al jazeera. i'm morgan read radford. "techknow" is next, and we'll see you at noon eastern. nerds. tonight sharks. we are tracking some of the misunderstood cret cite cret cre dry cre creatures in the sea. we are behind the wheel of the fruifuture testing out the drivs car. tonight police, science and a

computer program may be able to predict crime before it happens. i am an ento entomologist. that surthat is our team and leo some science. ♪ hi guys an welcome to techknow. and rita rear going to start with you. your story combines two of the coolest things armed -- around. you mean robots and sharks. >> robots and sharks. >> this is the coolest thing i have done and i was at the call state shark lab. and they are using a new piece

of technology that is follow; is thasharks under water to revolutionize the way we are looking at science. let's take a look at it. this is catalina island. 27 miles off the coast of los angeles. a place known for it's beauty both above and below the ocean that surrounds it. most of the dish that call these waters home go relatively unnoticed. but one spic species is impossio miss. leopard sharks. hundredses of them. >> if you are the director of the shark lab and you are trying to revolutionize the way sharks had studde studied it's not a bad way to set up shop. chris lowe is the director of calcal state long beach's shark lab. getting to know him and his work is getting your feet

wet. obviously here a day at the office is a diffe different attd a different look at the world. >> it takes a few moments under the water to understand chris' passion for the othe ocean and e sharks he study:whe : >> when i caught my first shark there was something about it. it looked so different from all of the other fish i caught and it looked so streamline and sleek. it didn't match all of the fish i caught. >> what about it from the sharks threat that interested you in a sciencivic perspective. >> they are at the top of the food chain. they are the canary of the coal mine and they tell us how healthy the oceans are. the wheel lengt challenge is ha. you want to th want to the share here and they do and mostly they

don't. that is a tricky part. how do we find a way to study them where we don't have to be right there to influence their behavior. >> the answer he believes is this. >> this may look like a tor toro but this is a robot they are talking about. chris clark you are the man gee behind it . >> we have a av and we want to collected datcollected data abo. it use us sensors and a compass and a doppler velocity log. >> what are the sensors and what are they doing. >> we attach sensors for the that listen for the sharks. it listens for the tags ateached to the sharks and it will drive around and follow the sharks as they move. what we have here are dummy

plugs and these attach to a hydro phone. it's like a mike r microphone bt goes under water. the hydro phones are listening for acoustic categor tags and te things this big that attach to a fish or shark. every two seconds they will ping, ping. >> these robots have been used to shall for a decade now. they are used to mo monitor temperature and light and all things you want to know to monitor the ocean. we are asking the robots to do one more thin thing. we want them to follow the shark and characterize the enviroment. so we can build a 3-d map of the animal that we are tracking. and we know where the animal is

in that 3 3-d space. and when the animal does something different is there anas spenanas anas suspectanaspect of their et is changing. you have a fishery that is being over fished but how do you know, just like when i was a boy the fishinfish didn't move away. it's a possibility. our ability to understand that is that managers can better manage fis fisheries . that is one example of knowing where animals go. >> this is all easier said than done which is why the group comes to canad catalina testing. >> we are trying to find it and get

as accurate as position on it as possible. ♪ zblrch the two chri. >> the two chris know when they have hit the mark. what is it like from being a boy the cool part is fro being a kid asking those basic questions. i'm still asking those questions but we have bet er better tools. >> what is the end game here how do you see the nothing changing and marine science. >> i envision a day of when we will have a fleet of these

robots and they will enable us to do things that we have never been able to do. measures as spen aspects of behr that we have never done before. i think this is going to change our field. do they think there is potential for this robot to alter the behavior they are observing? i know if i had a robot tailing me all day i would act a little different. >> that is a good question. i talked to them about that and they are interested in shark mivbehavior. and this is a device that is following them in real-time and keeping a healthy distance away. they feel confident that it's not impacting behavior. >> we are going from sea sharks to a land shark. you can be stuck in traffic on

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>> hello and welcome back. costa you went on a very hand off deprive. drive. tell me about the drive you went on. >> i got to take a test drive in nissan's new car yo you no longr have to operate your car. it drives you to work and driving you home. you -- drives you home. that is what i got to play with the future. >> did you feel safe. >> i felt incredibly safe. it drives me. >> awesome let's take a look. >> the road to a driverless car has been a long one. this is the way general motors envisioned the future in 1967. >> you are now in control. hand off steering. >> nissan's race for the first non-production vehicle is in the hand of the japanese.

theswho had me figure out how it works. >> these are your laser scanners and they have big beams of laser and they figure out the distance and here we have a radar panel that figures out 200 meters ahead and in the back of the vehicle we have radar panels as well. and they have. >> twenty meters. and all of these little guys are for parking they are sonar. and then you have cameras on every side of the car. yes. it's a normal nissan and it's totally proto. and g if i open this up rnlg ths >> this is kind of secrets. don't touch it. >> we are going to put it on you a toyoua atonomus mode. >> you have no hand. the camera is reading the speed limit sign now. and we are going to watch it

slow down. >> yes, yes. automatically red light. camera is cit detecting it. the car says "signal is red." >> it's not a coo color camera how did it know? >> the position. >> the system explains what it's doing so the driver is not confused ever. >> how did it know to go to the left instead of the ride ro rig. >> it follows the line. >> what happens if a kid comes out chasing a ball? >> oh, my god. oh, my god! we almost killed that guy. it checks to see if is anybody behind us or next to us. it makes the decision to brake or swerve. can we park it now? >> yeah. >> hwe cancel do can do that frk seat right? >> this is my space.

>> it's calling dibs on that spot and now it's parking. i love watching the steering wheel just spin itself. >> what happens if i inter interresult it? it stops. as car makers head toward that date it may not be the technology but the human factor. at stanford automobile lab they are using a state of the art stimulator to answer the question how fast can a driver react when they are thrust back into control of a an autonomous car. when is the most dangerous time in a car. >> the moment when the car shifts back to the driver. to get what we call situation awareness. where there was none.

and that turns out to be in inextraordinary challenge. >> i'm going to be placing the. eeg elec electrodes to your hea. we hook up the driver and we have an eye tracker what their brain is doing and their heart is doing. >> this simulator is built to help us better understand the ways to alert the driver that a to autonomous mode is being switched after several minutes of texting when the car is driving, watch what happens when i have to take control. the car just asked me to disable auto makes. aut autautoyou a auto

mation. you had sensors on my han hand and what is that doing. >> it's determining how excited you are and ready for action you are. a good drive is neither too excited or too calm. >> are we required to be plugged into a car so it knows what it's doing. eventually cars will drive themselves. making the car the designated driver but for steve mayhem who is almost completely blind the cars will completely transform their lives lives. auto driving. google gave steve a look at the future. inviting him to take a seat in the first autonomous vehicle. >> look mom, no hands.

>> how did that feel. >> incredibly normal. >> the car was driving did you have any instinct responses. >> we are here at the stop sign. anyone up for a taco. i suggest that we go to taco bell. >> this is somest best driving i have done. >> do you think you will be able to be driving again in your lifetime? >> absolutely. >> that sounds like lot of fun actually. and i'm feeling pett pretty good with this technology i think an automatic car will drive better. >> there is a lot of discussion about this whether they are safe or not. right now they're doing research that is basically taking a race car driver's skill and putting it inside of the scar. car. so if you hit black ice while you are driving you don't know

what to do. imagine if you had the ewife equivalent of a race car driver who could take over for you. >> what is the bottom line here. is this going to happen? are we going to see driverless cars on the freeways. >> nissan has a 2020 date for having driverless cars on the road. they are talking about making the tess at tha testarosa autonomous. >> you went o went a on a ride t was a different technology. >> we were using a computer model going on the police beat. called predictive policing. >> fault lines, hard hitting... >> they're blocking the door... >> ground breaking... >> we have to get out of here. >> truth seeking... al jazeera america's breakthrough instigative

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>> more reporters. >> they don't have the resources to take the fight to al shabaab. >> more bureaus, more stories. >> this is where the typhoon came ashore. giving you a real global perspective like no other can. >> al jazeera, nairobi. >> on the turkey-syria border. >> venezuela. >> beijing. >> kabul. >> hong kong. >> ukraine. >> the artic. real reporting from around the world. this is what we do. al jazeera america. ♪ ♪ >> hey guys we're back here at techknow. i'm with crystal. you are about to take us with a little ride. >> i did a ride with two police departmentses. departments and they are using a new predictive policing program. to find the hot spot of crime.

>> compute hercomputer program s momodels to pro predict where te crime is going to occur. >> roll call the police department the calm before the storm. >> our crime stats are showing the efforts that you guys are making. >> we are down 12% in overall crime. as the men and women of dayshift lock, load and hit the road. they are armed with a new type of law enforcement weapon. all right, where are we going? >> the ain' ability to predict e crime is going to occur. we rolled out with them to see how it works. >> so downstairs here is where we house the operations division of the police department. deputy chief steve clark is a 20-year veteran of the santa cruz police department. owe knows th -- he knows the ple inside out. he also knows where to go in the future.

a knowledge that led him to a interactive predicting policing software. >> we were focusing on vehicle burglaries and we found the model was accurate predicting the timing times and locations e the crime will occur. >> it sounds like "minority report" the tom cruise movie where they apprehend the criminal based on preknowledge. >> what the computer takes into effect is the what has been reported. it doesn't know about the demographics in the area or the person, it's all area specific. >> today, it's more than a toy it tinker with. it's the main law enforcement tool in their arsenal. so taking a look now on dayshift. this is a live map of where we think the predictive zones are

for a thef for auto theft today. the orange zones are where we have had auto theft. there are no boxes around them. that is what the program does for us. algorithm weighs those and determines if it's a significant things to be loo looked at for this shift. >> when you look at police work you think of guys going with their gut and instinct to motivate. what is your response and what have you learned. >> we are not telling you how to do police work. we are telling you where are the best locations for you to be at any given time in the day. and police what you see. >> police what you see. and as it turns out, when you know what to look for and more importantly where to look for it. you can see a lot. it looks like there is a hot

spot in th in the neighbourhood. so should we check that out. >> let's take a look at seabright and murraymen murray e have an open car door and i have an open gate on this house as well. hi, police department. is that your car sitting out there with the door open? >> we just came home. >> i was just concerned and i saw it sitting there and saw the gate open and i thought i would stop and check. >> thank you. >> we are patrolling your neighborhood. and i'm sure you heard of the predicting strategy we are using. in the first year they saw you a assaults down nine percent and burglary down 11% and auto theft was up 22% and. we see how can is santa cruz is pioneering police work and it's

already spreading to other areas across the country. for the past three months the seattle pd has been incorporating the new soft wear in theiwear -- software in their patrol. >> any policing agency is tied to culture and we are tied to our past. this is a paradigm shift in how officers have been employss policings. you are successful if you it that ticket or make that arrest. but this if you are out there and your presentatio presence alone persuades a criminal from committing a crime you are successful. >> it's about combining innovation with instinct and ringing up results. >> it's amazing what you will see as you drive-thru a neighborhood. the things that pop out to you and the anomalies that dra that draws

your attention. i have my eyes on this guy who has his pants three quarters of the way down and he is walking through the business district. >> ho >> hi how have you been doing. how much have you been drinking. >> i don't drink. hands behind your back. i can't have you a little episodic here. >> we are here in the hot spottesupport spotand your instincts kick in and we stopped and talked to him and that is when you get clues. >> he is the type of person that we need to be contacting and workings the predictive policing system and it's inste intuition and gut instinct. >> it's easy to see why it's popular with the santa cruz pd

and gaining tracks shu tractionr law enforcement agencies. >> when i see police targeting certain areas the term "profiling" comes to mind. how are they trying to avoid that. this al g alabama go algorithm is no crimes are entered into the dat data base. >> there is nothing about there income or ethnicity. not even gender. >> it's not minority report. >> no people are not coming to your door, don't worry. >> fascinating stuff from all of you guys. >> thank you for sharing these stories. one thing before we go. most people think scientists are a bit nerdy and not that cool. but i think crystal's shoes here beg to differ. take a look at those. >> they are still nerdy.

>> go behind the scenes at aljazeera.com/techknow. follow your experts on twitter, >> welcome to al jazeera america. i'm morgan radford life from new york city. syrian tv reporting that four aid workers were wounded by gunfire as convoy enter the city of homs. plus the casualty of afghanistan soars. >> a march marking one month since a toxic chemical spill in west virginia. >> it's fairly