it was at dartmouth in $956.00 that mccarthy organized a summer long research project focusing on machine intelligence. it would become part of ai folklore and the place where the term artificial intelligence was 1st coined it would also bring it to the attention of the u.s. military. in those days the military was was the principal source of funding for computer science research and if you went into the founders you said you know we're going to make these machines smarter than people some day and whoever isn't on that ride is going to get left behind and big time so we have to stay ahead of this and boy you got funding like crazy as the defense department took over more of the funding the question started to being asked you know but what can we do with it now . the u.s. department of defense had its own research arm called the advanced research projects agency arpa the push for developing a i was driven by the logic of the cold war any technological advantage america

could get over the soviet union was pursued through our. the new field of artificial intelligence was flush with money and confidence about what it could achieve. but there were competing ideas about how i would lead the way to this brave new world. from the very 1st day there were 2 big approaches one of them was we're going to figure out the rules and we're going to teach the rules to the machine right we're going to say this is how you do this 1st or this 1st or that 1st of that so the 1st one is the so-called expert systems where you just codified old rules you can and say go for it the 2nd one was we're going to show it things we're going to feed it data and it's going to learn from the data you feed it the data and expected to build what people call a neural network which is that it looks at the data and the results and says ha ha

this this this goes together and then does it again and does it again and till it builds almost like a brain like structure. what happened was a book was published actually by marvin minsky one of his colleagues that basically showed that these neural networks could not really learn certain things. which typically happened in ai is. something comes along that makes us start to doubt a piece of technology and that closes to sort of go underground for a while while the other stuff gets more attention. development of neural networks slipped into the shadows of ai research as expert systems took center stage and all the money. but by the airlie 1970 s. the great advances promise by artificial intelligence had failed to materialize. a clumsy robot aptly named shaky and rudimentary processing machines fell way short of what the early ai visionaries had sold to their backers. for the us military ai

had lost both its appeal and its purpose. it cost what you call the ai winter which stopped for quite a while. the so-called ai winter would freeze state sponsored development of artificial intelligence for over 2 decades. chasse the number of bored possibilities is just astronomical. there's so many possibilities in chess that by the 20th move a chess board there are more possible ways the board could look than there were molecules of the universe. chess a measure of human intelligence for centuries had become a benchmark for how far computer technology had progressed and

a proxy for how smart computers could be. with state money frozen private companies such as i.b.m. funded their own development of ai. ringback and we did have this fall. in 1975 b m engineers built a computer the took on world champion garry kasparov in a series of chess matches. they called this computer deep blue. this is amazing engineering i thought it was so good it's 64000 processors going it really high speed through chess millions of noosa 2nd. between the 1st game of the 2nd game the computer was trained on lots and lots of casper of games so it wasn't just becoming a good chess player but it's becoming tuned to playing against that particular person i was there actually at the time here in this building where the game was

actually the machine was and where the machine was was invented and i was looking on the systems aspects of it it was search algorithms but search algorithms that were intelligent from the point of view of thinking about one another. over a series of 3 test matches deep blue beat gary kasparov at outmaneuvered outthought and out played the greatest chess grandmaster of his day. artificial intelligence had burst out of its winter and now looks set to blaze a revolutionary trail. very. high. that was a really key moment was in that when when i.b.m.'s deep blue be garry kasparov to me that it still gives me goosebumps that it's back to war 3 broke through at that point in time it was the pinnacle of intelligence for anybody to be able to play

chess at the level that the grand master of the play and beating the grandmaster itself is i think its importance cannot be overstated. but the capabilities that vent into it brought together algorithms. infrastructure which is hard and. sort of 3 of these aspects came together at that point and i would say it was the precursor to our latest we've all free i. i b m had built deep blue using the established expert systems model of ai the chess victory over kasparov was its greatest achievement to date. but to beat a person at a game involving set patterns and strategy was one thing beating humans at a game of general knowledge was another. the next big mark in the public

imagination was i.b.m. schwartz that was a machine that could play jeopardy. jeopardy is a game in the united states we give the answer to a question and then people have to try and work out what the question is. and became clear you couldn't win a game like jeopardy by just building an expert thing in each category there's just too much so they started moving to a different direction and they brought together bunch of people eventually from all parts of the company. by 2011 i.b.m. engineers were. working with new tools one key challenge was understanding human language using advancements in the new field of natural language processing they build layer upon layer of algorithms mathematical structures that allow the machine to learn human language through a mass input of data. language and communication. is the essence of us as being human beings. it's one of the hardest

tasks and hardest barriers for it to have crossed off the we did. this us president negotiated the treaty of portsmouth ending the russo-japanese war watson who is theodore roosevelt good for $800.00 what i.b.m. did was they played the best players in the world they made the t.v. came of the players who don't the best the 2 very top players and beat the. life on t.v. . i.b.m.'s watson computer like deep blue had triumphed in the battle between human and machine but unlike deep blue watson was not strictly an expert system its novelty was machine learning a branch of artificial intelligence that had been driven underground decades earlier. the machine learning side it

almost died out but from ninety's on when you started having the internet and all these digital devices in the mountains amount of a data and you started feeding this huge amount of data to these machine learning systems they were uncannily effective. far from being abandoned machine learning had continued developing away from the mainstream of artificial intelligence alongside technological advancements personal computers laptops mobile phones high speed microchips. and then came the world wide web search engines tech giants social media smartphones. machine learning now had the 2 ingredients that it always needed massive computer processing power and data masses and masses data. machine learning was now set to take off.

the united states government has been seeking to use machine learning to isolate targets for drone attacks for many years because i'm afraid we americans have a bit of a tin ear for irony it calls its program skynet. in which it is going to seek to try and find targets for attack when we talk about ai and warfare the other thing i want to be clear about is this isn't about the terminator right this isn't about killer robots what i want to talk to about is humans and targeting and the way that human intelligence analysts relate to information that comes out of semi-automated processes basically from people's cell phone metadata and we try to determine their so-called pattern a life where they're going to they know. who they talk to here's the problem i

think that the united states has the n.s.a. learned to collect it all well before they were able to understand it all faster is faster absolutely machine learning and artificial intelligence would permit the defense department to accelerate the process of target selection faster and always better. i want to make sure that people understand actually drones have not caused a huge number of civilian casualties for years the drone wars were an open secret in washington but it wasn't until 2012 that president obama officially acknowledged the program for the most part they have been very precise rescission strikes against al qaeda but that was the same year we started to hear about signature

strikes where the cia or the defense department would target not a name or an identity but essentially a phone this is a targeted focused effort at people who are on a list of active terrorists. they would collect signals data especially telephone data and put it through a secret algorithm they would decide you were a threat based on who you talk to where you went to your friends were but that's not precise at best it's an educated guess so i started to wonder what officials brother in law and his nephew were killed because of an algorithm. mornings and snowden time 29 years old i worked for booz allen hamilton as an infrastructure analyst for n.s.a. . in 2013 edward snowden blew the whistle on the u.s. national security agency's mass surveillance program he revealed that foreign intelligence gathering tactics were now being deployed at home casting

a nation wide net to catch a few bad fish. so while they may be intending to target someone associated with a foreign government or someone that they suspect of terrorism they're collecting your communications to do so. a year later michael hayden the former director of the cia and n.s.a. stopped short of disclosing the skynet program's existence but admitted the targets were being identified for so-called signature strikes using metadata collected from everyday communications we kill people based on. a signature strike would be selecting someone who looks like other people that you think are the people you're looking for you know one critique of this is demography is destiny in some sense. so we don't we can't know because of the nature of the beast right exactly what sky and whether skynet was ever used but it seems likely to me that given what we've said about signature strikes that some kind of algorithmic targeting process is

being used to isolate targets in places like yemen and pakistan using partly signals intelligence to be clear we have no evidence that that model was ever used in practice i would be shocked if it isn't being used machine learning is pretty good at finding elements from a huge pool of non elements when president obama took over the so-called war on terror he favored drones because they meant fewer boots on the ground and as the drone wars expanded the method of selecting targets changed metadata was now a key source of intelligence but there was far too much of it for human analysts to process the machine learning would be used to identify targets and sift the good guys from the bad at least that was the idea machine learning is good at this problem called binary classification so is someone part of a terrorist network are they not part of a terrorist network machine learning is also pretty good it asymmetric problems

where there are very very few things you're looking for in a sea of things you're not looking for a few people who are part of terrorist networks in a sea of civilians for example so where do you think the kind of statistical targeting is likely to go wrong humans too binary classification all the time ok we have to decide if we're looking at you know a bunch of for example a bunch of dogs at the dog park and which ones are dangerous and which ones aren't when we say no that dog is not dangerous but it is that's called a false negative we made a mistake we can go the other way we can have a false positive oh my gosh that dog's really dangerous but it's not. so people might take action on those false positives and will get innocent people killed i'm also worried about false negatives the thing about machine learning is that it assumes that the future is like the past it assumes that the things it's looking for in its prediction are like the things that it saw in the training ground so

if we have a problem where people are actively trying to disguise their activities then a machine learning model is likely to make a lot of false negative mistakes it's going to miss a lot of people who are likely terrorists that said i'm not sure that there's any other way to do it but the risks are very substantial and almost certainly mistakes that lead to people's deaths are going to happen here. we always knew the strike on final family was a mistake. we meant congressman we talked to senators we haven't spoke to people in the white house national security council but while everyone expresses regret for pfizer's loss no one could explain why it happened or how it happened.

talk to al jazeera. we ask problems and besides the instability is corruption we listen. who are pushing the united states and president trump into conflict we meet with global newsmakers and talk about the stories that matter is there are . a journey of personal discovery my great grandfather he was

a slave of the lead property al-jazeera as james gannon explores his family's legacy of slave ownership like my family status and wealth has benefited from their choice to slave people and america's debt to the black people today some oversaw even scared to speak out because it's a product that. al-jazeera correspondent a moral debt. in the hollywood the headlines on a protest leaders in sudan are accusing the ruling military jointer of using widespread intimidation to prevent a civil disobedience campaign starting on sunday at least 5 protest leaders have been arrested with some of them saying they were seen death threats they're

refusing to negotiate with the military unless certain conditions are met the military jump to has rejected any preconditions. i hope that our brothers in the other parties will respond without preconditions we appreciate the efforts of our friends and brothers who care for sudan we want to reach a solution but if we don't reach a solution or alternative it's clear we will form a caretaker government of people in kazakhstan have started voting to choose a new president nursultan nazarbayev led the country for 30 years his chosen successor. is favored to win but some have called for a boycott of the vote to stop what they call dynastic succession venezuela's president nicolas maduro has reopened the border with colombia after a 4 month closure thousands of people queued at the crossing to buy food and medicine in colombia because of shortages and high costs at home do the head shot the border to stop his political opponents bring a new u.s.

back aide who at the media in yemen say the armed group has targeted an airport in saudi arabia was several drone attacks it says just an airport which is near the border with yemen was hit at least 5 people have been killed in syria's last rebel held province on saturday activists say the government used missiles and barrel bombs indiscriminately in italy was shot at last as regime launched an offensive to recapture it in april fighting between rebels and government forces also continues in the northern how my province dozens have been killed in weeks of bombardment with at least 300000 displaced police in albania have used tear gas to disperse antigovernment protesters in the capital tehran or they're demanding the prime minister resign demonstrators accuse any rammer of electoral fraud and want an early general election president has canceled local elections which were to be held

at the end of the month those are the headlines we're back in half an hour you're up to date right now in algeria it's the big picture. my client faisal banally jobbers brother in law and nephew were 2 victims among hundreds caught up in the american drone war in yemen. protested the loss of civilian lives few knew that these were victims of computerized targeting built on data gleaned from phones and surveillance apparatus set into algorithms and narrowed down from possible terrorists to probable terrorists to definite terrorist . neither finals brother in law or nephew was a terrorist. as a human rights lawyer i had been investigating civilian casualties and drone

attacks in yemen and pakistan and over time we came to understand that the people we work with who lost loved ones were killed as a result of a semi automated algorithmic targeting process and there was a kind of article that came out about an n.s.a. slide deck that said well this this is how we're going to use machine learning to find an isolate targets in pakistan and somebody found you up as a statistician and asked for your take on this and you were like well look this is just this is just totally unsound yeah it was pretty unsound i mean is it just basically kind of racial profiling it's cal how do you say it well it's more complicated than that because the kind of information that we're working with in that case is to lessening that if the problem in that particular example that the n.s.a. analyst were trying to figure out was ok we identified the cia had identified a small number of people who were couriers for terrorist organizations were carrying around flash drives and messages among groups of terrorist organizations

work and the question is can you use the. phones calls that these people make and the places that their phones check in with the cells assuming we've got those people right but anyway you know i think i think that the court i'm willing to believe that they got these people right the questions how many more are there that they didn't get yet but can we use these people's information to disambiguate them to tell the difference between these people and all the other people in a city they live in can you tell how different they are so that you can just use that to leslie metadata to predict which of the people who we know are actually are terrorist couriers and how few other people can you include in that list as few false positives can you get in that classification and i was very skeptical about the particular model that was used in that case do you see some resonances here and you know we're talking about communities abroad who have basically designated

a threat and then targeting them for armed attack does that chime at all with some of the policing and other targeting of communities of color in the states that you've thought it. you know i i i resist the temptation to kind of essential why is these as the same in every part of the world in every context we do know though that. technologies predate these kinds of automated technologies about classifying and figuring out who might be a threat. disproportionately or targeting people who might have politics that are say more to the left people who are more interested in civil rights people who are advocates of human rights labor organizers for example so i think the question is again always underneath these projects where the values and the politics of who who's being assessed who's being classified for what

purposes and those are fundamental questions that are going to be with even with the next version of the technology top l.a.p.d. spying coalition did research on drones being deployed in l.a. in 2015 they produced a report and they actually drew very explicit lines between the use of drone technology in the middle east and the proliferation of drone technology in police forces across the united states through the urban area security initiative and they have been making these connections right the military is ation of the police. the increase in 3rd party private services that are bought by public institutions so what how do you see it you know the defense community affecting the development of these technologies is that the kind of original sin of the thing i think that particularly in academic contexts. the big chunks of funding have been for decades and continue to be from from defense i don't think that most

of the funding that comes out of the fence establishment that's for pure research. looks like it's going to be used to kill people the larger problem is that it creates a kind of philosophical or even ideological framework that it's ok to produce things for the defense establishment and that it makes sense to produce things for law enforcement because they're here to help us that failure of having a critical understanding of what military and police institutions do to the communities that are on the receiving end of their business i think that's the larger problem the residence i kind of see it and the reason i guess i asked the question is somebody who did work with those communities in yemen in pakistan is that they talk about feeling scrutinised and over police in a way that i hear when i hear you guys talk about these other communities you know the sharp end of the policing so it's almost as if the language that comes out of them that says we feel our whole community are suspect it's never point it is that

white collar crime the containment the prediction the assessment always seems to be at a community who we fear in some way in that we want to contain well and who the we is in that is very important because we also don't profile and track for example white supremacists nazis neo nazis in the same way we don't talk about them as domestic terrorists for example in the u.s. or in other countries so the framing of who is the threat is ultimately always the value question i think that's on the table that we have to be thinking about and of course the more you ought to me the profile of who the threat is who the threatening other is the more you flatten these conversations about values the harder it is to actually talk about what people are struggling for what struggles for justice around the world look like i mean and then some of the very companies who develop these technologies expand into other areas don't you see you've got

talent here the security and intelligence firm who developed tools for counterinsurgency in iraq then sold some of their kit to the l.a.p.d. recently inking a deal with the u.n. world food program seeking to help them spot fraud i mean. where then it makes you think mass knows no context we can sell our product anywhere as long as we're finding us to testicle relationship. people can take 500 pictures to get that perfect shy. which is something when i was 20 could not have done because of what happened on film and it was and you got what you got. one of his. vast swathes of the world with cameras on smartphones billions hooked

up to social media sharing images online gave machine learning engineers access to a massive data billions of images these images could now be used to train algorithms to teach themselves to detect particular features recognize particular forms this new breakthrough was called deep learning very soon ai would use deep learning to teach itself to recognize the form of a cat just by looking at millions of cat images on the internet. from there that made the leap to recognizing people. artificial intelligence now claimed the ability to pick out a specific face in a busy crowd to find the needle in the haystack. so what you have in france fear is a very typical surveillance saint's as a camera looking at a public street and people clearly want us to come face recognition go to work out that it's seen a person and then it's got to work out with a person's face and it's got to take

a biometric caution about face in essence something that it can pat can compare against watch list if there is a match that that will alert and you'll see thoughts come up on the screen stop person is now going to the system has been identified clearly you can set your system up to alert the right people when that happens right so if you wanted to kind of test it out on my face for example how would we make that happen so very simply we would have a surveillance photograph or it could be something taken from social media or just from the internet that would be loaded into the watch list as you can say here such that if you walk past a camera that is linked to that watch list then you should be attacked if you have been seen and then send it to the appropriate place so we give it a try and stand on our.

great crowded streets saying lots of people coming towards the camera. each time the camera attacks that i've seen a person but they will by the tree house that person and say if they're on the watch list so he can say here for example guys cliff faces on the person against the watch less than on that back consequent it up as it were also as if the camera doesn't say no it's ok. the facial recognition engine is working hard right now checking all of these people when clearly. you know coming now it's more strain and you know just like culture if your face in it michel is just who you are it will continue to identify you the level of confidence will change depending on your angle to come up but the minute in one single for a player on the list. these facial recognition technology is should not exist for what purpose are they being

brought into existence again who are they being pointed at and what kinds of protections should we have against the common critique of it is while it doesn't seem black faces very well but is that is that the whole problem with facial recognition i think for the people away joy. their position would be these technologies exist and black people will be ensnared in there especially black women the failure rate is greatest on black women are going to be misread by these technologies and therefore potentially harmed because they will now be able to kind of fight back against these technologies that are pointed out that. joy while i'm waiting of the massachusetts institute of technology showed how facial recognition programs were unable to recognize black faces particularly the faces of black women. the problem was data and bias engineers who were

mostly white males trained algorithms with a data set of images that were themselves overwhelmingly of white males. the resulting algorithm struggled to recognize non white non male faces the algorithm simply couldn't compute what they saw with what they'd been trained on the same racial and gender bias that existed in the wider world was trained into the system itself. one of the other key parts of the debate has to do with the extent to which the technology works on different faces so whether it's as effective on people of color or women is that changing does a kind of depend on the technology. is only them how it's trying so saw technology for example we have have trained it on different emma graphics in different parts of the world but certainly in terms of if you step right kind of strip thought about debates away the on the underlying all it's official intelligence is kind of

an illiterate company trying to in any which way they can clearly be trying to you know and have it in her bosses with and. one of the sharpest growth areas of artificial intelligence that is being acquired by government authorities all over the world at the moment is of course facial recognition right have you got some concerns about this technology do you think it's a good idea to be able to pick faces out of crowds or could it end badly the question is how much more is gained i think a by using facial recognition in terms of who's it deployed toward and in service of what you know one of the things we find is that often facial recognition technology these are argued for around law enforcement or terrorism do we have the data yet that says this is radically impacting the reducing terrorism is it working as a deterrent and effective deterrent for people to engage in crime the assumption underneath is very strong which is that we know who we're looking for and i think that's a very difficult to prove assumption from the point of view of law enforcement.

there's a lot of other mechanisms like this where massive data gathering helps law enforcement only in the aftermath not so much in the prevention you know if you capture every piece of information about all the video in a city after crimes been committed that may help you solve the crime it gives you very little ability to prevent the crime and i suspect this will be quite similar so the predictive power of it is in no way certain right we just don't know and meanwhile though these concerns about who it can see who it can't see bias so there are some researchers joy one way and others who basically have shown that it can't really see at least at the moment it can't see black faces is that a problem or one of several actually sees black women's faces the least effectively and so of course we want to make sure that there is accuracy especially if these things are used again to go make an arrest of someone and being used as the so called science that legitimate that arrest and i think this is one of the reasons

why those researchers are trying to pursue better accuracy higher accuracy i think there are others who would say. why are we legitimating facial recognition technology as we should actually be resisting them at every level i probably follow a little bit more along those lines and say why do we need these technologies who are they being pointed toward them why are they being trained on vulnerable communities in particular there's a big question why would we want to be included in these facial recognition technology is when the systems when they're doing harm to specific communities and what it makes me think of is you know are we in an era where errors are one of the ways in which we protest these systems over which we have no control because right now it doesn't seem like we have that many mechanisms in place there's no court needed system by which we can. protest or

abolish certain kinds of systems. or prevent them from being developed right so errors noise that sort of saying that seems increasingly like an area for fruitful discovery for civil disobedience the larger question of what we're trying to accomplish as a society is the issue here and the technology makes it somewhat explicit if one of the things we think we want is law enforcement seeing everything that happens in our society with video covering every square or every inch of the public square and facial recognition identifying every person wandering through that is that the society we want to live in it's not the society i want to live in i think that's a terrible world and there's something intimate about the face in particular isn't there i feel like we're only just starting to clock the ways that the data is gathered about all of us but i feel that people instinctively understand and have a lot of unease about their face being collected thinking about detroit earlier this year the city announced that it would be upping the number of surveillance

cameras that it's putting into the downtown area so that number will reach $500.00 after a 5 year mark. and this is an area of detroit that's meant to be redeveloped and you know all sorts of changes are taking place and there are a number of community community members that are really upset about this because they feel these cameras won't be only used for so-called security purposes they'll be used for other kind of this mission creep idea that it will start to affect how people socialize with one another and it's not just the public square is that right we see big kind of box stores wal-mart and others starting to test these these facial recognition software they say oh well we looked at it for shoplifters but we're not going to use that we just want to improve the customer experience how comforted are you by that i'm not i mean i think that again even if the if it's not law enforcement that's using these technologies but you know what does it mean that we're again we're trading off our privacy we're trading off

a certain quality of life that. we have come to rely upon to be ensnared in these systems so that these interoperable systems between companies can track my moves and of course they do this with our engagements on the internet and with our you know smart technologies in our in our pockets and in our bags i'm really concerned about that i mean that's much less as a technologist or as a scientist that worries me about as a civil libertarian and in particular i think about. restriction on our freedom to to associate if i associate with someone in the public square do i then take on some of that person's implicit guilt the point of these systems is to be modeling the level to which any of us should be subjected to additional law enforcement attention that's explicitly the point these techniques these tools are to highlight who law enforcement is to pay attention to there are plenty of people who will be watching this program who will say well we want to catch criminals in this does

make me feel safer but i think these these technologies also get deployed in other ways like using facial recognition software when you're in a job interview and answering questions and profiling your face and your emotions and deciding whether or not you are reliable or trustworthy and having a machine in fact make a prediction about what whether you'll be a great employee based on the kinds of facial gestures that you make i mean these kinds of things are being deployed right now they're being tested in industry and. that says a lot of mean the what the kind of statistical model of great employee facial gestures looks like i think is incredibly subjective it's cultural it's not universal it cannot be standardized and yet we will see these things increasingly rolling out. technology that can pick my face out of

a crowd of people may seem innocuous and even kind of impressive. but when you think about the consequences for millions of ordinary people including really serious consequences then the conversation looks a little different romford here in east london is one of the places where metropolitan police have been testing their live facial recognition technology and the way that it works is pretty similar. a camera on this van here. checks everybody who walks by against a database of known suspects if the camera on the software find a match that a person is stopped and searched and potentially arrested. london's metropolitan police has been trialing facial recognition technology since 2016. the u.k. capital already has the 2nd highest concentration of c.c.t.v. cameras in the world only beijing has more it's why there's a reluctance among civil liberty groups like liberty and big brother watch to

accept another layer of surveillance. we are supposed to just expect every time it's been used and we found that 98 percent of that much is have an accurate he identified in the survivors of the public as potentially once it's criminals 98 percent yes. a lot of this inaccuracy is down to bad data for quality images loaded into the algorithms images often taken from low grade c.c.t.v. footage. the technology is far from proven and its use mired in controversy that's why even a city like san francisco the home of tech has banned facial recognition from being used by civic authorities including the police but in london right now there is no bam this isn't just catching images of people it's an identity check it subjects members of the public to perpetual police lineup so what do you say when there's this comment made well actually if we could get this technology right then maybe it

will reduce some of the cup. by and so bias policing and so forth whether we're talking about humans eliminating discrimination or technology eliminating discrimination the hostile medians hand i want we can see already with this experimental technology being used it's never been tested potential racial biases there is no ins had to test the technology and see how it's working and see how it's affecting the oh so unfortunate i don't think this is going to solve any of those problems. over the next few hours we would see a number of arrests but not we were told because of matches through facial recognition technology these arrests were the result of old fashioned police work. more officers on the be leading to more arrests. just as the trial in romford was about to end for the day plain clothed officers

moved in to apprehend a man from a nearby fast food restaurant his image had been flagged by the facial recognition technology after police carried out identity checks he was arrested. artificial intelligence has come a long way since its early days of unfulfilled promise and shaky robots. but we're still far from building computers that can do all the things humans can do. and we're finding that machine learning can reflect some of our biases right back at us . in the next episode of the world according to a i will explore the choice we all face a lot of official intelligence biggest win prove the lives of everyone. or to keep power and privilege where they already are.

after decades of being programmed with instructions they turn gray computers can only on their own identifying problems and predicting human behavior. artificial intelligence can monitor ombudsman. and decide on. the big picture. of the world according to ai and exposes the bias inside the machine to on al-jazeera. the latest news as it breaks local communities here importing are very frustrated because the lack of post storm services with detailed coverage this parking lot of people thought it is struggling to make ends meet and just want a better life from around the world and obviously has been offered to those who rebel against the government of nikolai moda except those involved in human rights abuses a war crime. hello

there we've got lots of showers still a ripoff of the middle east that area of cloud is being with us for a good few days now making its way northward from saudi arabia and all the way up into parts of turkey is still with us there at the moment and it will still season more showers as we head through sunday and into monday as well again want to showers most of them are in the northern parts of i'm up here over parts of turkey but we're also seeing a few showers elsewhere wardle to around the northern parts of iran and plenty more as you head further east towards tesh kent and el monte further south it's largely fine and dry pretty warm now they have a couple where about 29 in forcing kuwait city up 42 here in doha it's no koan of not hot temperatures getting to around 44 at the moment set me very very hot at least it's a dry heat at the moment it's not sushi humid elsewhere it is more humid salalah at 33 it is sticky here we're all. so say more cloud around the coast of yemen and

that will give us a few thunderstorms more expected as we head through monday but maybe not quite as many of them as we head down to what the southern parts of africa most of the showers here are in the east imposible about just being brought on to the shore by these winds so if you have them i have a pause of mozambique a couple more over madagascar as well but further west is fine 19 is the maximum there in cape town. with stories generate thousands of headlines with different angles from different perspectives on just long standoff with international borders is finally over separate the spin from the facts the misinformation from the journalism protesters complain about the under reporting of police violence the sensationalizing of the demonstrations with the listening post on al-jazeera.

where every. call for widespread civil disobedience in sudan by the opposition but 5 of its leaders have been arrested. and has i'm sick of this is live from the. also coming up thousands protested in

hong kong against a proposed law that would allow extradition to china. voters in kazakstan choose a successor to the man who's been in charge for almost 3 decades. and were at a site described as the birthplace of civilization which archaeologists warn is crumbling before our eyes. allow a campaign of civil disobedience is expected to begin in sudan opposition groups say they won't stop until the military jump to gives up power at least 5 protest leaders have been arrested over the weekend on friday some of them met the visiting ethiopian prime minister who's trying to mediate the opposition says the military is targeting workers in banks electricity companies and airports they haven't been any negotiations between the jointer and protest leaders since

a violent crackdown on demonstrators last week when the one. i hope that our brothers in the other parties would respond without preconditions we appreciate the efforts of our friends and brothers who care for sudan we want to reach a solution but if we don't reach a solution our alternative is clear we will form a caretaker government the touch of a name has more. mohammed went from shaking hands with ethiopian prime minister abi ahmed to a jail cell in one day the sudanese opposition leader was part of a delegation that met akhmed after he arrived in khartoum on friday to act as a mediator he is one of several opposition members arrested during saturday morning raids their arrests are expected to hamper efforts to reopen talks between the opposition and the military earlier this week more than 100 protesters were killed

in a crackdown by the military hunta the opposition has issued a list of demands including restoring freedom of the press and access to the internet before they'll return to negotiations 1st the military council needs to recognize that the crime was committed secondly there needs to be an international investigation into the dispersal of the sit in fairly old political detainees and old political prisoners held by the previous regime need to be released. protesters have called for the immediate withdrawal of the paramilitary group the rapid support courses they are accused of raping and murdering protesters including children but some doubt that's possible i do have hope but i'm also willing to. raise the militia group. sudan has been suspended from the african union the un wants to send

a team into the country as soon as possible to investigate and monitor events want accountability. and also. we want annual military. to have. a mission to hand all the civil suit billions of the. forces a general strike is planned for sunday despite the internet blackout and restrictions on journalists protesters are pushing out videos on social media to ensure the world gets a clear view of what's happening in sudan natasha going to al-jazeera. and people have been protesting elsewhere in the world in solidarity with sudan's opposition demonstrators in london called on their government to put more pressure on sudan's military junk to foreign secretary jeremy hunt earlier condemned the crackdown

promising the international community would hold them to account in france protesters called on the sudanese military to transfer power to a civilian government they also condemn saudi arabia and the united arab emirates for supporting the jointer to regional powers plates $3000000000.00 in aid to the military council shortly before the crackdown began. and in washington d.c. many gathered in front of the u.s. congress building they want the united states to take a clear stand against the militant jointer the state department there is to dance leaders to quote desist from violence for and for both sides to return to talks. a tens of thousands of people are protesting in hong kong against the proposed extradition bill the changes would allow people to be sent to trial in mainland china potentially over vague national security charges opponents say it is another

sign of hong kong losing more of the rights it was guaranteed to keep in the 1907 handover from british rule of law on this let's speak to sarah clarke who's on the phone from hong kong for cerro just looking at these live pictures of people there filling the streets the organizers were hoping for around 300001 of the numbers looking right now. at the targets on the market started early was about half an hour's time but it started early because so many people over flowing through victoria park which is one of the largest targeted. advertising that you mentioned about 300002 be a huge number but the most expensive and many of the 1000000 in crowd around continue to rally throughout the evening now the marches going from here down to the lead the council building which is the government building where they'll hold more talks and more speeches and potentially the situation as a little capital building or a key concern for all of these people who are you know i could say in their

opposition to this extradition bill is that they're concerned anyone a fugitive a suspect could be extradited from hong kong to the mind that the trial and the concern is that china could target political opponents and that would receive a fair trial on the finance the bill has been fast tracked through the city parliament at the moment it could be got about a 2nd reading really is when. so what are the chances of this extradition bill being passed them or. well the government actually has the numbers here given it has been the jockey the bill will be passed the fact that 9 the committee hearing gridlock the billboard it sounds pretty good to have something in their hometown parliament that you might recall politicians from both sides having a ball actually on the floor in the parliament so it could have a lot of controversy here but it will be and the hong kong chief executive terry land she wanted for her to live and with parliament going from a grand on july a june 28th it's highly likely that you'll get through in the next month all right

sarah clarke on the line for us then from hong kong thanks here now the been clashes between protesters and police in kazakstan voters a county choosing a successor to the man who led the country for almost 30 years or so tanos unbias handpicked successor. took i have is expected to win easily but some of called for a boycott of the vote describing it as far from fair robin foresty a walk as more from tom the capital that was renamed in march in the long time presidents on a. because it's as always like to consider itself exceptional in this central asian region because it's got all the oil it's had all the wealth i missed in a survivalist and wilson time knows about who's run this country all this time has really been very interested in conserving his image as a statesman and as someone who wants to transition kazakstan out of this controlled

authoritarian system to a democratic one and that's why it was rather an exceptional move when he resigns rather than holding on to his position until he passed away as is so often very common in this region amongst a strongman he resigned and appointed a loyal to p.t. mr to be the interim president but everything here is extremely well managed and we do expect mr takara have to win very comfortably in these folks a day everything is in his favor he's got the government behind him he's got what we call administrative resources where the public public sector workers are urged very strongly to go out and support mr talkative nevertheless we have seen some indication that not everybody is happy with the political system in kazakstan after mr surprise resignation we had young people trying to make their protests known and

yet that was very strongly clamped down upon by the or thirty's with individuals detained and fines and in some cases jailed for a number of days i spoke to mr talk of the early after he gave his vote and he said that he the authorities to exercise restraint on those young people we seem to me an interesting development but he at the same time is just people in kazakstan to recognize the legitimacy of his government and his power structures. i hope the media in yemen say the rebels have launched several drones targeting saudi arabia's gisenyi airport in a tweet they said they were trying to hit saudi military facilities in the airport has been no confirmation of this no from the kingdom. out of hope these have also been releasing video they say shows other attacks inside saudi arabia the fighting

was close to the southern saudi city of magic then muhammad a lot of reports from the yemeni capital at santa. houthi say this video shows saudi forces retreating in the face of heavy fire in an attack which began with their care to share my side of strike before troops move then the whole these are reported to have advanced 30 talk in the matter 2 words held overlooking the city in saudi arabia. it's not the 1st attack on saudi positions there but this time they say they are staying. and this time it's a very special one you like you. are more direct you to. because right after the right 9. last month. if you can the men saying that there will be

a great military target 300 military. and united. the who say they are advance is on strategically important locations. just a small lightly armed force alongside saudi forces recruits from the south saudi arabia has neither of these attacks nor refuted them. operations are a last resort their aim is to riyadh to will come this talk all my greyman signed last december aimed. at ending the fighting around the port city. and free up the distribution of aid. whether it will work is open to question what we know is that 12000000 yemenis are in urgent need of food.