I want to introduce Lisa Rost, so Lisa loves to design data visualizations, she is currently the night Mozilla open news fellow at National Public Radio in Washington DC.

If any of you guys do not know NPR, let me tell you it was the number one thing I personally missed in the decade from 99 to 2011 that I lived in Germany. I'm almost as much as I miss Corey Vorst in the States now.

No seriously, it's amazing, it's way better than public radio here. You have way better public TV than we do, but we have way better public radio. So if you have an opportunity, check out NPR.org and look for shows like Radiolab, All Things Considered, Fresh Air, but anyway, enough about Lisa's... Absolutely, any other suggestions from the audience?

Absolutely, Morning Edition, I'm in New York City, so Brian Lehrer, lots of different options. But anyway, enough about Lisa's workplace. Lisa creates visualizations, I'm for NPR now, but previously when in Berlin, she designed for and with the open data city, Spiegl,

and Tage Spiegl, taught data visualization at universities and also organized the DataViz meetup. This is one of the talks I was looking forward to seeing, and so it's really kind of a privilege for me to be able to introduce Lisa, but I'm not the one here to see, so Lisa, take it away.

Thank you so much, thanks for having me and thanks for the introduction. I'm not sure if you got everything, I think what you need to know about me is that I take numbers and I put them into something like that, and I've done it for a long time now and I really like it.

And data visualization is definitely hyped, like the demand increased over the last 5 or 10 years, everybody wants to do it now, but only recently we started thinking about if these facts and figures that are visualized here actually matter. So that's what we did, especially this year,

like this year, we found out as a society, especially in the US, that some people take feelings and perceive them as a truth. So today I want to ask the question, can we take truth and make it evoke feelings? Can we take data points and make people care about them,

especially data points that can walk into a bar, meaning humans? And I want to ask this question with three questions. First, in the first part I want to talk about why feelings are good and why feelings are bad and why we can't have them and why we should have them. In the second part I will shortly talk about what it all has to do with data visualization and the third part

I want to bring specific examples. So feelings, we all have these blurry things, they sometimes come to us and then sometimes they leave. These are only some of them, like right now for example, I'm pretty happy to be here. I'm also grateful for being here

and I also have like a small version of fear which is nervousness, actually that's a huge part right now, but there are two feelings here that are a little bit separated and these are empathy and compassion, because empathy and compassion we direct towards somebody else and they can have as a content everything that's in this list. So let's define some terms here, let's make

some distinctions. Empathy is when we feel a feeling somebody else has, we put ourselves in their shoes. If you would have empathy with me right now you would also feel nervous.

And compassion is more like sympathy, like if you would have compassion with me you would not be nervous, you wouldn't have these negative feelings, but you feel would feel more like positive feelings like love or sympathy for me. And almost everybody on this planet can agree that having empathy and compassion is better than not having empathy and compassion. A quick google search found that smart people on

the internet think that empathy is the only way we will survive war, that empathy makes for good people and good people make for good societies. And Obama is a big fan of empathy saying empathy makes it harder not to act, harder not to help. So empathy is something that comes in all of us,

we are really good at that, we're really good at directing our empathy to one of us, like for example this child that most of you already know was on a show in 2015 in Turkey. But we have some troubles directing our empathy at two people. Imagine I would have brought my

beloved clone and she would have given a talk to here at the stage slightly similar but also slightly different. It would be hard for you to direct your attention towards me and towards her talk at the same time. And it would be really hard if all of us would be at the stage except you and you would listen to all of us giving a talk. I'm not sure if you would get anything

out of that talk and it would be super hard to direct your attention. And that's the same with empathy. We're really good at directing empathy to one person but we're really really bad at directing it to lots of people. That's why we can have empathy with this one kid but

not with the 3,770 other people who also died crossing the Mediterranean Sea in 2015. And I mean that scales up, that's not something that you feel and it's like a little bit blurry etc. But this photo of that kid, it actually led to huge donations to the Red Cross and it also changed politics. The Guardian wrote that European leaders have been shocked into forming

more compassionate policies by previously hostile media outlets took a more conciliatory tone. And look at the wording here, shocked into. The emotions were the reason for that. It almost feels like they were forced to have these implications thanks to the emotions.

That's the conclusion tutorial. Our lives are actually not all worth the same value. We value lives more if it's only like one or two or three. And it's like the more lives they are the harder to process and we don't really have much empathy for them left.

That's pretty sad. I mean yeah it's really easy for us to have like this one person and to have empathy for that but we can't multiply it with 3,770.

That's why I concluded that emotions suck. Feelings are the worst. Okay it's not the worst but they're not really articulate. They are good and bad. You have one candy that's good. You have another candy that doesn't make you double as happy. It's the same with bad feelings. If you have one death that's bad. If you have two deaths that's not making you double as sad.

And it might be even worse than that. Paul Slovic who did a lot of research into empathy, he did that study where he showed people a child. Like take the child for example. She has a miserable life. She's living in Syria and you can help her. You can make a donation

and she will have a better life. Would you donate? I think lots of people of you would. Again like empathy is something we're really good at. But then I would tell you okay you can help that child but you can't help her neighbor. Like she's staying in Syria. She's like she will have like a very uncertain future and all the donations will go to this first child

but not to the second one. And then I will tell you all the same thing about all these other children that you can't help them. And 40 percent. 40 percent is the drop in donations that the researchers have seen towards that first child. People are less likely to help if they are reminded of all the people they can't help. We want to make a

difference. It's called like a warm clothes theory. We want to feel good about helping. And we're feeling, yeah we want to feel like we make a difference and we don't want to get reminded of all the difference we can't make. So maybe it's even like that Paul Slovic suggests. Maybe actually we value one life even more than like three thousand lives. Three thousand

lives mean nothing to us but one life we're really invested in. Like it's a huge difference for us if one child dies or not but it doesn't really matter if three thousand seven hundred seventy people die or three thousand seven hundred seventy one. Sucks. Emotion sucks. It's actually okay.

It's yeah no but not articulate and there is this weird ego wants to have impact thing going on. It makes me pretty angry. How about we don't do feelings anymore and just decide everything rationally. Rationality is good.

Paul Plume is like a big opponent of empathy. He says if you want to be good and do good empathy is a poor guide and it's not just because of that because of empathy has this weird we can't really value lives properly thing but also because empathy is not fair we tend to

we tend to help people and to have empathy towards people who look like us who are looking cuter who look more like they need help. That's not the same with rationality of course you would tweet everybody the same. But then again would we tweet anybody actually because why should I care? Why should I care when I don't care? Why should I care for some child

in Syria that has maybe some very far away impact on the economy but actually you know I don't care. So maybe rationality is actually also not dissolution. I think we need both. We need the numbers and the feelings. We need numbers and narrative and anecdotes and abstraction.

We need the slow system one if you wrote Kahneman and the fast system two. I think that's how it should be. We should make people care about a topic and then we should tell them what to do and how to do it in a very rational way. First we want to show them that they should do something and we want them to decide to do something.

And then we can show them in rational terms how to do it and what to do. And that's what I want to talk about in the rest of the talk. So first data visualization what does it have to do with that? Well most data visualization looks like that still.

It doesn't really do justice to the people we present. These are about malaria deaths and traffic fatalities and unemployed people and it doesn't really you know make me care so much. It's like really more on a number scale. It really speaks to my analytical self. And I think some of you might say oh that's actually good right? Like data visualization

is supposed to speak to the rational mind and that's I actually like that it doesn't try to manipulate me like these super manipulating emotional photos of kids at the shore. And I would say okay that's fair. It really depends on your goals in the end. I think data visualization is just a tool. You can use it to represent data in a very

objective way but you can also you should be able to do something like that that speaks more to your emotions. In the end it's like language. Language can also be super objective and like super harsh and cold or you can have poems that make you really feel things. Data

visualization is a tool and if you want to evoke emotions with data visualization I feel like you should be able to. We should build a tool kit to make that possible even if most data visualization will still stay in the rationality term. So that's the rest of my talk. How to make

fields with data visualization. I have some ideas but I'm also very happy to to hear your ones. First one, easy one, simple one, make use of colors. We're all using colors anyway in data visualization. This for example is a serial tracker that tracks the depth of certain people

and it comes in a very comfortable cozy like very nice looking blue. I think that really is not what it's about in the end. I feel like again you would do just as more to what you represent if you would show it in a slightly different way and that's the least you can do.

In fact like the three most intense most emotional data visualizations of the past years make equate use a very impactful use of colors. The first one is about gun deaths in the US. The second one is about victims of the second world war and the third is about

deaths from drones and they all have black as a background and they all have these highlights of colors and yeah this is really one of the simplest tools to create that empathy. Show what the data would mean for your experience. That's an interesting one. Maybe

imagine three layers. First you have the numbers, just a table just like black and white like all your numbers. You don't really understand them well and they don't have any meaning for you because you don't understand them. So that's why you add the visualization. That's what makes you understand the data. That's what shows you what's actually in the data and

tells you the stories but then you want the other layer, the experience layer or like a meaning layer that tells you why you should care. That's why everybody is freaking out about VR because VR does exactly that. It puts you into a situation. It makes you feel things in a situation because you're there because you have the experience.

So yeah experience makes you feel things and I think that's something a lot of you have seen and I want to show that again because it's doing that really well not putting you in a situation but bringing the situation towards you. Let's see if that works.

This video had more like 55 million clicks of views until now. It's really impactful. Again it brings you, it doesn't bring you into the situation, it brings the situation to you and that's one step further than visualizations like these ones. I think you've seen these ones

before where they ask you to enter your zip code or something and then they tell you what the data looks like for you right now. But this is, these things are more like thought experiments like the Berliner Monck did recently. The US is pretty far away, you have Trump's wall there,

whatever that means. They take the wall and put it in front of your door basically. You can see what the door looks like or would look like if it would be actually there in your environment, in your experience that you have right now. Something similar is doing the BBC with this news game where they put people in the lives of Syrian refugees and let them make decisions.

So for example you can decide to pay somebody the deposit or refuse to pay them the top deposit. Again that's bringing you into the situation. That was pretty advanced but you can actually make something more simple and do some calculations. CNN was doing that where they

calculated what it would mean if one to one point three percent of a population would be killed. Like it's the case right now in Syria. I mean I don't think that so many Americans actually care about Syria but if three to four million Americans would be killed in their own country like wow it would be would be Armageddon. Yeah there are lots of questions you can ask to

make these thought experiments these parallel universes and I would really like to see that more often done in 2017 in the data visualization scene. Another example zoom into one dot

every project needs a story as the Berliner monk post guys would say and that's exactly what they do. Like they always have these data visualizations beautiful at the top here for example one that shows where people who currently live in Berlin actually come from but then they also go on the street and ask people and zoom into the one dot into that one data point and ask them and are like where are you from why do you live here do you

like it in Berlin etc. So that people can relate to somebody. And that's an old journalistic trick right that's from the NPR website. Most especially feature stories start with like an anecdote at the beginning give example a photo of one person and then go up level and high level and show you the overview and show what the data

means or like how many how many people are actually have like similar stories because they share they are the similar in a similar data bin. And of course advocacy organizations are doing that a lot that's actually interesting because it actually states like we can't lose sight of

the individuals actually says exactly that don't just look at the numbers like you will never see something like that that will show you a data visualization of how many people die they will always show you a photo an individual. And that's one of my favorite Twitter bots.

As somebody who works with the American Census a lot I really like it. It shows you one data point of the American Census and tells you all the data it knows about the data point and I think that's that's that's a great example of like how you have data about millions

of people. It's like a statistics. If you have data about one person it's a story. Show what you're talking about. That's something that's also pretty old. Otto Neurath and his graphic designer Ged Anz already did it in the 1930s where they showed data about people with actual symbols of people. And that's what the New York Times is still doing or has still

done in the last years. And here the Washington Post. And show the mass as individuals the last point. It's similar to the zooming into dots thing but it's more like you don't just

zoom into one dot and show them as an example but actually show like all the dots as like the whole data. The alcoholics and the normals are doing that for example they focus on a small step they say. Also of course being abstinent for the rest of their lives is the goal of the program alcoholics are told to stay sober one day at a time or one hour at a time. You focus on

what's close. You focus on what's achievable. And you're putting the data closer as you do with this example for example. 800,000 killed in the last 800 days versus one life lost every 11 seconds. The first number you can calculate with and that's super important too but the second

number is what speaks to your heart what speaks to your emotions. Parship is actually doing something it's similar with their like Parship the German local cupid. They're like they advertise their service their matchmaking service with saying a single thoughts and laugh every 11

minutes on their website. Whatever that means. They don't say like 50,000 people per year fall in love on Parship. They like focus on the individual because you're standing on a subway platform and you see that advertisement and you can actually you can actually imagine

being that single or like that single he was alone and then he found someone and he's happy and then you can say okay every 11 minutes there's actually a lot maybe I should sign up to be this lonely. And that's a data visualization I showed before from Periscopic about

U.S. gun deaths which does something super super interesting and similar. So it's actually an animation but I will show the slides to explain them. What you can see is arcs being drawn for every person but then they drop like the dots drop at some point because they get killed by a gun and then they keep drawing the arc to show you how long that the person

would have lived. And they show one example why they explain the data visualization by showing one example and then they show another example and then another one and then they show three at one point etc. And it goes almost it goes always faster and faster

and it accelerates a lot until you end at something like that. So you can still see the dots and that's the point I want to make. It's not like this one data bar chunk that you have you can still see and go into every dot if you want to. There's

Hertzberg there were not six million Jews murdered there were one murder six million times and I urge you to do it the next time you see like a big number about people. Imagine that thing that is described about it three hundred thousand people being actually happening to one person and then just multiply it. This is not quite six million this is five million six hundred thousand.

It's the last number the artist Román Albalca painted. He painted every single number from one to exactly this number. He can see him doing that and I always I wonder if he actually is the

person in this world who can judge big numbers the best who can actually who actually knows what a big number means because he spent time with every single number right. If these were people he would know what it means because it took him years years to like write these down but every number took only like half a minute or so to write down. Dear Data is a project that did

something similar. Stephanie Posarek and Xocha Lupi wrote each other postcards where they're through the data. So for example this is a postcard from Xocha Lupi where she shows all the songs she listened to in in one week and it's not it's not generated by the three chairs

or like R or something she actually drew all these things she spent time with every single data point. Now we're going from like the user side to the creator side like this is something you can do as a creator to understand big data better. And Xocha Lupi was writing about that she was she called something like that data humanism and she said exactly that

instead of saving time with data spend time with data and instead of data as numbers data as people. So yeah that's that's what I wanted to talk about. Let me sum that up. Why feelings are good and why we don't have them. I argue that that feelings are like pretty

bad for like big numbers but that we still need them to make us actually care. We can do that with data visualization we don't have to we can do it though I think we should think about how we can achieve that. And then I was talking about all the options how to make feelings

with data visualization for example making use of colors zooming into a dot showing what you're talking about with people symbols showing what the data would mean for your experience and showing the masses individuals. So yeah thank you. Oh no wait wait wait. These were three important points I think a fourth one is missing here which is also super important. Once you made the feelings

you need to do something with it. You can't just leave people with their feelings. You have some responsibility if you create feelings on people because they get helpless as heck when they don't know what to do with it. If you're angry you need to punch something and if you're sad you need to cry and if you have empathy for something you may need to

make a donation or something to not feel like the world is burning if you don't do anything. That's not something I will talk about today but keep it in mind your responsibility as somebody who makes people feel. Thank you very much. Thank you. Thank you. That was awesome.

Thanks. That was awesome. So one quick announcement before we take questions. We're going to clear the room after the FAQ is over. That means everybody who is in will go out and use both doors.

Hi Lisa. Thank you for your talk. You very briefly mentioned VR and the possibilities for empathy in VR and I think I kind of don't really see it that way so I'm curious about how you see it and if you could say more

about that. Thank you. I'm not a VR expert but I would love to know why you don't see it anyway. I'll tell you after you tell me. I mean I can no I mean I'm happy to talk about it but I'm just sort of interested in how you're seeing if you think of a continuum of kinds of visual techniques that we have to generate empathy and feelings with different

kinds of data points then data is one and VR is another that's been kind of talked about a lot. I think people like Sam Gregory sort of discuss what's sort of problematic with this in that it just kind of makes it it says that it's going to immerse you in an

experience but what it does is it just puts you into that experience and then drops you it doesn't actually take you anywhere with it and just you having the experience is the most important part of VR. I mean there are some which are slightly different more interesting and I can think of some examples but I'm kind of curious to think to hear about what you would

feel about VR and as somebody who works with data and numbers like what does that seem like on the horizon? That's super interesting. Thank you for your point. Again I'm not a VR expert. I've done it once. I was blown away like a pretty good river.

I think there's some reason that so many newsrooms like the New York Times invest in VR so much. Of course it's like shiny and fancy and new and that's why they love it too but I think there's something maybe just to the newness you know if you're like I can

I can still remember the first VR experience I had and if this first VR experience would have been about Syria or something I would have like I would have still remembered that because it's something we don't see every day. I wonder now like I really like your point about how people get dropped into a situation and then it's like that's it and they can always

escape. I wonder if that's actually the opposite of beneficial like if it actually hurts because yeah because you don't you don't live there like you have to experience it you can always escape this is I wonder I'm not sure but thank you. So we can do one more question maybe two if

they're quick. I'll go out but I'm sure Lisa will take some time outside as well for more discussion. Hi thank you for your talk. I was wondering if you would be giving this talk in front of a whole bunch of right-wing horrible people would you give the same talk? Right-wing horrible people like how horrible?

Is it six of ten horribles? I don't really believe in horrible people but I think I would need to go through the slides again but actually it feels like there's nothing that

should offend them too much. I will let you know though the next time I will give that talk in front of like lots of horrible right-wing people and then we you know we can have a discussion about what I should leave out or something to not get hurt. 30 seconds. Okay thank you for a really inspiring talk. Most of the great visualizations

I've seen were designed as a very personal experience for one single person to experience or observe at once and I'm curious if you had thoughts about visualizations that are designed to connect people or to be experienced by more than one person. Oh wow okay I've never thought about that at all. This is super interesting. You mean like

visualizations that are supposed to be seen or like experienced by lots of people. I mean I've definitely seen data visualizations in museums and I think this is the closest one I can think of like 3D visualizations or visualizations you need to build together I guess. Let's talk more after. Can you guys continue outside?

We will. Let's talk about it afterwards. It's super interesting. Thank you. I'm sure there'll be a great conversation outside.