’ thousand most-read articles, mix up their order – even weigh down popular American publishers if necessary – and finally advertise the first ten items from this list. But ultimately, until technological solutions actively negate the biases they overlie, Pocket will lie on the same spectrum as the tools that produce the biases. I admit fact-checking in this paradigm could be labour-intensive, as could relevance-checking vis-à-vis arXiv, but I also think the latter would be better problems to solve.

Analysis Science

For coronavirus claims, there is a world between true and false

In high school, you must have learnt about Boolean algebra, possibly the most fascinating kind of algebra for its deceptive ease and simplicity. But thanks to its foundations in computer science, Boolean algebra – at least as we it learnt in school – is fixated with ‘true’ and ‘false’ states but not with the state of ‘don’t know’ that falls in between. This state may not have many applications as regards the functioning of logic gates but in the real world, it is quite important, especially when the truth threatens to be spun out of control.

Amitabh Bachchan recently published a video in which he delivered a monologue claiming that when a fly alights on human faeces containing traces of the new coronavirus, flies off and then alights on some food, the food could also be contaminated by the same virus. The Wire Science commissioned a fact-check from Dr Deepak Natarajan, a reputed (and thankfully opinionated) cardiologist in New Delhi. In his straightforward article, Dr Natarajan presents evidence from peer-reviewed papers to argue that while we know the new coronavirus does enter the faeces of an infected person, we don’t know anything about whether the virus remains viable, or capable of precipitating an infection. Second, we know nothing of the participation of flies either.

The thing to remember here is that, during a panic – or in a pre-panic situation that constantly threatens to devolve into a panic – society as such has an unusually higher uptake capacity for information that confirms their biases irrespective of whether it is true. This property, so to speak, amplifies the importance of ‘not knowing’.

Thanks to scientism, there is a common impression among many experts and most non-experts that science has, or could have, the answers to all questions that could ever be asked. So when a scientist says she does not know something, there is a pronounced tendency among some groups of people – particularly, if not entirely, those who may not be scientistic themselves but believe science itself is scientistic – to assume the lack of an answer means the absence of an answer. That is, to think “If the scientist does not have an answer, then the science does not have an answer”, rather than “If the scientist does not have an answer, then the science does not have an answer yet” or even “If the scientist does not have an answer yet, she could have an answer later“.

This response at a time of panic or pre-panic forces almost all information to be classified as either ‘true’ or ‘false’, precluding the agency science still retains to move towards a ‘true’ or ‘false’ conclusion and rendering their truth-value to be a foregone conclusion. That is, we need evidence to say if something is true – but we also need to understand that saying something is ‘not true’ without outright saying it is ‘false’ is an important state of the truth itself.

It also forces the claimant to be more accountable. Here is one oversimplified but nonetheless illustrative example: When only ‘true’ and ‘false’ exist, any new bit of information has a 50% chance of being in one bin or the other. But when ‘not true/false’ or ‘don’t know’ is in the picture, new information has only a 33% chance of assuming one of the truth values. Further, the only truth value based on which people should be allowed to claim something is true is ‘true’. ‘False’ has never been good enough but ‘don’t know’ is not good enough either, which means that before we subject a claim to a test, it has a 66% chance of being ‘not true’.

Amitabh Bachchan’s mistake was to conflate ‘don’t know’ and ‘true’ without considering the possibility of ‘not true’, and has thus ended up exposing his millions of followers on Twitter to claims that are decidedly not true. As Dr Natarajan said, silence has never been more golden.

Culture Op-eds

Two sides of the road and the gutter next to it

I have a mid-October deadline for an essay so obviously when I started reading up on the topic this morning, I ended up on a different part of the web – where I found this: a piece by a journalist talking about the problems with displaying one’s biases. Its headline:

It’s a straightforward statement until you start thinking about what bias is, and according to whom. On 99% of occasions when a speaker uses the word, she means it as a deviation from the view from nowhere. But the view from nowhere seldom exists. It’s almost always a view from somewhere even if many of us don’t care to acknowledge that, especially in stories where people are involved.

It’s very easy to say Richard Feynman and Kary Mullis deserved to win their Nobel Prizes in 1965 and 1993, resp., and stake your claim to being objective, but the natural universe is little like the anthropological one. For example, it’s nearly impossible to separate your opinion of Feynman’s or Mullis’s greatness from your opinions about how they treated women, which leads to the question whether the prizes Feynman and Mullis won might have been awarded to others – perhaps to women who would’ve stayed in science if not for these men and made the discoveries they did.

One way or another, we are all biased. Those of us who are journalists writing articles involving people and their peopleness are required to be aware of these biases and eliminate them according to the requirements of each story. Only those of us who are monks are getting rid of biases entirely (if at all).

It’s important to note here that the Poynter article makes a simpler mistake. It narrates the story of two reporters: one, Omar Kelly, doubted an alleged rape victim’s story because the woman in question had reported the incident many months after it happened; the other, the author herself, didn’t express such biases publicly, allowing her to be approached by another victim (from a different incident) to have her allegations brought to a wider audience.

Do you see the problem here? Doubting the victim or blaming the victim for what happened to her in the event of a sexual crime is not bias. It’s stupid and insensitive. Poynter’s headline should’ve been “Reporters who are stupid and insensitive fail their sources – and their profession”. The author of the piece further writes about Kelly:

He took sides. He acted like a fan, not a journalist. He attacked the victim instead of seeking out the facts as a journalist should do.

Doubting the victim is not a side; if it is, then seeking the facts would be a form of bias. It’s like saying a road has two sides: the road itself and the gutter next to it. Elevating unreason and treating it at par with reasonable positions on a common issue is what has brought large chunks of our entire industry to its current moment – when, for example, the New York Times looks at Trump and sees just another American president or when Swarajya looks at Surjit Bhalla and sees just another economist.

Indeed, many people have demonised the idea of a bias by synonymising it with untenable positions better described (courteously) as ignorant. So when the moment comes for us to admit our biases, we become wary, maybe even feel ashamed, when in fact they are simply preferences that we engender as we go about our lives.

Ultimately, if the expectation is that bias – as in its opposition to objectivity, a.k.a. the view from nowhere – shouldn’t exist, then the optimal course of action is to eliminate our specious preference for objectivity (different from factuality) itself, and replace it with honesty and a commitment to reason. I, for example, don’t blame people for their victimisation; I also subject an article exhorting agricultural workers to switch to organic farming to more scrutiny than I would an article about programmes to sensitise farmers about issues with pesticide overuse.

Life notes Scicomm

GM: confronting contradictions

There was a rash of articles published online recently – such as this one – about how the adult human mind, when confronted with information that contradicts its existing beliefs, does not reorganise what it knows but rejects the information’s truthfulness itself. During political conversations, this aspect of how we think and learn is bound to influence both the way opposing parties argue and the effects of propaganda on people. However, this notion’s impact seems to me to be more dire w.r.t. the issue of genetically modified (GM) crops.

Even when confronted with evidence in support of GM crops from the scientific literature, anti-GM activists reflexively take recourse in the deficiencies inherent in the scientific method, even if the deficiencies themselves are well-known.

In the specific example of GM mustard, there is no clear answer: the variant developed by Deepak Pental & co. has lower yield than some non-GM varieties but higher pest-resistance and is easier to breed. As a result, any single discussion of GM mustard’s eligibility to be a food crop (it hasn’t been released into the market yet) should address its pros and cons together instead of singling out its cons.

It would seem anti-GM activists are aware of this pressure because whenever scientists raise the pros of GM mustard, the activists’ first, and often last, line of reasoning is to quote even other studies. They are in turn rebutted by more studies, and the backs and forths go on until the entire debate becomes hinged on disagreements over minutiae. Granted, allowing bad GM crops to be commercialised can have deadly consequences. But this is also true of a score other enterprises in which we are happy to go along with approximations. Why the selective outrage?

It can’t be that farmer suicides touch a nerve because they are driven not just by crop failure but also by crop insurance, grain storage/distribution and pricing indices (such as the differences between rural CPI and MSP). Estimating these three factors is a task ridden with inaccuracies, many ill-supported assumptions and, frequently, corruption. However, we don’t seem to have raged against them with as much intensity as we have against GM mustard. We should have because of what Harish Damodaran eloquently expressed in The Indian Express on June 1:

Why is there so much opposition to a technology developed, after all, by Indian scientists in the public sector? Yes, the original patent for the [Barnase-Barstar-Bar hybridisation] system was filed by Plant Genetics Systems (now part of Bayer CropScience), but the CGMCP scientists improved upon it, for which they obtained patents (three US, two Canadian, one European Union and Australian each). Yet, we see no value in their work. The opponents — from the so-called Left or the Right — haven’t even bothered to visit the CGMCP, most accessibly located in Delhi University’s South Campus, while taking time out for anti-GMO jamborees in Brussels and The Hague. All this opposition is reflective of a unique Us and Them syndrome. For “us”, nothing but the latest would do. But farmers will have no right to grow GM mustard and assess its performance on the field.

The persuasion to constantly reject one study for another and our hypocritical stand on the ownership of GM crops together suggest that the pro/anti-GM debate is going to be settled by neither of these tactics. They are both the effects of a common flaw: ideological stubbornness. Even I – being pro-GM – am inclined to consign some farmers’ opposition to GM mustard to fear-mongering by activists. Sometimes I can find something easily refuted but at others, I struggle to change my mind even if the facts are evident. Anyway, while I can’t think of what it is that we can do to make ourselves less stubborn (each to her own, perhaps?), I do think it’s important we stay aware of our biases’ impact on our public conversations.

PS: If my post seems one-sided, addressing the behaviour of only anti-GM groups, one reason is that anti-GM expression in the mainstream as well as social media overshadows pro-GM expression. I’m also biased, of course.

Featured image credit: WikimediaImages/pixabay.