Archive for RSS

ten recommendations from the RSS

Posted in Statistics, University life with tags , , , , , , , , , , , on March 21, 2021 by xi'an

‘Statistics have been crucial both to our understanding of the pandemic and to our efforts to fight it. While we hope we won’t see another pandemic on this scale, we need to see a culture change now – with more transparency around data and evidence, stronger mechanisms to challenge the misuse of statistics, and leaders with statistical skills.’

  • Invest in public health data – which should be regarded as critical national infrastructure and a full review of health data should be conducted
  • Publish evidence – all evidence considered by governments and their advisers must be published in a timely and accessible manner
  • Be clear and open about data – government should invest in a central portal, from which the different sources of official data, analysis protocols and up-to-date results can be found
  • Challenge the misuse of statistics – the Office for Statistics Regulation should have its funding augmented so it can better hold the government to account
  • The media needs to step up its responsibilities – government should support media institutions that invest in specialist scientific and medical reporting
  • Build decision makers’ statistical skills – politicians and senior officials should seek out statistical training
  • Build an effective infectious disease surveillance system to monitor the spread of disease – the government should ensure that a real-time surveillance system is ready for future pandemics
  • Increase scrutiny and openness for new diagnostic tests – similar steps to those adopted for vaccine and pharmaceutical evaluation should be followed for diagnostic tests
  • Health data is incomplete without social care data – improving social care data should be a central part of any review of UK health data
  • Evaluation should be put at the heart of policy – efficient evaluations or experiments should be incorporated into any intervention from the start.

congrats, Pierre!!!

Posted in Statistics with tags , , , , , , , , , on March 3, 2021 by xi'an

Yikes! “AI can predict which criminals may break laws again better than humans”

Posted in Books, pictures, Statistics with tags , , , , , , , on February 28, 2020 by xi'an

Science (the journal!) has this heading on its RSS feed page, which makes me wonder if they have been paying any attention to the well-documented issues with AI driven “justice”.

“…some research has given reason to doubt that algorithms are any better at predicting arrests than humans are.”

Among other issues, the study compared volunteers with COMPAS‘ or LSI-R predictive abilities for predicting violent crime behaviour, based on the same covariates. Volunteers, not experts! And the algorithms are only correct 80% of the time which is a terrible perfomance when someone’s time in jail depends on it!

“Since neither humans nor algorithms show amazing accuracy at predicting whether someone will commit a crime two years down the line, “should we be using [those forecasts] as a metric to determine whether somebody goes free?” Farid says. “My argument is no.””

we have never been unable to develop a reliable predictive model

Posted in Statistics with tags , , , , , , , , , , , , , , , on November 10, 2019 by xi'an

An alarming entry in The Guardian about the huge proportion of councils in the UK using machine-learning software to allocate benefits, detect child abuse or claim fraud. And relying blindly on the outcome of such software, despite their well-documented lack of reliability, uncertainty assessments, and warnings. Blindly in the sense that the impact of their (implemented) decision was not even reviewed, even though a portion of the councils does not consider renewing the contracts. With the appalling statement of the CEO of one software company reported in the title. Blaming further the lack of accessibility [for their company] of the data used by the councils for the impossibility [for the company] of providing risk factors and identifying bias, in an unbelievable newspeak inversion… As pointed out by David Spiegelhalter in the article, the openness should go the other way, namely that the algorithms behind the suggestions (read decisions) should be available to understand why these decisions were made. (A whole series of Guardian articles relate to this as well, under the heading “Automating poverty”.)

bootstrap in Nature

Posted in Statistics with tags , , , , , , , , , , on December 29, 2018 by xi'an

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’!