So, hi, everybody. And yeah, thank you so much for voting to make uh this talk public to everybody uh and to being here today.So I'm very pleased to join uh you to today to talk about the topic that is I am so passionate about that is uh how to make the world a better place uh through technology. And uh I am a data scientist and machine learning engineer and I've been dedicating my career in the past years uh to A I applied to social impact. So uh maybe uh like me, uh some of you also grew up in the nineties and um as, as I was a kid, I was super excited about the future about robots and futuristic cities and flying cars and all the cool stuff. And uh well, uh we know that we are uh for uh over two decades in the 21st century and it is not necessarily the case. Uh However, of course, we managed to do uh quite a cool stuff with science such as like putting robots on the surface of another planet just to explore it and so on. But of course, we have technology everywhere. And uh we use technology on a daily basis.

Uh for the most mundane things like uh taking pictures, move around the city and among other technologies, uh there's also a I that can help us to uh for example, recommend items that you want to buy or to predict whether uh uh in the, that we have as a spam or not or if we are uh there is some fraud in our credit cards.

And uh that's all very nice. But of course, that um we can still ask ourselves uh what if we could actually use uh this uh so such powerful uh tool like a I to actually address other social problems in our society. So as you may know, almost all nations in the world, like around 100 and 93 nations in the world agreed uh to uh help to reach the Sustainable Development goals by 2030. So uh these are uh the those sustainable development goals are a collection of signed and interconnected goals uh to reach uh what, what it's called like a blueprint to achieve a better and more sustainable future for all. And those goals go uh from uh healthcare, education uh addressing poverty among many other things. So these are like the most um concerning topics of our time and you can think like how we can actually use technology to address them. Uh But maybe the first question we need to ask is what is society. Like, what do you understand as society? And uh when you think about it, it has some ingredients. Like here I put a couple of them and that doesn't mean that of course they exist in all societies and so on.

But like, uh we all have like, uh when we had like our normal lives and even nowadays, uh during the, the COVID times, we have, you know, like people to help us to, to, to keep us safe as police and, and I don't know, firefighters. And uh we also have like uh places that provide us with services such as supermarkets or like the post office and um town hall and so on. And we have of course like infrastructure such as like uh to provide us um a supply of energy or gas or water. And we have like places where we live and so on. And um when we think of all of this uh society, we can still think that we can cluster all of these elements of society into a more uh general topic like into a more general topic. Sorry. And here I am showing just a couple of them like uh just as an example of how we can society in terms of all those clusters. And um there is this one ingredient that is still missing like when you think about uh society and this is the challenges that we have in it. So, in the 21st century, we've been, we, we came to the 21st century.

We have a lot of problems that we had before. And there are also like a piling up, I would say. And uh for example, we have the topic of overpopulation and it is estimated that by 2050 we're gonna have 9.7 billion people on earth. And uh that brings a lot of limitations to our resources and a lot of, for example, conflict, uh there are conflicts that we already have actually like a manmade conflicts that are created um through a like a societal political differences. And uh that can, for example, lead to the refugee crisis that like um I'm trying to show here uh down the bottom to the right. And um this, this refugee crisis is also something that uh can become even worse with uh the problem of climate change as well. So we have uh nowadays, the climate change uh challenge. We, one of the biggest ones together with the environmental crisis that we have at the moment. And uh this is putting our planet to the limit. So uh we have like co2 emissions, we have plastic pollution and we also have of course, like a risk of extinction of many species that are crucial to keep the biodiversity in our planet. And um at the same time, we still a lot of nowadays, we have never been in such an era of our world in which we have access to so much information and technology. And at the same time, funnily enough, we are getting to the era of misinformation.

So nowadays, we're reaching the point that uh every thing that is on the news uh is more like there is more uh fake information on the news than actually real information. So we have like all those challenges um present in our society, apart from all the ingredients that we need society to work. And uh but there's another ingredient uh to consider this ingredient is technology. And this is, this is what I'm trying to convince you all of this talk today. And uh my idea with this talk is to ask you the question, how we as uh people from the technology fields, from my P like A I but in of you in other fields as well as as well in technology, how we can tackle all those problems within those parts of society with technology? So there are many applications uh of A I for, you know, like companies to just uh uh improve production or just make uh companies earn more money. But uh the idea is that like, how can we also use uh technologies to make the world a better place through? For example, automation of um or even like a help with all those problems that we have that need to be sol solved urgently.

So many of the problems that I mentioned need to be solved like a, just for example, the climate crisis because uh we don't really have uh time and uh that's the power, at least that I see the potential that is re automate many of those problems that we have. And um just try to us to like a safe time that is crucial to solve these problems. So in the next minute, be teasing you a little bit with just a couple of those of how we can use A I to actually make the world a better place. Of course, there are many other applications and uh if you're interested, you're more than welcome to, you know, reach out and talk to me and so on and also like many of my other friends that are also in this kind of link in this um in this challenge together. So um I will start with health care. Uh Healthcare is associated with sustainable development goal number three, that is about uh well being and health. And uh and in this topic of health care, I can play a massive role such as for example, um automating and speeding up processes for, for example, drug discovery. So drug discovery is a matter of trying to and which uh of a drug can be uh useful to create a new one that might be more efficient and so on.

And this is exactly the the kind of like thing that A I is very efficient at and data analysis and just like automating processes, just analyzing several things at the same time. And so so for this data analysis and in machine learning as well can be very helpful. And when it comes to diagnosis, uh computer vision, there is one technique of A I that is just like the ability of actually uh process images and extract information from images uh together with deep learning that is um and machine learning, there are also other A I techniques uh can be crucial, understand the diagnosis faster.

So they are extremely powerful techniques. And so just to mention of examples like uh for cancer, uh A I can detect cancer, like uh we've even the image here is that uh that A I can detect uh breast tumor four years before it was developed. And um this is a study from the Google Health and this is uh the publication. And um it's like now we know that A I can uh detect a cancer more accurately than doctors at this point in time. And this can help reducing false positives and also predict the chances of a patient to live. And of course, if you can predict this faster, then we can treat the patient faster. And this can be crucial whether someone will survive or not. And um extremely important um to uh help uh the doctors to just make an automation of their tests. So for example, instead of they have to look into several images, they can actually spend their time um like they can have the A I doing this for them and then they can really spend their time um focusing on uh on research on, on things that are more um we need more the intellect and their act knowledge.

So in this sense, A I cannot replace doctors, of course, but it can be an O I let's have to say. And uh just to mention in an example, this is a work that me and my colleagues here did. Uh we want the A I healthcare hackathon and uh by creating an engine that uh not only detects uh fractures in X ray images, but it also generates a report. So this is an entire automation of the medical process that would uh that is still in many place, is still done like very manually and that it requires someone to take out the image and look and, and write a report by hand sometimes even. So this is an entire commission of the process. And this is crucial. So for example, to make doctors prioritize patients and just be faster through the entire process, which for example, now in COVID times is extremely important. So that's it for help. Um Oops, sorry, this shouldn't be here. Uh We can also talk about uh how A I can help to make the world a cleaner and greener uh place uh by having just more sustainable solutions. So just to mention a couple of them, we can think of computer vision again and a geospatial analysis to, for example, uh help uh detecting animals and counting them.

And this is important because as I mentioned, we have like this, uh several animal animals in our species are in the risk of extinction. And um by for example, being able to track animals like a tracking device on, on those uh endangered species. And then we can see whether they are um safe, for example, whether there are other predators around and so on this way, we can protect them. And uh so for example, you can have drones that come and just uh see like that doesn't disturb them so much that they can just see whether they are there and so on. And by that, they can, they recognize the images of the animals and um and just count uh how many of them are there if they reproduce and so on. And uh we also have computer vision that can also be used to automate installations of solar panels. For example, uh you can just like uh see images of rooftops from the top or from satellite images and use this account. And uh of course, um it's also we can also have like a A I for helping us to sort our trash. For example, you can take a picture of, of your trash and like, for example, if you have a bottle of water or something, and then I can help you to like with machine learning. For example, you can use techniques to classify what kind of trash is that?

And then help you to, to tell with your, with your uh trash. So just these are just a couple of examples, things that I worked with before and uh and like uh yeah, it can also be used for safety. So nowadays, we have at home a lot of people uh online and um we uh the beginning of the pandemic became clear uh that uh there is a lot of uh domestic abuse happening nowadays uh because everybody is locked. And uh thanks to the uh data analysis or uh natural language processing, like text analysis, we can see for example, what kind of uh topics are being posted on social media, what kind of topics are being researched on Google for example, and or search sorry on, on Google, for example.

And then this way we can know uh we managed to track the correlation between the hori of um searches for domestic abuse uh keys and so on. And this way we managed to identify that this is actually something that is happening in the world nowadays, like a worldwide as a matter of fact. And uh now we actually, we have like a probably remember like last year we created a symbol, the symbols that we could use to if you are in a call and you want to say that you are suffering domestic abuse and so on. These are like uh things that we get to know through text analysis using machine learning as another example. And of course, we have the the unfortunate case of like uh kids also being exposed to predators online. So this is something that uh we can also use N LP. So for example, to create, to understand the risk of this conversation, to understand the kind of like a language the predator use and uh analyze the risk of a conversation to be a predatory conversation in this way. Also, for example, create a warning system or even create a chatbot that can help kids to just say like, hey, this is a dangerous conversation. We actually have this in some uh platforms and maybe kids as well.

And uh just to mention the last example, I just want to mention that we also have art and the art is not necessarily something that is like an obvious application of A I for good, but it's also like a way that understand ourselves that like a artist is part of the human condition.

So to say, and in the past, art was done mostly by human beings. And nowadays, we start to have this combination of machine that learns from the patterns of a famous artist or basically who whoever artists and can help artists and uh even people that are not necessarily artists to actually understand art and participate on the and just to mention here, a couple of examples, we have the portrait of Bellamy that is something that was done uh with uh guns.

So this is like uh this was not painted by anyone. And we also have the chapter of Harry Potter that was written with a recurrent neural networks just like by understanding the sequences and so on. And we also have like this uh idea of a style transfer that you can, it's a technique from deep learning that you can uh understand the patterns of some paintings or something and then apply it to other kinds of techniques. Uh sorry, other parts of images. So this way you can have the same techniques um and kind of make a combination of art and so on. And um I just want to say like uh to finalize, saying that of course, we still have a lot of um challenges in society, but we still have a lot of uh technologies such as A I and many others that can have the potential to help. And of course, we have to still uh integrate our A I and technologies to our daily lives and uh address topics such as bias and ethics and, and data literacy as well. But we have a powerful technology and if you want to think that we are in the 21st century, for real, we have to really start to use these technologies.

And this is, are all examples that are being used and there are many others into um and, but also addressing all those topics that are, that come also the challenges that come with the technology as well. So this way we can finally uh uh sustainable development, better society.

And uh I'll end uh with a call of action that uh we need a lot of diversity in this uh uh field like and also to change the world. And um the more women that we have uh involved and the more minorities that we have involved in all these initiatives of A I for good. Uh be it through NGO S or through industry. This is extremely important to, to us to, to become a better society. And in my opinion, I also like better humans. And uh it doesn't really matter if you're starting in the field or if you're already like a very experienced person. Uh We need uh everybody, we need the help of everybody. So here I leave with um um just showing you some communities that you can join that are doing a lot of good work in terms of A I for good. And uh also try to connect with like minded people. I uh took me a while but I managed to find all my friends that are like people that are like me are also very passionate about this topic and I'm pretty sure that many of you are as well. So um reach out to me like here is my contact and uh, I'll be happy to discuss more with you. Thank you.