You to here . Guest so im actually a researcher. I work on integrated optical sensing methods and technology. Host and before we get into what those are, whats your background . Guest so i have a background in solid state physics and semiconductor devices. Wheres your degree from . Guest berkeley. Ucberkeley. Host and ph. D. . Guest my undergrad was at iowa state university. Guest are you from iowa . Guest im from minnesota originally. [laughter] host well, youre here at bell labs now, and youre working again on guest im working on optical sensors. Host which is what . Guest really anything that detect light. The most familiar youd be familiar with is a camera which we all basically carry on us every day. Typical cameras only see twodimensional images. So what im working on are 3d Optical Imaging techniques very similar to radar but using light. Host arent those in practical use today already . Guest yes. There are some uses of these. One of them is in the medical field, its a technique called optical coherent [inaudible] and you can use it to do 3d imaging in the eye, for example. You can actually get a micronscale resolution of your entire eyeball and the retina just with light. Host and thats pretty common, isnt it, today . Guest yeah. These systems are becoming more and more common, especially in optometry. But the systems tend to be rather large. They take up a large table and cost tens, even hundreds of thousands of dollars. Host so whats your research doing . Guest so im working on taking that entire system and shrinking it down to the size of a chip, something that we could actually integrate maybe in all of our phones, possibly even on the clothes we wear. And allow us to not just monitoring ourselves, but also the environment around us in full three dimension. Host now, how far are we away from that technology . Something theres a lot of challenges we still have to overcome, but we right now have all of the Building Blocks that weve kind of developed with the Optical Communication Technology that bell labs has pioneered in the past. Were now repurposing this technology for this new tech anesthesiology. Host so in your work, is it completely healthrelated . Is that where youre headed . Guest thats definitely where im headed, is healthrelated. Really sensing the biochemistry of the human being and basically monitoring our health on a day to day basis. To me, its really one of Biggest Challenges we face as humanity, is how we feel, and its really something that we dont monitor. And so really theres a lot of opportunities and challenges to overcome to really make dontous Health Monitoring a reality. Host so in a sense, is it sensors and then the math that goes into the optics . Guest yeah, yeah. So theres really a whole spectrum of work that needs to be done. Both making the components that can be small and integrated, putting it in a system. Theyre actually copping the developing the algorithm to actually diagnose things with these tools. Im not a doctor. I dont have a medical background. So what i do is i really make tools, new tools that can help those professions actually do their job better. Host so, mr. Eggleston, you talked about the 3d eye image. Where else can or is this being used today . Guest yeah. So its really seeing a lot of uses. So the second most common is in skin care. So, for example, if i have an abnormal growth or something on my hand, i can actually do a full 3d scan of it and tell is it cancerous, is it benign, is it something i need to look at. And its completely noninvasive. You dont have to cut anything off, you dont have to take a blood test. Theres many other fields people are using it. Dentistry, you can actually look at the enamel of the teeth and see microfractures before they develop into cavities. Even inside the body theyre using this to do internal surgeries where theyre needing to see what theyre doing on the inside of of the body. So really the range of possibilities is kind of endless. Anything youd want to see or sense you can kind of use this technique. Host now, a lot of us are familiar with mris. How old is that technology, and is it related to what youre doing . Guest yeah. Mri is a pretty old technique. Functional mri was actually pioneered here at bell labs, and its a great technique. It lets you scan the entire body. But the resolution is on the order of millimeters to centimeters. Its very, very challenging to scale down, and thats why theyre very expensive and people dont have access to them. Now, with these optical techniques, they can be very small, very cheap, and they can allow us to do a lot of the things that were doing with mri but at much lower cost. Host so whats more important in your work, the scale or the technology . Guest so to me, i think they kind of go hand in hand. But at the end of the day, when you can scale something down to a small size, you can make it cheap, and really you enable it to use for a mass audience. So an mri is great, if we all had access to mri in our daily lives, it would significantly enhance our health. So, to me, really helping everyone is one of my main goals, so thats ooh why i think driving the size down with the technologies we have is so important. Host now, on your door here is a sign that i want to ask you about. Danger, invisible laser radiation. [laughter] guest yes. Host happening in here. What guest so a lot of the sensing that we do is in the infrared. So its longer wavelengths of light than what you can see. And we tend to use rather highpowered systems when were demoing them in the lab. So this is just a warning that depending on what experiments were running, you might have to wear safety goggles. Now, as you can see, my door is open. Thats how i usually work. Usually we dont use these lasers, because were really looking at something thats used to scan the eye, so its actually completely safe. Host where is a laser . [laughter] do you have one in here . Guest were surrounded by lasers. I can bring you over here and show you some examples. Host and these date back, in a sense, to einstein, dont they . Guest yeah. So, lasers date back to the late 50s, early 60s. Host based on his work . Guest yes. His ideas. They usually come in a form like this. Host so thats a laser in there . Guest this is a laser. This is a pretty nice laser thats used for medical imaging. And the actual laser is much, much, much smaller. The lasers can actually be, actually even, for example, if you have the air pods with your iphone, those have three lasers in them. Youactually make them very, very small which is part of the reason theyre so attractive. Now we can embed them in everyday devices, and they have an incredible amount of added functionality. So, yeah, this is a laser. We actually have several lasers on this table here. And theyre all different form factors, shapes, sizes and really its all about packaging. Lasers are tiny, but we put them in large boxes because then theyre easier to handle. Host so before we interrupted your day today, what were you working on . Guest so im working on a new method to actually implement these systems on chips. So a lot of it actually is about when you come to system integration, its writing codes and algorithms to actually to do what you want to do. When everythings tiny, you cant physically change it, so everything has to be automated. So i was actually writing code to do this. Host where did your interest in this topic, in these topics come from in. Guest so ive always been fascinated with light. Host with light . Guest with light. To me, like, my vision is my number one thing. And so when i went to school, i learned more about light. And light is amazing because everything it touches, it actually picks up the signature of that material. So every beam of light that bounces off you and hits me actually carries information about you. If i look at it in the right way, i can discern an incredible amount of information from that. So that kind of curiosity has led me down this path. Host Michael Eggleston with bell labs, thank you. Guest thanks. Host and the communicators continues its visit to Nokia Bell Labs in new jersey, and joining us now is a gentleman named sean kennedy. Mr. Kennedy, what is your position here at bell labs . Guest so im a department head, and i lead the math and networks team. Were interested in a lot of things, but Artificial Intelligence, augmented intelligence and, you know, a whole host of other Network Algorithms we try and develop here. Host before we get into those guest sure. Host what do you mean by map of networks . Guest well, networks are, from one point of view, just a structure you can look at. We study the properties of these structures, and then we, generally we build algorithms to solve problems. So whether its questions about how you get information from one part of the network to another part of the network, or, i mean, you have facebook which is just a large network, so lots of networktype problems come from studying these, the structures of these networks, and you can decide things like who you should be friends with next and these other questions that, you know, we experience on a daytoday basis. Host you mentioned Artificial Intelligence. How do you define that . Guest thats a good one, actually. Im not exactly sure how i would define it in general. I mean, i think people tend to think about replacing human intelligence and thinking machines. We have, like, selfdriving cars and things like that. I tend to think about it a little bit more like a mathematician, so right now Artificial Intelligence is just a giant optimization problem where we build ma cheaps or machines or mathematical models that do a good job of answering the questions. For example, we may have a lot of data that is cat images and a whole bunch of data thats not, and we build a model that is able to decide which images are cat images and which ones are not. Its a large optimization problem. Host is siri Artificial Intelligence . Guest yeah, i think so. Whether or not theyre thinking machines, i would say, no, but in the space of an optimization problem, they definitely fall into that realm. Host whats the difference between a thinking machine and a learning machine . Guest uh host are we there yet . Guest no, no, definitely not. We dont have intuition built into these machines. If i show you a cat picture, youll probably do 95, 96 getting it right. But the machines do ap excellent job as well of identifying cat pictures, right, but theyre not really sometimes theyre surprising us. You also probably drive a car really well, and machines are able to drive cars now. I think theyre not yet thinking machines. Theres no they dont really show a lot of intuition behind what theyre doing. Host dr. Kennedy, what kind of research or whats the, whats the back end of that machine recognizing the face of a cat . I mean, what kind of technology is that . Guest so its generally a big network. Its a convolutional Neural Network. Dont have a picture here, but they are Large Networks where you input the image just by the pixel values, you know . An image is nothing. You have these dots on the screen, and they show up with different intensities so you can turn this into some sort of digital signal. So you feed it into this network, and theres a whole bunch of nodes in the middle of this with edges that use this to compute different values as it pushes itself through the network. Im not sure thats the clearest answer here, but host well, lets go to the 1s and the 0s before we look at whats on the board. Why is everything in iss and 0s in 1s and 0s in your world . Guest well, because we digitize everything host right, but what do they mean . Guest they can mean anything. They can represent your heart rate in your watch thats reading your heart rate, or they can be the pixel images that we send to the screen or an image that we can produce on the screen. Its just the way that a Computer Stores information, is in 1s and 0s. So thats normally the way we deal with information. Host all right. We are in whats called the anomaly room here at bell labs. What are you going to show us . Guest so what were talking or what we have here is called augmented intelligence. So rather than trying to replace the human thinker, what were trying to do is were trying to build tools that help humans understand information. And so were not doing this in a way that is just for data scientists, we want to build a tool that is simple enough for children to look at. Indeed, i have examples of ingesting data from pokemon that kids love to play with. We took this to a robotics conference, and a whole bunch of kids were playing this and explaining the me how pokemon worked. But what we want to do is ingest data of all types across all spaces whether its iot sensors or image sensors or tax data, etc. , scraping the web for documents, etc. , or even, you know, your web site that has videos, etc. , we could scrape this information. What we want to do is build an interface that allows people to explore this information so they can see this information in a way that theyve never seen it before, allow them to compare things inside this data set so they start to understand why things are showing up on the screen, and then ultimately, we with want to use this information to create knowledge. What we mean by creating knowledge is we want to be able to make decisions about this information. You could imagine youre given some huge spread sheet or some web site, some document you want to ingest. Ultimately, whats useful for you is to take that data, so the 1s and 0s of the document, turn it into information, but ultimately knowledge that you can use to answer questions. Maybe your boss is asking you for some information from this document. So what we have here is what we call augmented intelligence and what we think of as assisted thinking tools. So theyre tools that allow us to think better, to answer questions better. Host well, lets hit be pokemon and walk us through what augmented intelligence can do. Guest gotta have a special touch. Host ah, i guess you got to be a mathematician. Okay, im going to stand back. You go ahead and walk us through guest this is just massive information from pokemon. Like, we ingested you have the different creatures, whatever you call them, the pokemon, i guess. And you have a whole bunch of extra features about these pokemon. The screen shows a global ranking of what the smart machines that underpin this machine thought were the most important things. So if theres something on here that you find interesting, another feature we feel if youre going to play with data and use data, you want to interact with data. So perhaps you find this guy interesting. So you simply touch him. Now, by touching him, what youve done is youve indicated to the machine that this is the piece of information that youre interested in. Its not showing here, but we also have the ability to tell the machine youre not interested in certain piece obviously information. So once with i did that, what you see is immediately the screen was reorganized around the pieces of information that were interesting. So you can see these are different, you know, properties of these different pokemon whether its their way that they breed, i guess, or their name, general category overall. Continue . Host yeah. Go right ahead. Guest this is a bit of a toy example and, you know, we did this mostly for kids to think about information, but, you know, or, you know, just to play with information or just to get contact. But, you know, when youre thinking about a problem, what you want to do is you want to take that information, and you want to quickly kind of streamline it to the pieces of information that youre interested in. I mean, i guess you could think about doing an interview. Youd quickly like to be able to scrape these documents and go through and extract the pieces of information. Something would catch your eye in a document, and youd collect that, and you would hope youre able to reorganize the screen to help you filter on these pieces of information. So, of course, when youre thinking about things that are, when youre thinking about a problem, lots of times we dont want to think about the things that are just immediately related to the subject, we want to look further out. And, you know, thats a what im able to do with this machine. Im able to zoom in and out on the data to look for things that are related. So maybe well go, ill see if i can come up with a slightly different example here. You have questions . Keep going . Host keep going. Guest lets see if this one works. I never get to play with this screen. Obviously, i dont have this in my office. I dont think this is the one that i want. Or maybe yeah, lets go with this one. So one of the curious things about Artificial Intelligence which i get maybe comes to crux of why these machines arent really, you know, theyre not intelligent in a sense is that if you were to train up a Neural Network or to recognize cats, to go back to our simple example from before. You did a good job of sticking images in. If you put in a cat image, 100 of the time it says cat, if you put in an image thats not a cat, it says not cat. So the question is whats it going to do. Did you learn anything about that cat. Or what about similar things like, whats going to happen, for example, if i stick in an image of a fire truck. Is it going to solve my problem . Have i learned something about the structure of cats thats going to help me recognize fire trucks . You know, its curious that it could kind of return either thing, right . It doesnt really contain any intuition that is helping you get closer to recognizing different types of images. Youve done a really good job of training on cats, for example. So is we get here in this space, we said, well, what we should be able to do is train a big Neural Network and then use this Neural Network to help us understand what things are similar and what is happening in the inside of a Neural Network. So, for example, is there something here that catches your attention . Ill give you a second chance, no third chance, to touch the screen. So tennis serve. Host will it teach me a better tennis serve . Guest well, i would hope so. A. [laughter] these are all images related to tennis serves. This is not based on keywords, more important this is on deep learning features that underpin each of these images. So you can see why these images are similar is not because of the tennis serve, theyre similar i mean, you can just tell as a human when you look at all these images in the middle, they seem very similar, right . Perhaps you could describe it, right . But getting a machine to to describe it has become a little more difficult. Host so augmented intelligence is being used now, correct . Guest well, yeah. Right now. Host well, i mean, in a practical sense. Guest i mean, i think so. We build tools as humans very naturally, right . So the idea of augmenting our physical limits is being used. And, you know, for example, google can be thought of as, like, augmented memory in a sense, right . You dont have to remember anything. You can go to google, and it will likely pull it up for you. Of theres lots of tools which try to augment. We believe this is a different spin on the actual way that were using this tool. Host Artificial Intelligence, are we using it today in today . Guest well, like host not in this room, but on a practical level . Are people in the world using Artificial Intelligence . Guest yeah, yeah, for sure. I mean, like google and facebook and selfdriving cars, like, these things exist, right . These are real examples of machines that are able to do things that humans cant anymore, right . Host how far along with rein our research and our knowledge of a. I. . Guest i mean, i think weve done a very good job i mean, so we are where we are right now in the Artificial Intelligence space because of the massive amounts of data that are available to us and the massive amounts of Computing Power that exist now for essentially free and for our ability to transport and our ubiquitous activity, the fact that we can collect this data from anywhere at almost any time. And these things together i mean, the ideas behind reenforcement learning techniques are 30, 40yearold techniques, right . Right now we have a lot more computational power and data to make these techniques actually work well. So as for this leading to smart machines or intuition, its hard to say. I mean, i think we will continue along this path. I think we will be continually surprised by what machines can do yearoveryear. Whether or not theres builtin intuition, thats a good question. Host sean kennelly, youre also working on Virtual Reality . Guest i am not host you are not. Guest no, ive watched a lot, but i dont think i should be given you one. Host so Artificial Intelligence, augmented intelligence are the two things youre working on here at bell labs. Guest my main focus, yes. Host thank you for your time today. Guest youre very welcome. Host and now on the communicators on our tour of bell labs in new jersey we want to introduce you to [inaudible] what is your title here at bell labs . Guest i run the Research Department where we work on the next generation of asic for telecommunications. These are highly specific circuits. They differ from your traditional microprocessors which do general computational tasks. These could be for wireless designed only for that specific host now, anything that youve worked on, is it in the public right now . Are people using one of your products in. Guest so there are actually some of the stuff. I havent been around for that long here, only eight years, but certainly stuff that bell labs has built has been in the industry, and we have recently released some products where we use our communication [inaudible] yes, theyre going to be out there. Some of your traffic of your cell phone internet goes through that. Host so what are you working on now . Guest well, a lot of things. I guess on the fore or front probably the most exciting is for 5g communication host which is . Guest so 5g is an interesting thing because its in a hundred years since we had marconi with the first wireless communication, but this has changed our species. This is what we do. Thats what all wireless communication is, your wifi, your bluetooth. But what we want to do is we want to go to a new era of communication, and that era of communication is directed beam communication. As opposed to broadcasting the signal be everywhere, you want to target the beam at individuals. And the reason we want to do this is because our thirst for data is never ending. So we always want more and more. And we have saturated our spectrum at lower frequencies. We simply dont do it anymore. So we have to go to higher frequencies, and these have many other challenges. One of the challenges is that the signal loss through the years is too much. We cant do [inaudible] if i want to talk to you, i have to direct my beam directly at you and get some day from you and then move to the next person. So this is a completely changing paradigm in in communications. And with that, of course, a huge set of challenges. The entire Wireless Industry is [inaudible] host and its being looked at being rolled out in the next couple of years, isnt it . Guest yeah, yeah. Its an ambitious goal. Different vendors want to try this and give users the ability to do it. Its exciting and difficult for everybody, and i think its a great bell labs problem, because theres so many things you need to solve and mostly in terms of cost, performance, integration. And this itself means that you need a really mullingty disciplinary environment to target these different problems. Thats why bell labs is so good, because we so much expertise ino many different areas, it can all come together and produce results that could be quite revolutionary. Host now, my guess is that bell labs is not the only Research Facility working on guest oh, no, not at all. Host is it a competition . Guest well, i mean, everything is a competition, otherwise it wouldnt be worth doing. It is an exciting and worthwhile problem, and certainly a lot of big people, a lot of smart people in our industry are working on it. And, actually with, everyones innovations are going to come together to create this next revolution in communication, and i think were all excited about it. Host how will 5g change our daily lives . Guest so essentially at its core what we wanted to do is give you more data than you can currently get. So with that, we can change the way you use your smart devices, your computers, your cell phones. So right now, for example, lets say if in the future you want augmented or Virtual Reality, this type of technology is by their nature need a lot of data, and that data is not very well supported in our current, existing wireless networks. So if you want to enable those technology, really enable them on a mobile basis where you can use them freely and wouldnt have to think about it, then thats what you would need. And this doesnt even include all the other High Resolution 4k tv series that you want to watch, whether you have your next cell phone transmit tens of gigabytes of data all the time around, thats the only way to do it. So if you want to get to a point where you can do this freely, we have to get this 5g problem solved. Host you cant develop this or work on 5g in a vacuum, right . Guest yes, of course. Host other people are working on similar or related products . Guest yeah. So as far as my expertise is on the circuit design, on that asic thing you were talking about earlier. So we will be making the communication ics. But, of course, that will then have soft some sort ware that have some software that runs, a mow dumb, processing that happens, and some application layers. It also needs manufacturing, material engineering, civil engineering, theres all of these different disciplines have to come together, and we have to Work Together. Its not like the 18th century where you could walk out of the door and discover something. Now almost everything is a hugely collaborative work. So thats the nature of research nowadays. And we are standing on the shoulders of giants, the people who have done the work before us. I think its quite exciting. Host do you have access to all those different expertises here at bell labs . Guest yes, yes, definitely. Bell labs is probably one of the most multidisciplinary institutions in the world, and is we have quite a range of expertise here ranging from software, even quantum computing. So its definitely going to be, make it easier to have all of this together. And we also, of course, collaborate with universities and even other competitors. We always Work Together in a way to make this happen. And i think its going to happen. Its just a matter of time. Host whats your background . Whats your degree in . Guest i have a p. Dish in electrical ph. D. In Electrical Engineering from canada. I worked on similar circuits but not exactly wireless applications, thats the thing about having a ph. D. K it isnt necessarily about the exact thing they teach you, its more of a thinking method, how to learn few things is already new things is really what a ph. D. Is all about. This is one of the reasons why its such a nice research institution. Everybody comes with the mentality to want to learn more, invent and innovate. Its quite amazing. Host is Electrical Engineering, is that a misnomer in a sense . Guest well, in a way, im more of an Electronics Engineer than an electrical engineer, but, yeah, my expertise lies in electronics. And this involves, also, optical communication that we also work on, we build quite a few optical components as well which is quite exciting. Its just not for 5g, but it really is for the same reason. We want to send more and more data through our fiber optic networks, the same we want to send through our wireless networks. So for that, you need innovation in the same way. Host is spectrum unlimited . Guest well, in the law obviously the universe, yes. But in the laws of government, no. [laughter] so is you have to be very careful, and the rule is placed to make sure you dont step on someone elses spectrum. This is, obviously, so people can Work Together. So whenever you make something that you want to ultimately commercialize, you have to make sure you obey by those regulations. And spectrum is very precious. M carriers purchase these for hundreds of millions of dollars, if not more sometimes, to be able to own that spectrum so that when you make a device, you occupy their spectrum. And this is a normal technique, and its even true in optical communication even though youre only within a fiber, you still have to confine yourself to within a particular wavelength and particular frequencies,st just the way it is. These innovations will continue to some degree. A lot of it has come from bell labs. Mimo is an interesting wireless communication technique where you have multiple transmitters and receivers simultaneously talking to each other. Even though at any instance of time all the signals are mixed together with clever digital processing so you can separate them again. This increases the capacity of whatever medium you are using. If you want to take these ideas to highfrequency where 5g is supposed to be, that makes it more challenging. Its very ambitious but he thought to take most of the spectrum, thats what you need to do. Host you mention mentionedr from candidate. Spectrum is borderless. So how do you get the standards the same in the u. S. And canada, and around the world . Guest of course. There are some differences especially with europe, a different entity. Youre right, in the sense that it some collaboration between government agencies, between corporations, especially International Corporations came to make sure every product works into the country. Sometimes went to modify what we make for Different Countries to make it suitable. In japan there might be spectrum thats not available in the United States so that would allow you but thats common as with anything, even with cars. Look at the automobile industry. Rules and regulations are not the same everywhere so there are some tweaks that need to be made between cars in Different Countries. Its exactly the same with spectrum. Host has that evened out a little bit, the International Standards . Guest i would imagine that yes, people obviously want to make less variations of whatever they invented you dont want to make 20 different versions because there are 20 different rules. Certainly there is some uniformity across the world just make things simple, the special if youre to have her cell phone traveling around the world. It will have to work everywhere. You cant put every type of wavelength into a frequency on top of the same device. So yes, there is some collaboration. This is going to continue. Host we were staying in an actual lab. You build things here. What are we looking at over here. What can you tell us about . Guest this as a prototype for a phase array that we built a couple years ago. We demonstrated this and was quite exciting. What is unique about this particular system is the operational frequency is very high. This thing operates at 90 gigahertz. As you can see the antenna on the surface of this board, very, very small. Host these are antennas . Guest yes. Theres about 20 of them in each little section. The reason theyre so small is interesting thing about antennas is make it small as the frequency becomes high. Its just the laws of physics. So 90 ghz your traditional antenna that would normally be very large becomes a tiny dot. It makes integration quite exciting. By the same time making circuits work at 90 ghz becomes that much harder. Theres a challenge of making it. This thing is capable of sending many, many bluray dvds per second. It can steer the being electronically as i was mentioned earlier and target different people. Host is this part of your 5g research . Guest this is definitely part of the 5g research but the frequency that this particular prototype is working on isnt necessarily a 5g frequency thats going to be in the first deployment. The first of one is looking to be about 28 gigahertz. The philosophy is it you can solve problems at 90 ghz you can definitely solve them at 28 gigahertz. We are doing the tougher problems to the risk then and evaluate the feasibility. Host thanks for your time today. Guest you are very welcome. If you like to see more of cspans communicates programs go to cspan. Org and look under the series link on the homepage. Cspan, or history unfolded daily. In 1979, cspan was created as a Public Service by americas cabletelevision companies and is brought to you today by their cable or satellite provider. Talus about how it works in the brain . You can think of it as light at the outer and. While it is true humans seem to be endowed with the capacity for care, the result of having these babies were to take it, you know, amy him capacity can go awry during development. Psychopathy as a development of disorder that seems to be at least partly related to genetic problems, not completed but in part. That seems to result in people having no capacity to care for anybody but themselves. It is something that occurs in a severe form in about one or 2 of the population. What we discovered is people who are psychopathic have brains through the opposite of people are very altruistic. So were have brains were active, people are so psychopathic are smaller. The title of your book is the fear factor. What role does fear it will be deleted capacity to recognize fear in others, what role does that have in psychopathy . One of the things thats been observed for beginning, research scientifically for maybe 60 or 70 years now, is a people of ten get sort of a bold personality. They are not susceptible to punishment. They dont respond to things that are threatening very strongly and this is one of the reasons people are psychopathic came to a thin and reoffend over and over again because way they that punishment is supposed what is that if you fear getting punished you will do the thing that will result in punishment. It doesnt seem to be the case of people are psychopathic have that response. For a long time it was suspected something must be wrong in thin because it is essential for the ability to develop a normal fear response. You and ive had this discussion. Theres also the inability to recognize fear in others. How does that play out . Why do some of you cant spot fear in someone else tend them towards psychopathic acts . This is i think some of the most Interesting Research questions that ive been doing over the last couple of years. What we think weve discovered is when you see or hear or think about somebody else who is experiencing fear, in order to understand the emotion they are feeling you have to recreate or simulate that emotional state within your own brain. Its essential a cinch of livie experience for yourself answer if you dont have a strong response when you see of your somebody else is afraid, you cant recreate without emotion is like and you fundamentally cant understand what the other person ceiling. You cant emphasize at the very lowest level. So the breaks that would stop a normal person from hurting that of the person, those about there . Thats exactly right. Normally if one of us also made was fight by something we were saying or doing, our ability to simulate with that fear would be like would be enough to stop us from doing that thing. If you dont have the ability to do that, he just go right on the head. You can watch this and other programs online at booktv. Org. Hello. Were going to get started here tonight. My name is seth mnookin. Im the director of the communications forum, and a couple of quick announcements before we start. First, communications forms are held three times a semester, six times a year. If youd like to be informed of future events, there is a signup sheet over there. Put your name and email and we promise will only send you news about our six events a year. We have pretty good ones