of tuesday's midterm elections. it comes as twitter has deleted thousands of fake accounts posting messages purporting to be from us democrats discouraging people from voting. polls show the race in many states is too close to call. the us is reimposing all sanctions on iran that were lifted under the 2015 nuclear deal. the measures, which the white house say are the toughest ever imposed, target the country's energy, shipping and banking sectors and will come into effect on monday. pakistan authorities have reached agreement with protesters who've been demonstrating against the acquittal of asia beebee, a christian woman sentenced to death for blasphemy. under the agreement, aasia bibi will be barred from leaving the country, but it's unclear for how long. in a moment we'll have newswatch, but first here's click. ai.

that's what the future is about, if you believe the hype. computer programmes that learn from past experience, that improve and that sometimes, learn to solve problems in ways that even we hadn't thought of. well, here at microsoft, future decoded events, ai is at the top of the agenda. these days, there are very real examples that al are starting to be able to do things that were once only the reserve of humans. it is learning to drive, to play games.

it has learned to paint. it has learned to understand what we say. each ten year or so we seem to have a breakthrough moment where we take a piece of human ability and defeat it with machine. ‘96 it was chess, go, last year — and we all worry. what that is demonstrating is that our al's are extraordinarily good and superhuman in tasks that we can specify and understand. they can improve and self improve. the challenge is this whole idea of general intelligence or transfer across tasks and that proves much more challenging, much more difficult. we think it will take many decades to unfathom that, and the old adage was, you cannot teach a machine to do something without programming, but if you have a learning capacity in the system that allows it to go beyond the performance that was originally given to the system. and it is certainly true that al is already replacing us

in particularjobs. we will talk more about that later. but we thought we would start with an interesting phenomenon which is happening in certain parts of the developing world, where ai is actually creating jobs. see, in orderfor artificial intelligence to learn, it needs to have access to loads and loads of data. for example, self driving cars need access to images where all the objects in them are correctly tagged. that work is being done by humans. david lee sent this work, not from california, but where the artificial intelligence journey really starts. this is the kibera slum in nairobi, kenya. more than 1 million people live here. i am 10,000 miles in what feels like an entire universe away from the lush campuses of silicon valley. how are you? hello!

the people i am here to meet are every bit as vital to the next wave of cutting edge tech as anyone you could meet in california. you have your brother living here? yes, my brother, my daughter and my mum. are they all supported by you? yes. they are supported by me. this is brenda, a 26 year old single mother, this is brenda, she's a 26 year old single mother, who has lived in kibera her entire life. how does it feel to be creating the technology that is going to change the future? it feels so good. at least you get to do something unique from others. at least with my work that i am doing, i believe i work for something that is go to help me. not even me in the future, but it will help someone in the future. every workday, brenda travels for around two hours to a building on the other side of nairobi. she is among a team of around 2,000 people who work in this building for samasource, an organisation that recruits people from the very poorest parts of the world.

in some cases, that means those who are earning less than $2 a day. here, they earn around $9 a day and there are importantjob is to give artificial intelligence its intelligence. when artificial intelligence works, it sometimes feels like magic. but really, what it is is data, lots and lots of data. if you want a self driving car to know what a person is, you have to feed it loads of pictures of people. if you want it to know what tree is, it takes millions and millions of pictures of trees. that is what is called "training data", and it is here where that data is created. so, depending on the instructions, we are going to basically tag, or annotate, items of interest. right. from the street to the vehicles, the buildings, even to the sky. right. how is that? that's good. is that good? not quite right?

not quite right. laughter. the item needs to be squarely inside that box. if we zoom in... turns out no pixel can be out of place, or unaccounted for. the sky and the street signs, the pedestrians and the lanes, everything needs tagging. once the work is done, a supervisor will check it is up to scratch. the quickest, sharpest annotators in the team will win prizes, such as shopping vouchers. samasource‘s clients include google, salesforce, ebay, yahoo and many others, working on everything from self driving cars to online shopping. one recent project from microsoft's bing search engine helped it become better at identifying certain types of clothing. the building in many respects feels like a typical silicon valley campus, complete with subsidised food. 52% of employees here are women, in a country where having a child can typically rule you out from having a career. while most of their employees are of course in the developing world, the compa ny‘s headquarters can be found in san francisco's mission district.

when i first started this business ten years ago, very smart people in the tech world and in the world of big philanthropy for it was a wonderful idea, but it would never work. lila touts her companies record on quality and security, reasons why tech firms come to them. but of course, there is a very obvious reason why these tasks are outsourced to places where wages are rock bottom and people are desperate for work. some of your clients are the biggest, richest companies in the world. can they not afford to pay more than $9 a day for this work? we make a guarantee to every single worker at samasource that they are paid a living wage. if we were to pay people substantially more than that in some of the markets we are in, we would throw everything off and it would have a potentially negative impact on the cost of housing, the cost of food, et cetera and the communities in which our workers live and thrive. so, for us, we are on average, increasing our workers household income by over 500%. that impact can be seen right in the heart of kibera, it is too small for my big head.

you know the way you remember you are good at something and it turns out you weren't? this is me discovering that with batting. luckily, indian cricket legend anil kumble was on hand to realise how it was done. the most important thing is that speed and how much twist at the time of impact and the quality of the shot itself, how close to this sweet spot here. bat speed, is and how close you are to the sweet are now measurable thanks to new artificial intelligence technology, power bat. it is being developed by kumble‘s company, spektakom. it is hidden under the bat. this is a cluster of sensors, you have a bluetooth area, but also gyro sensor which measures

the twist of the bat, the velocity as well. there is also a sense of vibration so you can detect where the ball is hitting in approximation to that all—importa nt sweet spot. the sticker sends those measurements for the speed, the twist, the quality of the shot and they are being combined to calculate the power. it is essentially the energy you get into the shot. the system aims to take fans watching the game up close to what's happening on the pitch. the first use is to enhance fan engagement. everybody talks about timing of the shot. this was powerfully hit. this was sweetly banged. what does that all mean in real—time numbers, in real time data? the amateur version of power bat communicates directly to a mobile phone via bluetooth, but because you can't carry a mobile in professional games,

with the pro set—up, all data runs to a device hidden behind the stumps. this is how the professional system works. the data comes from a tag on the back of a bat and then comes to stumpy, the stump bot buried underground. you can see the antenna, this bit will be poking out from the top of the pitch. the data is sent down the cable to the cloud where an algorithm does its work. with a technology into a game like cricket, insight to what is actually happening at the cricket at. technology can now help with the

coaches and the players achieve any level performance. the pro power bat might end up being used by umpires, especially for broadcasters now using it in the indian professional league, calling out bad on—field umpiring decisions. the mobile app is more about cricket fans and amateur players getting closer to emulating their heroes. for the fan out there who wants to look up to his hero, what is the benchmark for him to achieve? can you emulate him? can you be as close to power that he can deliver, can you do that? that is something you can do. at the end of the day, in a polite arrangement, anil let me bowl him out. yes, it was fake by the got first ball. it felt great. watch this for a second. see, all you needed was just one ball. that is it for the shortcut of click

today. the full version is up on my player. we are all over social media. we live on facebook and twitter at bbc click and instagram at bbc click. and don't forget our youtube channel. youtube.com/...guess what? bbc click. we will see you soon. bbc news to put a negative spin on the data? bbc news to put a negative spin on the data ? we bbc news to put a negative spin on the data? we speak to the outgoing economic editor and asking about his new management role as editorial director of news. first corner the hazards of broadcasting live outside the studio is the danger of members of the public accidentally or deliberately distracting the audience. interviews on college green by the houses of parliament have fallen prey to this risk. as vicki young found on monday. watch the demonstrator change his position according to the camera. iain duncan smith suggested restoring the working allowances and you get

even if you're in work. that is another way of ensuring that money does go to the right people at the right time. i expect we will hear something from the chancellor about universal credit. do you think he should go further or pause the roll out? or do you think that in principle it is the right thing to do? anti—brexit campaigners have been active around camera crews for the past few months and some feel more should be done to prevent them from getting their message on screen and one asked: we put that to bbc news and they told us:

when it came to that afternoon's budget the bbc‘s live coverage and analysis was extensive, with economics editor kamal ahmed crunching the numbers for the news. philip hammond tried to change the economic story of this government. away from cuts and controlling the nation's debts, and towards spending and tax cuts.