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0:00 In the last episode, we introduced you to Dr. Cynthia Noll, 0:04 NASA Technical Fellow for Human Factors, 0:05 for a conversation about how understanding human capabilities can lead to safer, more effective systems. 0:12 This week, we're continuing that conversation. 0:15 We'll take a closer look at how memory, perception, 0:17 and even intuition shape the way we interact with complex systems, 0:21 and why designing with those human capabilities in mind can make all the difference. 0:26 This is Small Steps Giant Leaps. 0:28 Welcome 0:37 to Small Steps Giant Leaps, the podcast from NASA's Academy of Program, Project, and Engineering Leadership, 0:43 or Apple. I'm your host, Andres Almeida. 0:46 Let's jump back into the conversation on human factors with Dr. Cynthia Noll. 0:50 Let me talk a little bit about memory. 0:53 So one of the times of memory that you really notice that is a little bit problematic is short-term memory. 1:00 When somebody dictates a phone number or two and you're trying to remember it. 1:04 There was a very famous study done late 50s, early 60s. 1:07 And what that was, was the number of items that you could hold in short-term memory so that you could repeat them. 1:13 Seven is sort of like the number of digits and a phone number without the area code. 1:17 If you're actually getting a phone number from your area code, that becomes really easy. 1:21 You only have to learn this thing. 1:22 You only have to memorize the seven digits because the first three, you go, oh, mine. 1:25 And so that's held up pretty well. 1:28 But if you put somebody under stress, That seven sort of creeps down. 1:32 Maybe four might be a better estimate. 1:34 And then you'd say, oh my goodness, people's short-term memory is horrible. 1:38 What are we going to do about that? 1:39 There are other things about short-term memory that weren't obvious when that paper was written. 1:44 And that is, the number of items doesn't have to be a singular item. 1:48 It could actually be a group of items. 1:51 So I don't know if you ever did this at a birthday party, but we used to do this at birthday parties. 1:55 The mom would dump 20 or 25 somethings on the floor, toys, so whatever they were, plastic fruit things, right? 2:04 And then after a few seconds, well maybe a couple minutes, 2:09 you throw a towel over or something and then you were supposed to remember or write down all the things you remember. 2:14 If you actually were trying to be competitive and play that game, you'd probably get somewhere around seven. 2:19 That could be a little less, could be a little more, 2:21 but if you took the task a little bit differently and looked at them and put them into categories and went, 2:27 those are animals. 2:28 Those are vegetables. 2:31 Those are transportation items. 2:33 Then those groupings end up the seven things and the items in the group are also buried within that. 2:39 And so if you actually categorize them, organize them, that 20 things don't become, aren't 20 things anymore. 2:45 20 things can become a much shorter list. 2:48 And so people will remember things like the year they got married. 2:52 And so if that's in a phone number you don't have to remember all the digits. 2:55 It's just the year you got married, the year you graduated from high school, the year you were born, 3:00 those kind of things, numbers that are meaningful just in life. 3:04 Now the other part of forgetting is that the brain is designed to be very efficient. 3:10 And it has rules about essentially getting rid of stale memories, 3:17 organizing memories into networks, and just dumping stuff that's not important. 3:23 So, in life in general, unless you're someone diabetic or with some other medical concern, 3:31 which would make this data important, 3:33 knowing what you ate for lunch yesterday has no real value, no survival value, 3:38 doesn't have much social value, and so the brain doesn't decide to keep that. 3:43 Now, if you actually have to know that for medical reasons, 3:45 then you can override that general process that says, I forget what I eat yesterday. 3:49 But we sort of think, like, if you really were good at memory, you'd memorize everything. 3:56 Our memories don't work like that. 3:58 Our memories are looking for patterns. 4:00 Our memories are looking for... 4:03 Yes. Utility. And it organizes things so that they're valuable to you. 4:09 It also has essentially what's been called two systems. 4:13 One is the very system that runs in the background. 4:16 Kahneman and Tversky called it System 1. 4:18 System one is not something you can access consciously. 4:22 You can't go, hey, system one, I wanna know the answer to this question. 4:26 But it's in the bag doing things. 4:27 It's been in the bag doing all sorts of things. 4:29 If you're an athlete, that's what you're training when you're doing all those repetitions so that 4:34 you can hit the tennis ball from wherever it comes to or all those kinds of things. 4:38 But system two also has a lot of other knowledge besides balance and reaction time and all those other kinds 4:44 of things. For our generation, that's where the multiplication tables are. 4:47 So things can be in that memory and can get there very very intentionally and they don't have 4:53 to be Just physical things they can actually be cognitive things and that's where most of our brain works And 5:02 it's very efficient and it's highly networked and organized When you're trying 5:06 to remember something sometimes and you try to remember some of these name and you just say well It'll come 5:11 to me later. 5:11 Well, that's just the one that's searching for it for you 5:15 And sometimes the first thing you'll get is things like it begins with an S. 5:19 Well, that could be part of the organizational structure or they might be organized by where you knew them, 5:24 childhood friend or someone in graduate school or someone at work. 5:27 There's a variety of ways that can be organized that could be very different from one person to another, 5:32 but they are highly networked and it's highly organized. 5:35 So what System 2 does is it answers the hard questions, which could include what am having for lunch, 5:40 but mostly what I usually say, you know, 5:45 like engineering should be done with a pencil because that's where system two works. 5:50 But the thing about system one is it also can give us lots of answers to questions. 5:54 So sometimes when you have this thing that you call an intuition, 5:59 you know, somebody's asked a question, it just pops in your head out of nowhere. 6:02 Well, that's actually expertise. 6:03 It's all buried in system one. 6:05 The network was busy. 6:06 It went and found the answer to the question and then pops it in your head and you don't know 6:10 where it came from Because you it didn't come from you making a list It didn't come from you doing that kind 6:15 of problem-solving you do actively right? 6:18 It didn't come from you saying all right six times two Divided by add pie and I'll get something right? 6:26 Okay, and so when something pops up and it just pops up We call that intuition 6:31 so what cognitive psychologists call that is expertise, and that's part of what's in our massive memory. 6:40 So there are ways that our memory can fail us, absolutely, 6:44 and there are ways that you can help so it doesn't fail you, 6:48 and that's one of the things that human factors bring to the table when you decide how to phrase things, 6:54 how much information to put on display, 6:56 where you should put it on a display, how to display it, all those other kind of things. 7:01 If you understand how the sensory system works, 7:04 you would know that the sensory system will continue to take a signal as long as the signal is changing. 7:10 But if the signal becomes completely constant, the sensory system goes, I'm out of here. 7:16 You can feel that for yourself by just pushing a fingernail into your thumb. 7:21 Just push any fingernail into your thumb and just like put it behind your back or don't pay any attention 7:27 to it, talk to me, do something else. 7:29 And eventually you won't actually feel your fingernail or you can then move your hand forward and you go, oh, 7:34 it's still there. 7:35 That's because when a signal is the same over and over and over again, the system says, no new information. 7:41 I'm out of here. 7:42 Okay, so that should tell you something about whether people are very good at monotonous tasks. 7:49 So if you're sitting in front of a display that's not changing, think about a nuclear power plant, 7:54 think about a nuclear power plant where there are dials and things like that. 7:59 But if everything's working, the temperature is the same, The pressure is the same, 8:03 this rate's the same, everything's the same. 8:06 And it looks like that almost every day, all day long. 8:10 And so you can say, well, man, people are really bad at monitoring. 8:14 I hear this all the time. 8:16 And the fact is, we're horrible at monitoring when nothing changes. 8:20 Because we were designed to respond to things that are changing. 8:23 Because what could change be? 8:25 Change could be something good, change could be something bad, and you need to be able to know the difference. 8:29 Otherwise, you end up lunch. 8:30 no signal at all is not interesting so if you have a complicated array of displays and they don't change 8:38 for a long period of time and then on one of them a light goes out because data is no longer coming in 8:45 you might not see that for a long time because you've got so many things you're supposed to be scanning 8:52 and nothing is changing and your brain is just going like nothing's changing again is it 8:58 but that's that's not complacency no it's not complacency. 9:01 So what happens is that if you make a signal that's red and flashing in a monotonous display you'll see it. 9:08 If you make a small white light go away you'll eventually see it but it's not meaningful 9:13 and it doesn't work very well with our perceptual system that's looking for changes 9:17 and that's really too minor a change to notice in a sea of no change. 9:24 And so we can come up with all sorts of words for this like complacency, 9:27 but it's actually you've designed in an error trap. 9:32 You've designed a task that people are not good at, but are we designed for monitoring? 9:37 Well, let's think about that. 9:38 Where did we start? 9:40 Well, we started like all the animals somewhere, 9:44 and what's your job? 9:45 Your job is to find food. 9:47 Your job is to not get eaten. 9:49 Yeah, avoid predators. 9:50 We avoid predators. 9:52 And so it's a massive monitoring job. 9:55 The amount of signals that our sensory system is taking in all the time. 9:59 Now, your two eyes are not exactly lined up, so your brain then lines them up to give you depth perception. 10:04 And it's doing all that work all day long, and then it's looking for change. 10:09 And seeing that change may have you, when you're driving, actually slam on your brakes. 10:13 And then you're going, why did I do that? 10:15 And then you look around and go, oh, red car. 10:18 And then you go, Thank you system one because you can't actually be looking everywhere all the time 10:23 But system but system one can be analyzing the scene and looking for changes when you're looking for things 10:28 that you are worried about It's looking for the things that it's worried about all 10:32 of these things are happening simultaneously So monitoring is something we're amazingly good at but 10:37 I can design a technical system that defeats all of your ability to monitor and you will look 10:45 like a bad monitor or I could design a system that was actually meant for you to monitor 10:52 and that worked with your capability as opposed to sort of falling into the trap 10:59 of what your system is saying not interesting to. 11:03 And so that's one of the important things that we do as we look at problems and tasks and we try to say, 11:09 well, what are the capabilities we're bringing to the table and how do we make things so 11:13 that they're consistent with our capability as opposed to working against it. 11:19 So when we ask you to memorize long lists of things to transfer it from one screen to another, 11:24 we're working against you. 11:25 When we make cut and plate paste so you can do it with a control C, then we're working with you. 11:31 You have to understand what the memory, 11:33 what memory does to then decide whether you're good or bad at it and then how to design the workspace, 11:40 the work Environment for that. 11:42 I mean, it doesn't matter whether it's mineral or physical, right? 11:46 I could have you Attaching things and I could say this has to be torqued to a certain level and if 11:51 I create the place So you're working blind and can't see the torque wrench then you could under torque 11:56 or over torque it When you under torque it you can probably pull the wrench out read the number and 12:01 then put it back on but you've over torqued It now you're in a problem if you can't see it 12:04 You can't actually control that and can't feel it. 12:07 So that's a bad design that goes back to that access thing And so you can say well people he was careless. 12:13 He didn't he wasn't paying attention to torquing Well, 12:16 you can't do it blind and so and unless you create a different system now You could add things on 12:22 to your torque wrench So it gave you an auditory signal or some other signal when it was getting to the max 12:27 of the torque and and then it Would be fine So you either have to give them visual access or you have 12:33 to redesign the tool to give them the information they need It's not neither and so that that's sort 12:40 of the trick And so when we're doing human factors, we think about the social-technical context, 12:46 the organizational context, the environmental context, all of those contexts. 12:51 And then we ask, what is the job of the human? 12:54 And we also want to make sure we take advantage of all the human's capability. 12:59 We're flexible. When something happens, 13:02 we don't expect we can still have hypotheses about what the right thing to do is next. 13:07 We are highly resilient and we're needed until we can develop technologies that never fail. 13:16 And I'm pretty sure as long as they have mechanical parts or whatever else, 13:21 that there's going to be roles for humans everywhere. 13:25 The trick is balancing the technology, the mission, the humans to make sure that you up with success, 13:33 efficiency, safety, in the end. 13:36 And that's where human factors comes in. 13:38 How did you get into this role in the first place? 13:41 What has led you to this? 13:42 So I started my undergraduate degree in mathematics. 13:46 And when I was ending my undergraduate career, I didn't quite know where to go. 13:52 And my dad said I had to go to graduate school. 13:54 So I was, I said, okay, I'll figure it out. 13:58 So, I picked quantitative psychology because it sounded like math, 14:03 and it's basically all the statistical and mathematical modeling that you might do of human behavior. 14:11 And so, most of my classes in graduate school were statistics, 14:15 and some of them were basically about human performance and human behavior. 14:19 And then I ended up a college professor at William & Mary. 14:22 And when you're the only statistician in the department, you end up helping everyone do their projects. 14:28 And so one day you're helping the faculty member do some work on same memory, 14:34 the next day you're helping a student who's doing a project on fetal alcohol syndrome with rats or something 14:41 like that. And so you're getting every part of behavior from sensory behavior to team behavior and everything 14:49 in between. And I never felt like I should just like not know anything. 14:53 And so they, you know, I'd read a little bit about it and learn a little bit about it so 14:58 I could be more helpful in helping design experiments and things like that. 15:02 And so although I had my own research career, 15:05 I spent a lot of time developing knowledge of all aspects of behavioral performance. 15:14 And at some point NASA called me and asked me if I'd like to work for NASA. 15:18 My first thought was, has anyone ever turned NASA down? 15:23 I was a college professor at William & Mary, but I got called by Ames. 15:28 I had done a project at Langley with someone in human factors about seven years or so before 15:34 on a topic called workload, one of the many metrics we use. 15:38 Just not about doing the task correctly, but how much work are you doing? 15:43 Anyway, I had done a workload task, 15:45 and so they offered me a job to be a branch chief at, in the human factors division at Ames. 15:52 And I went, okay, yeah, that sounds good. 15:57 So even though I love being a professor, and I love teaching students, I brought my family to California. 16:04 And the group that I was in charge of was the group that was doing the scientific 16:10 data on how people work, and also how they work with tasks, 16:15 but they were mostly very basic scientist still doing behavioral performance, 16:20 but in the context of NASA's environment, 16:23 so the different kinds of stresses NASA has, 16:26 because all the basic work we have on human capability doesn't necessarily apply in all the environments that 16:32 we use because we're doing these extreme environments like CO2, 16:36 or on the moon we're going to be in very dark places and things like that. 16:40 All the knowledge we have doesn't necessarily go to all those places, 16:43 and And so my job was to translate what we did to other people at NASA to essentially explain why what 16:52 we were doing in human factors was important across the agency, 16:55 which again gave me expanded my view of behavioral performance as I was working with all the different groups 17:04 at Ames and then at Langley and JSC eventually and then eventually across the agency. 17:11 And so I ended up with a broad breadth of at least the one sentence elevator speech on why it's important 17:17 to consider whatever it is. 17:20 So short term memory or decision making or whatever it might be. 17:25 So I became the person that had the essentially experience and allowed me to think about how 17:33 you triage a problem. 17:35 So when someone comes to you and you hear that they're working on a particular problem, Well, 17:40 what kind of human factors do you need there's over probably two hundred specialties You could have 17:47 in our discipline that you get a PhD in and so all my background in doing things 17:53 that were Helping doing statistics for a variety of different projects Trying to explain the work we did 18:01 which meant I had to learn what the work was right getting deeper into work in different directions and sort 18:06 of put me in a really good position to be the person who looks across the agency and says, 18:12 are we using the right methods? 18:14 I don't expect myself to have the expertise. 18:17 I expect that I can have a good view of what the discipline is. 18:22 And I also have a pretty good view of the capabilities of the people within NASA. 18:27 And then I can match those up with the problems that the NESC has, 18:31 or if it's just a program And I just hear that there's a problem that might not be something 18:37 that needs an investigation but could use a different point of view than I can suggest who they can talk to. 18:43 What are some best practices in knowledge management? 18:46 Like, how do you ensure everyone has that knowledge? 18:48 One of the things we do in the NESC is we have NESC Academy videos where 18:54 if somebody is doing something interesting, we try to get them to come and talk about it. 18:58 The NESC Academy has things for all of the disciplines. 19:02 So it's not just human factors We have quite a few human factors things there. 19:06 Some of them are about assessments We've done some of them are about things we did for a program and project 19:12 that really turned out Well kind of things we're beginning to do more of the you know interviews like this 19:19 with different experts on very specific topics that we think would be useful and 19:25 And the other thing we're doing is we're building, 19:27 we're building new tools that are specifically designed for NASA. 19:31 So our target mission was humans to Mars. 19:34 And the question was, well, what kind of expertise do you need? 19:38 And how much can you put in one person's head? 19:42 How do you think about that? 19:44 What kinds of things need on board expertise and what can wait to phone home? 19:50 Even if phoning home is infrequent. 19:52 And so we've actually built a modeling tool where you can redesign your mission and then 19:59 we can put that in and see what that pushes out for the crew size. 20:04 So there's a lot of thought process that has to go into how you think about what crew role really is. 20:12 What was your giant leap? 20:14 My giant leap was just olden flag. 20:17 I wasn't the kid who, I saw all the launches, 20:21 I mean, but I didn't imagine myself working for NASA the week before they called. 20:28 A lot of my colleagues, you know, they knew NASA was their destination and then they just had 20:35 to figure out how to get here. 20:36 I didn't know NASA was my destination, 20:39 but I think if you look at what I've done since I've gotten here, 20:43 you realize I bought in immediately and that was my big leap was probably 20:52 holding the flag and swearing in. 20:55 That's great. Well, thank you, Cynthia. 20:57 Thanks for your time. 20:58 It was fun. 20:58 Thank you. That's it for this episode of Small Steps Giant Leaps. 21:03 For a transcript and for all other episodes, visit nasa .gov slash podcasts. 21:08 While you're there, check out our other podcasts like Houston we have a podcast, Curious Universe, 21:13 and Universo Curioso de la NASA. 21:15 As always, thanks for listening. 21:29 This is an official NASA podcast.
متن خودکار (ممکن است خطا داشته باشد). این متن را رایانه از روی صدا نوشته است، نه ناشر؛ اگر جایی با صدا نمی‌خواند، به شنیدن اعتماد کن.
درباره‌ی این قسمت Dr. Cynthia Null, NASA Technical Fellow for Human Factors, discusses the myths of human limitations and how she got involved in the scientific discipline of human factors.
Small Steps, Giant Leaps (NASA) .
تولید ناسا؛ طبق nasa.gov «محتوای صوتی، تصویری و تصویر ناسا عموماً در آمریکا مشمول کپیرایت نیست» (مالکیت عمومی)؛ نشان و نام ناسا و مواد شخص ثالث مستثناست.