Is Technology Contributing to a Better Humanity?

[Music] Hello, my name is Given. I come from Zambia. I'm a student at UWC Atlantic College, a college in the United World colleges movement. I'm sponsored by Pestalozzi to pursue the IB diploma for two years in Wales and have a huge interest in artificial a huge interest in artificial intelligence and the power it has to improve people's lives, especially for the future generations. I'm here today with Priya Lakhani, the founder of CENTURY. Priya, would you please introduce yourself. Thanks so much for having me Given.

I'm Priya. I am the Chief Executive Officer of CENTURY Tech. I am also the company's founder. CENTURY is a company where we blend a company where we blend artificial intelligence technology say artificial intelligence technology say true Ai and a machine that learns by true Ai and a machine that learns by itself with neuroscientific theories and itself with neuroscientific theories and essentially it learns how the brain essentially it learns how the brain learns so you can put any content on it learns so you can put any content on it any curricular and the idea is it can any curricular and the idea is it can spot gaps and misconceptions and then spot gaps and misconceptions and then fill those gaps with personalized fill those gaps with personalized learning and then provide real-time data learning and then provide real-time data insights to uh to educators and then Insights to uh to Educators and then provide overall intelligence to the provide overall intelligence to the school or the multi-academy trust or the school or the multi-academy trust or the college or the University or the college or the University or the publisher publisher um I'm also a non-executive uh director um I'm also a non-executive uh director at the department for digital culture at the department for digital culture media and Sport which is an incredible media and Sport which is an incredible honor to have that role and I also sit honor to have that role and I also sit on the UK government's artificial on the UK government's artificial intelligence Council which is all about intelligence Council which is all about uh uh uh we can make the UK the most attractive we can make the UK the most attractive we can make the UK the most attractive place to build these Technologies and place to build these Technologies and place to build these Technologies and what we need you know for the sort of what we need you know for the sort of what we need you know for the sort of short medium and long term and so so short medium and long term and so so short medium and long term and so so that's me oh yes hearing from that it that's me oh yes hearing from that it that's me oh yes hearing from that it seems and I've seen also from the seems and I've seen also from the seems and I've seen also from the internet you have a huge diverse career internet you have a huge diverse career internet you have a huge diverse career background what have you learned from background what have you learned from background what have you learned from your diverse career background your diverse career background your diverse career background yeah it's a bit mad I think that's a yeah it's a bit mad I think that's a yeah it's a bit mad I think that's a polite way of saying it's a bit crazy polite way of saying it's a bit crazy polite way of saying it's a bit crazy you were a barrister and then you set up you were a barrister and then you set up you were a barrister and then you set up a food company and then Ai and what have a food company and then Ai and what have a food company and then Ai and what have I learned that's a really really good I learned that's a really really good I learned that's a really really good question question question um I suppose there's a couple of things um I suppose there's a couple of things um I suppose there's a couple of things so no matter what I've done so no matter what I've done so no matter what I've done um it's it's always been about this sort um it's it's always been about this sort um it's it's always been about this sort of one sort of North Star this kind of of one sort of North Star this kind of of one sort of North Star this kind of anchor and it's it's about purpose it's anchor and it's it's about purpose it's anchor and it's it's about purpose it's about your why so about your why so about your why so um since I was very young I've always um since I was very young I've always um since I was very young I've always wanted to try and change it was wanted to try and change it was wanted to try and change it was something we've got in common is that um something we've got in common is that um something we've got in common is that um I'm actually East African Indian so my I'm actually East African Indian so my I'm actually East African Indian so my family is from uh yeah my father's from family is from uh yeah my father's from family is from uh yeah my father's from Nairobi and my mum is from Kampala Nairobi and my mum is from Kampala Nairobi and my mum is from Kampala um and I spent a lot of time when I was um and I spent a lot of time when I was um and I spent a lot of time when I was very young very young very young going to uh going to East Africa just going to uh going to East Africa just going to uh going to East Africa just for holidays and to see family members for holidays and to see family members for holidays and to see family members and from a very nice part of Cheshire in and from a very nice part of Cheshire in and from a very nice part of Cheshire in England so during term time I spent time England so during term time I spent time England so during term time I spent time uh in a very nice leafy part of the uh in a very nice leafy part of the uh in a very nice leafy part of the northwest of England and then I spend northwest of England and then I spend northwest of England and then I spend these sort of Summers or winter holidays these sort of Summers or winter holidays these sort of Summers or winter holidays in parts of East Africa and my why since in parts of East Africa and my why since in parts of East Africa and my why since I was very very young my purpose has I was very very young my purpose has I was very very young my purpose has always been how can I try and do always been how can I try and do always been how can I try and do something to try and create opportunity something to try and create opportunity something to try and create opportunity for those that don't have the for those that don't have the for those that don't have the opportunity that I feel very privileged opportunity that I feel very privileged opportunity that I feel very privileged to have had throughout my life and so to have had throughout my life and so to have had throughout my life and so um I've also I've learned looking back um I've also I've learned looking back um I've also I've learned looking back at three very different careers if you at three very different careers if you at three very different careers if you like that actually having that Y is like that actually having that Y is like that actually having that Y is really really important because when really really important because when really really important because when you're you know I had to fight to become you're you know I had to fight to become you're you know I had to fight to become a barrister it wasn't easy especially in a barrister it wasn't easy especially in a barrister it wasn't easy especially in the 90s if you look at barristers they the 90s if you look at barristers they the 90s if you look at barristers they didn't look like me and they usually didn't look like me and they usually didn't look like me and they usually tend to be male white been to Oxbridge tend to be male white been to Oxbridge tend to be male white been to Oxbridge and I was challenging the status quo and I was challenging the status quo and I was challenging the status quo really by trying to get into that really by trying to get into that really by trying to get into that profession at the time and received profession at the time and received profession at the time and received quite a lot of challenge quite a lot of challenge quite a lot of challenge um and then even with the food company um and then even with the food company um and then even with the food company it's very difficult to get to it's very difficult to get to it's very difficult to get to supermarkets and produce something uh supermarkets and produce something uh supermarkets and produce something uh with a proper supply chain and you know with a proper supply chain and you know with a proper supply chain and you know and scale a business like that and then and scale a business like that and then and scale a business like that and then with AI you know I'm not a former Google with AI you know I'm not a former Google with AI you know I'm not a former Google engineer so uh what makes me think that engineer so uh what makes me think that engineer so uh what makes me think that I can build an AI company but with all I can build an AI company but with all I can build an AI company but with all of those things and being again through of those things and being again through of those things and being again through a pandemic and a pandemic and a pandemic and you know you have your.com boom and then you know you have your.com boom and then you know you have your.com boom and then your.com bus and then you've got your your.com bus and then you've got your

your.com bus and then you've got your recessions and austerity periods recessions and austerity periods recessions and austerity periods actually having that little star on that actually having that little star on that actually having that little star on that purpose and that why you know from your purpose and that why you know from your purpose and that why you know from your age younger even all the way through is age younger even all the way through is age younger even all the way through is really important because it anchors you really important because it anchors you really important because it anchors you and it allows you to face adversity and and it allows you to face adversity and and it allows you to face adversity and face these challenges face these challenges face these challenges um and continue to persevere and sort of um and continue to persevere and sort of um and continue to persevere and sort of show that resilience and perseverance show that resilience and perseverance show that resilience and perseverance and resilience the two words that we and resilience the two words that we and resilience the two words that we like to talk about quite a lot in terms like to talk about quite a lot in terms like to talk about quite a lot in terms of how we want to upskill young people of how we want to upskill young people of how we want to upskill young people what kind of skills and traits that we what kind of skills and traits that we what kind of skills and traits that we want them to have in characteristics and want them to have in characteristics and want them to have in characteristics and they're incredibly important when you're they're incredibly important when you're they're incredibly important when you're an entrepreneur because you will always an entrepreneur because you will always an entrepreneur because you will always face challenges they'll always be the face challenges they'll always be the face challenges they'll always be the naysayers the people that say no you naysayers the people that say no you naysayers the people that say no you can't do this or they don't want to fund can't do this or they don't want to fund can't do this or they don't want to fund you to to be able to grow or um or you to to be able to grow or um or you to to be able to grow or um or you'll face a pandemic with everybody you'll face a pandemic with everybody you'll face a pandemic with everybody else and you know face macroeconomic else and you know face macroeconomic else and you know face macroeconomic challenges that we are at the moment so challenges that we are at the moment so challenges that we are at the moment so obviously with the war that's going on obviously with the war that's going on obviously with the war that's going on with the supply chain challenges with the supply chain challenges with the supply chain challenges um with inflation where it is and um with inflation where it is and um with inflation where it is and interest rates it's a challenging interest rates it's a challenging interest rates it's a challenging environment for for businesses at the environment for for businesses at the environment for for businesses at the moment and and having that having that moment and and having that having that moment and and having that having that North Star allows you to continue to North Star allows you to continue to North Star allows you to continue to tell your story allows you to to keep tell your story allows you to to keep tell your story allows you to to keep fighting really to achieve what you want fighting really to achieve what you want fighting really to achieve what you want to believe in so that's one big lesson to believe in so that's one big lesson to believe in so that's one big lesson that I've learned is that how important that I've learned is that how important that I've learned is that how important that is you know it sounds like it's that is you know it sounds like it's that is you know it sounds like it's quite quite quite um fluffy and frivolous and maybe a bit um fluffy and frivolous and maybe a bit um fluffy and frivolous and maybe a bit silly when you're a bit younger but silly when you're a bit younger but silly when you're a bit younger but actually actually actually um it's really really important and the um it's really really important and the um it's really really important and the second is the uh and I think it's a second is the uh and I think it's a second is the uh and I think it's a theme throughout all of the careers but theme throughout all of the careers but theme throughout all of the careers but is um is the focus on disruption and is um is the focus on disruption and is um is the focus on disruption and Innovation these are two things that Innovation these are two things that Innovation these are two things that sometimes make people feel quite sometimes make people feel quite sometimes make people feel quite uncomfortable you know because people uncomfortable you know because people uncomfortable you know because people don't really like the change really they don't really like the change really they don't really like the change really they get really comfortable with uh the way get really comfortable with uh the way get really comfortable with uh the way things are and think what you mean you things are and think what you mean you things are and think what you mean you know that what I'm used to using right know that what I'm used to using right know that what I'm used to using right now might be obsolete in a few years now might be obsolete in a few years now might be obsolete in a few years time um but actually time um but actually time um but actually um Innovation and and disruption in um Innovation and and disruption in um Innovation and and disruption in terms of terms of terms of um thinking outside the box and trying um thinking outside the box and trying um thinking outside the box and trying to solve problems with new tools and to solve problems with new tools and to solve problems with new tools and Technologies is really important Technologies is really important Technologies is really important um and it's something that I'm very um and it's something that I'm very um and it's something that I'm very comfortable with comfortable with comfortable with um and it's something that I think we um and it's something that I think we um and it's something that I think we all need to get comfortable with and all need to get comfortable with and all need to get comfortable with and what I've learned is that Innovation is what I've learned is that Innovation is what I've learned is that Innovation is one of those things that's not a one of those things that's not a one of those things that's not a desirable you know it's it's about desirable you know it's it's about desirable you know it's it's about survival so no business is too small to survival so no business is too small to survival so no business is too small to succeed or too big to fail and we know succeed or too big to fail and we know succeed or too big to fail and we know that from Plenty of stories over the that from Plenty of stories over the that from Plenty of stories over the last five to ten years looking at some last five to ten years looking at some last five to ten years looking at some of the largest Enterprises that we of the largest Enterprises that we of the largest Enterprises that we thought would be around forever and and thought would be around forever and and thought would be around forever and and they've closed their doors you know and they've closed their doors you know and they've closed their doors you know and it's really really sad when that happens it's really really sad when that happens it's really really sad when that happens but actually that failure to innovate but actually that failure to innovate but actually that failure to innovate um is uh is sometimes signing a um is uh is sometimes signing a um is uh is sometimes signing a business's death warrant really so it's business's death warrant really so it's business's death warrant really so it's just so it's you know there's a bunch of just so it's you know there's a bunch of just so it's you know there's a bunch of lessons in terms of culture in terms of lessons in terms of culture in terms of lessons in terms of culture in terms of people that I won't I won't bore you people that I won't I won't bore you people that I won't I won't bore you with today given but but I think those with today given but but I think those with today given but but I think those are the two big threads so is don't be are the two big threads so is don't be are the two big threads so is don't be afraid of innovation don't be afraid to afraid of innovation don't be afraid to afraid of innovation don't be afraid to disrupt because otherwise you'll be disrupt because otherwise you'll be disrupt because otherwise you'll be disrupted so which side do you want to disrupted so which side do you want to disrupted so which side do you want to be on be on be on um and the second is having that North um and the second is having that North um and the second is having that North Star that anchor that that purpose that Star that anchor that that purpose that Star that anchor that that purpose that why as to you know why are you studying why as to you know why are you studying why as to you know why are you studying why are you here from Zambia what do you why are you here from Zambia what do you why are you here from Zambia what do you want to achieve what's important to you want to achieve what's important to you want to achieve what's important to you within and then keeping hold of that you within and then keeping hold of that you within and then keeping hold of that you know and being able to communicate that know and being able to communicate that know and being able to communicate that both internally to yourself but also as both internally to yourself but also as both internally to yourself but also as you grow and as you might build things you grow and as you might build things you grow and as you might build things you might have a team you might have a you might have a team you might have a you might have a team you might have a department you might have a company department you might have a company department you might have a company whatever it is but but retaining that whatever it is but but retaining that whatever it is but but retaining that knowledge as to why you're doing what knowledge as to why you're doing what knowledge as to why you're doing what you're doing that keeps you very engaged you're doing that keeps you very engaged you're doing that keeps you very engaged because also as a leader as people because also as a leader as people because also as a leader as people become leaders it allows you to then become leaders it allows you to then become leaders it allows you to then communicate that and have people follow communicate that and have people follow communicate that and have people follow you and and you know follow your journey you and and you know follow your journey you and and you know follow your journey with you so anyway those are the two with you so anyway those are the two with you so anyway those are the two sort of big things throughout very very sort of big things throughout very very sort of big things throughout very very different careers that I've certainly different careers that I've certainly different careers that I've certainly learned about important well yeah I've learned about important well yeah I've learned about important well yeah I've always wanted to to direct always wanted to to direct always wanted to to direct um at my growth in artificial um at my growth in artificial um at my growth in artificial intelligence and oh I'm researching intelligence and oh I'm researching intelligence and oh I'm researching about artificial intelligence towards about artificial intelligence towards about artificial intelligence towards better in humanity with the work you are better in humanity with the work you are better in humanity with the work you are doing with um Century how are you using doing with um Century how are you using doing with um Century how are you using AI to direct it towards a better for AI to direct it towards a better for AI to direct it towards a better for Humanity that's it I'll read your question so say that's it I'll read your question so say one of centuries um well we've got this one of centuries um well we've got this one of centuries um well we've got this sort of cultural statement when people sort of cultural statement when people sort of cultural statement when people join the company in front of their join the company in front of their join the company in front of their employment contracts that they sign and employment contracts that they sign and employment contracts that they sign and um and one of the key ones there is to um and one of the key ones there is to um and one of the key ones there is to improve the lives of many through improve the lives of many through improve the lives of many through education so I really like the way you education so I really like the way you education so I really like the way you phrase your question because it is about phrase your question because it is about phrase your question because it is about improving humanity and I really believe improving humanity and I really believe improving humanity and I really believe that while artists I know this is not that while artists I know this is not that while artists I know this is not quite the question you've asked and I quite the question you've asked and I quite the question you've asked and I will come to that in a second but you will come to that in a second but you will come to that in a second but you know people like to think about AI know people like to think about AI know people like to think about AI intelligence actually makes people he he intelligence actually makes people he he intelligence actually makes people he he sort of goes straight to the sort of sort of goes straight to the sort of sort of goes straight to the sort of dystopian future tip might not dystopian future tip might not dystopian future tip might not understand it very very well I think understand it very very well I think understand it very very well I think there are definitely threats and ethical there are definitely threats and ethical there are definitely threats and ethical issues that we need to think about and issues that we need to think about and issues that we need to think about and guard ourselves guard ourselves guard ourselves um against but but AI can be fantastic um against but but AI can be fantastic um against but but AI can be fantastic in augmenting What the hi so I always in augmenting What the hi so I always in augmenting What the hi so I always actually say that AI is a perfect tool actually say that AI is a perfect tool actually say that AI is a perfect tool to try and augment human intelligence so to try and augment human intelligence so to try and augment human intelligence so what makes us more human and how can we what makes us more human and how can we what makes us more human and how can we help ourselves how can we help Humanity help ourselves how can we help Humanity help ourselves how can we help Humanity how can we help solve huge problems how can we help solve huge problems how can we help solve huge problems using this technology and so to answer using this technology and so to answer using this technology and so to answer your question the way in which we've your question the way in which we've your question the way in which we've done this in century was we looked at done this in century was we looked at done this in century was we looked at the education system right the education the education system right the education the education system right the education system and we have over half a million system and we have over half a million system and we have over half a million teachers who sign up to do their jobs teachers who sign up to do their jobs teachers who sign up to do their jobs every day every day every day um in this country work really really um in this country work really really um in this country work really really hard they don't go home at 3 30 like hard they don't go home at 3 30 like hard they don't go home at 3 30 like everyone thinks you know they're marking everyone thinks you know they're marking everyone thinks you know they're marking and planning every evening and and their and planning every evening and and their and planning every evening and and their jobs are really really difficult jobs are really really difficult jobs are really really difficult and they work really really hard to try and they work really really hard to try and they work really really hard to try and differentiate and personalize for and differentiate and personalize for and differentiate and personalize for every student but that's really really every student but that's really really every student but that's really really impossible to do when you've got a class impossible to do when you've got a class impossible to do when you've got a class of 15 or 20 and obviously in many cases of 15 or 20 and obviously in many cases of 15 or 20 and obviously in many cases 30 35 in a classroom you can't possibly 30 35 in a classroom you can't possibly 30 35 in a classroom you can't possibly as one human teacher differentiate for as one human teacher differentiate for as one human teacher differentiate for every student when they're struggling every student when they're struggling every student when they're struggling when they need further stretch try and when they need further stretch try and when they need further stretch try and keep them engaged it's difficult to do keep them engaged it's difficult to do keep them engaged it's difficult to do it's an impossible task and to do for it's an impossible task and to do for it's an impossible task and to do for everyone so with Century what we've done everyone so with Century what we've done everyone so with Century what we've done is we've combined is we've combined is we've combined um artificial intelligence and when I um artificial intelligence and when I um artificial intelligence and when I talk about AI I don't talk about the talk about AI I don't talk about the talk about AI I don't talk about the marketing AI term that people like to marketing AI term that people like to marketing AI term that people like to use they have 40 of companies according use they have 40 of companies according use they have 40 of companies according to the financial times use AI as a to the financial times use AI as a to the financial times use AI as a marketing term and it's not a true AI marketing term and it's not a true AI marketing term and it's not a true AI I'm talking about a machine that's I'm talking about a machine that's I'm talking about a machine that's learning by itself that's getting learning by itself that's getting learning by itself that's getting smarter with every bit of data that it smarter with every bit of data that it smarter with every bit of data that it is able to learn from itself and then is able to learn from itself and then is able to learn from itself and then make uh make decisions so we've got a make uh make decisions so we've got a make uh make decisions so we've got a machine that can track machine that can track machine that can track um proprietary Telemetry system that um proprietary Telemetry system that um proprietary Telemetry system that tracks the interactions of students on tracks the interactions of students on tracks the interactions of students on our technology platform so you go in and our technology platform so you go in and our technology platform so you go in and you learn maths or geography or law you you learn maths or geography or law you you learn maths or geography or law you know whatever it is and it could be in know whatever it is and it could be in know whatever it is and it could be in English it could be in French it could English it could be in French it could English it could be in French it could be in Spanish it could be in Arabic when be in Spanish it could be in Arabic when be in Spanish it could be in Arabic when you're learning it's tracking your you're learning it's tracking your you're learning it's tracking your interactions interactions interactions it will then learn by itself through it will then learn by itself through it will then learn by itself through machine learning and through deep machine learning and through deep machine learning and through deep learning so what we call Knowledge learning so what we call Knowledge learning so what we call Knowledge tracing tracing tracing um and it will learn well you're um and it will learn well you're um and it will learn well you're struggling in this area because actually struggling in this area because actually struggling in this area because actually the machine is identified accurately the machine is identified accurately the machine is identified accurately it's because you're struggling in a it's because you're struggling in a it's because you're struggling in a prerequisite foundational area and then prerequisite foundational area and then prerequisite foundational area and then the machine will give you that the machine will give you that the machine will give you that foundational area so that then you can foundational area so that then you can foundational area so that then you can progress and you don't get stuck and it progress and you don't get stuck and it progress and you don't get stuck and it will do it by itself so for a teacher to will do it by itself so for a teacher to will do it by itself so for a teacher to be able to do that in the classroom in be able to do that in the classroom in be able to do that in the classroom in real time with you know 30 kids in front real time with you know 30 kids in front real time with you know 30 kids in front of them is really really difficult and of them is really really difficult and of them is really really difficult and challenging to even know that somebody challenging to even know that somebody challenging to even know that somebody is struggling if they put their hand up is struggling if they put their hand up is struggling if they put their hand up um is really really difficult and we um is really really difficult and we um is really really difficult and we know most kids many kids do put their know most kids many kids do put their know most kids many kids do put their hands up right hands up right hands up right um to say that they're struggling and so um to say that they're struggling and so um to say that they're struggling and so the machine helps the humans by the machine helps the humans by the machine helps the humans by identifying how you're doing and and identifying how you're doing and and identifying how you're doing and and picking up you know where where you picking up you know where where you picking up you know where where you might be stuck and and actually might be stuck and and actually might be stuck and and actually pinpointing you know sort of laser focus pinpointing you know sort of laser focus pinpointing you know sort of laser focus accuracy what's going with it where you accuracy what's going with it where you accuracy what's going with it where you need help well the machine then does is need help well the machine then does is need help well the machine then does is we look at a second problem in education we look at a second problem in education we look at a second problem in education that's that's that's delivery of education and personalize delivery of education and personalize delivery of education and personalize for every child and I am and you know to for every child and I am and you know to for every child and I am and you know to the broader question of how it helps the broader question of how it helps the broader question of how it helps Humanity while education is incredibly Humanity while education is incredibly Humanity while education is incredibly important if not one of the most important if not one of the most important if not one of the most important sectors in the world it important sectors in the world it important sectors in the world it affects absolutely everything it affects affects absolutely everything it affects affects absolutely everything it affects affects everyone you can see how affects everyone you can see how affects everyone you can see how Healthcare is related to education and Healthcare is related to education and Healthcare is related to education and you can see how everything is related to you can see how everything is related to you can see how everything is related to education so this is all about promoting education so this is all about promoting education so this is all about promoting that personalized education and that personalized education and that personalized education and improving outcomes right improving improving outcomes right improving improving outcomes right improving outcomes for every student so that the outcomes for every student so that the outcomes for every student so that the idea is that you have opportunity idea is that you have opportunity idea is that you have opportunity opportunity and choice when you leave opportunity and choice when you leave opportunity and choice when you leave formal education so it's making that formal education so it's making that formal education so it's making that education delivery better but the second education delivery better but the second education delivery better but the second point then that we identified that point then that we identified that point then that we identified that needed uh fixing if you like with with needed uh fixing if you like with with needed uh fixing if you like with with the teacher problem right so teachers the teacher problem right so teachers the teacher problem right so teachers spend spend spend more than half of their time given more than half of their time given more than half of their time given marking assessing trying to figure out marking assessing trying to figure out marking assessing trying to figure out what's going on so I like to say they're what's going on so I like to say they're what's going on so I like to say they're teachers by day and data analysts by teachers by day and data analysts by teachers by day and data analysts by night right so they go home and they're night right so they go home and they're night right so they go home and they're marking your work and everyone thinks marking your work and everyone thinks marking your work and everyone thinks our teacher's gone home actually they're our teacher's gone home actually they're our teacher's gone home actually they're usually then planning the next lesson usually then planning the next lesson usually then planning the next lesson they're trying to figure out who doesn't they're trying to figure out who doesn't they're trying to figure out who doesn't understand what but you have to then you understand what but you have to then you understand what but you have to then you have to create a test you have to give have to create a test you have to give have to create a test you have to give out a test you have to mark the test 30 out a test you have to mark the test 30 out a test you have to mark the test 30 times you have to figure out who's got times you have to figure out who's got times you have to figure out who's got things wrong why they've got things things wrong why they've got things things wrong why they've got things wrong I think this is a lot of work wrong I think this is a lot of work wrong I think this is a lot of work right to do for every single topic and right to do for every single topic and right to do for every single topic and our curriculum is huge if you look at our curriculum is huge if you look at our curriculum is huge if you look at our national curriculum it's the size of our national curriculum it's the size of our national curriculum it's the size of The Hobbit in words it's the same size The Hobbit in words it's the same size The Hobbit in words it's the same size it's absolutely massive it's bloated it's absolutely massive it's bloated it's absolutely massive it's bloated curriculum and so teachers have to do curriculum and so teachers have to do curriculum and so teachers have to do all of that so while the system's all of that so while the system's all of that so while the system's personalizing for students students personalizing for students students personalizing for students students logging in because we use big data in logging in because we use big data in logging in because we use big data in you know it's big data and ai go hand in you know it's big data and ai go hand in you know it's big data and ai go hand in hand we then just analyze that data and hand we then just analyze that data and hand we then just analyze that data and provide dashboards for teachers so the provide dashboards for teachers so the provide dashboards for teachers so the idea as a teacher actually doesn't have idea as a teacher actually doesn't have idea as a teacher actually doesn't have to mark anything a teacher can log into to mark anything a teacher can log into to mark anything a teacher can log into the dashboard with one click and it the dashboard with one click and it the dashboard with one click and it would tell them who's struggling where would tell them who's struggling where would tell them who's struggling where why so the teacher then can make that why so the teacher then can make that why so the teacher then can make that human intervention so I don't think AI human intervention so I don't think AI human intervention so I don't think AI will ever replace humans uh in the will ever replace humans uh in the will ever replace humans uh in the classroom we're not going to be taught classroom we're not going to be taught classroom we're not going to be taught by a bunch of you know sort of Robotics by a bunch of you know sort of Robotics by a bunch of you know sort of Robotics and AI all kind of messed up yeah um are there any risks with um up yeah um are there any risks with um AI uh I've seen you are talking about AI uh I've seen you are talking about AI uh I've seen you are talking about the data part as well so are there any the data part as well so are there any the data part as well so are there any risks even Beyond data is it possible risks even Beyond data is it possible risks even Beyond data is it possible that artificial intelligence could that artificial intelligence could that artificial intelligence could become more powerful and better than become more powerful and better than become more powerful and better than humans as we had in terms of automation humans as we had in terms of automation humans as we had in terms of automation as well so I was thinking of this as well so I was thinking of this as well so I was thinking of this scenario scenario scenario um um um the machine is helping the teacher the machine is helping the teacher the machine is helping the teacher then yeah the machine does 80 of what then yeah the machine does 80 of what then yeah the machine does 80 of what the teacher is doing and one of the the teacher is doing and one of the the teacher is doing and one of the issues we have is issues we have is issues we have is lack of teachers so if the machine is lack of teachers so if the machine is lack of teachers so if the machine is helping what eighty percent if the helping what eighty percent if the helping what eighty percent if the machine is doing eight percent of the machine is doing eight percent of the machine is doing eight percent of the job that the teacher is doing job that the teacher is doing job that the teacher is doing it might mean later on won't need as it might mean later on won't need as it might mean later on won't need as many teachers so it might solve the many teachers so it might solve the many teachers so it might solve the problem of our teacher need so in a way problem of our teacher need so in a way problem of our teacher need so in a way take out I think the questions yes is take out I think the questions yes is take out I think the questions yes is that possible that possible that possible yeah well I think that the roles will yeah well I think that the roles will yeah well I think that the roles will change I think that we do have a change I think that we do have a change I think that we do have a shortage of teachers where 40 000 shortage of teachers where 40 000 shortage of teachers where 40 000 teachers short teachers short teachers short um within the next few years and there's um within the next few years and there's um within the next few years and there's no magic wand that's being waived I no magic wand that's being waived I no magic wand that's being waived I think what will happen is that there think what will happen is that there think what will happen is that there will be different roles in schools and will be different roles in schools and will be different roles in schools and in colleges so you will have expert in colleges so you will have expert in colleges so you will have expert teachers and subject experts who are the teachers and subject experts who are the teachers and subject experts who are the teachers that you know today I think teachers that you know today I think teachers that you know today I think then you will have a layer of what we then you will have a layer of what we then you will have a layer of what we call sort of facilitators or coaches who call sort of facilitators or coaches who call sort of facilitators or coaches who are not subject experts but they will be are not subject experts but they will be are not subject experts but they will be using the data from a machine like this using the data from a machine like this using the data from a machine like this to make targeted interventions and to to make targeted interventions and to to make targeted interventions and to facilitate the sort of delivery of facilitate the sort of delivery of facilitate the sort of delivery of teaching and learning and then obviously teaching and learning and then obviously teaching and learning and then obviously you've got the student so again though you've got the student so again though you've got the student so again though that's about augmenting it's about using that's about augmenting it's about using that's about augmenting it's about using the tool to augment and support the the tool to augment and support the the tool to augment and support the humans if you like I mean you started humans if you like I mean you started humans if you like I mean you started the question with you know what about the question with you know what about the question with you know what about like major risks and data and there's like major risks and data and there's like major risks and data and there's obviously that as well right so we need obviously that as well right so we need obviously that as well right so we need to ensure that when these technology to ensure that when these technology to ensure that when these technology companies are collecting data on companies are collecting data on companies are collecting data on students we've got to make sure there is students we've got to make sure there is students we've got to make sure there is an algorithm bias we have to make sure an algorithm bias we have to make sure an algorithm bias we have to make sure that you know it's not learning that oh that you know it's not learning that oh that you know it's not learning that oh you know here is a female who is Indian you know here is a female who is Indian you know here is a female who is Indian from Indian origin from Indian origin from Indian origin um and here is the demographic the um and here is the demographic the um and here is the demographic the economic background of her parents economic background of her parents economic background of her parents therefore this is maybe how she learns therefore this is maybe how she learns therefore this is maybe how she learns because it's learned that other kids because it's learned that other kids because it's learned that other kids have the same demographics learn in that have the same demographics learn in that have the same demographics learn in that way you've got to make sure that you way you've got to make sure that you way you've got to make sure that you separate the personal data from the separate the personal data from the separate the personal data from the behavioral learning that the machine is behavioral learning that the machine is behavioral learning that the machine is creating which is something that Century creating which is something that Century creating which is something that Century has done so we have separated has done so we have separated has done so we have separated architecture to avoid that bias but we architecture to avoid that bias but we architecture to avoid that bias but we need to know that all companies building need to know that all companies building need to know that all companies building AI in this space are doing that can you AI in this space are doing that can you AI in this space are doing that can you imagine an AI That's used for a imagine an AI That's used for a imagine an AI That's used for a different purpose given say for example different purpose given say for example different purpose given say for example imagine an AI That's recommending jobs imagine an AI That's recommending jobs imagine an AI That's recommending jobs right and imagine if that AI trolls right and imagine if that AI trolls right and imagine if that AI trolls LinkedIn and it looks at the people with LinkedIn and it looks at the people with LinkedIn and it looks at the people with certain jobs now we know today we certain jobs now we know today we certain jobs now we know today we absolutely know that certain sectors are absolutely know that certain sectors are absolutely know that certain sectors are not representative of society so if a not representative of society so if a not representative of society so if a machine decided to troll LinkedIn then machine decided to troll LinkedIn then machine decided to troll LinkedIn then wouldn't that then be reinforcing wouldn't that then be reinforcing wouldn't that then be reinforcing certain bias into recommendations it certain bias into recommendations it certain bias into recommendations it might recommend to maybe you or me you might recommend to maybe you or me you might recommend to maybe you or me you know who look a certain way who are from know who look a certain way who are from know who look a certain way who are from a certain place so so what we have to a certain place so so what we have to a certain place so so what we have to we've got to be aware of the risks of we've got to be aware of the risks of we've got to be aware of the risks of the data how it is the data shared whose the data how it is the data shared whose the data how it is the data shared whose data is it essentially we're very firmly data is it essentially we're very firmly data is it essentially we're very firmly of the and take the start of the data of the and take the start of the data of the and take the start of the data with the students and obviously the with the students and obviously the with the students and obviously the school was actually through a proxy sort school was actually through a proxy sort school was actually through a proxy sort of give access to that when they sign up of give access to that when they sign up of give access to that when they sign up to using our program but who does the to using our program but who does the to using our program but who does the actual person who does that belong to actual person who does that belong to actual person who does that belong to um it is very very clear for us but we um it is very very clear for us but we um it is very very clear for us but we have to ask those questions and it's one have to ask those questions and it's one have to ask those questions and it's one of the reasons why with um Sarah Anthony of the reasons why with um Sarah Anthony of the reasons why with um Sarah Anthony Selden who is uh he was head teacher at Selden who is uh he was head teacher at Selden who is uh he was head teacher at Wellington College Wellington College Wellington College um and he was also Vice Chancellor at um and he was also Vice Chancellor at um and he was also Vice Chancellor at Buckingham University and Professor Rose Buckingham University and Professor Rose Buckingham University and Professor Rose lackin who is um from The Institute of lackin who is um from The Institute of lackin who is um from The Institute of education at UCL and we co-created uh education at UCL and we co-created uh education at UCL and we co-created uh The Institute of ethical Ai and The Institute of ethical Ai and The Institute of ethical Ai and education and it was chaired by Lord Tim education and it was chaired by Lord Tim education and it was chaired by Lord Tim Clement James who at the moment is Clement James who at the moment is Clement James who at the moment is actually I believe he's chairing The actually I believe he's chairing The actually I believe he's chairing The Joint Committee for the online online Joint Committee for the online online Joint Committee for the online online safety bill online Hans Bill and that's safety bill online Hans Bill and that's safety bill online Hans Bill and that's going through a government right now going through a government right now going through a government right now he's in the Lords and the reason we did he's in the Lords and the reason we did he's in the Lords and the reason we did it was to create a framework of what it was to create a framework of what it was to create a framework of what should you be looking at as an should you be looking at as an should you be looking at as an educational institution and what educational institution and what educational institution and what questions should you be asking of AI questions should you be asking of AI questions should you be asking of AI suppliers to know that you are then suppliers to know that you are then suppliers to know that you are then putting technology into your school or putting technology into your school or putting technology into your school or University or whatever and you're University or whatever and you're University or whatever and you're guarding against the risks that that you guarding against the risks that that you guarding against the risks that that you sort of pointed out might exist sort of pointed out might exist sort of pointed out might exist thank you what gives you hope that that thank you what gives you hope that that thank you what gives you hope that that visual intelligence will contribute visual intelligence will contribute visual intelligence will contribute towards the good for Humanity and our towards the good for Humanity and our towards the good for Humanity and our planet planet planet yeah and that's a big question isn't it yeah and that's a big question isn't it yeah and that's a big question isn't it I I'm an optimist um look I this I I'm an optimist um look I this I I'm an optimist um look I this technology was created for good technology was created for good technology was created for good our sufficient intelligence was created our sufficient intelligence was created our sufficient intelligence was created for good AI Technologies and systems for good AI Technologies and systems for good AI Technologies and systems different new technologies not even AI different new technologies not even AI different new technologies not even AI usually they're all created by good usually they're all created by good usually they're all created by good people for good they're created by people for good they're created by people for good they're created by people to solve problems they're created people to solve problems they're created people to solve problems they're created by people by people by people um and further developed by people to um and further developed by people to um and further developed by people to advance us right to try and solve advance us right to try and solve advance us right to try and solve problems if you look at just how problems if you look at just how problems if you look at just how artificial intelligence is used in artificial intelligence is used in artificial intelligence is used in healthcare right and in terms of how healthcare right and in terms of how healthcare right and in terms of how machine learning is used for example in machine learning is used for example in machine learning is used for example in pattern recognition and symptoms to try pattern recognition and symptoms to try pattern recognition and symptoms to try and pre-diagnose you know very very and pre-diagnose you know very very and pre-diagnose you know very very early early early um cancer and and to look at how men um cancer and and to look at how men um cancer and and to look at how men Pharmaceuticals you know medicine is is Pharmaceuticals you know medicine is is Pharmaceuticals you know medicine is is effective so using technology is to be effective so using technology is to be effective so using technology is to be able to preempt to predict you can see able to preempt to predict you can see able to preempt to predict you can see how these Technologies are used to try how these Technologies are used to try how these Technologies are used to try and solve very Vapor problems and the and solve very Vapor problems and the and solve very Vapor problems and the idea is that we want to advance Humanity idea is that we want to advance Humanity idea is that we want to advance Humanity we want to try and you know level the we want to try and you know level the we want to try and you know level the playing field in many areas but with all playing field in many areas but with all playing field in many areas but with all of these Technologies you'll always have of these Technologies you'll always have of these Technologies you'll always have Bad actors and I think that you know Bad actors and I think that you know Bad actors and I think that you know that's just where we need to be careful that's just where we need to be careful that's just where we need to be careful that's where we need regulations that's that's where we need regulations that's that's where we need regulations that's where we need to help to understand what where we need to help to understand what where we need to help to understand what you know preempts actually what those you know preempts actually what those you know preempts actually what those Bad actors could be thinking about so so Bad actors could be thinking about so so Bad actors could be thinking about so so I am a fundamental believer that these I am a fundamental believer that these I am a fundamental believer that these Technologies are there and they're being Technologies are there and they're being Technologies are there and they're being developed for good and we should developed for good and we should developed for good and we should continue to develop them for good continue to develop them for good continue to develop them for good because you continue to invest them because you continue to invest them because you continue to invest them don't be scared of them and say fearful don't be scared of them and say fearful don't be scared of them and say fearful that you don't want to get involved that you don't want to get involved that you don't want to get involved because actually every one of us has an because actually every one of us has an because actually every one of us has an individual perspective to offer as to individual perspective to offer as to individual perspective to offer as to how these Technologies could help us in how these Technologies could help us in how these Technologies could help us in our daily lives and our families and we our daily lives and our families and we our daily lives and our families and we just need to safegua

2023-04-21 23:29

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