I would think you should admire her for taking a strong moral stand at the expense of the business. She added a number of grievance-oriented features to reduce "bigotry", "xenophobia", etc; thereby making the product less able to render reality; thereby hurting its value proposition; thereby losing users; thereby cratering the share price.
Criminality is congenital. Social interventions will not fix the kid. Neither for that matter will prison, but at least it will protect the rest of us from his increasingly violent depredations.
High frequency trading (measuring latency, inferring event ordering, etc). Since most crypto derivatives trading takes place at ap-northeast-1, it feels like AWS is orienting this release towards financial markets customers.
Sorry, is your criticism that IQ proponents conflate point estimates with unknown population parameters? Is that what other IQ critics see as the core of the disagreement in this debate?
But these controls could be done for any IQ-related study. Is IQ-skepticism based on the belief that IQ researchers generally don't use controls? That lead-IQ researchers alone do this?
Question for any IQ skeptics here (e.g. "it just measures your ability to take tests" or "it just tells you how rich your parents are"): what's your response to studies like this? Is there anything that can be said about the effect of lead on cognitive function? Why might IQ be a good measure of lead-induced stupidification, but unreliable for literally anything else?
* average 1% asset management fee (modal number if you poke around)
* 0% investment carry (hedge funds get away with charging this, but most asset managers don't)
* 9% effective tax rate (revenues disproportionately go to high earners)
gets you $1.8B lost tax revenues. The 0% carry assumption is very conservative, so the $1.8B is a lower bound. Even so, CA and NY collect about $400B annually. As a first order thing, this doesn't move the needle very much.
> The United States seeks fair consideration and back pay for asylees and refugees who were deterred or denied employment at SpaceX due to the alleged discrimination.
Does anybody know how such penalties are calculated? In "role-based damages," penalties would be limited to the total wages for the hiring reqs in question. This corresponds to the counterfactual where each of the roles would have been gone to an asylee. But I could also see the DOJ arguing that every "deterred" asylee is owed foregone wages. This "applicant-based damages" doesn't correspond to any serious counterfactual, but it has the virtue of being a much bigger number.
Because models are trained and validated on real data. Given a training set of crimes and corresponding surveillance footage, arrestee info is a (not noisy) label for “who is the guy in the movie.”
With a moment's thought, even the most emotive amongst us should see that the mugshots will be part of the training set--the photographed individuals are, after all, the class of true positives.
This doesn't rescue their claim. If the suggested class imbalance really exists in the training/test sets, the model will preferentially identify whites as criminals.
Are black faces overrepresented or underrepresented? According to AI researchers, we're faced with Schrodinger's Mugshot--there's simultaneously too many and too few!
> "We believe this results from factors that include the lack of Black faces in the algorithms' training data sets..." the researchers wrote in an op-ed for Scientific American.
> The research also demonstrated that Black people are overrepresented in databases of mugshots.
The sort of clear-headed thinking that makes the AI bias field as respected as it is.