Archive for Facebook

Hong Kong under CPC iron fist

Posted in Kids, Travel with tags , , , , , , , on July 14, 2020 by xi'an

“Students in Hong Kong are now banned from any political activity in schools including singing, posting slogans and boycotting classes, the territory’s education minister has said.” BBC, 8 July

“Books by prominent Hong Kong pro-democracy figures have become unavailable in the Chinese-ruled city’s public libraries as they are being reviewed to see whether they violate a new national security law, a government department said.” ABC, 6 July

“Lawyers and legal experts have said China’s national security law for Hong Kong will fundamentally change the territory’s legal system. It introduces new crimes with severe penalties – up to life in prison – and allows mainland security personnel to legally operate in Hong Kong with impunity. The legislation gives Beijing extensive powers it has never had before to shape life in the territory far beyond the legal system.” BBC, 1 July

“Based on the [new] law, the Hong Kong authorities can dictate the way people around the world talk about the city’s contested politics. A Facebook employee could potentially be arrested in Hong Kong if the company failed to hand over user data on someone based in the United States whom Chinese authorities deemed a threat to national security.” NYT, 7 July

Prairie chair

Posted in pictures, Statistics, University life with tags , , , , , , , , , , , on October 2, 2019 by xi'an

Today is the launching day of PRAIRIE, one of the four Instituts Interdisciplinaires d’Intelligence Artificielle (3IA) supported by the French government. Taking place in Paris Dauphine, with Yann Le Cun as guest speaker. I have been fortunate to be endowed with one of these chairs for the coming years, along with my CEREMADE colleagues Laurent Cohen and Irène Waldspurger.

AIQ [book review]

Posted in Books, Statistics with tags , , , , , , , , , , , , , , , , , , on January 11, 2019 by xi'an

AIQ was my Christmas day read, which I mostly read while the rest of the household was still sleeping. The book, written by two Bayesians, Nick Polson and James Scott, was published before the ISBA meeting last year, but I only bought it on my last trip to Warwick [as a Xmas present]. This is a pleasant book to read, especially while drinking tea by the fire!, well-written and full of facts and anecdotes I did not know or had forgotten (more below). Intended for a general audience, it is also quite light, from a technical side, rather obviously, but also from a philosophical side. While strongly positivist about the potential of AIs for the general good, it cannot be seen as an antidote to the doomlike Superintelligence by Nick Bostrom or the more factual Weapons of Maths Destruction by Cathy O’Neal. (Both commented on the ‘Og.)

Indeed, I find the book quite benevolent and maybe a wee bit too rosy in its assessment of AIs and the discussion on how Facebook and Russian intervention may have significantly to turn the White House Orange is missing [imho] the viral nature of the game, when endless loops of highly targeted posts can cut people from the most basic common sense. While the authors are “optimistic that, given the chance, people can be smart enough”, I do reflect on the sheer fact that the hoax that Hillary Clinton was involved in a child sex ring was ever considered seriously by people. To the point of someone shooting at the pizza restaurant. And I hence am much less optimistic at the ability for a large enough portion of the population, not even the majority, to keep a critical distance from the message carried by AI driven media. Similarly, while Nick and James point out (rather late in the book) that big data (meaning large data) is not necessarily good data for being unrepresentative at the population at large, they do not propose (in the book) highly convincing solutions to battle bias in existing and incoming AIs. Leading to a global worry that AIs may do well for a majority of the population and discriminate against a minority by the same reasoning. As described in Cathy O’Neal‘s book, and elsewhere, proprietary software does not even have to explain why it discriminates. More globally, the business school environment of the authors may have prevented them from stating a worry on the massive power grab by the AI-based companies, which genetically grow with little interest in democracy and states, as shown (again) by the recent election or their systematic fiscal optimisation. Or by the massive recourse to machine learning by Chinese authorities towards a social credit system grade for all citizens.

“La rage de vouloir conclure est une des manies les plus funestes et les plus stériles qui appartiennent à l’humanité. Chaque religion et chaque philosophie a prétendu avoir Dieu à elle, toiser l’infini et connaître la recette du bonheur.” Gustave Flaubert

I did not know about Henrietta Leavitt’s prediction rule for pulsating stars, behind Hubble’s discovery, which sounds like an astronomy dual to Rosalind Franklin’s DNA contribution. The use of Bayes’ rule for locating lost vessels is also found in The Theorem that would not die. Although I would have also mentioned its failure in locating Malaysia Airlines Flight 370. I had also never heard the great expression of “model rust. Nor the above quote from Flaubert. It seems I have recently spotted the story on how a 180⁰ switch in perspective on language understanding by machines brought the massive improvement that we witness today. But I cannot remember where. And I have also read about Newton missing the boat on the precision of the coinage accuracy (was it in Bryson’s book on the Royal Society?!), but with less neutral views on the role of Newton in the matter, as the Laplace of England would have benefited from keeping the lax measures of assessment.

Great to see friendly figures like Luke Bornn and Katherine Heller appearing in the pages. Luke for his work on the statistical analysis of basketball games, Katherine  for her work on predictive analytics in medicine. Reflecting on the missed opportunities represented by the accumulation of data on any patient throughout their life that is as grossly ignored nowadays as it was at Nightingale‘s time. The message of the chapter [on “The Lady with the Lamp”] may again be somewhat over-optimistic: while AI and health companies see clear incentives in developing more encompassing prediction and diagnostic techniques, this will only benefit patients who can afford the ensuing care. Which, given the state of health care systems in the most developed countries, is an decreasing proportion. Not to mention the less developed countries.

Overall, a nice read for the general public, de-dramatising the rise of the machines!, and mixing statistics and machine learning to explain the (human) intelligence behind the AIs. Nothing on the technical side, to be sure, but this was not the intention of the authors.

Der Kunst ihre Freiheit [and the scare of the nude]

Posted in Books, pictures, Travel with tags , , , , , , , , , , , , , on February 17, 2018 by xi'an

A poster campaign advertising for several exhibits of modernist painters in Vienna, including major paintings by Egon Schiele, has met with astonishing censoring from the transport companies posting these advertisements. (And by Facebook, which AIs are visibly too artificial and none too intelligent to [fail to] recognise well-known works of art.) Not very surprising, given the well-known conservatism of advertising units in transportation companies, but nonetheless appalling, especially when putting these posters against the truly indecent ones advertising for, e.g., gas guzzling machines and junk food.

major confUSion

Posted in Books, pictures, Statistics with tags , , , , , , , , on November 19, 2016 by xi'an

crossing the Seine in RER C near Maison de la Radio, Nov. 09, 2012In a recent evening talk-show on France Inter, the French national public radio, the debate was about the [bad] surprise election of the donald and the fact that the media had missed the result, (self-)blaming a disconnection with the “real” country. One of the discussants, Julia Cagé, Professor of Economics at Science Po’, started the discussion with the amazing confusion [at 5’55”] between the probability that Hillary Clinton would win [evaluated at 84% on the last day] and the percentage of votes in her favour [which was around that figure in Manhattan]…

On a related if minor theme, my post on Flaxman et al.’s early [if preliminary] analysis of the said election got so many views that it became the most popular post for 2016! (If not competing with Ross Ihaka’s call to simply start over with R!)

And yet another related entry today in Libération, blaming the disastrous result partly on the social media and their algorithms (again!) that favour items of information (or dis-information) from the same perspective and do not rank those items by their reliability… The author of the tribune is an econometrician at Essec, but there is no methodological content in this ideological entry that seems to call for a super-monitor which would impose (how?) diversity and (which?) ranking on social media. A post-truth era, for sure! Shifting the blame from the deplorable voters themselves to anything else…