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Silvija Seres: Hello, and welcome to this edition of Lørn.Tech.. I'm Silvija Seres. Our topic is Big Data and my guest today is Arturo Amador. Big Data-scientist at. At Acando. Is that right?
Arturo Amador: Yes, that's right.
Silvija: Welcome.
Arturo: Thank you.
Silvija: Well, maybe you can tell us a little bit about who you are and what you do? And I'm fascinated by the transition from really academic physicist into Big Data!
Arturo: Yes, absolutely. So I'm Mexican. I come from Mexico. I took a bachelor and master's degree in theoretical physics back in Mexico. Then I moved in 2010 to Trondheim where I got a position to do a PhD in theoretical physics.
Silvija: Sunny Trondheim after Mexico.
Arturo: Yes. It was a 30 degrees transition, actually, and when it comes to temperature. Then I did my PhD from 2010 until 2015, and then I made the transition into the private sector to become a data-scientist for Telenor Norway for the business Division. And it was to work with this service. They have been creating, called Mobility Analytics, which is all about transforming signals from the cellular network into insights on how people move and how they behave and…
Silvija: Is it about their geographical movement or is it about their data usage, or what?
Arturo: They both are related. It´s both at the same time. So, basically when you are using your phone, you are a constantly sending data packages through the cellular network. This is produsing a signal. This signal – it has encorded your location to the base station of where you're connected, right, so it is geographical location and it’s data in the form of signals that we use. Then we can say ”Okey, if you are in this region for eight hours, you're at your workplace”. If during night, we are spending time on this fixed location. Maybe this is where you live, and in between. where do you go shopping, how do you transport, where do you take your tea, take your children to school, etc, and all these things are things that can be looked into.
Silvija: What what did you do in your PhD?
Arturo: I did something that is called Quantum chromodynamics. So it's… you can think of it of a statistics applied to physical systems composed of many, many, many particles. So you use the statistics to find out from first principles theories that describes this very complex systems.
Silvija: Okay, I don't think we'll go deeper into that.
Arturo: Okay, hehe!
Silvija: Okay, what I'd like you to explain to me is…so I hear a Acondo is a very cool company when it comes to Big Data. Why?
Arturo: Well, we have actually a really great Tech departement. We have guys that work in embedded systems; programming actually hardware that we sent to The Land Rover on Mars. We have the connection of this Harlow-guys to the IO industrial IoT Division, and we also can put the analytics on top of all this data being generated by hardware sensors.
Silvija: What does that mean putting analytics on top of it – IoT data?
Arturo: Yes, you know…
Silvija: IoT, let's start with that.
Arturo: Yes IoT. So you hear very often this analogy that Big Data is the new oil. It is a very good analogy for many reasons. One of them is that you have to do something with oil to extract value out of it. If you digitalize all of Norway and you put sensors everywhere and you put any…every process in digital - you're going to produce a lot of data and the data standing there by itself has little to no value. Once you can put what I say…
Silvija: Through the data?
Arturo: Yes, put the analytics and the data then is when you can really obtain a huge, huge value from from this Big Data.
Silvija: And how does one do that?
Arturo: One has to be very, very well aware of the business needs. The business use-case. That's why, you know, it's very often said that these data scientist have to be programmers as a decisions. But also business people because it's very important for you to establish this bridge and I am a physicist right, but I don't know anything about tourism. I don't know anything about retail. I don't know much about public transportation, but I have been working in this delivering insights for this sectors - this industry sectors, because I think I have learned how to understand this business needs that people have in this segment.
Silvija: Can you give us a couple of really good examples of where a Acondo does this?
Arturo: Well, we have this agreement with Telenor where we help them create this monetization service. Web…
Silvija: Sorry. That really means that, for example, I can pay for my transportation…or what's the monetization?
Arturo: Okay. Yeah, it's called Big Data monetization. Why? Because Telenor is generating all these data on how people move, how people use their cellular network. And typically this is used only internally to know where to deploy the network, where to put more capacity in the network, and typically this is only internal use cases. But then with the help of the Telenor research and Acandom, they come up with a really good privacy framework. So they say ”okay, we follow these steps”. All this data is anonymized. It’a not possible to identify Silvija or Arturo. And then we say, ”okay, you know what, in tourism industry, retail industry in Norway - we have this data that can help you understand how people move”. You can…it's up for sale…
Silvija: So basically it’s systemic trends in the movement of people and then helping all relevant parties understand the way the world moves?
Arturo: Exactly. It's like how…how long do you spend in Sandvika Storsenter if you go there? What method of transportation did you use? Where were you one hour before you came back to Sandvika Storsenter? Did you go to CC Vest before you came to Sandvika Storsenter, or? These things - when aggregated - are protect privacy of the end user and have a lot of value for alot of Industries.
Silvija: So, we talk about Big Data in very generic terms, but it has to do with a lot of data being gathered and it has to do with this data as you say being refined so it can actually be used - before the gathering maybe! It starts with the problems one wants to solve. So, you know, it will be gathered properly and then it has to do with applying the right statistics on top of that data. And many statistical models looking for these patterns including things that has to do with machine learning.
Arturo: Yes.
Silvija: People talks about the three V's of Big Data. Can you teach us a little bit more about that?
Arturo: Yeah, that's very a common definition where the three Vs´ stands for velocity, variety and velocity. This is not something new that has a…I think…
Silvija: What do they mean?
Arturo: Those three V's?
Silvija: Yeah.
Arturo: The velocity is that it is alot of data being generated at a really fast pace. The volume is the useage of the ”big” in Big Data. And the velocities; that is not just…not just the noise, right. And then its even people that go to adding value is the definition, right. So that it's not just trash-data.
Silvija: Yeah.
Arturo: Yes. And this is all…this is all from the 90’s basically - the…this term, Big Data.
Silvija: You say it appeared first in the 1997 paper by scientists at Nasa?
Arturo: Yes.
Silvija: Why…what you know…tell us where Big Data comes from?
Arturo: Yeah. They were trying to construct visualisations of very large atmospheric-data sets. And then in the paper, they mentioned that they run into a big data problem because they're super-computers were not able to visualize all these data. And actually nowadays - putting things on the cloud, you know, With the deploy in services with a few clicks; you can analyze and visualize terabytes of that data. There are billions and billions of rows. And this is very, how do they say – democratized - because really anybody can can access this these servers to crunch Big Data.
Silvija: What's in your opinion the most exciting thing about working with these Big Data problems?
Arturo: Oh, It’s the…coming from the experience I have from these mobilanalytics projects is that people have been wondering for so long can be solve really fast with the use of Big Data technologies. Really, really fast. And you see experts that have been working on their fields for 20 years and you come with this insights and they are WOW’ed! And I'm…I'm just a simple physicist so for me, that's really, really nice to see an impact on people.
Silvija: And the dark side of the moon?
Arturo: All the etichs. The challenges…
Silvija: Like what?
Arturo: You know…
Silvija: Privacy?
Arturo: Exactly. Privacy is one of them. You have to be really sure that you're not messing up things and you're not going to put people on risk, because you can really put people's lives on risk if this is not treated the proper way.
Silvija: So policing the technology the right way?
Arturo: Yes. Yes.
Silvija: Who’s responsible when your Big Data actually lies?
Arturo: Yes. That's a very tricky thing. I think we're making good progress in Norway. But it is still a long way to go.
Silvija: Your favorite international example of Big Data?
Arturo: I like this data that is being generated by companies like Facebook. I should say just Facebook because I don't think there are any like…
Silvija: …many others, yeah. Maybe Amazon!
Arturo: Yeah. Yeah, maybe. I'm more on the commercial side. But this companies are capturing interactions between humans among humans. That's really interesting for me because again, one of the reasons I transition from physics was that everything was so abstract and so theoretical. With data-science and this data produced by, for example Facebook, you can see the impact that certain models have on society. Look at the elections in the US.
Silvija: And Cambridge Analytica and the psychology of it.
Arturo: Yes.
Silvija: Agreed. I think we should all read up on what happened with Cambridge Analytical by the way. There is a really good article in MIT Technology Review that explains how… actually this has been published research for years and then…and then everybody - including politicians - got scared it and surprised, where we actually have been talking about how you can do psychometrics on people very easily.
Arturo: Yeah, we are very sensitive. There is…I recommend you to…if you can use Googleto search the term AI Notch.
Silvija: AI Notch?
Arturo: AI Notch. Basically, we humans…I think we are identified to be running on 50 different kinds of biases. Handside bias, availability bias. And this AI Notch is just says, okay, giving your knowledge of how people interact, u can just push them a little bit towards this direction. Even all these biases we leave on. People are going to do this, we're going to do a or b or c, and then it is a really manipulation with the use of…
Silvija: So you are basically playing to the hidden Beast inside us, but in a super manipulative way?
Arturo: Yes.
Silvija: And given that we know how marketing works in general. This can be scary if used by wrong hands.
Arturo: Absolutely. Absolutely.
Silvija: So a mexican guy in Norway. What impresses you about Norway and digitalization? what keeps you here - other than the sunny weather?
Arturo: Well, my wife. But no, it's really the country. It is so digital. So, I come from Mexico. And yes, just take money for example. Nobody uses cards in Mexico, while almost nobody uses cash in Norway. And this is producing data again; transaction data. I think it's just the way the society is built in Norway. So amazing. So well organized. Well as comparing to other countries.
Silvija: Can you tell us a little bit about some of the telenor projects you mentioned to me? Like Big Data for social good? What was that?
Arturo: This is something that they're in our research has been working very actively and they haven't managed to do it yet in Norway. They have done it in Pakistan. Actually with the cooperation of Harvard Health Institute, and it's just to study how the human mobility correlate with the spread of the Dengue Fever. There are plans to use mobility data that we are creating in Telenor Norway to study how does the flu spread in Norway. This is still to come, and we have to basically generate the data and make it available for telenor research.
Silvija: I imagine their applications - other applications for the public sector, that have to do with public security and safety and things like that. I mean you can you can notice movement before it's obvious to everybody else.
Arturo: Yes. We are not quite there yet, but there is a really good book called Social Physics, and this just goes into exploring how the mobility of people in certain cities in the U.S change dramatically when there is political discontent when there is going to be manifestations or political…for political reasons. All these can be measured utilizing basically humans and it's mobility as sensors. We are very sensitive to our environment and all this can be now access with the use of Big Data technologies.
Silvija: Very interesting. You mention also the book Weapons of Mass Destruction by Kathy O'Neill. What else would you…would you recommend people to peruse for inspiration?
Arturo: I think there are some really good books that focus on how can we actually apply these analytic mindset in our day to day lives. One of them is called Super Forecasting. Just talking about normal people - retired citizens in the U.S cannot apply this kind of a statistical thinking - base thinking - to try to forecast happiness on the political world. That one is really good! And…I can probably send you a list that you can put on the podcast notes!
Silvija: Very cool. Arturo, you touched upon this whole kind of social physics and mobile interaction management more than anyone else we've talked to, and I think that's a really interesting aspect where the, you know, this kind of new technology - in this case big data analytics, doesn't only change the nature of business, but it can also be very, very efficient and relevant for society. And I think that…so if you were to leave people with a, you know, an image in their heads that summarizes our conversation, what would it be?
Arturo: There is work in Norway being done on that aim to have really frictionless cities. Cities are the main drivers of economy in the world. Period. That's a fact. Yeah.
Silvija: Frictionless cities? What does that mean?
Arturo: Yes. You go to work without any friction, go shopping without friction, do what you want to do with the less possible friction. So that means excellent public transportation. You don't need to use your private car because you can jump on the bus and you're going to get there really fast and without any problems. And this makes cities attractive and this allows it to grow without any problems. This also reduces actually health issues. And once you have this you are going to be an attractive - more attractive - country in the world. You're going to grow your economy. You're going to grow your innovation. So this is really inspiring because this is being done in Norway as web speak.
Silvija: Very cool! Arturo. Thank you so much for joining us today, for sharing your knowledge with us about Big Data and its social impact.
Arturo: Thank you for having me. It’s been my pleasure.
Silvija: And thank you for listening.
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