Our second main contribution is to characterize the extent of identifiability of the causal model under our faithfulness assumption.

Privacy watchdogs in Europe are considering a complaint against Apple made by a former employee, Ashley Gjøvik, who alleges the company fired her after she raised a number of concerns, internally and publicly, including over the safety of the workplace. Gjøvik, a former senior engineering program manager at Apple, was fired from the company last September after she had also raised concerns about her employer's approach towards staff privacy, some of which were covered by the Verge in a report in August 2021. At the time, Gjøvik had been placed on administrative leave by Apple after raising concerns about sexism in the workplace, and a hostile and unsafe working environment which it had said it was investigating. She subsequently filed complaints against Apple with the US National Labor Relations Board. Those earlier complaints link to the privacy complaint she's sent to international oversight bodies now because Gjøvik says she wants scrutiny of Apple's privacy practices after it formally told the US government its reasons for firing her -- and "felt comfortable admitting they'd fire employees for protesting invasions of privacy", as she puts it -- accusing Apple of using her concerns over its approach to staff privacy as a pretext to terminate her for reporting wider safety concerns and organizing with other employees about labor concerns. A spokesperson for the ICO told TechCrunch: "We are aware of this matter and we will assess the information provided."

Temperatures in the Arctic have been rising so fast in recent decades they have confused a computer designed to measure them. Scientists monitoring a site in Alaska have found that an algorithm at the weather station, which has been recording temperatures for nearly 100 years, deleted all of its data from 2017, and even some from 2016. In what the experts are now calling an'ironic exclamation point' to rapid climate change, the algorithm flagged the abnormal temperatures observed at the station, as it assumed they were too high to be accurate. When scientists set out at the beginning of December to review the previous month's climate data, they noticed something'odd': everything from Utqiaġvik, Alaska was missing. The data from 2017 and some of 2016 had been flagged as artificial.

This is the first, non-technical, part of this series. See the second part for more detail. I was recently looking for a good machine learning task to try out, and I thought that doing something NFL-related would be interesting, because the NFL season is about to start (finally!). Why was I looking for a good machine learning task to try out? I have mostly done my data analysis work in R, but recently, I have been moving over to Python.