We are all biased

Welcome to the Product Bakery. I'm Christian and as always here with my co-host Alex. Hey Alex. Hi Christian. How was your day so far? Intense but good. I have to say that the new job is really picking up now, which is fun to see and I think we have some really nice initiatives on the table at the moment. When you said exhausting, I just saw the look on your face changed. Why that? No, but the thing is, whenever I reach the evening and we jump on our call, that's usually something that I'm looking forward to, right? So you're just glad to see me, just say it Alex. It was just like my small reflection about the day and I was like, actually, I'm tired, but I'm happy that we're now closing the day. How about you? Really well. I had today actually a day off, so this is my first and last meeting. Luxury from exhausting to I didn't do anything. Yeah, almost. So maybe like just a fun anecdote, because at the moment we are doing some interviews to better understand some of our users and we have some features that we also want to test. And I feel like I'm always a big advocate of talking to people and getting them in. So, yeah, I now started also to sit in some of these interviews, just as an outtaker, silent observer, letting the others do the hard work. Ah, come on, you just want to be in the field. But so today we were actually testing a prototype and there was one thing that made me smile a little bit, because one of my designers and a disclaimer, she's really great. I really love working with her. But obviously, as you're in the flow and you talk to people and you just throw in some questions, she showed him a screen and she was like, do you like that the way we present the information here follows the way we presented the information on the previous screen? Let me guess. He said yes. That's that's the thing. That's the thing. I do this all the time myself. It just happens. Literally, I'm sure it happens like in every interview that I do have some sort of bias and the way I ask the questions and so on, and I think it even goes wider. And I try to be very conscious about whenever I develop features or when whenever I have ideas to take out all the possible biases and so on. So I was actually I was thinking that this is something that I really would like to discuss with you, Ryan, to see how many biases you run into on a daily basis. So you want to talk about the power of being able to manipulate yourself and others. Yes, yes, correct. Because it's funny, I recently read the book, The Undoing Project, and it's a story about Daniel Kamen and his colleague and how they were challenging how humans think and how irrational they think sometimes because they have never, ever all relevant data fully in place. You can have a lot of data in place, but never all of them. And also how we are quickly getting to being biased based on our opinions. And it's quite interesting. Yeah. Where do we start with that? I don't know. What are the common mistakes that make people biased? I tried to Google it, but obviously with my memory, I forgot about it again. There is, let me see. You can hear me typing. I think there is. Oh, yeah, there is something like around 188 different types of biases. So I think it's hard to talk about all of them. I have a question. What makes you sure it's 188? I'm biased. I read an article, Google pointed me in that direction. No, but I think like always, when you have some smart people coming up with some things, right, you have a process and people call it agile. You have some methodologies and then suddenly you talk about design thinking and so on. There is always someone who gives some things a name. Fancy names. I think in this case, I can tell you there was like Buster Benson. And there's actually a list on Wikipedia with all the 188 cognitive biases, and he put them together in a nice infographic. So yes, that's where my information for the number of cognitive biases is coming from. And what are the most common patterns or reasons why people are getting biased? What are the rookie mistakes? I don't know. Do you usually use stereotypes? Come on, don't give me that face. Of course you do. Sure. Yeah. But I think that's where it starts. And that's an easy example of a bias that you might have, where you might go into an interview and you already have a picture of the user that you're talking to. And this is influencing the way you interpret what he's saying or the way you're interpreting also the way he's using a product and so on and so forth. And I think this is a very common one and someone that is very rooted in ourselves, because we see media and so on and so forth. And all the way down to, we talked about personas, right? Even a persona can bias you, right? We talk about the millennials spending all the time on Instagram and being super tech savvy. This already could bias you right before you go into an interview and you talk to this person. Give me a second. I'm just browsing for Instagram. Okay, I'm ready now. Yeah, I think one issue that I ran into a couple of times was being overexcited, being overexcited about what I was building. And you want people to like what you are proposing or what you are planning. And that led me sometimes to actually ask also a biased question and asking like, okay, is this understandable for you? Or better understandable for you than the screen before? Or do you like that one more? So terrible question, obviously. But yeah, it sometimes happens, right? Yeah. And what you just brought up is the confirmation bias where we also, we are in love or we prefer obviously the data that confirms our existing hypothesis. Absolutely. And I think there is also an easy way to navigate a little bit around this with you. As you said, right? You should never really ask a user, hey, did you ever try to press this button? Or did you ever think to sign up to a service that does this, right? Yeah. Because that's already where you are bringing your bias into the question. And you're kind of leading the user to tell you, to give you the answer that you want to hear. And I think here as well, like earlier, when we talked about stereotypes or generalizations, it is important that you're aware that these biases exist, that this is like how we think and how we work and how we tend to frame questions and how to do things. Because only like this, you can sit down, think about, okay, what is the right type of question? What are maybe some ideas or some notions that I have in my mind that I need to avoid? And you could even write them down. You could say, okay, I expect this user to be super tech savvy and so on and so forth. Or, yeah, no, I won't talk about other stereotypes because otherwise it might get racist and we need to cut this out. But then you can go through this list of maybe the hypothesis that you had initially or the generalizations that you had at the beginning and make sure that you can keep them out of the results. Yeah. And additionally to that, I think, first of all, you need to be aware of the fact that you are being biased. And I know that's already very tough, but something that I've learned, especially when we were working at SumUp and hiring new people and setting up the hiring processes, was that once you have understood that you are biased, that you start to disprove yourself, that you try to step out of your shoes and objectively to understand what this thing is about. Maybe you see someone just coming into an interview with the suit and you are like, wow, must be a snobby guy. Sometimes we tend to make these false premises very quickly. And therefore it's important also to realize, okay, maybe he isn't that uncool. Maybe I should figure out what kind of hobbies he has. And we have some overlapping interests. Yeah. I've learned that it's very powerful to take a step back and try to disprove yourself. Yeah. You need to play the devil's advocate on your thoughts and on your ideas and on your beliefs and challenge them in order to make sure. But then again, I think it starts very early, right? Making sure that you avoid these sort of things means that you need to understand them and that you need to understand the human brain and the way we think. Because another thing is that it doesn't have to be necessarily be only you who's biased. It could also be that your user is biased. It could be you or the note taker. But I think it's something to keep in mind that there is a lot of different methodologies. Let's maybe talk about something like card sorting, right? Where you give users a lot of different options and they can sort them, rearrange them and so on and so forth. Now, what happens if you have a long list of items? The human brain gives more importance or emphasizes the first and the last items. So even the way you structure the exercise could lead to different results. And this is the same with participants that you hear at the beginning and at the end, or the first things that someone says in an interview and the last things that someone says in the interview. You're always biased towards giving them more importance than others. Yeah. What would you say are the most important things to do to avoid biases during an interview? Be aware of all of them. Try to go through the 188 biases and check each one of them. You don't need the 188. I think then we're going into the area of psychology a lot. I think there is probably, I don't know, 5, 10 that you need to think of when working in products. And I think you need to know how they work. You need to know how to avoid them. How to avoid them because there is no rule of thumb. If you don't know that such a bias exists, you can hardly navigate around it. If you don't know that even your to-do list has a bias towards seeing the first and last items more important as the one in the center, then you can never work around it. And you can never be conscious about looking at the ones in the center. And you need to know the stereotypes that exist. You need to know what... I think it's also a lot about reflecting. And I don't know, another good example, like how often have you been spending a lot of time on a project and the more time you spend, the more you get attached to it, right? Never. The harder it was to say, oh no, I just dumped this. Yeah, agree. This is being biased. And then in that case, if, okay, this is how we tend to function, you need to force yourself or a whole team say, okay, let's try and break it down so that we, and a lean startup or lean UX in general, let's try to have them a small experiment so you don't get too attached to it. Make sure that you are comfortable with throwing all your ideas in the bin, right? This, you're not biased towards something specifically. And yeah, I think it's being conscious about it. Yeah, fully agree. Is there something that you would recommend us to read to dig deeper into the whole topic of biases? I will put the link about an article that I recently read into the link so that you can read it. Alex, nice talking to you and have a great sunny evening in Berlin. I definitely will. Have a good night.