the future of conferences

The last issue of Nature for 2018 offers a stunning collection of science photographs, ten portraits of people who mattered (for the editorial board of Nature), and a collection of journalists’ entries on scientific conferences. The later point leading to interesting questioning on the future of conferences, some of which relate to earlier entries on this blog. Like attempts to make them having a lesser carbon footprint, by only attending focused conferences and workshops, warning about predatory ones, creating local hives on different continents that can partake of all talks but reduce travel and size and still allow for exchanges person to person, multiply the meetings and opportunities around a major conference to induce “only” one major trip (as in the past summer of British conferences, or the incoming geographical combination of BNP and O’Bayes 2019), cut the traditional dreary succession of short talks in parallel in favour of “unconferences” where participants set communally the themes and  structure of the meeting (but ware the dangers of bias brought by language, culture, seniority!). Of course, this move towards new formats will meet opposition from several corners, including administrators who too often see conferences as a pretense for paid vacations and refuse supporting costs without a “concrete” proof of work in the form of a presentation.Another aspect of conference was discussed there, namely the art of delivering great talks. Which is indeed more an art than a science, since the impact will not only depend on the speaker and the slides, but also on the audience and the circumstances. As years pile on, I am getting less stressed and probably too relaxed about giving talks, but still rarely feel I have reached toward enough of the audience. And still falling too easily for the infodump mistake… Which reminds me of a recent column in Significance (although I cannot link to it!), complaining about “finding it hard or impossible to follow many presentations, particularly those that involved a large number of equations.” Which sounds strange to me as on the opposite I quickly loose track in talks with no equations. And as mathematical statistics or probability issues seems to imply the use of maths symbols and equations. (This reminded me of a short course I gave once in a undisclosed location, where a portion of the audience left after the first morning, due to my use of “too many Greek letters”.) Actually, I am always annoyed at apologies for using proper maths notations, since they are the tools of our trade.Another entry of importance in this issue of Nature is an interview with Katherine Heller and Hal Daumé, as first chairs for diversity and inclusion at N[eur]IPS. Where they discuss the actions taken since the previous NIPS 2017 meeting to address the lack of inclusiveness and the harassment cases exposed there, first by Kristian Lum, Lead Statistician at the Human Rights Data Analysis Group (HRDAG), whose blog denunciation set the wheels turning towards a safer and better environment (in stats as well as machine-learning). This included the [last minute] move towards renaming the conference as NeuroIPS to avoid sexual puns on the former acronym (which as a non-native speaker I missed until it was pointed out to me!). Judging from the feedback it seems that the wheels have indeed turned a significant amount and hopefully will continue its progress.

statistics in Nature [a tale of the two Steves]

In the 29 November issue of Nature, Stephen Senn (formerly at Glasgow) wrote an article about the pitfalls of personalized medicine, for the statistics behind the reasoning are flawed.

“What I take issue with is the de facto assumption that the differential response to a drug is consistent for each individual, predictable and based on some stable property, such as a yet-to-be-discovered genetic variant.”S. Senn

One (striking) reason being that the studies rest on a sort of low-level determinism that does not account for many sources of variability. Over-confidence in causality results. Stephen argues that improvement lies in insisting on repeated experiments on the same subjects (with an increased challenge in modelling since this requires longitudinal models with dependent observations). And to “drop the use of dichotomies”, favouring instead continuous modeling of measurements.

And in the 6 December issue, Steven Goodman calls (in the World view tribune) for probability statements to be attached as confidence indices to scientific claims. That he takes great pain to distinguish from p-values and links with Bayesian analysis. (Bayesian analysis that Stephen regularly objects to.) While I applaud the call, I am quite pessimistic about the follow-up it will generate, the primary reply being that posterior probabilities can be manipulated as well as p-values. And that Bayesian probabilities are not “real” probabilities (dixit Don Fraser or Deborah Mayo).

Nature Outlook on AI

The 29 November 2018 issue of Nature had a series of papers on AIs (in its Outlook section). At the general public (awareness) level than in-depth machine-learning article. Including one on the forecasted consequences of ever-growing automation on jobs, quoting from a 2013 paper by Carl Frey and Michael Osborne [of probabilistic numerics fame!] that up to 47% of US jobs could become automated. The paper is inconclusive on how taxations could help in or deter from transfering jobs to other branches, although mentioning the cascading effect of taxing labour and subsidizing capital. Another article covers the progresses in digital government, with Estonia as a role model, including the risks of hacking (but not mentioning Russia’s state driven attacks). Differential privacy is discussed as a way to keep data “secure” (but not cryptography à la Louis Aslett!). With another surprising entry that COBOL is still in use in some administrative systems. Followed by a paper on the apparently limited impact of digital technologies on mental health, despite the advertising efforts of big tech companies being described as a “race to the bottom of the brain stem”! And another one on (overblown) public expectations on AIs, although the New York Time had an entry yesterday on people in Arizona attacking self-driving cars with stones and pipes… Plus a paper on the growing difficulties of saving online documents and culture for the future (although saving all tweets ever published does not sound like a major priority to me!).

Interesting (?) aside, the same issue contains a general public article on the use of AIs for peer reviews (of submitted papers). The claim being that “peer review by artificial intelligence (AI) is promising to improve the process, boost the quality of published papers — and save reviewers time.” A wee bit over-optimistic, I would say, as the developed AI’s are at best “that statistics and methods in manuscripts are sound”. For instance, producing “key concepts to summarize what the paper is about” is not particularly useful. A degree of innovation compared with the existing would be. Or an automated way to adapt the paper style to the strict and somewhat elusive Biometrika style!

Nature science image of the year

bootstrap in Nature

A news item in the latest issue of Nature I received about Brad Efron winning the “Nobel Prize of Statistics” this year. The bootstrap is certainly an invention worth the recognition, not to mention Efron’s contribution to empirical Bayes analysis,, even though I remain overall reserved about the very notion of a Nobel prize in any field… With an appropriate XXL quote, who called the bootstrap method the ‘best statistical pain reliever ever produced’!

spotlight on Xi’an!

preprints promote confusion and distorsion, and don’t blame journalists!

“…anyone considering publicizing a preprint have a responsibility.”

On my way to the airport, flying to B’ham, I read an older issue of Nature that contained this incredible editorial entry from Tom Sheldon Tim Horton, calling for regulation of preprints or worse, for the reason that journalists could misunderstand their contents and over-hype a minor or worse wrong claim. Taking as mistaken illustration the case of the Séralini et al. paper, about the Monsanto maize, which happened to be published under “embargo” conditions and reproduced in most media before a scientific storm erupted on the lack of significance of the samples. This call is unbelievably cheeky and downright absurd as it shifts the responsibility away from the journalists to the scientific community, throwing the “check your sources” principle of investigative journalism down the drain. As if the only reason for immediately publishing front-page discoveries is not to beat the competition and attract more readers…

The irony of seeing this piece in Nature is that a few pages later, there is a news entry on German and Swedish institutions breaking negotiations with Elsevier, as the publisher refuses to join a global package of open source publications. Nothing seems amiss about this nice aspect of scientific publishing with the author of this editorial, nor with the further reports of retraction of published paper in the same issue. Presumably because journalists have already moved to the next hot discovery by the time the retractions at last appear…! And to answer the final question of “Should all preprints be emblazoned with a warning aimed at journalists that work has not been peer reviewed?”, no, no, and no: preprints are not written for journalists or the general public. Unsurprisingly, the tribune induced outraged reactions from Nature readers.