and generosity and come to live because that's the only way we can try to solve any of the problem is together. that wells is there is so important. we make those connections. have the news. i'm alamo here until how with the headlines on al jazeera, the televisions cofer interior has arrived in afghanistan. capital for talk soon, forming a new government's will a dual gone abroad to lead the groups negotiations. in doha, the taliban says the future governments will be inclusive. charlotte, bella says more from cobble was unclear what's going on behind the scenes. the very secretive about these communications we're getting is the old folks are sure that they're actually meeting, but as 10th of the substance remains to be seen. we do know that the taliban are

very concerned about legitimacy. it's very important to them. the us have told us that in terms of the leverage that they still have with the telephone, that they have a money and they have legitimacy. and that is what they are relying on. they say that they know or the telephone want to be respected on a world stage. and that part of that is including government leaders and having an inclusive government that represents elements in society. new more tens of thousands of people are still trying to get tired of f ganna sun. 6 days after the taliban should cover, at least 12 people have been killed in and around the airport. greece has completed a 40 kilometer extension of its board of war with turkey and use surveillance system as also in place to store potential asylum seekers trying to reach europe. the taliban takeover of afghanistan as waste fears of a repeats of the refugee crisis in 2015. hey

t government is facing growing criticism as it struggles to get a 2 survivors of a powerful earthquake. a week ago, there were desperate scenes in the hard hit city over the k, as people scram moved for supplies. many in we were, larry is still waiting for help. hundreds of people have been arrested in australia after anti locked and protest term violence that came on the same day. health authorities reported a record 900 new cove at 19 infections. most of them in sydney, the health minister denounced the rallies as selfish catholics in sir lanka are putting up black flags to demand justice for the victims of the 2019 easter bombings. many are angry over what they call the governments incompletes investigation into the attacks. the killed, more than 260 people will actually have stayed stay, stay with us. more years after all held a lot of algorithm i

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 the from google searches to gps navigation algorithms are everywhere. we don't really think too much about them,

but increasingly government's 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 been called the robot at scandal. back in 2016, a decision was made to fully automated a key part of the israeli 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 this were investigated by government employee. first, with automation,

all human checks were removed. the government had instituted an algorithm that essentially said, let's match 2 lots of data together and smashed them together and see if people have a day. so some of the math was just bad, just plain wrong, like it was spreadsheets to matching, to sell together and the self do a job. asha wolf is a journalist who has been reporting on the road. good, good 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 all we started getting people talking together on social media, on twitter that we realized. actually, the government, the town, it was almost like 100000 people have been gas lighted, 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. these trillion government disagree

. we're doing all compliance checks because we want to be more sarah price if we are covering greatest example and we are retrieving 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 a fallback activities. and what was even worse was the systems were imposed on paper with intellectual disabilities with homelessness, with chronic health issues. people who know was fairly literal, not literally all people who didn't know how to use a computer, people who living in my communities with that access to internet, people who just had no bloody clue how to deal with this sort of administrative, your credit, bumble, david digna, was notified,

he incorrectly declared anything come from a teaching job while he was on a disability pension back in 2011. ready his brother, debt. ready $4088.00. in essence, what rabbit he is wearing an accusation toward you that you've done that change, done the wrong thing. i know i hadn't, i want to detailed, have a joke here. i did. and i was told i couldn't have that. and the reason i was told was that the computer looks my personal information and then source a piece of information from another patient. he another patient of me. and they can provide to me because it comes in too many pipe and we simply back, in other words, the algorithm is crucible. it's totally unknowable. even the staff don't really understand it. rather can you tell me how much evidence or how much notification certainly provide you. proving that there was a good many provide me with anything other than that. 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 hear the hours you work that really i found it. it should any confidence that i had in that the government will do the right thing. the fact that i couldn't prove to me that i owe the money really concerned me. so, you know, 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. that you should have been eligible for the services. but we didn't tell you, therefore we're telling you now and we come back pay. nobody gets back paid. in fact, you're only eligible for like back. i think it's 6 weeks with government services

that the government convertible debt you back for many, many automation, computerization algorithm optimization. if that's even a word they're always sold to us is such a positive thing. all upside, no downside. as a strong 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 had he challenges system that has no face, no 9, and nobody signs the bottom of your letter say, you know, i'm in charge of this good afternoon. welcome to the department of human services. since like on a good day, it end up sitting on hope for a couple of hours trying to speak to a human. the real question is, how has it come about that the government has over pay people 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 800000 citizens had made mistakes or sets the case and the system is too difficult for people to negotiate. so i'm not here shaking my fist at technology, it's not digital fall, it's 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 issuing them fullstep. this is something i heard from virtually everyone. i spoke to that rubric and 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. there are 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 stands bytes, algorithm and automation in the welfare system. we do repassed compliance to be applied to the black line we recruit. we've recovered the $300000000.00 to the tax through that process. so the system is working and we will continue with that system there at least 20 different laws in australia that explicitly enable algorithms 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 the united states has a longer history of algorithm use than many other countries in 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, 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 in 820 to build actual poor houses was a decision 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 junior 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 their 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 an up 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 they had in the past, which is just to discriminate against people. and that for 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 as just simple administrative upgrades sort of natural and inevitable. but in fact, they're systems that make really important concept when shall 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 seventies close to 50 percent of those living below the poverty line. and the united states received some form with 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, 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,

who owes money back to 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 being 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. this school is then used by judges to help them determine who should be released and who should be detained, pending trial. now the judge has to consider a couple factors here. there's public safety and flight risk on the one hand, but under the real 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, defend his eyes and tries to say, hey, you're high risk person or your 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 sentence $260.00 is imprison, 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 units. 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 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 at this sort of equal playing field. and 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 because justice system, we don't just want to have an equal playing field of 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 compass software has defended its algorithm. it points to

research commission that the company meets industry standards for fairness and accuracy, whether 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 done a human in part because i believe these 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 is 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, see 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 is 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, that buys 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. ringback 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 algorithms? will the biggest thing outlet from speaking with asha virginia shirad and many other is that i've actually got the question 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. 2 human biases, human intersections, that's what we see reflected to now algorithm. and without that oversight, we which, reinforcing our prejudices and social inequality such algorithm our

program was shame that the future that they wanted. 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 to be future scenarios different from the old. of course we can build better tool and algorithms 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 fair 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 and every single tool

use. 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 the data available as possible. so to encourage people to look at death, a, 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 even so my biggest pieces of thought is to never underestimate your invoice. you know, you might be fighting some shane, some computer system that you've never been able to make or say, but has in flicked into huge, harmless suffering. but your words can make government scared, your voices combined can make senates and quote,

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 these systems, we have to, we have to claim our space as decision making and decision makers at these tables. and we can't do that if we think that these technologies are somehow god, 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 take with algorithms that they're called the move that we do to them. the more data we pritchard. we're in the midst of a great,

great the data and big companies around the empires are rising on a wealth of information and we other commodity. in the 2nd 5 part series. 90 re examined whether corporations are colonizing the internet, like meet the popularity and power of the big techs on a jazzy ah, ah, ah ah, ah, it's too late for the journey to winter sponsored by kettle airways high there. well, grace has made a landfall for the 2nd time in mexico, central mexico, just north of vera cruz and i need landfall is a category 3 hurricane

a major hurricane. i sustained winds of more than 200 kilometers per hour. that's enough to peel bruce office homes and toppled trees. rain will be a big concern here, and let's remember this is a mountainous area, so that much rain falling, that high above, is just going to gush to the ground and trigger landslides and bud slides. so mexico city mans neo in the line of fire before grace pushes out toward the pacific . you know, we are also keeping tabs on tropical storm on re, as it moves up the atlantic. this one's really interesting because it could make a rare landfall as a hurricane in this area. and we're thinking somewhere along new york long island and then the new england region up to the west coast of the us. and we've got some strong offshore winds filtering into s f and mixing down. so san francisco looking to see gusts of about 40 hello meters per hour since big big storms through southern parts of chile, the winds powerful enough to benson street signs here. and that disturbance,

we can see it, it's circulation right there is that pushes out toward the south atlantic on sunday . that sure weather update see a soon ah, sponsored cat on airways, which she does with it. very glamorous. it's part of our whole job to, to our very, very special occasion. and for that people who spend money, everything is dealing because what they do is going to be longevity. they don't have to come in and turn things around my, my dear, and i'll do their the latest news as it breaks down here in the north and they're doing the best job they can. we've seen one water to teen at wells far further with detail covering the government since the taliban is relying on human shields and losing people shot the phones from around

the world. the price tax, the tokyo games have officially helped $15000000.00 that already the most expensive summer games ever stage. with the news this is al jazeera ah, a little from bill i'm. how am i hearing that the user coming up for you in the next 60 minutes? the taliban school leader is in our system to begin to form a transitional government. as the chaos cobble airport shows widespread criticism, the taliban.