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Artificial Intelligence Has Race, Gender Biases (axios.com)
An anonymous reader shares a report: The ACLU has begun to worry that artificial intelligence is discriminatory based on race, gender and age. So it teamed up with computer science researchers to launch a program to promote applications of AI that protect rights and lead to equitable outcomes. MIT Technology Review reports that the initiative is the latest to illustrate general concern that the increasing reliance on algorithms to make decisions in the areas of hiring, criminal justice, and financial services will reinforce racial and gender biases. A computer program used by jurisdictions to help with paroling prisoners that ProPublica found would go easy on white offenders while being unduly harsh to black ones.
AI, like humans, makes mistakes like "correlation = causation".
AI doesn't care about "correlation == causation". It only cares about "correlation == correlation". Humans may infer causation, but that's not the fault of AI.
He's getting rather old, but he's a good mouse.
What are they calling "bias"? We read constantly about so-called racism based merely on the fact that one race objectively exhibits a particular trait over other races. That's called data, not bias.
It's a tricky question. Just because something is data, does not mean that it isn't biased: data can be biased-- in fact, 90% of what we do in experimental science is understanding the bias in data and figuring out how to get an unbiased measurement out of a biased data set. Almost all data is biased one way or another.
If, for example, white people caught shoplifting are usually given a warning and let off while black people caught shoplifting are arrested and prosecuted ("shopping while black"), the data will show a higher rate of shoplifting among blacks. You will need to go to the raw data to see the actuality. See: https://www.theguardian.com/la...
An AI with no correction for bias will reflect the bias of society.
The article linked is merely a summery of the propublica article, which is has more detail, here: https://www.propublica.org/art...
The problem is not that the data set reflects the reality. The problem is not that the AI makes mistakes, but that the particular mistakes the AI makes reflect the bias of the society that programmed it.
The link in the summary is to an article which is itself a summary. From the original (here: Machine Bias There’s software used across the country to predict future criminals. And it’s biased against blacks.), the software attempted to predict the probability of future offenses of criminals on probation. It did not, of course, always get it right. But when the actual percentage of re-offenses was compared to the predictions, the AI got it wrong differently for blacks than for whites. Here's what the article said.
We also turned up significant racial disparities, just as Holder feared. In forecasting who would re-offend, the algorithm made mistakes with black and white defendants at roughly the same rate but in very different ways.
The formula was particularly likely to falsely flag black defendants as future criminals, wrongly labeling them this way at almost twice the rate as white defendants. White defendants were mislabeled as low risk more often than black defendants.
90% of murdered blacks were killed by blacks, whilst 83% of murdered whites were killed by whites. And 57% of all murders were commited by blacks. Was it 99%? no - but it wasn't far off from 90%, the real statistic...
Browsing at +1 - no ACs, I ignore their posts. So refreshing!
Not necessarily....black people DO commit a large proportion of violent crimes than other races in the US, per capita.
They are only about 13-15% of the population, but commit vastly more violent crimes in the US.
Skip to about 1:09 on the video to get to the meat of the presentation.
Light travels faster than sound. This is why some people appear bright until you hear them speak.........
"Further, the fact that more people of a particular race are prosecuted is not a reflection of bias in the data, rather a bias in the prosecution."
In this case, "persecuted" was more accurate.
Data is Data. It cannot exhibit a bias.
I can only surmise that you're not an experimental scientist. Data has bias all the time.
In physics (my field) the bias usually has no social consequence-- astronomical statistics, for example, are biased toward bright stars (since they're much easier to see than faint ones, and hence overrepresented in the data set). In social "sciences," however, the bias very often does have social consequences. SAT scores from children whose parents spend tens of thousands of dollars on SAT Prep courses, for example-- surprise!-- score better on SAT exams than ones who don't. The data shows a correlation of SAT score with parental income. Is this real? Better correct for the SAT-prep course effect before making a conclusion.
Data is biased. All the time. Be ready for it.
...Plus, being from the Guardian, I am skeptical that they didn't twist the data some to obtain their desired outcome, which ironically touches on the subject of this story.
Huh? MIT Tecnology Review and Propublica were the source. The link in the summary was this: https://www.axios.com/algorith... which linked here: https://www.propublica.org/art... and here MIT Technology Review
No he's making a very simple argument.
You have two sets of populations. Say, hypothetically, the exact same percentage of each set carries contraband around, Members of one set are stopped and frisked with no probable cause more often than the other. That set will have a higher rate of arrest for that contraband not because they are more likely to have it, but because they are more likely to be searched.