Sentences with phrase «bad use of data»

«We're not going to be able to go out and find every single bad use of data, but what we can do is make it a lot harder for folks to do that going forward,» he said.

On whether Facebook can audit all app developers: «We're not going to be able to go out and necessarily find every bad use of data,» Zuckerberg said, but confidently said, «I actually do think we're going to be able to cover a large amount of that activity.»

Not exact matches

As The Verge wrote of the bot's downfall: «It's a joke, obviously, but there are serious questions to answer, like, how are we going to teach AI using public data without incorporating the worst traits of humanity?»

The incapacitating of communications and data retrieval at Hollywood Presbyterian Hospital was accomplished using a game - changing innovation for bad purposes.

Facebook is facing its worst privacy scandal in years following allegations that Cambridge Analytica, a Trump - affiliated data mining firm, used ill - gotten data from millions of users through an app to try to influence elections.

Cyber enemies could use a range of new battlefield tactics to try to cripple financial markets, from destroying the course of banking and trade settlement transactions to using poison pill algorithms to flood markets with bad data and fake trades in order to drive trading volatility and market collapse.

The key is to find stocks that are currently mispriced (good or bad) and value has been a phenomenal way of doing so (using only «backward» data at that)

I am quite leary about the institute's agenda as one of the researchers is none other than Mark Regnerus, who admits to using bad data to support his theory that gay parents and marriage is bad for kids.

And this inflammatory use of a «relative percentage risk» rather than relative risk or absolute risk... for example, even if assuming the writer's awkward data is valid, you can to look at infant living rates and see 99.6 % vs 98.4 %, which means there's only a 1.2 % higher risk of bad outcome from at - home birth than hospital.

All sorts of hilarious errors — using one type of data (ICD10 code data from «white healthy women» and essentially comparing the best possible data from one set of hospital data related to low - risk births to the worst possible single set of data related to high - risk at - home births)-- if you use the writer's same data source for hospital births but include all comers in 2007 - 2010 (not just low - risk healthy white women), the infant death rate is actually 6.14 per 1000, which is «300 % higher death rate than at - home births!»

But you do like to use bad data all the time and if NY has an average utility bill of $ 75 that's really sort of meaningless.

Using simple statistics, without data about published research, Ioannidis argued that the results of large, randomized clinical trials — the gold standard of human research — were likely to be wrong 15 percent of the time and smaller, less rigorous studies are likely to fare even worse.

Here's the notice for «Characterization of Hydroxymethylation Patterns in the Promoter of b - globin Clusters in Murine Fetal Livers»: Continue reading Use of data «without permission,» bad authors list, and hidden funding sink mol bio paper

Researchers examined federal government data to assess rates of awareness, screening and the use of cholesterol - lowering statins among adults aged 20 and older with extremely high levels of «bad» LDL cholesterol.

The Environmental Working Group has compiled an excellent data base where you can personally look up the products you use and the level of toxicity is graded on a scale of 1 - 10 (10 being the worst).

But rest assured that it's happening: ask any of your friends or coworkers who use the app and they can regale you with stories about their Tinder dates, both good and bad, and Tinder's Twitter account even claims that the app is leading to a «sh*t ton» of marriages (although hard data is thin on the ground here).

In some areas, I propose using data from multiple years, and I also mix up the type of measure depending on what I thought was the worst side - effect to avoid.

If three years of data is used there is about a 25 percent change that a teacher who is «average» would be identified as significantly worse than average, and, under new evaluation systems, perhaps fired.

The U.S. is off to a bad start when it comes to using data to improve schools, concludes a National Education Policy Center October 2013 report entitled Data Driven Improvement and Accountability by Andy Hargreaves and Henry Braun of Boston Colldata to improve schools, concludes a National Education Policy Center October 2013 report entitled Data Driven Improvement and Accountability by Andy Hargreaves and Henry Braun of Boston CollData Driven Improvement and Accountability by Andy Hargreaves and Henry Braun of Boston College.

When I talk about the use of data in education (and specifically school accountability) I tend to get one of two reactions — it's seen as either a pet project, at best peripheral to, and at worst a distraction from, school improvement strategies; or that I'm a cog in an (evil) technocratic takeover of public education.

This study reiterates what others have found before it: teacher effectiveness, which can be partly evaluated using test score data, has the power to affect the futures of innumerable students, for better or worse.

The evaluation system pushed by the zealots is bad for teachers, but it's even worse for children: their days will become nothing but an endless round of mindless testing just to generate «data» that can be used in «assessments.»

It's a tool used by a lot of hackers and bad actors to steal data or passwords, so that sort of limits the functionality of this website.

I have a Z10 and it's an awesome phone minus paying android / iOS rates for data in a developing country this is a bad recipe due to getting similar features on cheap android phones, another mistake BlackBerry has made is taking too long to release the Q5, a lot of the 3 million blackberry subscribers in this market use the cheap 8520 curve and if the Q5 Is not released in time for their 24 month contract renewal android will be the logical choice for the non BlackBerry loyalist.

Using more than 80 years of securities data, Fama and French investigated each removal (delisting) from the data set and determined whether it was as a result of either a «Good Delist» or a «Bad Delist».

The key is to find stocks that are currently mispriced (good or bad) and value has been a phenomenal way of doing so (using only «backward» data at that)

Like many using these false advertisements, its website omits a phone number and physical address — a bad sign, since that means you will have to provide your personal data before even speaking with a member of its organization.

Now that Morningstar is tracking such data, investors bad behavior is finally quantified, as well the advantages of using a passive advisor who helps reduce investor error.

Robert Shiller's website contains US stock market data from 1871 to the present day, a 147 - year history which I have used to calculate the average, worst - case and best - case scenarios for investments of varying length.

Just last year, in a letter to California Assembly Member Katcho Achadjian, Chair of the Committee on Local Government, opposing AB - 2343, Longcore argued (using L.A.A.S. data through 2012) that «policies put in place after the Hayden Act [1999] have resulted in an increase in the percentage of cats taken in to shelters that are deemed to be feral, suggesting that the stray / feral cat problem has become worse» (emphasis mine).

We have been criticised for not publishing an updated Polar Urals chronology using the updated data (and accused of worse here).

According to a study commissioned by Canada's National Energy Board and based on 20 years of Beaufort Sea data, three of the most widely - used oil spill containment methods — burning spilled oil in - situ, deploying booms and skimmers, and aerial application of dispersants — would be impossible due to bad weather or sea ice 20 - 84 percent of the brief, June - to - November open - water season.

This is really bad news because it seems to suggest that our data of the 19th century has not got enough precision to be used in climate studies.

McIntyre doesn't just use bad (or out of context) data, he also * manufactures his own * if bad data aren't readily available:

Their thought is that if you have a huge pile of data, some of which is good, some bad, and some ugly, you should just use the good data rather than busting your head figuring out how to deal with the bad and the ugly.

Worse, the sets of pre-processed model data that he provided for use in the two related studies, while both apparently deriving from the same set of model simulation runs, were very different.

Surely the biggest problem is going to be the cascading effect of bad data being used by one paper, then that paper being referenced by many others?

This version of the spreadsheet does that and more: it also ignores 1950 - 1990 on the ground that the data being used to estimate SAW has been too badly corrupted by human activities in general (as opposed to CO2 alone) to be trusted.

My support was to use satellite based geodesy methods to obtain the same information in spite of cloudy bad weather conditions which limited optical data quantity and quality.

Yet despite these data, story after story continues to peddle the claim that the weather is getting more extreme, using whatever recent string of bad weather as the hook.

Can this be even started when the «hockey stick» is so blatantly used (by the IPCC and others) to provoke political / policy changes based on bad science and bad processing of that data?

Using this kind of data in the calculation of the warming indicator makes the indicator worse, i.e. more noisy and less accurate over short or medium long periods.

He completely screwed the application, failed to meet any of the requirements and used bad data.

Worse, they portray the data from approximately 70 glaciers (ie, the total number of glaciers used excluding those from the Alps) as though it were the full 169 glaciers considered.

Multiple sources, using the all of the data available, rightly show the long term trend is far worse than your dissembling, cherry - picked case.

An example of bad practice, widely used by the IPCC, is the misleading comparison of data obtained using one method with data obtained by a different method.

It is a characteristic signature of using uncorrelated random data (or really really bad temperature proxies).

Now, Stephen Briggs from the European Space Agency's Directorate of Earth Observation says that sea surface temperature data is the worst indicator of global climate that can be used, describing it as «lousy».

But worse is your paper with Nic Lewis, which seems to go out of its way to get a low ECS by purposely not using the best data available for surface temperatures, ocean heat content, and with no consideration of aerosols at all.

Maybe if the AGW proponents stopped calling those skeptical of their hypotheses «deniers», and did something about the continued tenure of those who engaged in unscientific practises such as data bending, opaque statistical massaging and weighting, email deletion, undermining the peer review process and subverting journal editor's independence, then the big bad nasty «deniers» might stop using the «Alarmist» tag and highlighting climategate.