in the context on bbc news. a moment our weekly l( artificial in a moment our weekly look at artificial intelligence speaking to do titans of tech to find out how they are adopting ai for the workforce. but we will ask is al also a threat to ourjobs. we will talk all things ai in just a moment, but first let's head to the bbc sports centre, paul scott has all the details. let's start at royal troon, where day one of the 152nd open is drawing to a close, and it was a tough day for many of the world's best golfers. more on that in a moment, but sat on top of the leaderbaord is irishman shane lowry on 5—under. he's a shot clear of

daniel brown, who's not yet completed his first round. two—time major—winnerjustin thomas finished the day 3—under, while there's a chasing pack of five players ready to make a move on 2—under, including englishmanjustin rose. meanwhile, it was a day to forget for rory mcilroy. the world number two made a bogey on the first hole, and things went downhill from there. the northern irishman finished with a 7—over—par 78 to end the day 13 shots behind the lead and facing a tough taskjust to make the cut. i was actually surprised how difficult i felt like the back nine played and i thought we were going to get it a bit easier than we did, but the course was planned tough. the conditions are very difficult and in a winds we have not seen so far this week. just one of the days where i did not adopt a well enough to be conditions. former chelsea boss graham potter says he's "ready" for a return

to management after being heavily linked with the england job following gareth southgate's resignation earlier this week. potter's been out of work since leaving stamford bridge over a year ago, but speaking after being recognised with an honorary doctorate by leeds beckett university, he refused to be drawn on the england vacancy. i don't think today is the day to speak about that. i think gareth has done a fantasticjob. don't think there's anybody in the country that is more respected in football than gareth. i think him and his team led the country and the team in a really good way, and i have a huge respect for him. and i think today is the day to wish him a nice break, because he's earned that, and wish him well and whatever he does in the next part of his career. tadej pogacar has retained his overall lead of more than three minutes with just three stages to go at the tour de france, but stage 18 belonged to an emotional victor campenaerts. moments after claiming the biggest win of his career, the belgian celebrated with a video

call to his partner along with his month—old baby. rafael nadal is through to the quarterfinals at the swedish open after beating britain's cameron norrie in straight sets, but nadal had to work for it. he came back from 4—1 down in the second set to win 6—4, 6—4 as he prepares for the paris olympics. the men's singles there start in nine days�* time. nadal will face mariano navone in the next round. things were a lot more straightforward for holger rune. the 21—year—old eased past marco trun—gelliti the 21—year—old eased past marco trungelliti in straight sets in hamburg, becoming the first dane to reach the last eight of this tournament in the open era where he'll face france's arthur fils. security preparations ahead of the paris olympics are continuing as the start of the games draws ever closer. the opening ceremony is due to take place on the river seine, which provides additional security challenges for authorities. as a result, organisers have erected kilometres of metal fencing with access to certain areas

of the city denied to those without the necessary qr code. ollie pope's sixth test century ensured that england finished day one of the second test against the west indies in a commanding position at trent bridge. after losing the toss and the early wicket of zak crawley, england finished the day all out for 416. the innings was built on pope's ton as he top—scored with 121. in addition, the bens — duckett and stokes — were in the runs, both passing 50. it was a tough day in the field for the west indies, for whom alzarri josoph took three wickets. and that's all the sport for now. you can never you can never have you can never have too many people named ben. you are watching the context on bbc news. it is time for our weekly segment ai decoded. welcome to ai decoded,

that time of the week when we look, in depth, at some of the most eye—catching stories in the world of artificial intelligence. this week, we turn our attention to employment and what impact artificial intelligence will have on the world of work. according to this cnn business article, ai is replacing human tasks faster than you think. more than half of large us firms plan to use ai within the next year to automate tasks previously done by employees in a bid to cut costs, boost profits and make their workers more productive. we'll talk to cisco and salesforce in a moment about their plans to adopt generative ai in the workplace, but what is the potential human cost? the new york times reports generative ai could automate activities equivalent to 300 million full—time jobs globally. openai chief executive sam altman says governments will need to assume the bulk of responsibility in supporting workers ai labour market disruptions. and will employees end up training ai systems only

to be replaced by them? the new york times also looks at how call centre workers are quickly being overtaken by generative ai, and there are now warnings the entire industry could be comprised mostly of ai chatbots in as soon as a year. later in the programme, we'll speak to the writer of both those new york times articles. with me now is our regular ai contributor stephanie hare and also with us, chintan patel, chief technology officer for cisco in the uk and ireland. and joining us from san francisco is nathalie scardino, president and chief people officer at salesforce. really good to have you all on the programme tonight. let me start with the numbers on how manyjobs could be destructed by aim i think you put it at 23% of all jobs will evolve.

it sounds manageable as a number, but when you start to look at the individual roles, it is a huge number. , , . individual roles, it is a huge number. , ., ., ., ., number. this is a transformational area at the — number. this is a transformational area at the moment. _ number. this is a transformational area at the moment. often - number. this is a transformational area at the moment. often with i number. this is a transformational- area at the moment. often with these sorts of— area at the moment. often with these sorts of technological changes we see that we tend to overestimate the impact _ see that we tend to overestimate the impact in _ see that we tend to overestimate the impact in the short term and underestimate the long—term impact. what we _ underestimate the long—term impact. what we see is that the type ofjobs that are _ what we see is that the type ofjobs that are now actually being created as a result — that are now actually being created as a result of ai are very interesting across a broad spectrum of industries and spectrum of professions. we believe that actually— professions. we believe that actually some of the mundane activities — actually some of the mundane activities and tasks that can be automated are being automated are driving _ automated are being automated are driving up _ automated are being automated are driving up productivity for organisations which can only be a good _ organisations which can only be a good thing in its broadest sense. there _ good thing in its broadest sense. there was— good thing in its broadest sense. there was always that concerned that al there was always that concerned that ai will pinch all of ourjobs and we will talk about how these models will talk about how these models will get taught and trained, but people will have a real fear that the technology will put them out of work. ., . ., , , , .,

work. there are certain types of “obs that work. there are certain types of jobs that i _ work. there are certain types of jobs that i think _ work. there are certain types of jobs that i think are _ work. there are certain types of jobs that i think are much - work. there are certain types of jobs that i think are much more | jobs that i think are much more vulnerable than others, if you are a hairdresser or florist or doing something with your hands, accuracy from computers at the moment. ai will actually probably make your life better in terms of invoicing or annoying accounting tasks. if you are working in a call centre, something where yourjob could be automated, that is something you need to look out at the next few years and the openai ceo sam altman said is the government positive job to retrain people taking responsibility for all of the job losses. the government is us so it is really the taxpayer who will have to pick up the bill for this technology putting people out of work. ., ., , ., work. you are putting some of the s stems work. you are putting some of the systems into _ work. you are putting some of the systems into your _ work. you are putting some of the systems into your workplace, - work. you are putting some of the systems into your workplace, i - work. you are putting some of the l systems into your workplace, i think you said you have about 50 al power tools you've deployed within the offices there. what did they look like and what will they do? we have

been in the — like and what will they do? we have been in the business _ like and what will they do? we have been in the business of _ like and what will they do? we have been in the business of predictive i been in the business of predictive ai been in the business of predictive n for— been in the business of predictive n for the — been in the business of predictive n for the past— been in the business of predictive ai for the past decade _ been in the business of predictive ai for the past decade in- been in the business of predictive ai for the past decade in over- been in the business of predictive ai for the past decade in over a l ai for the past decade in over a trillion — ai for the past decade in over a trillion customer— ai for the past decade in over a trillion customer insights - ai for the past decade in over a trillion customer insights are l ai for the past decade in over a . trillion customer insights are built on our— trillion customer insights are built on our platform _ trillion customer insights are built on our platform every— trillion customer insights are built on our platform every single - trillion customer insights are builtl on our platform every single week. now, _ on our platform every single week. now. here — on our platform every single week. now. here we _ on our platform every single week. now. here we are _ on our platform every single week. now, here we are in— on our platform every single week. | now, here we are in the generative ai now, here we are in the generative ai revolution — now, here we are in the generative ai revolution. when— now, here we are in the generative ai revolution. when it _ now, here we are in the generative ai revolution. when it comes to - now, here we are in the generativej ai revolution. when it comes to the employee _ ai revolution. when it comes to the employee experience, _ ai revolution. when it comes to the employee experience, some - ai revolution. when it comes to the employee experience, some of- ai revolution. when it comes to the employee experience, some of the| ai revolution. when it comes to the l employee experience, some of the ai deployments — employee experience, some of the ai deployments are _ employee experience, some of the ai deployments are things _ employee experience, some of the ai deployments are things like, - employee experience, some of the ai deployments are things like, a - employee experience, some of the ai deployments are things like, a lot- deployments are things like, a lot of our— deployments are things like, a lot of our employees— deployments are things like, a lot of our employees are _ deployments are things like, a lot of our employees are spending i deployments are things like, a lot. of our employees are spending time looking _ of our employees are spending time looking at— of our employees are spending time looking at disparate _ of our employees are spending time looking at disparate systems - of our employees are spending time looking at disparate systems to - of our employees are spending time looking at disparate systems to find | looking at disparate systems to find knowledge — looking at disparate systems to find knowledge articles, _ looking at disparate systems to find knowledge articles, access - looking at disparate systems to find knowledge articles, access to - knowledge articles, access to benefits, _ knowledge articles, access to benefits, who _ knowledge articles, access to benefits, who to _ knowledge articles, access to benefits, who to speak - knowledge articles, access to benefits, who to speak to - knowledge articles, access to benefits, who to speak to onl knowledge articles, access to i benefits, who to speak to on the first day, — benefits, who to speak to on the first day, how _ benefits, who to speak to on the first day, how to _ benefits, who to speak to on the first day, how to and _ benefits, who to speak to on the first day, how to and ramp. - benefits, who to speak to on the first day, how to and ramp. nowj benefits, who to speak to on the - first day, how to and ramp. now with al applications — first day, how to and ramp. now with al applications we _ first day, how to and ramp. now with al applications we have _ first day, how to and ramp. now with al applications we have deployed, i ai applications we have deployed, they don't— ai applications we have deployed, they don't have _ ai applications we have deployed, they don't have to _ ai applications we have deployed, they don't have to have _ ai applications we have deployed, they don't have to have to - ai applications we have deployed, they don't have to have to go - ai applications we have deployed, they don't have to have to go to l they don't have to have to go to multiple — they don't have to have to go to multiple systems— they don't have to have to go to multiple systems any— they don't have to have to go to multiple systems any more. - they don't have to have to go to multiple systems any more. in. they don't have to have to go to - multiple systems any more. in fact, some _ multiple systems any more. in fact, some of— multiple systems any more. in fact, some of the — multiple systems any more. in fact, some of the other— multiple systems any more. in fact, some of the other ai _ multiple systems any more. in fact, some of the other ai deployments. multiple systems any more. in fact, . some of the other ai deployments are now serving _ some of the other ai deployments are now serving a — some of the other ai deployments are now serving a predictive _ some of the other ai deployments are now serving a predictive insights - some of the other ai deployments are now serving a predictive insights so i now serving a predictive insights so that if— now serving a predictive insights so that if you — now serving a predictive insights so that if you are — now serving a predictive insights so that if you are a _ now serving a predictive insights so that if you are a new _ now serving a predictive insights so that if you are a new higher, - now serving a predictive insights so that if you are a new higher, it - that if you are a new higher, it will say, — that if you are a new higher, it will say. hey, _ that if you are a new higher, it will say, hey, did _ that if you are a new higher, it will say, hey, did you - that if you are a new higher, it will say, hey, did you know. that if you are a new higher, itl will say, hey, did you know this that if you are a new higher, it. will say, hey, did you know this is where _ will say, hey, did you know this is where you — will say, hey, did you know this is where you should _ will say, hey, did you know this is where you should look _ will say, hey, did you know this is where you should look to - will say, hey, did you know this is where you should look to go - will say, hey, did you know this is where you should look to go for. will say, hey, did you know this is. where you should look to go for your forced _ where you should look to go for your forced day~ _ where you should look to go for your forced day this _ where you should look to go for your forced day. this is _ where you should look to go for your forced day. this is the _ where you should look to go for your forced day. this is the type - where you should look to go for your forced day. this is the type of- forced day. this is the type of information— forced day. this is the type of information you may- forced day. this is the type of information you may need if. forced day. this is the type of. information you may need if you forced day. this is the type of- information you may need if you are a new— information you may need if you are a new manager~ _ information you may need if you are a new manager~ -- _ information you may need if you are a new manager. —— first _ information you may need if you are a new manager. —— first day. - information you may need if you are a new manager. —— first day. how. information you may need if you arei a new manager. —— first day. how do you become — a new manager. —— first day. how do you become a — a new manager. —— first day. how do you become a new—

a new manager. —— first day. how do you become a new manager? - a new manager. —— first day. how do you become a new manager? you i a new manager. —— first day. how do. you become a new manager? you spend enough _ you become a new manager? you spend enough time _ you become a new manager? you spend enough time with — you become a new manager? you spend enough time with your _ you become a new manager? you spend enough time with your teams. _ you become a new manager? you spend enough time with your teams. ai - you become a new manager? you spend enough time with your teams. ai is - enough time with your teams. ai is now serving — enough time with your teams. ai is now serving up _ enough time with your teams. ai is now serving up that _ enough time with your teams. ai is now serving up that information - now serving up that information instead — now serving up that information instead of— now serving up that information instead of employees _ now serving up that information instead of employees having. now serving up that information instead of employees having to| now serving up that information - instead of employees having to look for it _ instead of employees having to look for it those — instead of employees having to look for it. those are _ instead of employees having to look for it. those are some _ instead of employees having to look for it. those are some of— instead of employees having to look for it. those are some of the - for it. those are some of the deployments _ for it. those are some of the deployments we _ for it. those are some of the deployments we have - for it. those are some of the deployments we have seen l for it. those are some of the i deployments we have seen at for it. those are some of the - deployments we have seen at large. i'm deployments we have seen at large. i'm looking — deployments we have seen at large. i'm looking at — deployments we have seen at large. i'm looking at what _ deployments we have seen at large. i'm looking at what that _ deployments we have seen at large. i'm looking at what that has - deployments we have seen at large. i'm looking at what that has allowedj i'm looking at what that has allowed to you to do, free of time and allow staff to do other things, same one quart of employees received a combined 50,000 hours. are you just there for putting those people for working harder or you are you saying, can you go home come you've saved loads of time, how do you square that circle? i saved loads of time, how do you square that circle?— saved loads of time, how do you square that circle? i think like any other benefits _ square that circle? i think like any other benefits of _ square that circle? i think like any other benefits of becoming - square that circle? i think like any other benefits of becoming more | other benefits of becoming more efficient — other benefits of becoming more efficient or — other benefits of becoming more efficient or more _ other benefits of becoming more efficient or more productive, - other benefits of becoming more efficient or more productive, it . other benefits of becoming more j efficient or more productive, it is now spending _ efficient or more productive, it is now spending more _ efficient or more productive, it is now spending more time - efficient or more productive, it is now spending more time on- efficient or more productive, it is i now spending more time on higher value _ now spending more time on higher value impact— now spending more time on higher value impact work— now spending more time on higher value impact work in _ now spending more time on higher value impact work in your - now spending more time on higher value impact work in yourjob. - now spending more time on higher. value impact work in yourjob. those are the _ value impact work in yourjob. those are the core — value impact work in yourjob. those are the core benefits _ value impact work in yourjob. those are the core benefits that _ value impact work in yourjob. those are the core benefits that we - value impact work in yourjob. those are the core benefits that we have i are the core benefits that we have seen _ are the core benefits that we have seen from — are the core benefits that we have seen from our— are the core benefits that we have seen from our teens _ are the core benefits that we have seen from our teens instead - are the core benefits that we have seen from our teens instead of. seen from our teens instead of spending — seen from our teens instead of spending 10% _ seen from our teens instead of spending 10% of _ seen from our teens instead of spending10% of your- seen from our teens instead of spending10% of your time - seen from our teens instead of. spending10% of your time looking for information, _ spending10% of your time looking for information, the _ spending10% of your time looking for information, the information . spending10% of your time looking | for information, the information to do your— for information, the information to do yourjob — for information, the information to do yourjob is _ for information, the information to do yourjob is coming _ for information, the information to do yourjob is coming to— for information, the information to do yourjob is coming to you. - do yourjob is coming to you. something _ do yourjob is coming to you. something it _ do yourjob is coming to you. something it has _ do yourjob is coming to you. something it has been - do yourjob is coming to you. something it has been a - do yourjob is coming to you. - something it has been a massive value-added _ something it has been a massive value—added for— something it has been a massive value—added for our— something it has been a massive value—added for our teams - something it has been a massive value—added for our teams and l something it has been a massive i value—added for our teams and they -ive value—added for our teams and they give us _ value—added for our teams and they give us a _ value—added for our teams and they give us a lot— value—added for our teams and they give us a lot of— value—added for our teams and they

give us a lot of feedback _ value—added for our teams and they give us a lot of feedback on - value—added for our teams and they give us a lot of feedback on it - give us a lot of feedback on it around — give us a lot of feedback on it around the _ give us a lot of feedback on it around the globe _ give us a lot of feedback on it around the globe as- give us a lot of feedback on it around the globe as well. - give us a lot of feedback on it around the globe as well. it l give us a lot of feedback on it| around the globe as well. it is give us a lot of feedback on it around the globe as well. it is such an interesting _ around the globe as well. it is such an interesting point. _ around the globe as well. it is such an interesting point. if— around the globe as well. it is such an interesting point. if you - around the globe as well. it is such an interesting point. if you freeze i an interesting point. if you freeze up an interesting point. if you freeze up time, it makes us more productive, but possibly does not give a —— give us the working beak extra time off that we all want. talk to me about skills because there is a danger that we focus on all of this on what it can't deliver, but frankly it needs people to understand it. not only to monitor it, but the risks, the things like cyber risks that we grow as we had talked to ai. or whether we are treating jobs for the future. —— the rightjobs. we are treating jobs for the future. -- the rightjobs— we are treating jobs for the future. -- the right jobs. -- the right “obs. we can draw a lot of parallels — -- the right jobs. we can draw a lot of parallels from _ -- the right jobs. we can draw a lot of parallels from what _ -- the right jobs. we can draw a lot of parallels from what we _ of parallels from what we have learned — of parallels from what we have learned as a company on the internet being _ learned as a company on the internet being the _ learned as a company on the internet being the heart of the internet for over 40 _ being the heart of the internet for over 40 years and when you think about— over 40 years and when you think about it. — over 40 years and when you think about it, there is no ai without data. _ about it, there is no ai without data, there is no data without the network _ data, there is no data without the network to — data, there is no data without the network to actually connect, act as the connected tissue to the algorithms answering our questions and if— algorithms answering our questions and if you _ algorithms answering our questions and if you cannot secure that and to and if you cannot secure that and to and that—

and if you cannot secure that and to and that is— and if you cannot secure that and to and that is where the trust issue comes— and that is where the trust issue comes in— and that is where the trust issue comes in as _ and that is where the trust issue comes in as you mention around cyber security _ comes in as you mention around cyber security. when we first started the journey _ security. when we first started the journey in — security. when we first started the journey in the internet we saw the opportunity to actually train people around _ opportunity to actually train people around a _ opportunity to actually train people around a programme called cisco networking academy that has been going _ networking academy that has been going for— networking academy that has been going for over 25 years. we trained 20 million — going for over 25 years. we trained 20 million people and 190 countries around _ 20 million people and 190 countries around the — 20 million people and 190 countries around the world. we see the same thing _ around the world. we see the same thing happening again where we have to train— thing happening again where we have to train the _ thing happening again where we have to train the next generation and both— to train the next generation and both the — to train the next generation and both the advanced ai skills but in some _ both the advanced ai skills but in some of— both the advanced ai skills but in some of the fundamental skills that we need _ some of the fundamental skills that we need. we have an increasing divide _ we need. we have an increasing divide between those who have the top and _ divide between those who have the top and skills, but actually perhaps those _ top and skills, but actually perhaps those who — top and skills, but actually perhaps those who do not have the more basic digital— those who do not have the more basic digital skills _ those who do not have the more basic digital skills that we need to. a lot of— digital skills that we need to. a lot of the — digital skills that we need to. a lot of the research from organisations like the future. now which _ organisations like the future. now which talks about the gap that exists — which talks about the gap that exists in — which talks about the gap that exists in society on doing the basics — exists in society on doing the basics so— exists in society on doing the basics. so we have to do both to help— basics. so we have to do both to help society. basics. so we have to do both to help society-— help society. that is the skills . a . _ help society. that is the skills lal. i help society. that is the skills gap- lwonder— help society. that is the skills gap. i wonder whether - help society. that is the skills gap. i wonder whether firms i help society. that is the skills i gap. i wonder whether firms are ready. looking at numbers, and only 7% of companies saying, i guess they know they need to do it but 14% say

they... know they need to do it but 14% say the ., �* . know they need to do it but 14% say the ., �* , ., know they need to do it but 14% say the... ., . they... that's quite a gap. we saw esterda they... that's quite a gap. we saw yesterday the _ they... that's quite a gap. we saw yesterday the prime _ they... that's quite a gap. we saw yesterday the prime minister - yesterday the prime minister discussing _ yesterday the prime minister discussing the _ yesterday the prime minister discussing the plan _ yesterday the prime minister discussing the plan of- yesterday the prime minister discussing the plan of the - yesterday the prime minister. discussing the plan of the king speech— discussing the plan of the king speech of— discussing the plan of the king speech of the _ discussing the plan of the king speech of the new _ discussing the plan of the king speech of the new policies - discussing the plan of the king speech of the new policies of i discussing the plan of the king . speech of the new policies of the government _ speech of the new policies of the government it— speech of the new policies of the government. it was _ speech of the new policies of the government. it was then - speech of the new policies of the government. it was then on - speech of the new policies of the government. it was then on al. i speech of the new policies of the | government. it was then on al. it was a — government. it was then on al. it was a moment— government. it was then on al. it was a moment for— government. it was then on al. it was a moment for the _ government. it was then on al. it - was a moment for the government to say this— was a moment for the government to say this is— was a moment for the government to say this is how— was a moment for the government to say this is how we _ was a moment for the government to say this is how we will _ was a moment for the government to say this is how we will update - was a moment for the government to say this is how we will update the - say this is how we will update the uk education _ say this is how we will update the uk education curriculum - say this is how we will update the uk education curriculum saying. say this is how we will update the | uk education curriculum saying we need _ uk education curriculum saying we need to— uk education curriculum saying we need to train — uk education curriculum saying we need to train everyone _ uk education curriculum saying we need to train everyone up - uk education curriculum saying we need to train everyone up in - uk education curriculum saying we need to train everyone up in al, i uk education curriculum saying we l need to train everyone up in al, who is weak. _ need to train everyone up in al, who is weak. is _ need to train everyone up in al, who is weak. is that— need to train everyone up in al, who is weak, is that the _ need to train everyone up in al, who is weak, is that the companies, - need to train everyone up in al, who is weak, is that the companies, willi is weak, is that the companies, will they put— is weak, is that the companies, will they put their — is weak, is that the companies, will they put their money _ is weak, is that the companies, will they put their money where - is weak, is that the companies, will they put their money where their. they put their money where their mouth— they put their money where their mouth is— they put their money where their mouth is to — they put their money where their mouth is to train _ they put their money where their mouth is to train people - they put their money where their mouth is to train people up? - they put their money where their mouth is to train people up? a l they put their money where their. mouth is to train people up? a week talking _ mouth is to train people up? a week talking about — mouth is to train people up? a week talking about overhauling _ mouth is to train people up? a week talking about overhauling the - mouth is to train people up? a week talking about overhauling the age i talking about overhauling the age curriculum — talking about overhauling the age curriculum from _ talking about overhauling the age curriculum from age _ talking about overhauling the age curriculum from age 5—18 - talking about overhauling the age curriculum from age 5—18 and - talking about overhauling the age l curriculum from age 5—18 and then into universities, _ curriculum from age 5—18 and then into universities, who _ curriculum from age 5—18 and then into universities, who is _ curriculum from age 5—18 and then into universities, who is funding i into universities, who is funding that and — into universities, who is funding that and who _ into universities, who is funding that and who has _ into universities, who is funding that and who has the _ into universities, who is funding that and who has the skills - into universities, who is funding that and who has the skills to l into universities, who is funding i that and who has the skills to even do it? _ that and who has the skills to even do it? ., , ., , that and who has the skills to even doit? ., _, , , ., ., do it? that is a big question. you are always _ do it? that is a big question. you are always our — do it? that is a big question. you are always our guide _ do it? that is a big question. you are always our guide on - do it? that is a big question. you are always our guide on the - are always our guide on the programme for all things ai and i know you have questions for our panel. we have two big players here. what you want to know. but panel. we have two big players here. what you want to know.— panel. we have two big players here. what you want to know. but i want to know is first — what you want to know. but i want to know is first of _ what you want to know. but i want to know is first of all, _ what you want to know. but i want to know is first of all, all _ what you want to know. but i want to know is first of all, all of _ what you want to know. but i want to know is first of all, all of this - know is first of all, all of this automation, saying we will get rid of more banal tasks and leaving

people more free to do value—added tasks, but the value add is going to ceos and shareholders, it is not going back to people, not meaning we can work less for instance. what can we do so we can make it that al is valuable for everyone and notjust the usual people who profit from technology. the usual people who profit from technology-— the usual people who profit from technolo: . h ., ., ., technology. let's throw that to you because you've _ technology. let's throw that to you because you've been _ technology. let's throw that to you because you've been not _ technology. let's throw that to you because you've been not knocking | because you've been not knocking along here. == because you've been not knocking along here-— because you've been not knocking alonl here. ., ., ., , ., along here. -- nodding along. great luestion along here. -- nodding along. great question would _ along here. -- nodding along. great question would you _ along here. -- nodding along. great question would you think— along here. -- nodding along. great question would you think about - along here. -- nodding along. great question would you think about us, | question would you think about us, equality. _ question would you think about us, equality, inclusion, _ question would you think about us, equality, inclusion, how— question would you think about us, equality, inclusion, how do- question would you think about us, equality, inclusion, how do you - question would you think about us, . equality, inclusion, how do you make sure that _ equality, inclusion, how do you make sure that you — equality, inclusion, how do you make sure that you exact _ equality, inclusion, how do you make sure that you exact point, _ equality, inclusion, how do you make sure that you exact point, ai - equality, inclusion, how do you make sure that you exact point, ai is- sure that you exact point, ai is used _ sure that you exact point, ai is used to— sure that you exact point, ai is used to democratize _ sure that you exact point, ai is used to democratize access - sure that you exact point, ai is used to democratize access to| sure that you exact point, ai is- used to democratize access to jobs, access— used to democratize access to jobs, access to _ used to democratize access to jobs, access to different _ used to democratize access to jobs, access to different experiences. - used to democratize access to jobs, access to different experiences. we j access to different experiences. we are focused — access to different experiences. we are focused on— access to different experiences. we are focused on that _ access to different experiences. we are focused on that even _ access to different experiences. we are focused on that even in - access to different experiences. we are focused on that even in our- are focused on that even in our hiring _ are focused on that even in our hiring organisation— are focused on that even in our hiring organisation right - are focused on that even in our hiring organisation right now, i are focused on that even in our. hiring organisation right now, we have _ hiring organisation right now, we have been— hiring organisation right now, we have been leveraging _ hiring organisation right now, we have been leveraging ai - hiring organisation right now, we have been leveraging al to - hiring organisation right now, we have been leveraging al to the l have been leveraging al to the planet— have been leveraging al to the planet for— have been leveraging al to the planet for talent. _ have been leveraging al to the planet for talent. we - have been leveraging al to the planet for talent. we receive l have been leveraging al to the i planet for talent. we receive over 2 million _ planet for talent. we receive over 2 million applications— planet for talent. we receive over 2 million applications every— million applications every single year here — million applications every single year here at— million applications every single year here at sales _ million applications every single year here at sales force - million applications every single year here at sales force and - million applications every single year here at sales force and wel million applications every single - year here at sales force and we want to make _ year here at sales force and we want to make sure — year here at sales force and we want to make sure we _ year here at sales force and we want to make sure we are _ year here at sales force and we want to make sure we are not _ year here at sales force and we want to make sure we are not leaving any| to make sure we are not leaving any talent _ to make sure we are not leaving any talent on _ to make sure we are not leaving any talent on hidden. _

to make sure we are not leaving any talent on hidden. ai _ to make sure we are not leaving any talent on hidden. ai is _ to make sure we are not leaving any talent on hidden. ai is helping - talent on hidden. ai is helping us optimise — talent on hidden. ai is helping us optimise that _ talent on hidden. ai is helping us optimise that. so _ talent on hidden. ai is helping us optimise that. so i _ talent on hidden. ai is helping us optimise that. so i do _ talent on hidden. ai is helping us optimise that. so i do see - talent on hidden. ai is helping us optimise that. so i do see the - optimise that. so i do see the advancements— optimise that. so i do see the advancements of— optimise that. so i do see the i advancements of democratizing optimise that. so i do see the - advancements of democratizing access to ai advancements of democratizing access to al through _ advancements of democratizing access to ai through those _ advancements of democratizing access to ai through those efforts _ advancements of democratizing access to ai through those efforts as - advancements of democratizing access to ai through those efforts as well. - to ai through those efforts as well. but it— to ai through those efforts as well. but it is— to ai through those efforts as well. but it is something _ to ai through those efforts as well. but it is something we _ to ai through those efforts as well. but it is something we think- to ai through those efforts as well. but it is something we think abouti but it is something we think about all of— but it is something we think about all of the — but it is something we think about all of the time _ but it is something we think about all of the time related _ but it is something we think about all of the time related to - but it is something we think about all of the time related to trust - but it is something we think about all of the time related to trust and making _ all of the time related to trust and making sure — all of the time related to trust and making sure that _ all of the time related to trust and making sure that how _ all of the time related to trust and making sure that how you - all of the time related to trust and making sure that how you are - making sure that how you are creating — making sure that how you are creating your— making sure that how you are creating your products, - making sure that how you are creating your products, who l making sure that how you are | creating your products, who is building — creating your products, who is building your— creating your products, who is building your products, - creating your products, who is building your products, is- creating your products, who is building your products, is it i building your products, is it representative _ building your products, is it representative of— building your products, is it representative of the - building your products, is it representative of the world | building your products, is it . representative of the world of societies _ representative of the world of societies of— representative of the world of societies of communities. - representative of the world of societies of communities. all| representative of the world of l societies of communities. all of these _ societies of communities. all of these things _ societies of communities. all of these things are _ societies of communities. all of these things are super- societies of communities. all of these things are super ct. - societies of communities. all of these things are super ct. to i societies of communities. all of these things are super ct. to the desi . n these things are super ct. to the design process. _ these things are super ct. to the design process. i— these things are super ct. to the design process. i second - these things are super ct. to the design process. i second those i design process. i second those comments and i would also say companies like cisco and others have signed _ companies like cisco and others have signed to— companies like cisco and others have signed to the rome call by the vatican— signed to the rome call by the vatican which is centred on the fact we cannot— vatican which is centred on the fact we cannot lose sight of human dignity— we cannot lose sight of human dignity as— we cannot lose sight of human dignity as we develop the systems and as— dignity as we develop the systems and as we — dignity as we develop the systems and as we create a inclusive future for all _ and as we create a inclusive future for all where everyone prospers. at the heart _ for all where everyone prospers. at the heart of— for all where everyone prospers. at the heart of what we are doing like sales— the heart of what we are doing like sales force. — the heart of what we are doing like sales force, at cisco we are focused on building — sales force, at cisco we are focused on building a responsible ai framework but one that extends out and brings— framework but one that extends out and brings large parts of society together— and brings large parts of society together and helps us collectively

progress — together and helps us collectively progress. we together and helps us collectively llroress. ~ ., ~' together and helps us collectively llroress. ~ . ~ ., . progress. we will talk more about this, so progress. we will talk more about this. so much _ progress. we will talk more about this, so much more _ progress. we will talk more about this, so much more to _ progress. we will talk more about this, so much more to discuss - progress. we will talk more about this, so much more to discuss as| progress. we will talk more about i this, so much more to discuss as far asjobs are concerned, this, so much more to discuss as far as jobs are concerned, but really i will play in all of that, but for now thank you. coming up on al decoded. are we destined to teach ai how to do ourjobs? we'll speak to one reporter who's been researching the threat posed to workers and how some are fighting back. around the world and across the uk, this is bbc news.

welcome back to ai decoded. let's now focus on the impact of ai in the workplace. the tech may be able to speed up and automate monotonous or repetitive roles, but there's also a concern that tech like intelligent chatbots could replace roles that have traditionally relied on a human touch like customer service or call centre helplines. stephanie hare, our regular ai contributor and presenter is still with me, and we can now introduce emma goldberg from the new york times.

emma is a business reporter covering workplace culture and the ways work is evolving in a time of social and technological change. good to have you with us. i touched on your report in the introduction to this programme and ice to leave essentially, you have been looking at people who have been finding in the peculiar position of having to train the technology that will ultimately do theirjobs. ultimately do their “obs. exactly. i thinki ultimately do their “obs. exactly. i think l what h ultimately do theirjobs. exactly. i think i what people _ ultimately do theirjobs. exactly. i think i what people look _ ultimately do theirjobs. exactly. i think i what people look at - ultimately do theirjobs. exactly. i think i what people look at what i ultimately do theirjobs. exactly. i| think i what people look at what ai is capable — think i what people look at what ai is capable of, there is no question it will— is capable of, there is no question it will transform the way we all do ourjobs — it will transform the way we all do ourjobs. there was a goldman sachs estimate _ ourjobs. there was a goldman sachs estimate that recently, ai could automate the equivalent of up to 300 million _ automate the equivalent of up to 300 million full—time jobs. that is a loss— million full—time jobs. that is a loss of— million full—time jobs. that is a loss ofjobs. what experts caution is that— loss ofjobs. what experts caution is that it _ loss ofjobs. what experts caution is that it is — loss ofjobs. what experts caution is that it is not going to automate away— is that it is not going to automate away entire jobs. it is going to change — away entire jobs. it is going to change the way they are done. it will come — change the way they are done. it will come in and do particular tasks. — will come in and do particular tasks, probably fasterand will come in and do particular tasks, probably faster and may be better— tasks, probably faster and may be better than humans do them. but then

there are _ better than humans do them. but then there are some roles also where people _ there are some roles also where people wonder, are these jobs going to -o people wonder, are these jobs going to go away— people wonder, are these jobs going to go away entirely? some workers are feeling — to go away entirely? some workers are feeling the effect of that already— are feeling the effect of that already and they are starting to ask. _ already and they are starting to ask. who — already and they are starting to ask, who was going to protect us. what _ ask, who was going to protect us. what entities are going to step in to take _ what entities are going to step in to take responsibility for retraining or providing opportunities for workers whose jobs may be _ opportunities for workers whose jobs may be entirely eliminated by ai technology and call centre workers are clamouring to get answers to that question in particular. we will talk about the _ that question in particular. we will talk about the case _ that question in particular. we will talk about the case study - that question in particular. we will talk about the case study because | talk about the case study because you met with a worker is subject to that but i am interested in the ethics around this. what are employers to ask of their staff. we've invested in all of this new kit, hejust needs we've invested in all of this new kit, he just needs to learn how to do your job, kit, he just needs to learn how to do yourjob, so off you go and teach it. that's not ok, is it? i do yourjob, so off you go and teach it. that's not ok, is it?— it. that's not ok, is it? i think it would be _ it. that's not ok, is it? i think it would be incredibly _ it. that's not ok, is it? i think it| would be incredibly demoralising it. that's not ok, is it? i think it i would be incredibly demoralising if anyone were asked to do that. so employers like to think about the messaging, but also that after plan. so once you've trained up in al to

do your supposedly banal tasks, what are employers offering, higher value, more creative tasks, offering you a new career path, that will involve a lot of money and strategic investment in time for employers to do so. one question i wanted to ask emma since we have her on the programme, a great article she wrote in the new york times, i wonder if you would actually see an increase in union membership for private—sector workers in the united states. the article mentions in something like 6% of workers in the private sector in the us are in unions. two we see something much bigger going on as a response to this? �* ,., ., bigger going on as a response to this? �* ., i. ., ., this? i'm so glad you asked that luestion this? i'm so glad you asked that question because _ this? i'm so glad you asked that question because when - this? i'm so glad you asked that question because when we - this? i'm so glad you asked that question because when we ask. question because when we ask ourselves— question because when we ask ourselves what entities are going to step help _ ourselves what entities are going to step help workers feel feel their 'obs step help workers feel feel their jobs at — step help workers feel feel their jobs at our address because because of ai. _ jobs at our address because because of at. a _ jobs at our address because because of at. a lot _ jobs at our address because because of ai, a lot of workers are saying this is— of ai, a lot of workers are saying this is an — of ai, a lot of workers are saying this is an important role for for unions — this is an important role for for unions to— this is an important role for for unions to play. but i think this is particularly — unions to play. but i think this is particularly the case for workers who don't— particularly the case for workers who don't have as much education or

don't _ who don't have as much education or don't have _ who don't have as much education or don't have the ability that some higher— don't have the ability that some higher income white—collar workers do to— higher income white—collar workers do to easily— higher income white—collar workers do to easily switch between jobs. if some _ do to easily switch between jobs. if some workers see that al is coming for their— some workers see that al is coming for theirjob. — some workers see that al is coming for theirjob, they may very easily be able _ for theirjob, they may very easily be able to— for theirjob, they may very easily be able to shifted to more interesting or exciting or fulfilling roles, but a lot of workers. _ fulfilling roles, but a lot of workers, particularly those without as much _ workers, particularly those without as much education, will have a harder— as much education, will have a harder time doing so so they are going _ harder time doing so so they are going to — harder time doing so so they are going to rely more heavily on their unions to— going to rely more heavily on their unions to advocate for them. particular. _ unions to advocate for them. particular, the role i am seeing unions — particular, the role i am seeing unions play isjust reminding employers that they should be bringing workers to the table to help make in shape decisions around ai is help make in shape decisions around al is used _ help make in shape decisions around al is used in— help make in shape decisions around ai is used in the workplace. it is an argument — ai is used in the workplace. it is an argument that _ ai is used in the workplace. it 3 an argument that people making all of the decisions about al are not the ones who will be affected by that change. it is workers further down the food chain who find their job disappears than the ones sat in the boardroom.— job disappears than the ones sat in the boardroom. exactly. what i am

heafinl the boardroom. exactly. what i am hearing from _ the boardroom. exactly. what i am hearing from a _ the boardroom. exactly. what i am hearing from a lot _ the boardroom. exactly. what i am hearing from a lot of _ the boardroom. exactly. what i am hearing from a lot of workers - the boardroom. exactly. what i am hearing from a lot of workers is - hearing from a lot of workers is that they — hearing from a lot of workers is that they want to feel that their voices— that they want to feel that their voices are — that they want to feel that their voices are part of the process in deciding — voices are part of the process in deciding how ai is going to be used. especially— deciding how ai is going to be used. especially call centre worker, the one i_ especially call centre worker, the one i shadowed, she felt frustrated because _ one i shadowed, she felt frustrated because she felt she was being asked to train— because she felt she was being asked to train her_ because she felt she was being asked to train her replacement whenever she used _ to train her replacement whenever she used in— to train her replacement whenever she used in al tool because the ai she used in al tool because the al was watching her do hijab to the best of— was watching her do hijab to the best of her ability. so what she was asking _ best of her ability. so what she was asking from — best of her ability. so what she was asking from her union was the ability— asking from her union was the ability to— asking from her union was the ability to be at the table making decisions — ability to be at the table making decisions about al along with company— decisions about al along with company executives. this decisions about al along with company executives. this made me think of the — company executives. this made me think of the difference _ company executives. this made me think of the difference between - company executives. this made me | think of the difference between what it is like to work in the united states where you need representation is so low and often opposition with management to models we have seen in france or germany where it is a more collaborative arrangement between unions and management within companies. i almost feel like the model for unions is to be updated for the 21st century as well. how do you see that playing out? kid we see

that cultural change happened not just in the us but even more widely across the globe? it is just in the us but even more widely across the globe?— just in the us but even more widely across the globe? it is an important luestion across the globe? it is an important question coming — across the globe? it is an important question coming at _ across the globe? it is an important question coming at a _ across the globe? it is an important question coming at a moment - across the globe? it is an important question coming at a moment when unions _ question coming at a moment when unions of— question coming at a moment when unions of the us have already been enjoying _ unions of the us have already been enjoying an upswing. so popular sentiment towards unions in america i’ilht sentiment towards unions in america right now— sentiment towards unions in america right now is — sentiment towards unions in america right now is at the highest point it has been — right now is at the highest point it has been in — right now is at the highest point it has been in decades. unions are becoming — has been in decades. unions are becoming much more popular. the number— becoming much more popular. the number of— becoming much more popular. the number of workers that they represent is still quite low, but you are — represent is still quite low, but you are seeing union drives at companies like starbucks and amazon. many companies that had not previously been unionised and industries that had not previously been _ industries that had not previously been unionised like architecture for example _ been unionised like architecture for example. so people are hoping that this momentary shift of power towards — this momentary shift of power towards unions will turn into a more long-term _ towards unions will turn into a more long—term and sustained power moment for unions _ long—term and sustained power moment for unions and that they can then play a _ for unions and that they can then play a role — for unions and that they can then play a role in pushing companies to treat workers well as they are bringing — treat workers well as they are bringing ai treat workers well as they are bringing al to the table. one final

luestion, bringing al to the table. one final question. a _ bringing al to the table. one final question. a lot — bringing al to the table. one final question, a lot of _ bringing al to the table. one final question, a lot of the _ bringing al to the table. one final question, a lot of the time when l bringing al to the table. one final i question, a lot of the time when we talk aboutjob loss as a result of ai, we are looking at lower—level jobs, like a pyramid, or middle level. can we flip it on the its head, sink and we actually replace ceos or executives having ai run companies getting rid of expensive salaries altogether.— salaries altogether. when chatgpt emerl ed salaries altogether. when chatgpt emerged people — salaries altogether. when chatgpt emerged people had _ salaries altogether. when chatgpt emerged people had to _ salaries altogether. when chatgpt emerged people had to throw - salaries altogether. when chatgpt emerged people had to throw out | salaries altogether. when chatgpt i emerged people had to throw out the door any— emerged people had to throw out the door any preconceived notions they had about— door any preconceived notions they had about whatjobs door any preconceived notions they had about what jobs were most at risk because of automation for a long _ risk because of automation for a long time. — risk because of automation for a long time, people thought the most at risk— long time, people thought the most at riskjobs were like long—haul truckers— at riskjobs were like long—haul truckers who would be replaced by self driving cars. now all the sudden — self driving cars. now all the sudden chatgpt kid great shakespearean she experienced sonnets — shakespearean she experienced sonnets and write code and make decisions — sonnets and write code and make decisions so people are realising that you — decisions so people are realising that you have to throw out the door who was _ that you have to throw out the door who was at — that you have to throw out the door who was at risk and say everyjob will be _ who was at risk and say everyjob will be changed and be just hope the workers _ will be changed and be just hope the workers whose jobs are changing have a voice _ workers whose jobs are changing have a voice and _ workers whose jobs are changing have a voice and saying how. the}r

workers whose jobs are changing have a voice and saying how.— a voice and saying how. they will not vote for— a voice and saying how. they will not vote for it _ a voice and saying how. they will not vote for it if _ a voice and saying how. they will not vote for it if they _ a voice and saying how. they will not vote for it if they are - a voice and saying how. they will not vote for it if they are the - a voice and saying how. they will| not vote for it if they are the ones finding theirjobs replaced. a final thought with all of this, briefly, there is a real issue about who is responsible for retraining, is workers going to find that otherjob or employer saying, this is gone but here some help to find something else. ., ., ., ,. here some help to find something else. ., ., .,, ., , . else. you have to be realistic you are not suddenly _ else. you have to be realistic you are not suddenly going _ else. you have to be realistic you are not suddenly going to - else. you have to be realistic you are not suddenly going to get - else. you have to be realistic you are not suddenly going to get an | are not suddenly going to get an engineering degree in two weeks or learn cybersecurity overnight. these are highly complex skills that usually require years of training so this i think will involve, again looking at the danish model of companies and government working together to sponsor re—education and workers, it will take a really long time. this is a total pipit of our economy. time. this is a total pipit of our economy-— time. this is a total pipit of our econom . ., , ., ., economy. rarely get to have you with us lluidin economy. rarely get to have you with us guiding us — economy. rarely get to have you with us guiding us through _ economy. rarely get to have you with us guiding us through this. _ economy. rarely get to have you with us guiding us through this. emma, i us guiding us through this. emma, thank you, we will read closely as your investigations continue. same time next week. bye—bye.

hello. we've seen some very warm weather today, particularly across the south and the east of the uk. it's been a bit more complicated further north and west with more cloud, a little bit of rain, but tomorrow it will be warmer generally and hot for some of us. we could see the highest temperatures of the year so far, 31 celsius possibly. quite a humid feel as well. thejet stream is running to the north of the uk at the moment, allowing us to bring in this feed of warm and humid airfrom the south. but with that increasing humidity, as we head through tonight, we will see quite a lot of mist, and murk, and low cloud rolling into coasts and hills in the west. today's rain, i think, tending to peter out. the best of the clear skies further south and east. certainly not a cold night — in fact, quite a warm one, temperatures holding up in most places between 13—17 celsius. so, into tomorrow morning, quite a warm start, and where we see that sunshine, the best of it across england and wales, while the temperatures really will start to climb. still some of this mist and murk clinging to western coasts. northern ireland and scotland generally seeing a bit more in the way of cloud. and this frontal system will start to bring some outbreaks of rain at later.

temperatures, though, 22 celsius for aberdeen, 25 celsius for liverpool, 30 celsius in london, somewhere in the southeast likely to get to 31 celsius, so well above the seasonal average. but into friday evening, we will see those misty, murky conditions out towards the west and some outbreaks of rain in northern ireland and western scotland, as this frontal system moves its way in. now this front is going to bring a big change through the weekend. it will eventually bring cooler air from the atlantic, but it looks like this front will take its time to move eastwards, so still a chance across eastern parts of england for some pretty warm weather on saturday. some spells of sunshine here. we may see some sharp showers and thunderstorms erupting as we head through the late afternoon. but out towards the west, our frontal system bringing a slow—moving band of heavy rain. underneath the frontal system and behind it, it is going to turn cooler. so, 18 celsius for plymouth, 16 celsius for belfast.

but ahead of that front, i wouldn't be at all surprised if we got up into the high—20s celsius in some parts of eastern england. however, that weather front will then slide its way northwards and eastwards, and all of us will be in the cooler air for sunday. not a bad day weather—wise — some spells of sunshine, just one or two showers, but temperatures at best between 15—22 celsius.

hello, i'm ben thompson. you're watching the context on bbc news. looking frail and unsteady, it is almost painful to watch joe biden making his way home to isolation. there could not be a worse time for him to catch covid. it's really incumbent on people around joe biden to step up at this point and help the president. and help the man they love. we don't know whatjoe biden is going to do. i my democratic sources, - mostly on capitol hill tell me that it's looking more and more likely that it'sjust not sustainable that| he stays at the top of the party. but the next 72 hours are going to be critical — joining me tonight on the panel. leslie vinjamuri, director of the us and americas programme at chatham house and former us federal prosecutorjoe moreno.