Say you need to store a square image 1,000 pixels wide to a side with the smallest filesize (setting aside compression techniques). The image begins with the colour #009900 on the left side and, as you move towards the right, gradually blends into #1e1e1e on the rightmost edge. Two simple storage methods come to mind: you could either encode the colour-information of every pixel in a file and store that file, or you could determine a mathematical function that, given the inputs #009900 and #1e1e1e, generates the image in question.
The latter method seems more appealing, especially for larger canvases of patterns that are composed by a single underlying function. In such cases, it should obviously be more advantageous to store the image as an output of a function to achieve the smallest filesize.
Now, in information theory (as in thermodynamics), there is an entity called entropy: it describes the amount of information you don’t have about a system. In our example, imagine that the colour #009900 blends to #1e1e1e from left to right save for a strip along the right edge, say, 50 pixels wide. Each pixel in this strip can assume a random colour. To store this image, you’d have to save it as an addition of two functions: ƒ(x, y), where x = #009900 and y = #1e1e1e, plus one function to colour the pixels lying in the 50-px strip on the right side. Obviously this will increase the filesize of the stored function.
Even more, imagine if you were told that 200,000 pixels out of the 1,000,000 pixels in the image would assume random colours. The underlying function becomes even more clumsy: an addition of ƒ(x, y) and a function R that randomly selects 200,000 pixels and then randomly colours them. The outputs of this function R stands for the information about the image that you can’t have beforehand; the more such information you lack, the more entropy the image is said to have.
The example of the image was simple but sufficiently illustrative. In thermodynamics, entropy is similar to randomness vis-à-vis information: it’s the amount of thermal energy a system contains that can’t be used to perform work. From the point of view of work, it’s useless thermal energy (including heat) – something that can’t contribute to moving a turbine blade, powering a motor or motivating a system of pulleys to lift weights. Instead, it is thermal energy motivated by and directed at other impetuses.
As it happens, this picture could help clarify, or at least make more sense of, a contemporary situation in science journalism. Earlier this week, health journalist Priyanka Pulla discovered that the Indian Council of Medical Research (ICMR) had published a press release last month, about the serological testing kit the government had developed, with the wrong specificity and sensitivity data. Two individuals she spoke to, one from ICMR and another from the National Institute of Virology, Pune, which actually developed the kit, admitted the mistake when she contacted them. Until then, neither organisation had issued a clarification even though it was clear both individuals are likely to have known of the mistake at the time the release was published.
Assuming for a moment that this mistake was an accident (my current epistemic state is ‘don’t know’), it would indicate ICMR has been inefficient in the performance of its duties, forcing journalists to respond to it in some way instead of focusing on other, more important matters.
The reason I’m tending to think of such work as entropy and not work per se is such instances, whereby journalists are forced to respond to an event or action characterised by the existence of trivial resolutions, seem to be becoming more common.
It’s of course easier to argue that what I consider trivial may be nontrivial to someone else, and that these events and actions matter to a greater extent than I’m willing to acknowledge. However, I’m personally unable to see beyond the fact that an organisation with the resources and, currently, the importance of ICMR shouldn’t have had a hard time proof-reading a press release that was going to land in the inboxes of hundreds of journalists. The consequences of the mistake are nontrivial but the solution is quite trivial.
(There is another feature in some cases: of the absence of official backing or endorsement of any kind.)
So as such, it required work on the part of journalists that could easily have been spared, allowing journalists to direct their efforts at more meaningful, more productive endeavours. Here are four more examples of such events/actions, wherein the non-triviality is significantly and characteristically lower than that attached to formal announcements, policies, reports, etc.:
- Withholding data in papers – In the most recent example, ICMR researchers published the results of a seroprevalence survey of 26,000 people in 65 districts around India, and concluded that the prevalence of the novel coronavirus was 0.73% in this population. However, in their paper, the researchers include neither a district-wise breakdown of the data nor the confidence intervals for each available data-point even though they had this information (it’s impossible to compute the results the researchers did without these details). As a result, it’s hard for journalists to determine how reliable the results are, and whether they really support the official policies regarding epidemic-control interventions that will soon follow.
- Publishing faff – On June 2, two senior members of the Directorate General of Health services, within India’s Union health ministry, published a paper (in a journal they edited) that, by all counts, made nonsensical claims about India’s COVID-19 epidemic becoming “extinguished” sometime in September 2020. Either the pair of authors wasn’t aware of their collective irresponsibility or they intended to refocus (putting it benevolently) the attention of various people towards their work, turning them away from the duo deemed embarrassing or whatever. And either way, the claims in the paper wound their way into two news syndication services, PTI and IANS, and eventually onto the pages of a dozen widely-read news publications in the country. In effect, there were two levels of irresponsibility at play: one as embodied by the paper and the other, by the syndication services’ and final publishers’ lack of due diligence.
- Making BS announcements – This one is fairly common: a minister or senior party official will say something silly, such as that ancient Indians invented the internet, and ride the waves of polarising debate, rapidly devolving into acrimonious flamewars on Twitter, that follow. I recently read (in The Washington Post I think, but I can’t find the link now) that it might be worthwhile for journalists to try and spend less time on fact-checking a claim than it took someone to come up with that claim. Obviously there’s no easy way to measure the time some claims took to mature into their present forms, but even so, I’m sure most journalists would agree that fact-checking often takes much longer than bullshitting (and then broadcasting). But what makes this enterprise even more grating is that it is orders of magnitude easier to not spew bullshit in the first place.
- Conspiracy theories – This is the most frustrating example of the lot because, today, many of the originators of conspiracy theories are television journalists, especially those backed by government support or vice versa. While fully acknowledging the deep-seated issues underlying both media independence and the politics-business-media nexus, numerous pronouncements by so many news anchors have only been akin to shooting ourselves in the foot. Exhibit A: shortly after Prime Minister Narendra Modi announced the start of demonetisation, a beaming news anchor told her viewers that the new 2,000-rupee notes would be embedded with chips to transmit the notes’ location real-time, via satellite, to operators in Delhi.
Perhaps this entropy – i.e. the amount of journalistic work not available to deal with more important stories – is not only the result of a mischievous actor attempting to keep journalists, and the people who read those journalists, distracted but is also assisted by the manifestation of a whole industry’s inability to cope with the mechanisms of a new political order.
Science journalism itself has already experienced a symptom of this change when pseudoscientific ideas became more mainstream, even entering the discourse of conservative political groups, including that of the BJP. In a previous era, if a minister said something, a reporter was to drum up a short piece whose entire purpose was to record “this happened”. And such reports were the norm and in fact one of the purported roots of many journalistic establishments’ claims to objectivity, an attribute they found not just desirable but entirely virtuous: those who couldn’t be objective were derided as sub-par.
However, if a reporter were to simply report today that a minister said something, she places herself at risk of amplifying bullshit to a large audience if what the minister said was “bullshit bullshit bullshit”. So just as politicians’ willingness to indulge in populism and majoritarianism to the detriment of society and its people has changed, so also must science journalism change – as it already has with many publications, especially in the west – to ensure each news report fact-checks a claim it contains, especially if it is pseudoscientific.
In the same vein, it’s not hard to imagine that journalists are often forced to scatter by the compulsions of an older way of doing journalism, and that they should regroup on the foundations of a new agreement that lets them ignore some events so that they can better dedicate themselves to the coverage of others.
Featured image credit: Татьяна Чернышова/Pexels.