Archive for Florence Nightingale

Amy in Randomland [book review]

Posted in Statistics with tags , , , , , , , , , , , , on August 15, 2022 by xi'an

Amy’s Luck is a short book by David Hand that I recently received for review in CHANCE. David, whom I have known for quite a while now, is professor at Imperial College London. This is not his first book, by far! But this may be the most unusual one, if not the shortest. Written as a pastiche of Alice’s Adventures in Wonderland, it tells of the adventures of a young girl named Amy in the pursuit of luck or at least of its meaning. It has about the same number of chapters as Carroll’s book and could easily be read on a leisurely boat trip from Oxford to Godstow. While non-sensical and playing on the imprecision of the English language, its probabilist is both correct and rational. References to the original Alice abound and I presumably missed a fair portion of them, having read Alice (in French) decades ago. The book also contains illustrations from the author, gathered into a charm bracelet printed on the cover and a most helpful appendix where David points out the real world stories behind those of Amy, which is also full of gems, like Kolmogorov being a train conductor in his youth. (Missing an addition about Galton’s quincunx, esp. when his cousin Darwin is more than mentioned.) Or Asimov creating the milihelen to measure how much beauty was required to launch a ship. Overall, it is quite charming and definitely enjoyable, if presumably not accessible by the same audience as Alice‘s. And unlikely to take over Alice‘s! But from “She could understand the idea that coins had heads”, to a Nightingale rose renamed after Miss Starling, to the permutation of Brown, Stein, and Bachelier into Braun, Stone, and a bachelor, David must have had fun writing it. As others will while reading it and trying to separate probabilistic sense from non-sense.

[Disclaimer about potential self-plagiarism: this post or an edited version will eventually appear in my Book Review section in CHANCE.]

Sousaphonic graph!

Posted in Books, pictures, Statistics with tags , , , , , , , , , , on January 17, 2022 by xi'an

Florence Nightingale Bicentennial Fellowship and Tutor in Statistics and Probability in Oxford [call]

Posted in Statistics, Travel, University life with tags , , , , , on July 29, 2019 by xi'an

Reposted: The Department of Statistics is recruiting a Florence Nightingale Bicentennial Fellowship and Tutor in Statistics and Probability with effect from October 2019 or as soon as possible thereafter. The post holder will join the dynamic and collaborative Department of Statistics. The Department carries out world-leading research in applied statistics fields including statistical and population genetics and bioinformatics, as well as core theoretical statistics, computational statistics, machine learning and probability. This is an exciting time for the Department, which relocated to new premises on St Giles’ in the heart of the University of Oxford in 2015. Our newly-renovated building provides state-of-the-art teaching facilities and modern space to facilitate collaboration and integration, creating a highly visible centre for Statistics in Oxford. The successful candidate will hold a doctorate in the field of Statistics, Mathematics or a related subject. They will be an outstanding individual who has the potential to become a leader in their field. The post holder will have the skills and enthusiasm to teach at undergraduate and graduate level, within the Department of Statistics, and to supervise student projects. They will carry out and publish original research within their area of specialisation. We particularly encourage candidates working in areas that link with existing research groups in the department to apply. The deadline for application is September 30, 2019.

If you would like to discuss this post and find out more about joining the academic community in Oxford, please contact Professor Judith Rousseau or Professor Yee Whye Teh. All enquiries will be treated in strict confidence and will not form part of the selection decision.

Florence Nightingale´s 199th anniversary

Posted in Statistics with tags , , , , , , , on May 12, 2019 by xi'an

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.

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