to support the trail of young men fighting for their country while knowing each day could be their last. i've got to stand own battles on a judge. oh, i can, but i'll and oh, how about the story fair on the reports of the 4 people crushed to death, the cobbles airport, as afghans desperately trying to leave the country the uses. it's mathematically impossible to evacuate thousands of africans by the august 31 deadline. fed by us president joe biden. most d u countries have agreed to take an a small number of afghans flo not cobble european commission president to live on the line. visited a spanish military airport being used as a temporary transit point for the evacuees, shinta guns,

fish. that's legal. it is very important that we offer legal options to those who have to flee afghanistan because of their convictions because they have worked for us because they are women's rights activists. or because they a journalist, we must now offer them safe ways to leave the country and be accepted on the list. millions of people in the us to be more to prepare for affairs, winds and heavy rain as hurricane henry heads to the east coast. the national hurricane santa says it could bring life threatening storm searches and flooding the storms. expected to make land full and long island, new york or southern new england. on sunday, a we calling from haiti is devastating earthquake. survivors are facing severe shortages of age and shelter. the government is facing growing criticism of its response to the disaster onto their visited a makeshift camp and found a pool and conditions. at least 41 palestinians, including children, have been injured self to the israeli army, find

a protest is demonstrating near the gulf border. the protest as were reportedly hurting fire bombs from behind. the strips for defense and israeli soldier was also injured. these really army says it's launched as strikes against 4 hamas positions in garza, in response to the protests. israel's defense minister has said his country will not accept any violations at the board offense. thousands of parents and teachers in peru have rallied for their government to real schools. most children have not been in classes mall 12 to you. that's when the government closed the legislation facilities due to the pandemic. local official, the new year saying armed group is killed, 17 people, and wounded 5 others. the group attacked the village near tilbury, north of north west, rather of the capital nail. no official say it happened on friday night. it was the headlines i'll have another day for you here on al jazeera, after all, hale the algorithm a reason

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trust is fundamental to all our relationships, not just with our family and friends. we trust banks without money. we trust doctors without really personal information. but what happens to trust in a world driven by algorithms as more and more decisions are made for us by these complex pieces of code? the question that comes up is inevitable. can we trust algorithms from google searches to gps navigation algorithms are everywhere. we don't really think too much about them, but increasingly, governance corporations and various institutions are using them to make decisions about who gets public services, who gets denied, how people are monitored and policed. how insurance is charged. i want to start

here in australia. we're an algorithm used by the government has resulted in more than 400000 people being in debt to the countries welfare system centrally. it's being called the robot scandal. back in 2016, a decision was made to fully automate key part of the welfare system. the part with the earnings of low income people compared with the amount of government money they received. the government says they do this to ensure the right amount of financial assistance as well. the data matching algorithm officially called the online compliance intervention had been in place since 2011. any discrepancies previously flagged by the system were investigated by government employee. first, with automation or human checks were renewed, the government had instituted an algorithm that essentially said, let's match 2 lots of data together and smashed them to and see if people have a day. so some of the math was just bad, just plain wrong,

like it was spreadsheet. so imagine to sell together in the self do a job. ashley wolf is a journalist who has been reporting on the road. good debt story since it broke. she's also an activist, one of the chief organizes of the not my debt ross routes campaign. often people didn't realize that this was automated in the 1st place. and it wasn't always started getting people talking to get social media on twitter that we realized. actually the governors town, it was almost like 100000 people have been gas slotted into thinking they've done the wrong thing. that it was their fault and are outraged when they realized that there was a fault in the actual algorithm in the current. the israeli government disagree we are doing more compliant checks because we want to be more price if we are covering greatest examples and we are recruiting money for the tax. more checks is a bit of an understatement. the old system resulted in around $20000.00 discrepancy

notice of the year. but in the early days of the new automated system that jumped 220008 week. more than a 1000000 letters had been sent out by the algorithm. sometimes disputing government payments from as far back as seventy's. and what was even worse was the systems were imposed on paper with intellectual disabilities, with homelessness, with chronic health issues. people who know fairly literature will not literate at all. people who didn't know how to use a computer, people who living in remote communities with that access to internet, people who just had no bloody clue how to deal with this sort of administrative, bureaucratic bumble, david digna, was notified. he incorrectly declared even come from a teaching job while he was on a disability pension back in 2011. ready his brother, debt. ready ready $4088.00 in the us and what robert, he is going and he's ation towards you that you've done that change. you've done

the wrong thing. i know i hadn't, i wanted details of how they go out of my day and i was told i couldn't had that. and the reason i was told was that the computer looked at my personal information and then thought a piece of information, lia, another patient here. and i'm a patient of the to me and they can provide all right, timmy, that comes in jimmy pike. and we can bring back, in other words, the algorithm is crucible. it's totally unknowable. even the staff don't really understand it. rather than can you tell me how much evidence or how much notification provide you. proving that there was a good many provide me with anything other than this. and the other thing that i have is finally a text message came through to say, hi the money you are doing today. the fact that you couldn't get any concrete evidence about this is how we have calculated your debt. here is what you

here are the hours you work that really i found it. sure. any confidence that i had in the government will do the right thing. the fact that they couldn't prove to me that i owe the money really concerned me. i didn't find that you received a letter in the mail that generated by an i that essentially says why the government wants to let you know that we underpaid you by $5000.00 or that you should have been eligible for these services. but we didn't tell you therefore were telling you now and we come back pay. nobody gets back paid. in fact, you're only eligible for like back pay as i think it's 6 weeks with government services that the government convertible debt you back for many, many automation, computerization algorithm association. if that's even a word they're always sold to us as such a positive thing. all of side, no downside. as israel used department of human services put it computerized

decision making can reduce red tape, ensure decisions are consistent and create greater efficiencies for recipients and the department. the problem is how the challenges system that has no face, no name, and nobody signed spot him if your letter say, you know, i'm in charge of this good afternoon. welcome to the department of human services centrally on a good day. it end up sitting on hold for a couple of hours trying to speak to a human. the real question is, how has it come about that the government has overpaid people by billions. because really the criminal weiss is occurring at the end of the governance line. it's the government that's doing this. otherwise you're saying a 100000 citizens had made mistakes. well, if that's the case, then the system is too difficult for people to negotiate. so i'm not here shaking my fist at technology, it's not digital phone, it's not

a computers fault. this system has been designed quite explicitly by government governments responsible for its failures and governments really responsible for the hell they're putting all sorts of welfare recipients through unfairly, by assuming them fullstep. this is something i heard from virtually everyone i spoke to that day. they said, we're not against technology, it's not like algorithms are all bad. it's the people and the institutions designing these codes, we can't seem to trust. and this really gets to the heart of our relationship with algorithms. they're often complex, hidden behind walls of secrecy, with no way for those whose lives are actually impacted by them to produce them because they've been kept off limits. busy despite all the criticism and even a form of inquiry, the sterling government stand by its algorithm and automation in the welfare system . we do re past compliance to be applied to the last 6 months align with

recruit. we've recovered the $300000000.00 to the tax free that prices. so the system is working and we will continue with that. there are at least 20 different laws in australia that explicitly enable algorithm to make decisions previously made by ministers or staff. we don't really know the full extent of how these are being applied, but there are places around the world whether use of algorithm or even more widespread. like here in the united states where algorithms are being used to make big decisions across everything from the criminal justice system. health education and in the united states has a longer history of algorithm use than many other countries. silicon valley is a big reason for that, of course, but also there's much lisa regulation here when how private companies and governments can collect and use data. but for those studying the effects of algorithms on american society, one thing is clear. often it's the poor,

marginalized who get the worst you i'm on my way now, troy in new york state to meet with virginia. you think she's already on everything to do with the automating inequality here. actually the title, one of her books, virginia says america's poor working class had long been subject to invasive surveillance and punitive policies. she writes about prison like poor houses of the 19th century. the bad conditions were brought to discourage undeserving poor from supposedly taking advantage of the system. what i see as being part of the digital poor house are things like automated decision making tools. statistical models that make risk predictions about how people are going to behave in the future or algorithms that match people 2 resources. and the reason i think of them as a digital poorhouse is because that the decision that we made an 820 to build

actual poor houses was a decision of that public service systems should. first and foremost, be moral thermometers that they should act to decide who is most deserving of receiving their basic human rights. the genius studies into the automation of public services in the united states points to developments in the late sixties and seventies. along with the civil rights movement came a push for welfare rights. people are forced to live in the most in human situations because of that poverty, african americans, and unmarried women who are previously borrowed from receiving public funds could now demand state support when they needed it. while technology was touted as a way to distribute financial aid more efficiently, it almost immediately began to serve as a tool to limit the number of people getting support. so you have this moment in history where there's a recession and

a backlash against social spending and social movement. that's winning successes, that ends discriminatory treatment. and there really is no way to close the roles. they can't close the roles the ways that had in the past, which is just to discriminate against people. and that the moment we see these tools start to be integrated into public assistance. i think it's really important to understand that history. i think too often we think of these systems, it's just simple administrative upgrades sort of natural and inevitable. but in fact, their systems that make really important consequential political decisions for us. and they were from the beginning, supposed to solve political problems among them, the power and the solidarity of foreign working people. in the early 19 seventy's close to 50 percent of those living below the poverty line in the united states received some form of cash welfare from the government. today it's less than 10

percent in public assistance. the assumption of many folks who have not had direct experience with these systems is that they're set up to help you succeed. they are not in fact set up to help you succeed. and they're very complicated systems that are very diversionary that are needlessly complex. and that are incredibly stigmatizing and emotionally, very difficult. so it shouldn't then surprise us that a tool that makes that system faster and more efficient and more cost effective. further, that purpose of diverting people from the resources that they, that they need. having algorithms make decisions such as who gets financial aid money that the government has cause concern among many different groups. but what's holding a full on panic system is the fact that algorithms are being used to actually make predictions about people. one of the most controversial examples is the

correctional offender management profiling for tentative sanctions. it's a bit of a mouthful, but it's short form is compass and it's an algorithm that's been used in courtrooms across the country to assist judges during sentencing. now of course, algorithms can't weigh up, arguments, analyze evidence, or assess remorse. but what they are being used for is to produce something known as a risk assessment school to predict the likelihood of a defendant committing another crime in the future. disco is then used by judges to help them determine who should be released and who should be detained, pending trials. and now the judge has to consider a couple of factors here. there's public safety in flight risk on the one hand, but under the wheel cost, social and financial of detention on the defendant on their family and the other. now historically, what happens is the judge looks into this defendant eyes and tries to say, hey, you're high risk person, or you're a low risk person. i trust your, i don't trust you. now,

what elkins are helping us do is make those decisions better. the compass algorithm was brought in to offset balance out inconsistencies in human judgment. the assumption being of course, that a piece of code would always be less biased and less susceptible to prejudice. however compass is faced several criticisms, primarily accusations of racial bias, inaccuracy and lack of transparency. in 2016, a man named eric loomis, sentenced to 60 years in prison, took his case to the with sconces states supreme court. his allegation was that the use of compass violated his right to due process. it made it impossible for him to appeal his sentence. since the algorithm is a black box impenetrable, unquestionable eric limits didn't get very far. the supreme court ruled the use of compass unit sentencing was legal. the verdict, however, revealed the ways in which the ever increasing use of algorithms being normalized.

the court had a funny argument saying that like, nobody knows where the decisions are coming from. and so it's, it's okay, you know, it's not that the state has some particular advantage over the defendant, but that everyone is that this sort of equal playing field. it's not that there's an informational advantage for one side or the other. now, to me, i find that somewhat dissatisfying, i do think that in these high stakes decision, particular criminal justice system, we don't just want to have an equal playing field. no one knows. but i think we need to have the equal playing field of everybody. we need to have this transparency built into the system for the record equivalent, the company that sells companies software has defended its algorithm. it points to research commission that the company meets industry standards for fairness and accuracy where the compass so most of the privately developed algorithms meet acceptable standards for transparency. is another question. even when they are used in the provision of public services,

algorithms are often close to the public. they cannot be scrutinized. regardless of that, sharon says that in certain cases he would still be comfortable being judged by robust algorithm. so i do think it's true that many of the people in the criminal justice system are the most disadvantage. and the reality is they probably don't have a lot of say in their futures, in their faith and how these algorithms are going to evaluate them. whether this would happen, if more powerful people are being judged by these algorithms, i don't know. now, me personally, i would rather be judged by a well designed algorithm than a human in part because i believe the statistical methods for assessing risk in fact are better than than humans and may situations. and it can, at least when it's well designed, eliminate a lot of these biases that, that human decision makers often exhibit. the united states has

a massive racial discrimination problem and public services. that's real. so it is really understandable when agencies want to create tools that can help them keep an eye on frontline decision making in order to maybe identify discriminatory decision making and correct it. the problem is that that's not actually the point at which discriminant discrimination is entering the system. and this is one of my huge concerns about these kinds of systems as they tend to only understand discrimination as something that is the result of an individual who is making a rational decision. and they don't, the systems are not as good at identifying bias that is systemic and structural. the promise of algorithms is that we can mitigate. the bi sees that human decision makers always have, you know, we always have, we're, we're always responding to the way somebody look this way somebody acts. and even

if we try as hard as we can, and if we really have these good intentions of a try to just focus on what matters, i think is exceptionally difficult. now that again is the promise of algorithms. the reality is much more complicated. the reality is that allianz are trained on past human decisions, and they're built by fallible humans themselves. and so there's still this possibility that the bases creep in to the development and application of these algorithms. but certainly, the promise is that we can least make the situation better than it currently is. one of the things i'm really concerned about about these systems is that they seem to be part of a philosophy that increasingly sees human decision making as black box and unknowable and computer decision making as transparent and accountable. and that to me is really frightening because of course, computer decision making is not as objective and as not as unbiased as it seems. at

1st glance, we build bias into our technologies, just like we build them into our children, right? we teach our technologies to discriminate, but on the other hand, people's decision making is actually not that opaque. we can ask people about why they're making the decisions that are making, that can be part of their professional development. and i think this idea that human decision making is somehow unknowable is a sort of ethical abandonment of the possibility to grow and to change that we really, really need as a society to truly address the systemic routes of racism in classes and sexism in our society. so it feels to me like we're saying, we'll never understand why people make discriminatory decisions. so let's just let the computer make it. and i think that's a mistake. i think that's a tragic mistake. that will lead to

a lot of suffering for a lot of people. ready so going back to the question that started us on this journey, can we trust el group? well, the biggest thing outlet from speaking with asha virginia shirad and many is that i've actually got the question around. it isn't really so much about with that algorithm trustworthy. it's more about the quality of the data that feeds and the objectives of designing and controlling human biases, human intersections, that's what we see reflected now algorithm. and without that oversight, we which we think our prejudices and social inequality such algorithms our program to show that the future when it's well and by the path, that's often things the stigma and bias and stereotypes and rejection and

discrimination. and really what we need is to allow for new and different from the old. of course we can build better tool tools and i see them everywhere that i go. but what makes a difference about good tools about just tool is building those tools with a broader set of values from the very beginning. so not just efficiency, not just cost savings, but dignity and self determination and justice and fairness and accountability and mayor process. and all of those things that we really care about as a democracy have to be built in at the getting from step one in every single tool the, we're actually getting our hands on the data, we're analyzing the data. now one thing that we've done is we try to make as much

of that data available as possible. so to encourage people to look at death, one of our, one of our projects is called the stanford open policing project. we release lots of data and the criminal justice system, we release code for people to play with the data. and i encourage everyone to look at that and try to understand what's going on. and maybe they'll discover a pattern that easy. so my biggest pieces of die is to never underestimate your invoice. you know, you might be fighting some shane, some computer system that you've never been able to mate or say that has been flicked into huge, harmless suffering. but your words can make government scared. your voices combined can make senates and quotes sit up and pay attention together. we can shape the way these tools are created and the ways that they impact us as a political community. if we want better outcomes from the systems, we have to,

we have to claim our space as decision making decision makers at these tables. and we can't do that if we think that these technologies are somehow god's, they're built just just the way we build our kids. we build these technologies and we have a right to be in dialogue with them. i think of some of the biggest companies in the world today, all of them think tech with algorithms that they're called the move that we do to them. the more data we pritchard wearing them. it's a great race. the data and big companies around the empires are rising on a wealth of information and we need other commodity. in the 2nd 5 part series 90 re examined whether corporations are colonizing internet like me,

the popularity and power of the big tech on jazz. ah, ah ah, ah. hello, they were expecting some severe weather in north america in the coming days. in particular for north eastern areas of the u. s. am eastern parts of canada, and that's thanks to on re as it's to rent and moving north, upset, east coast. now we take a closer look. it's expected to make landfall in southern parts of new england. it will be the 1st hurricane to hit the area in 30 years, and we have had warnings out for new york for connecticut and massachusetts,

as it works its way inland. we've already seen coastal flooding. we are likely to see no more flooding as we are expecting $200.00 millimeters of rain to fall in areas and the damaging winds to kick in. now it isn't predictable storm but come mondays expected to swing out to the north east, taking the wet and windy weather with it to eastern parts of canada. now elsewhere, we are expecting some severe storms to roller, cross the canadian prairies and into the mid west, edging into the great lakes. by the time we get into monday for the west, it is looking fine and dryer. we are seeing wet weather though, for the florida panhandle, with the scattered storms and showers here, but much of the weather can be found in mexico as we move to central america. that western coast, getting a drenching from the remnants of hurricane great news on county. because the thought of our economy can be of the financial crisis that

the u. s. blogs. accent fans with the billions of $1.00 and $7000000000.00 lawsuit against the mining giant behind brazil, dead list environmental disaster counting the cost on al jazeera, the. ready full 2 people crushed to death while forcing their way into the cannibal airport. as the us is criticized, it's evacuation efforts. a week after the telephone seized, our co founder income also talks to hammer out and you government? ah, other i'm given l. this is elisha or lie from doha. also coming up. we report on the haitian stroke.