it gave me a perspective on individuals i didn't have in my formal role. thanks to you for taking on the work as well as being informative for the public. it's been a great time to spend with you and congratulations on the book and thank you for sharing it with us. >> thank you so much. >> cspan, where history unfolds daily. in 1979, cspan was created by a public service by the cable companies and is brought to you today by your cable or satellite provider. >> in your new book, streaming, sharing, stealing, big data in the future of entertainment, you open with for the creative

industries, music film and publishing, these are the best of times and worst of times. what do you mean that by that. >> the best of time is the tremendous amount of content proliferation. a lot of people are interested in watching and the ability to reach the international market is like never before. the worst of the time is that we are experiencing all sorts of expansions. now you're facing unprecedented competition that you never faced before, especially from some of the same technology firms who are very good at creating technology. they now have decided they want to get into the content business and have some significant competitive advantage that the traditional firms don't have. now it's a combination of both. you have great opportunities, but then you have to navigate all this competition. >> who are these technology companies and what are their

advantages. >> think about amazon, netflix, google. netflix is a perfect example. they started as what we call a distributor. he was in the business of shipping dvds to people. it was able to then navigate the internet and property and world and said they could be a big player in streaming so it started streaming the movies and the content and the television shows into the user homes and your tablets. and then it decided that it has an enormous amount of customer data. it knows exactly what their customers want ,-comma what they don't like and, not only that, they they have a very large customer base. i think netflix has close to 80 million subscribers. these are technology firms so they are built up with data.

they make a lot of data-driven decisions. now these companies say i have all this user information, i can now use and exploit this user information in both how to price, how to promote and how to distribute the content to an individual users and use that information to actually start thinking about producing the content that i believe my users are going to like. think about netflix from an online distributor to becoming a pretty major player in content production. they have access to this data that the television networks are the studios don't have and we believe that provides them a significant competitive advantage and that's the sort of disruption that the book talks a little bit about. >> how do you use that data and how do you collect it? >> for netflix it's a one-on-one relationship between the user

and server. every time you login, every time you watch a particular show, every time you click the like button, every time you quit a particular show, all all of that is information that netflix has. one other example we have in the book is the house of cards. when the house of cards was being pitched to netflix television, including two netflix, netflix had data that sat at the time 30 or 35 million customers so they had a pretty good idea how many people liked that actor. how many people might like kevin spacey or political drama or any combination of that. now you have all this intelligence, you feel pretty good about making some predictions on whether the show is likely to be successful with my subscriber base. compare that with maybe some

traditional firms who have aggregate information so you have ratings and 70 people from 15 - 24 age or 15 - 40 years old are watching the show from nine to 945. sometimes the aggregate data, now you have netflix which knows exactly who watches what and it can promote the content appropriately. the house of cards, they had created six different trailers which could be used to promote the sort of thing. you like this sort of thing so let me highlight this part of house of cards. right there you can see having access to this detailed user information, and having the skills and willingness to use the data, you would think that provides them an advantage and you can see where the industry

is going. >> prof., what is a comcast or cox have that data through their set-top box as well? they know if someone is watching c-span or a football game or renting a certain series. >> so some of that is possible. for nbc or cbs, i think that data would be hard to get. they would know that my show was watched by 18 - 40-year-old during this prime time, but most of the television industry has sort of been driven by the standardize ratings like a nielsen rating which are based on very aggregate into sticks. that's how your revenues are generated. that's how everybody standardizes against. beyond having the data which i think some of the studios obviously don't have, i don't know how detailed they have that information, then the second part also comes in on whether or not you have the culture and the

skills in the organization to actually use the data in a meaningful way. when you have an industry which has operated based on its gut feeling or instincts to decide which project is likely to work, which is not likely to work, now you moved to a world of big data and sometimes there is no willingness to use the data. sometimes there's no skills to use the data so having data itself is a challenge and using it and consolidating it in a meaningful way is also a significant challenge. again, that is one of the matters in the book that not only you have a difficult beginning access to some of

these data, you don't don't have the right sort of culture and people to make decision based on that. >> what does that mean for the legacy corporation? in publishing and in movies, simon & schuster, comcast, what's the what's the long-term trend in your view? >> one of the things we try to avoid is to predict the future. it's hard to do that. one thing i think we cannot discount is that these people are very good at whatever they do which is creating content. they have a deep experience in creating the content and able to sell it to the end users. what i feel is going on, and i think michael and i kind of talk about that. >> your co-author. >> yes, my my co-author, we talk about the ground realities are peoples consumption pattern has changed significantly. the television from 9:00 p.m. to

945 prime time spot, that is rapidly changing where now netflix offers an opportunity for you to do binge watching. a lot of people don't want to wake weight every week for your show to come on. all of these changes are already happening. i don't know, the netflix had recommendation challenge a few years ago. they said we will give you a million-dollar if you can design and recommend a movie to its customer which is going to delight them. these companies are very much into the space where they want to provide the content to the

user that they know the content will be liked by the user. offer them what the content of the viewers are going to enjoy and pay them for that. >> whether the traditional firms will be able to react and exploit and use some of this data into their decision-making is probably going to play it a significant role in how long they keep sustaining that. how dominant they remain will depend on their ability to change to this new reality. that's on consuming the content and how all this information can be utilized that's appealing to end-users. >> one of the content providers simply pulled their product from digital services saying okay,

you can only get it here. >> that's a very good point. in fact, michael and i were teaching a class we had a senior executive from one of the studios, and discuss and give a guest lecture and his argument was somewhat similar that we are the content creators, these guys are basically distributors and they rely on other content. if we choose to not provide content to them, what will be the future on that platform. there are two challenges. one challenge we provide a nice example in the book. the content provider's ability to control the content itself has been deviated in the world of internet and broadband especially when infringement has

become so common. >> so you say we have this example of nbc, this is 2007 or 2008, they or 2008, they have a dispute with apple itunes. so they say were to take all the content out from itunes and put it on the nbc website. in the hope of maybe trying to influence him more favorable result. interestingly, what they find is what people did is as the content was removed from itunes, they started flocking all the privacy networks. basically the next day the search for the nbc content shot up by 15 - 20%. on one hand it's hard to control the content. secondly, the enemas on and netflix are extremely powerful when fixed dream scope and

reach. the best thing that happened in book publishing was amazon publishing came in the worst thing that happened was amazon game. they make it so easy for you to distribute and promote your book all around the world, but then at the same time, amazon takes advantage of the tremendous power in negotiating with the authors the terms that are much more favorable to amazon. i think they also realize they can't rely on content to the studios alone. what is netflix doing? we are all reading the stories and we see that it's five to $6 billion. they said why do i have to rely on the studios to supply me content. they have the customer base and data and ability more than anybody else so why not me produce the content and directly

compete with the traditional players rather than they dictate what type of content can and can't be available. i think the reality is complex. >> he has a professor at carnegie mellon university. >> the book at some level is a combination of research we have been doing for the past ten or 12 years. otherwise in the process we did a variety of research at the firm level and policy level. we did a lot of work on copyright infringement and how effective the policies are. we established the center for digital entertainment. the purpose is.

[inaudible] professor, have the legislators and regulators here in washington kept up with the changes in this world? >> i think much of the focus over the past ten years, as far as i think into regulation is basically protecting the content. how to stop the infringement of the content. when napster came in, the music industry is not what it was ten years ago. obviously the content industry definitely wants to be able to protect the intellectual property and copyright. it gets really challenging because now it's the individual

users and it's hard to go after them and stop them. sometimes we are playing this technology whack a mole. something comes in you and you stop that thing and something else comes in and you stop that thing. i think regulation has focused more toward how do we make sure the content production is protected and not misused. i don't know whether there is a lot of discussion on the market structure and who gets to dominate what. i think that something for the future. we will see. if one of them becomes too dominant and start using its power in some ways, maybe those are the discussions that will happen. >> you think the focus has been right for the legislatures and regulators. >> i think so. piracy is something we all agree is not beneficial. maybe it's been officials to the

consumers and the sjogren's but it's a huge industry that we export to the rest of the world. i think that focus is probably very valuable and it's an issue that needs some attention. you can't leave it to the market sometimes. they can really not do some things. once i create the content the cat is out of the bag and they have little availability to protect it. some sort of attention to the detail is relevant. now what the regulation is to come about is always contentious because there are different parties involved. >> for who is going to produce the content and what content, i think we should let the market play out. i don't think some needs to tell somebody you should be doing this or that as long as it's a fair competition.

>> i think that seems reasonable. >> we look back, maybe in ten or 15 or 20 years and see napster as a seminal point in our history? >> i believe so. napster has probably already become the seminal point. now when people talk about the music industry, it's usually what was before and after so definitely i think it was a combination of the growth of internet in the content providers may be controlled the content a little too much and that led to all this proliferation of various websites. >> has the napster generation come to expect things for free?

>> i feel like a lot of people are gravitating toward legal channels as long as that the lights them in the sense that, you offer a product at a reasonable price and its high-quality, i think people are migrating towards it. some of the legislative action also has been to degrade the quality of privacy product which is also been a little bit hopeful that people have to choose between getting the content from a big network which has now been significantly degraded versus going to netflix or amazon or who in getting it at a reasonable price point. i think, at least in the u.s., i would say it's a reasonable

fight against piracy. i think there's a chance we can fight it. >> chapter nine of your book, streaming, sharing and stealing is called moneyball. what's the point? >> this goes back to the discussion we had earlier about how to use the data and information in decision-making. if you look at the hayes history of the baseball, there are the scouts of the managers and they look at the aggregates and statistics and make a decision whether this picture or that has potential. oakland and billy dean who was a small market team, they didn't have the hundred million dollars budget that the late yankees and the red sox had. he said what can i do, how can i make my team better. more importantly, if if you have seen the movie, it makes it very clear, the word he said was a

gentle misjudgment. that is this aqua chamber that everybody starts believing in whatever we see and he says that's not the right thing to do. there's a better way to evaluate people. he was deeply interested in looking at the data and the statistics but this picture, which everybody thinks is really not that good is excellent because look, when given the right pieces, it's outstanding, doesn't matter whether he's going this way or that way. what billy dean and the moneyball did was use the data to figure out which players are overrated in which players are underrated. then make the decision based on that. obviously, it was very successful. moneyball was the moment in

sports where analytics became an important component and now i think it's very widely used but i see entertainment industry, the netflix and amazon also have entered and said we are going to look at data to make scientific decisions rather than make decisions on our instincts and so on. >> professor ,-comma what is this big data look like. netflix collects at all, apple collects collects all this data. what is it look like and how do you parse it out? >> well, it's truly a big data. imagine if i have information about every users activity on my website and i have an ability to quantify and store that data and then extract the data and make

some meaningful use of it. amazon's recommendation, we all are familiar with the amazon say people like this. what is it? it's exploiting big data. i'm not sure if you heard about the story, i think they call it the discover list or discover playlist. what spotify has been doing is they recommend you every week a list of songs that they believe you will like in the story was that it became so popular with people and i was reading and i won't go into the detail but that's a big data exercise and they use deep learning to figure out, were looking at the scale

and the scope of the data. that's really where the trend is going. >> the question or statement you write your book and then you answering your book, you can't use data to make creative decisions. if you do you'll interfere with the creative process. >> so that's probably one of the criticisms that you hear from the people in the creative industry. they say g, are you going to tell me and are you going to destroy our creative ability to create the content. >> i think it's a little bit of

habitable. we will see how things go. i don't know how this will play out. many times the data is used for green lighting successful products. at some level you're using data to figure out what content is likely to be successful with my audience and that helps in green lighting, and then you let the creator create the content as you see fret. there is also this element that somehow when the big data wasn't there people had this ability without any commercial aspect in mind, it's probably not true. the commercial nature was always

created in that in mind with that would be successful with our customers. that's versus the actual hard data. actually what we feel is, when you have good information, when you use that good information to make appropriate decisions, especially if you can have a more successful product, i feel the creators are more likely to be successful because they are working on things that will have a high level of potential to be successful. :

>> >> there is no such word bennett there in is date data education but i tell students and teach students look at the data that they assign if there is the indication then they want to know can you deal with it? because even if you are a