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[Assistant] And all of these sound sources are decreasing the acoustic space over which Arctic marine mammals can communicate.


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[Assistant] And these are the sounds with which they've evolved. And these are sounds that are vital to their very survival.


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[Assistant] These new sounds are loud and they're alien.


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[Assistant] It's as if we pluck these animals up from the quiet countryside and drop them into a big city in the middle of rush hour. And they can't escape it. So what can we do now?


[User] Please transcribe this text

[Assistant] But we can work on local solutions to reducing human caused underwater noise.


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[Assistant] One of these solutions is to slow down ships that traverse the Arctic, because a slower ship is a quieter ship.


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[Assistant] We can restrict access in seasons and regions that are important for mating or feeding or migrating.


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[Assistant] We can get smarter about quieting ships and find better ways to explore the ocean bottom. And the good news is, there are people working on this right now.


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[Assistant] So let's return to this idea of a silent world underwater.


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[Assistant] Especially long-lived species, like the bowhead whale, that the Inuits say can live two human lives.


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[Assistant] It's possible that these whales were alive in 1956, when Jacques Cousteau made his film. And in retrospect,


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[Assistant] Considering all the noise we are creating in the oceans today, perhaps it really was the silent world. Thank you.


[User] Please transcribe this text

[Assistant] How does it work? Just like a natural arm. You think of what you want it to do and...


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[Assistant] This is highly sensitive equipment. That's it. I'm calling the mayor's office directly. Peter Parker.


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[Assistant] How the hell are you? Speak of the devil.


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[Assistant] This isn't about safety infractions, is it?


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[Assistant] Peter. There's no we. Without the grant from the city, I can no longer pay you.


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[Assistant] If I were you, I'd look for a new job.


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[Assistant] Welcome to this meditation where we'll be talking about mindful eating and how to combat cravings. To start,


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[Assistant] Find a comfortable position and close your eyes.


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[Assistant] Allow the heart and chest to lift. Allow your shoulders and arms to relax.


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[Assistant] Straighten your spine as best as you can, as it helps to keep you alert and attentive.


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[Assistant] Now bring your awareness to the breath. Just taking natural breaths.


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[Assistant] Do you feel it most strongly flowing in and out of your nostrils?


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[Assistant] Decide where you notice your breath most strongly and place all your attention there.


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[Assistant] Paying attention to that one concentrated area as you breathe in and out.


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[Assistant] Hold your attention strongly, deliberately.


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[Assistant] Keep it glued to the movement of your breath as it comes into your body and as it leaves your body.


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[Assistant] Not getting swept away by them. Just noticing.


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[Assistant] Observe everything that arises with openness and curiosity and then let it all go.


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[Assistant] Now just relax your attention. Relax the body.


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[Assistant] Now and again in our lives, we experience a strong resolve to change our eating habits. People go on diets and hit the gym, trying to shed weight or become healthy.


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[Assistant] The way to lose weight isn't by restricting calories, though. It's by understanding how cravings work and changing our relationship to food. When we open the cupboard and are ready to rip open a bag of cookies, our mind believes that this will make us feel good.


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[Assistant] It can be extremely hard to say no to cravings when we believe food will satisfy us and give us pleasure.


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[Assistant] When we give in to our food cravings, there may be some immediate relief, a distraction, an escape, or a sense of comfort. But immediately afterwards, there's regret, shame, or an actual stomach ache.


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[Assistant] Even when we're eating and enjoying what we're eating, we already know how it's going to turn out. As someone who used to have a serious eating disorder,


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[Assistant] When we learn to stop and notice what's happening in our body.


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[Assistant] When as we experience food cravings, we can observe and accept the thoughts, emotions and sensations that arise and witness them without acting.


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[Assistant] What happens is we allow the urge to pass.


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[Assistant] This is how we develop the ability to work with cravings. So when we desperately want that piece of cake,


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[Assistant] We can stop and get curious about what's happening.


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[Assistant] Is this just a habit or are we actually hungry? Practice curiosity.


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[Assistant] The more we do, the easier it becomes to observe our urges to eat and stop before we succumb to our cravings.


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[Assistant] And when we do choose to have that snack, we can eat slowly and mindfully.


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[Assistant] Tuning into our senses so we know when we're full.


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[Assistant] The easier it becomes to resist our cravings. As Henepola Gunaratana said, mindfulness gives you time. Time gives you choices. Choices skillfully made lead to freedom. You don't have to be swept away by your feeling. You can respond with wisdom and kindness rather than habit and reactivity.


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[Assistant] That sounds familiar. Oh, Oscorp CFO. Wait. You don't think this has anything to do with Lee, do you?


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[Assistant] Alright guys, so now that we've covered creating user passwords, encrypting our database, as well as hashing passwords, we've kind of reached a level of security that most websites are at. Now there's a lot more security that we're going to learn about a little bit later on.


[User] Please transcribe this text

[Assistant] But you're actually at a point where you already know quite a lot about authentication and keeping user passwords secure.


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[Assistant] And definitely a lot more than a lot of people who actually run websites. And I know that some of you guys are keen to get a job. And if that is you, then I want you to go onto a website called plaintextoffenders.com. I'll link to it in the course resources.


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[Assistant] Here, what you'll find is emails that come from various companies where the user is requested to reset their password.


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[Assistant] And they're sending the user a plain text version of their password.


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[Assistant] Now at this point, we know to be able to even get the user's password in plain text, it means that they're doing some horrible things with securing the passwords.


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[Assistant] or Telecom Egypt, then you could actually just email these people and tell them that


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[Assistant] I'm a web developer and I know about authentication and securing users passwords. You obviously seem like you might need some help. Would you like me to work for you? I recommend giving that a go to if you're keen on getting a job.


[User] Please transcribe this text

[Assistant] If you're not looking for a job, then have a look at these websites and if you're signed up to any of them, be sure to delete your account because it's definitely not secure.


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[Assistant] And this is why a lot of companies and a lot of websites get hacked.


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[Assistant] Hacking passwords 101 class, if you will. Now most of the time I use my programming powers for good, but in this case I want to talk to you about how passwords might be hacked so that once we understand how the other side approaches this problem, then we can learn more about security and make our website safer for users.


[User] Please transcribe this text

[Assistant] And by the way, I have no idea why hackers are always portrayed in a balaclava. It's not like they're gonna burgle anybody. I mean, especially this guy. He must be incredibly warm sitting next to all these computers, wearing so much clothing on his face.


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[Assistant] But I digress. So as a company, this is probably one of the things that you least look forward to. The day when you wake up and you get a call and you've been


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[Assistant] And this has happened really recently to a lot of big companies like, uh, Adobe Creative Cloud got hacked in 2013, LinkedIn got hacked in 2012,


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[Assistant] And there's loads of accounts where their passwords get leaked. Lots of unhappy users who reuse their passwords and are feeling extremely vulnerable.


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[Assistant] And you can see that even to this day, people can purchase these hacked accounts where people might not have realized that their LinkedIn email and their passwords are linked and people are potentially buying that data up and using it to hack into their PayPal accounts or other similar payment portals.


[User] Please transcribe this text

[Assistant] So even if you don't learn anything from this lesson, I recommend just going to this website. Uhm, I'll link to it in the course resources just for educational purposes, but put in your email address and make sure that if you do have any passwords that show up,


[User] Please transcribe this text

[Assistant] But why is it that all of these big companies are getting hacked and leaking their users' passwords? Are they not at least encrypting or hashing their passwords?


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[Assistant] Well, they are, but consider this. So you're a hacker and you've managed to get into the LinkedIn user database.


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[Assistant] And just for simplicity sake, let's say it looks like this. You've got a username and you've got a hash. And thankfully they didn't store their user's passwords in plain text. You can't access their passwords straight away.


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[Assistant] However, if you look at this table a little bit more closely, you'll realise that three of the hashes are completely identical.


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[Assistant] Now, why might that be? Well, remember that the same password always turns into the same hash no matter how often you try it. And that's a core part of the hash function that we rely on in order to validate our users as well.


[User] Please transcribe this text

[Assistant] So that means a hacker would look at this table and realize that Angela, Tony, and Emily all have the same password. And what they can do is they can start to construct what we call a hash table. So you would take some of the most commonly used passwords.


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[Assistant] And then all you have to do is just look up the hash of the user and compare it against the hash you have in your table. So you search by the hash value and you land upon the password, which is QWERTY.


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[Assistant] All have the same password and it's QWERTY. So what if they didn't use one of the most common passwords and instead they use something else, say their date of birth or their pet's name? Well, let's see how we would make a hash table if we were a hacker.


[User] Please transcribe this text

[Assistant] You would probably start with all the words from a dictionary, and this is where the term dictionary attack comes from. You create hashes from all the possible words in a dictionary, and that will only be about 150,000 hashes that you would need to create. And then you add to that hash table all the numbers from a telephone book,


[User] Please transcribe this text

[Assistant] And all the combinations of characters up to six places. And then you add all of these together and you end up with something close to 19.8 billion combinations.


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[Assistant] Which admittedly sounds like a large number, right? How long would it take your computer to calculate that many hashes? So what do we do? Well, let's go shopping.


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[Assistant] Let's go and buy some of the latest GPUs or graphics cards.


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[Assistant] It'll only take one of these GPUs 0.9 seconds, which is nothing. It's not a lot of time to invest in order to hash so many people's passwords. And to make it even worse, large hash tables have been built for the most common passwords.


[User] Please transcribe this text

[Assistant] Because we've had so much data from previous hacks, such as the Adobe one or the LinkedIn one or TalkTalk or Equifax, we know what the most common passwords are that people use. And every year, companies like Splashdata will compile what are the most common passwords, say the top 25.


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[Assistant] And this is where all of those values that went into our table came from, but you can actually go one step further. There are pre-built hash tables that people have created for the top 10,000 most common passwords and you can see that MD5


[User] Please transcribe this text

[Assistant] Is one of the quickest hashes to calculate. And this is why it's very, very common to find MD5 hash tables. And you can even use Google as a basic hash table. You can paste in the hash that you found from the hacked database. You perform a simple Google search and you come up with the original password.


[User] Please transcribe this text

[Assistant] Now if at this point you're extremely scared and you're wondering, well, what exactly can you do about this? Well, consider that in our user table, there was one hash that was extremely difficult to find and it didn't match up.


[User] Please transcribe this text

[Assistant] With any of the hashes in this little simple hash table we built. So what if we put that into Google to search on a larger scale and see if it matches any of the hashes in the hash tables that people have generated?


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[Assistant] And it doesn't, it doesn't match anything. And the reason is because when John created his password,


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[Assistant] He had a very, very strong password with uppercase letters, lowercase letters, numbers, symbols, but most importantly, a long password. When you think about hashing as a mathematical formula,


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[Assistant] You'll realize that as the number of characters of your password increases, the computation time that it takes to crack it increases exponentially. So it doesn't matter if your account on LinkedIn or Adobe Creative Cloud or Ashley Madsen was cracked.


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[Assistant] As long as you had a strong password, they wouldn't be able to work it out from a hash table.


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[Assistant] As an example, there's a website called Password Checker.


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[Assistant] And you can put in your password and it'll tell you not only the strength, but also how long it'll take various types of machines to be able to crack that password. So let's say that I create a six character password composed of a random set of characters, right? One, two, three, four, five, six.


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[Assistant] And you can see that even for a standard desktop PC, it only takes about three seconds to perform a brute force attack to crack that password.


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[Assistant] But let's see what happens if I add another six more characters. One, two, three, four, five, six.


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[Assistant] Now it takes 31 years for a standard desktop PC to be able to crack it.


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[Assistant] And even a fast GPU takes two years to crack my password. So even though all of the websites encourage you to add a capital letter, a lowercase letter, some numbers and some random characters, if you only have six characters in your password, so a short password,


[User] Please transcribe this text

[Assistant] It still doesn't take very long to crack. So the most important thing of creating a strong password,


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[Assistant] That is almost uncrackable, it's just to increase the number of characters.


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[Assistant] And also to prevent yourself from being a victim of a dictionary attack, just make sure that you don't use a dictionary word or a place name or something that is in a directory somewhere, like a telephone number.


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[Assistant] All right, so at least after this lesson, you'll know how to keep yourself more secure.


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[Assistant] But in the next lesson, we're going to address these vulnerabilities that occur because of weak hashing algorithms. And we're going to learn how we can combat hackers who try to attack our database using a dictionary attack or by creating a hash table.


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[Assistant] So for all of that and more, I'll see you on the next lesson. But as a quick bonus, if you ever want to trick your friends into thinking that you're some sort of a hacker, at least according to Hollywood, I recommend checking out a website called hackatyper.net.


[User] Please transcribe this text

[Assistant] Where you can just mash the keyboard and you end up with something that looks extremely realistic. But word of warning, try not to do this on an airplane or in a government building unless you want to actually get investigated.


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[Assistant] I was slow to learn to read, went all the way through school not really reading more than the minimum and still to this day can't read silently much faster than I can read aloud. Uhm, but there were a lot of benefits to being dyslexic for me because when I finally did reconcile myself to how slow I was going to have to do it, then I think I came very slowly


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[Assistant] I fell air to languages, other qualities, which I think has helped me write sentences.


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[Assistant] Over a third of your followers follow from a country which is not your own. Global is the new scale. We know that.


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[Assistant] This point over here, the point at which the lines cross over, the pace of change,


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[Assistant] Overtakes the pace of learning, and for me, that is what I was describing when I was telling you about Midnight.


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[Assistant] What are we supposed to do? What do we do when we're like tossing and turning in bed late at night or doing shift work or whatever else?


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[Assistant] I don't know about you but uhm, I haven't quite figured out exactly what technology means in my life. I've spent the past year thinking about


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[Assistant] What it really should be about should I be pro technology? Should I embrace it full arms? Should I be wary? Like you, I am very tempted by the laziest thing. But on the other hand, a couple years ago I gave up


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[Assistant] All of my possessions sold all my technology except for a bicycle and rode across 3,000 miles on the U.S. Backroads under the power of my one body fueled mostly by Twinkies and junk food.


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[Assistant] And I've since then tried to keep technology at arm's length in many ways so it doesn't master my life.


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[Assistant] At the same time, I run a website on cool tools where I issue a daily obsession of the latest things in technology. So I'm still perplexed about what the true meaning of technology is.


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[Assistant] As it relates to humanity, as it relates to nature, as it relates to the spiritual.


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[Assistant] And I'm not even sure we know what technology is. And uhm, one definition of technology is that which is, uh, first recorded. This is the first example of the modern use of technology that I can find.


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[Assistant] It was a suggested syllabus for dealing with the applied arts and science.


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[Assistant] In Cambridge University in 1829. Before that, obviously technology didn't exist, but obviously it did.


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[Assistant] So it sums up a lot of what we're talking about. Danny Hillis actually has an update on that. He says, technology is anything that doesn't quite work yet. Which also,


[User] Please transcribe this text

[Assistant] I think gets into a little bit of our current idea. But I was interested in another definition of technology. Something again that went back to something more fundamental. Something that was deeper. And uhm,


[User] Please transcribe this text

[Assistant] I came up with a way of framing the question that seemed to work for me in my investigations.


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[Assistant] This morning, going to talk about this for the first time. So this is a very rough attempt to, to think out loud.


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[Assistant] The question that it came up with was this question. What does technology want? And by that I don't mean does it want chocolate or vanilla.


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[Assistant] By what it wants, I mean, what are its inherent trends and biases? What are its tendencies over time? One way to think about this is thinking about biological organisms, which we've heard a lot about.


[User] Please transcribe this text

[Assistant] In the trick that Richard Dawkins does, which is to say, to look at them as simply as genes, as vehicles for genes. So he's saying, what do genes want? The selfest gene. And I'm applying a similar trick to say, what if we looked at the universe in our culture through the eyes of technology? What does technology want?


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[Assistant] Obviously this is an incomplete question, just as looking at an organism as only a gene is an incomplete way of looking at it, but it's still very, very productive. So I'm attempting to say, if we take technology's view of the world, what does it want?


[User] Please transcribe this text

[Assistant] And I think once we ask that question, we have to go back actually to life. Because obviously, if we keep extending the origins of technology far back, I think we come back to life at some point. So that's where I want to begin my little exploration is in life. And like you heard from the previous speakers, we don't really know


[User] Please transcribe this text

[Assistant] What life there is on earth right now. We have really no idea.


[User] Please transcribe this text

[Assistant] Craig Venter's tremendous and brilliant attempt to DNA sequence things in the ocean is great. Brian Farrell's work is all part of this agenda to try and actually discover all the species on earth. And one of the things we should do is just make a grid of the globe and randomly, uh,


[User] Please transcribe this text

[Assistant] Go and inspect all the, all the places that the grid intersects just to see what's on life. And if we did that with our little Martian probe, which we have not done on Earth, we would begin to see some incredible


[User] Please transcribe this text

[Assistant] Species. This is not another plant. These, these are things that are hidden away on our planet. This is a ant that stores its, uh,


[User] Please transcribe this text

[Assistant] Have an exception somewhere by some organism. Every single thing we can think of, and if you heard Olivia's talk about the sexual habits, you will realize that there isn't anything we can say that's true for all life, because every single one of them is hacking something about it. This is a solar-powered sea slug.


[User] Please transcribe this text

[Assistant] There's a nudibranch that has incorporated in chloroplasts inside it to drive its energy.


[User] Please transcribe this text

[Assistant] This is another version of that. This is a sea dragon. And the one in the bottom is a...


[User] Please transcribe this text

[Assistant] The blue one is a juvenile that has not yet swallowed the acid, has not yet taken in


[User] Please transcribe this text

[Assistant] If we looked at the general shape of the approaches to hacking life, there are...


[User] Please transcribe this text

[Assistant] Current consensus, six kingdoms. Six different broad approaches. The plants, the animals, the fungi, the produce, the little things, the bacteria and the archipateria. The arches.


[User] Please transcribe this text

[Assistant] We have a view of evolution where rather than having evolution go over the linear time, we have it coming out from the center.


[User] Please transcribe this text

[Assistant] So in the center is the most primitive, and this is the genealogical chart of all life on Earth. This is all the same six kingdoms you see, 4,000 representative species. You can see where we are. But what I like about this is it shows that every living organism on Earth today is equally evolved.


[User] Please transcribe this text

[Assistant] Those, those fungi and bacteria are as highly evolved as humans. They've been around just as long and gone through just the same kind of, of, of trial and error to get here.


[User] Please transcribe this text

[Assistant] But we see that what, each one of these is actually hacking and has a different way of finding out how to do life. And if we take the long term trends of life, if we begin to say what are the, what does evolution want, there are several things that we see. One of the things about evolution is that


[User] Please transcribe this text

[Assistant] Nowhere on earth, on earth have we ever been


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[Assistant] Where we don't find life. We find life at the bottom.


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[Assistant] Of every long term, a long distance drilling core of into the center of rock, we bring it up and there's bacteria in the pores of that rock.


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[Assistant] And wherever life is, it never retreats. It's ubiquitous. And it's becoming, wants to be more, more and more of the inert matter of the, of the globe is being touched and animated by life. The second thing is we see diversity. We also see specialization. We see the movement from a general purpose cell to the more specific and


[User] Please transcribe this text

[Assistant] Specialized. And we see a drift towards complexity.


[User] Please transcribe this text

[Assistant] That's very intuitive, and actually we have current data that does show that there is actual drift towards complexity over time. And the last thing I bring back is Nudibranch.


[User] Please transcribe this text

[Assistant] Is one of the things we see about life is that it moves from the inert to increasing social ability. And by that it means that there is more and more of life whose entire environment is other life. Like those chloroplast cells, they're completely surrounded by other life and they never touch the inert matter.


[User] Please transcribe this text

[Assistant] There is more and more co-evolution. And so the general long-term trends of evolution are roughly these five. Ubiquity, diversity, specialization, complexity, and socialization.


[User] Please transcribe this text

[Assistant] Now, I took that and said, okay, what are the long-term trends in technology? And, again, my question is, what does technology want?


[User] Please transcribe this text

[Assistant] That, uh, we see there's a general hammer and hammers become more and more specific over time.


[User] Please transcribe this text

[Assistant] Obviously diversity. Huge numbers of things. This is all the contents of a Japanese home. I actually had my daughter, gave her a tally counter, and I gave her an assignment last summer to go around and count the number of species of technology in our household. And it came up with 6,000 different


[User] Please transcribe this text

[Assistant] And thirdly, the idea that machines are becoming biological and complex is, at this point, a cliché. I'm happy to say I was partly responsible for that cliché, that machines are becoming biological, but that's pretty evident. So the major trends in technology evolution actually are the same.


[User] Please transcribe this text

[Assistant] Is in biological evolution. The same drives that we see towards ubiquity, towards diversity, towards socialization, towards complexity.


[User] Please transcribe this text

[Assistant] That is maybe not a big surprise. Because if we map out, say, the evolution of armor, it can actually follow sort of an evolutionary type cladistic trait.


[User] Please transcribe this text

[Assistant] I suggest that in fact, technology is the seventh kingdom of life. That its operations and how it works is so similar that we can think of it as the seventh kingdom.


[User] Please transcribe this text

[Assistant] And so it would be sort of approximately up there coming out of the animal kingdom. And if we were to do that, we would find out


[User] Please transcribe this text

[Assistant] We could actually approach technology in this way. This is Niles Eldridge. He was the co-developer with Stephen Jay Gould of the theory of punctuated equilibrium. But as a sideline, he happens to collect cornets. He has one of the world's most largest collections.


[User] Please transcribe this text

[Assistant] is that if you look at those red lines at the bottom, those indicate basically


[User] Please transcribe this text

[Assistant] A parentage of a type of cornet that was no longer made. That does not happen in biology.


[User] Please transcribe this text

[Assistant] When something is extinct, you can't have it as your parent. But that does happen in technology. And it turns out that that's so distinctive.


[User] Please transcribe this text

[Assistant] That you can actually look at this tree and you can actually use it to say, to determine that this is a technological system versus a biological system. In fact, this idea of resurrecting old ideas is so important that I began to think about


[User] Please transcribe this text

[Assistant] What happens with old technology? And it turns out that in fact ...


[User] Please transcribe this text

[Assistant] Technologies don't die. So, I suggested this to a historian of science and he said, well, what about, you know, come on, what about steam cars? You know, they're not around anymore. Well,


[User] Please transcribe this text

[Assistant] Actually, they are. In fact, they're so around that you can buy new parts for a Stanley steam automobile. And this is a website of a guy who's selling brand new parts for the Stanley automobile. And the thing that really I like to serve is this one click add to your cart button.


[User] Please transcribe this text

[Assistant] I mean, maybe that's just a random sample, maybe I should do this in a more concerted way. So I took the great big nineteen, excuse me, eighteen ninety-five Montgomery Awards catalog and I randomly went through it and I took a page, not quite a random page, I took a page that was actually more difficult.


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[Assistant] Corn shellers, who, I mean, I don't know who needs a corn shell, but yea, corn shellers, you've got plows, you've got, uh, fan mills, all these things, and these are not, again, antiques, these are, you can order these, you can go to the web, and you can buy them now, brand new, made. So, so, in a certain sense, technologies don't die. In fact, uhm, you can, you can buy, for 50 bucks, a


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[Assistant] Stone age knife made exactly the same way that they were made 10,000 years ago. It's shirt, bone handle, 50 bucks. In fact, what's important is that this information actually never died out.


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[Assistant] It's not just that it was resurrected, it's continued all along and in Papua New Guinea they were making stone axes until two decades ago just as a course of practical matters.


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[Assistant] Even when we try to get rid of a technology, it's actually very hard. So we've all heard about the Amish giving up cars, we've heard about the Japanese giving up guns, we've heard about this and that, but I actually went back and took what I could find


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[Assistant] And then I tried to find out when they were, when they came back in because they always came back in. And it turns out that the time, the duration of when they were outlawed and prohibited is decreasing over time. And that basically you can delay technology but you can't kill it. So this makes sense because in a certain sense what culture is.


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[Assistant] Is culture is the accumulation of ideas. That's what it's for. It's so that ideas don't die out. And when we take that, we take this idea of what culture is doing,


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[Assistant] And added to what the long term trajectory again in, in, in, in life's evolution, we find that each case, each of the major transitions in life, what they're really about is accelerating and changing the way in which evolution happens.


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[Assistant] So what's happening over time in life is that the ways in which you generate these new ideas, these new hacks are increasing and the real tricks are ways in which you kind of explore the way of exploring. And that what we see in the singularity


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[Assistant] The prophesies by Kurzweil and others is the idea that


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[Assistant] Technology is accelerating evolution. It's accelerating the way in which we search for ideas.


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[Assistant] So what, if, so if you have life hacking, life means hacking the game of survival, then evolution is a way to extend the game by changing the rules of the game. And what technology is really about is better ways to evolve. That is what we call an infinite game.


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[Assistant] That's the definition of infinite game. A finite game is played to win, an infinite game is played to keep playing. And I believe that technology is actually


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[Assistant] The origins of technology was not in 1829, but was actually at the beginning of the Big Bang. And at that moment,


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[Assistant] The entire huge billions of stars in the universe were compressed. The entire universe was compressed into a little quantum dot. And it was so tight in there, there was no room for any difference at all. That's the definition. There was no temperature, there was no difference whatsoever. And at the Big Bang, what it expanded was the potential for difference.


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[Assistant] So as it expands, and as things expand, what we have is we have the potential for differences, diversity, options, choices, opportunities, possibilities, and freedoms. Those are all basically the same thing. And those are the things that technology bring us.


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[Assistant] That's what technology is bringing us. Choices, possibilities, freedoms. That's what it's about, is this expansion of room to make differences.


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[Assistant] And so, a hammer, when we grab a hammer, that's what we're grabbing. And that's why we continue to grab technology, because we want those things. Those things are good. Differences, freedom, choices, possibilities. And each time we make a new opportunity place, we're allowing


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[Assistant] A platform to make new ones. And I think it's really important because if you can imagine Mozart before the technology of the piano was invented.


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[Assistant] What a loss to society that would be. Imagine Van Gogh being born before the technologies of cheap oil paints. Imagine


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[Assistant] Hitchhawk before the technologies of film. Somewhere today, there are millions of young children being born.


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[Assistant] Whose technology of self-expression has not yet been invented. We have a moral obligation to invent technology so that every person on the globe has the potential to realize their true difference. We want a trillion zillion species of one individual. That's what technology really wants.


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[Assistant] I'm going to skip through some of the objections because I don't have answers to why


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[Assistant] There's deforestation. I don't have an answer to the fact that there are, seem to be bad technologies. I don't have an answer to how this impacts on our dignity other than to suggest that maybe the seventh kingdom, because it's so close to what life is about,


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[Assistant] Maybe we can bring it back and have it monitor, help us monitor life. Maybe, in some ways, the fact that what we're trying to do with technology is find a good home for it. It's a terrible thing to spray DDT on cotton fields. But it's a really good thing to use to eliminate millions of cases of death due to malaria in a small village.


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[Assistant] When I think about what technology wants, I think that it has to do with the fact that every person here, and I really believe this, every person here has an assignment. And your assignment is to spend your life discovering what your assignment is.


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[Assistant] Technology, because it is an essential part of our journey in finding out who we are. Thank you.


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[Assistant] I have to get that antiserum and start putting things right. There must be some way to reach Leonardo. Convince them to give up this crusade for revenge. They've both done so much good for the world. They can't throw their legacies away just to spite Norman.


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[Assistant] Okay, Norman's on his way to get the anti-serum. Better update Yuri.


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[Assistant] Don't worry, I'm on it. This'll all be over soon, I promise.


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[Assistant] Have to take care of these demons before I can follow Lee into the lab. Time to KO those snipers.


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[Assistant] But Lee has your client inside this building right now, and he's gonna kill him if we don't do something. We could fight each other, or we could fight Lee, but not both.


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[Assistant] Seems like the last stage of the plan is a direct assault on Oscorp. And most likely, Norman.


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[Assistant] Scorpion must be trying to poison the city's reservoir. Another Oscorp-owned property. Rhinos targeting Oscorp shoreline properties. Which is he hitting first, and why?


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[Assistant] What's Vulture doing in Times Square? I need to keep my guard up. Electro's disabling Oscore power plants. Makes sense.


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[Assistant] Please, going after the devil's breath anti-serum. Using something called Icarus?


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[Assistant] I'm Otto Octavius. There is no Icarus, is there?


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[Assistant] Yuri, Vulture and Electro are down. Four to go.


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[Assistant] It was Octavius' stage and ground. He's using the villains to pull apart Oscorp.


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[Assistant] Vulture and Electro were targeting power plants. Scorpion's going after water treatment. Not sure about Rhino yet. Something along the shoreline.


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[Assistant] Yeah. City's already on the brink. If we lose clean water, we might never come back. I'll update you when I make progress.


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[Assistant] That's what I was gonna ask you. I'm fine, but you and May are in the middle of it.


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[Assistant] Yeah, I heard that. Just make sure you protect yourself. Mask and gloves. And rest every now and then. All that goes double for me.


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[Assistant] Thanks, Mile. Give me my love, and be safe.


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[Assistant] What the? Is that a sea of poison? Can't be. This can't be real. Must be the poison. But I can't take any chances. Gotta get to higher ground and analyze whatever he injected me with. Should be safe for a minute. Need to analyze the neurotoxin so I can create an antidote.


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[Assistant] I need time, but I need an antitoxin to mix a permanent antidote.


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[Assistant] One of Harry's research stations was developing a synthetic atropine. Gotta get there fast.


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[Assistant] Where'd my suit go? I think I took decontamination a little too far.


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[Assistant] I better put some clothes on. Much better. Let's just go ahead and forget that ever happened.


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[Assistant] You mind if I toss a kinda thorny ethical question at ya? When is it okay to give up on a friend?


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[Assistant] Yeah. Yeah. Thanks, MJ. I gotta process some stuff, I think.


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[Assistant] Okay, you stay off your feet for a bit. I'll organize the unloading and check in with Miles. Deal? Deal.


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[Assistant] Incredible work, Miles. Stick close to Feast. If the convicts get desperate, they may try to raid the shelter.


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[Assistant] Yuri, figured out Rhino's deal. He's attacking Ozcorp's relief centers.


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[Assistant] To find the best pizza in the city? Yeaah. 10 hour odyssey for burnt toast with cold American cheese. How could I forget?


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[Assistant] I guess the work we do means today's kids can have their own Staten Island adventures. In safety. Kind of a circle of life thing.


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[Assistant] Alright Yuri, that's four down. Just Octavius and Lee left.


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[Assistant] I'd expect nothing less from our beloved mayor. Leave Devil's Breath to me. One of my best people is on it.


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[Assistant] I've already been through his office computer. Are you thinking his penthouse?


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[Assistant] Okay, it's risky, but we need that location. Wait for me to get nearby, then make your move. I'll be ready.


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[Assistant] Okay, MJ, I'm a couple blocks away. Let me know if you get into trouble.


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[Assistant] Can I make a comment? In the session this morning I talked about how my experience was that there's values that come from the founder, you know, we're talking about driven, obsessive, narcissistic, egotistical, whatever.


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[Assistant] They're there, and uhm, you have values amongst your founding team. And you're gonna, whether you say them or not.


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[Assistant] And my belief is that it's better to figure out what they are and try to codify them to make them more explicit to have that discussion even if you don't get them all because then


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[Assistant] You're starting to drive towards alignment and if you have clear values, people who don't agree with those values will not want to join the company.


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[Assistant] And values and culture are something that's important to be a deselection process as well as my take.


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[Assistant] This is actually in some sense a key breaking point in the course, which is


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[Assistant] In some sense, what we've done so far is give you a set of tools.


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[Assistant] To understand how to think about how consumers and producers make decisions.


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[Assistant] And then to understand how you compare positive and normative implications of economics.


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[Assistant] What we're gonna do for the rest of the class, for the rest of the semester.


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[Assistant] Uhm, is we're gonna start to talk about how you apply those tools to more realistic situations.


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[Assistant] Let me answer your very first question. What you learned today is not on the midterm.


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[Assistant] Okay, so that's the question that's all in your mind because


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[Assistant] It is. So, uh, the midterm tomorrow night will cover everything through, through what we covered through last week. Uh, but what we learned today will not be on the midterm. But don't leave, because it will be on the final. And it is interesting. So, uh, what we're gonna do today is talk about


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[Assistant] Taking the tools we've developed so far in this class and applying to more realistic situations. And the more realistic situation we're gonna start with is the case of monopoly. And we're gonna talk about monopoly profit maximization. Now so far on the producer side,


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[Assistant] We've been discussing one extreme of how the market's organized, which is perfect competition.


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[Assistant] But still does exist in reality, which is monopoly.


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[Assistant] Okay. Monopoly is a situation where a market only has one firm in it. So a market with one firm is a monopoly market.


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[Assistant] Okay, so, so that's basically a case where you have only one firm providing the good. Okay?


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[Assistant] Now in reality, most markets fall between perfect competition, which never truly exists, and monopoly, which rarely exists.


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[Assistant] Most markets are in between we call them oligopolies. That's markets with several


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[Assistant] Several firms, but not perfectly competing. And we'll get to that.


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[Assistant] But that's actually one of the harder things we'll cover, so we're going to start with this other extreme of monopoly, which gives us a lot of the insights we need for oligopoly, but in a much simpler case. Now, the key thing with monopoly, the key difference from what we've done so far,


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[Assistant] Is that now firms are going to be price makers, not price takers.


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[Assistant] That's gonna be the key change from the permanently competitive situation.


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[Assistant] Perfectly competitive situation, from any given firm's perspective, the price is something given to them by the great market.


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[Assistant] Okay, we talked with our two diagrams side by side about how the market gives the price.


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[Assistant] But we sort of, from any given parent's perspective, they were a price taker. They couldn't affect the price. Monopolis, however, when you're the only firm, you get to set the price.


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[Assistant] So monopolists are going to be price makers, not price takers.


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[Assistant] And that's what, that's gonna change the dynamics of everything we do, and that'll be our focus today. Okay? So that's gonna be the big, uh, the big change when we go from competitive markets to monopoly markets. Okay? Now,


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[Assistant] For the first two-thirds or three-quarters of the lecture, we're gonna make one other assumption.


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[Assistant] We're gonna assume there is one price in this market. That is no price discrimination.


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[Assistant] This monopolist sets the price, but he sets one price for everybody. So if a monopolist is selling a good, they sell that at one price to everybody who buys the good. Now once again, this is not super realistic. Monopolists often have different prices for goods.


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[Assistant] It's a ve- it's a very important, helpful extreme. And you gotta remember that we're imposing this constraint because it's gonna drive the intuition I'm gonna come to next. Okay? So you're a firm...


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[Assistant] The fundamental part of producer that holds is the goal of monopolist is to maximize his profits. Okay? Which is revenues minus costs.


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[Assistant] And as we showed before, profits are maximized when marginal revenue equals marginal cost. That's the profit maximization point. Now, nothing on the cost side is going to change. So, monopolist to monopolist.


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[Assistant] The way we get cost curves doesn't change. That's all about, remember, because that just comes to the technology of production, and that comes from input prices.


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[Assistant] Okay, so nothing on the cost side is going to change. All that hard and somewhat boring work we did.


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[Assistant] Deriving cost functions and stuff. That all is, that's done.


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[Assistant] The only place Monopoly gets exciting is on the marginal revenue side. Because before, we said marginal revenue was just price. For a price taker. But that's no longer true. Marginal revenue is no longer just price.


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[Assistant] Now marginal evidence can be more interesting. So the monopoly difference, if you will, or the imperfect competition difference.


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[Assistant] Doesn't come at all from the cost side. That side is done. Doesn't matter what kind of market you're looking at. Okay? All the interesting action here is on the revenue side. As we think about monopoly and oligopoly markets. Okay? So to think about that, let's go to figure, uh, 11-1. Okay?


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[Assistant] Think about, let's start by thinking about a competitive firm. This is a diagram I could have shown earlier, just sort of, is a way to think about a competitive firm. Think about a competitive firm's profits.


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[Assistant] So imagine that uhm, this firm, uh, to make life easy, let's imagine that uhm, we have a firm with marginal cost of zero. Okay? So, you've got demand curve.


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[Assistant] And so therefore any money you make is profit. And we're in the short run. Okay, so there's profit in the short run, even for this perfectly competitive firm. But a perfectly competitive firm faces a horizontal demand curve. So if they sell Q units, okay, they make profits of area A. Which is simply Q times P1. Little Q times P1. If they sell Q plus 1 units, they make an extra profit rectangle of B.


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[Assistant] So literally, the marginal, the extra profit they make is just the amount p. It's 1 times p1.


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[Assistant] The, the, the horizontal distance from Q to Q plus 1 is 1. The vertical distance is P1. So the marginal profit is just the price. Okay? Marginal revenue, I'm sorry, is just the price, yeaah.


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[Assistant] Right, in the short run there can be profit in the long run there's no profit.


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[Assistant] Okay, so basically their marginal revenue, what they make, that next unit they make, is the price. Okay?


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[Assistant] Now, let's think about a monopoly firm. A monopoly firm does not face a perfectly elastic demand curve.


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[Assistant] Because a monopoly firm's demand curve is the whole market. Notice little q has become big Q on the x-axis.


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[Assistant] The monopolist no longer faces only their perfectly elastic firm demand. They face...


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[Assistant] A market demand which can be any degree of elasticity but typically is somewhat elastic. It's downward sloping.


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[Assistant] Now let's say you're a monopolist and you're selling big Q units at a price P1. Your profits are C plus A. Once again, let's say marginal cost is zero and make this easy. Are C plus A. Now let's say you want to sell one more unit. Well, what's different?


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[Assistant] What's different is now you're facing a downward sloping demand curve.


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[Assistant] So if you want to sell one more unit, you have to lower the price. That's the difference. If you want to sell another unit,


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[Assistant] You can only do so by lowering the price. And you're a price maker, so you have to wait to do that. So if you want to sell another unit, two things are going to happen. A, you are going to sell a second unit and make money on that unit. That's the area B.


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[Assistant] But B, I guess say one and two. One, you'll still second you, that's the area B. Two,


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[Assistant] You will lose money on all the other units you sold.


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[Assistant] Because now you have to lower the price. Because remember, there's only one price. Okay? So basically, you used to make A plus C. Now you make A plus B. You've added B, but you've lost C. So what is the marginal revenue? The marginal revenue for monopolists is now the area B minus the area C. Or P2,


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[Assistant] So your marginal revenue is not this simple just priced more and more. Now it's this more complicated term. Okay? More generally, marginal revenue can be defined as, the marginal revenue is defined as, marginal revenue is defined as P plus delta P delta Q times Q. That's marginal revenue. Okay?


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[Assistant] The first term is positive. That's the money you make on the next unit. The second term is negative.


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[Assistant] Because by definition, the demand occurs downward sloping where there's no giving goods anymore in this class. Demand may be on a test, but not in reality. The demand occurs downward sloping. Okay? So this term is negative. Now once again,


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[Assistant] I'm writing delta, but really it's derivatives. So this is all incremented. This is all, this is sort of epsilon changes. This is q0.


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[Assistant] Okay, this is sort of epsilon changes. But the bottom line is for an epsilon change in price, you get, for an epsilon change in quantity, uh,


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[Assistant] You get, uh, the, the price on the unit you sell, minus the money you lost, the units you can no longer sell. Okay? This is the key intuition of monopoly math. The key, yeaah.


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[Assistant] This is your marginal revenue. I just did it graphically. That's, that's, that, that's your marginal revenue. You just see that from the graph. Okay? And I just rewrote it here. Okay? So basically, or for those of you into calculus, if you just differentiate


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[Assistant] Just, if those of you who are, who are, who have your calculus, if you just write, you know, dr dq, d revenue dq, okay, what do you get? You get p plus dp dq times q. That's just the derivative of the rev, of revenue with respect to quantity. Okay? So,


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[Assistant] Let's think intuitively what's going on here. This is very, very important.


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[Assistant] What's going on here is to sell another unit, you have to lower your price. You're working your way down your demand curve. And therefore it offsets the benefit you get from selling another unit. Okay? I like, I like to call this the poisoning effect.


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[Assistant] I mean it's not original to me, but it's a term that I've heard used that I like. The poisoning effect. The idea is that to sell another unit,


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[Assistant] I have to poison myself a little bit by lowering the price on all the previous units I sold. Okay?


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[Assistant] If I want to go out in the market and force consumers to buy one more unit, I've got to lower the price on all the units, which offsets money I used to make. So that's why we call it a sort of poisoning effect. Now, why doesn't a competitive firm face this issue? Why are we just bringing this up now? Why does a monopoly firm face a poisoning effect and a competitive firm doesn't? Or alternatively, another way to ask the question is,


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[Assistant] In what situation would a monopoly firm not face a poisoning effect? Yeah.


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[Assistant] They're not, but that's actually right. The competitor firm is the price taker. But in particular, even though they're price taker, why when they sell more quantity is there no poisoning effect?


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[Assistant] It doesn't, the price doesn't have to change to sell more units.


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[Assistant] Okay, but a monopolist faces a poisoning effect because it's got a downward sloping demand curve.


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[Assistant] Okay, so we can actually see this. So what we want to do in figure 11.3 is we graph the monopolist's marginal revenue curve. So let's actually work out the math here. Let's imagine there's a demand curve.


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[Assistant] Let's imagine that I've got a demand curve and I'm just making this up. Demands of the form Q equals 24 minus P. Okay? Let's just say that's the demand curve. Okay?


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[Assistant] Flip the way to express this and write this, write price as a function of quantity. Because now the monopolist is choosing his price. So we can write that p equals 24 minus q. Okay? Just inverting it, writing price as a function of quantity. Okay? So in this case, revenues, which are equal to p times q, are equal to 24q minus q squared. I just multiplied through by q.


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[Assistant] So once again, this is a new sort of mathematical trick you'll have to get used to. Flip the demand curve to express price of functional quantity, multiply through by Q, and then differentiate, and you get that marginal revenue is 24 minus 2Q. So you can see that in figure 11.3, the marginal revenue curve is the demand curve shifted in.


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[Assistant] We'll not always hold. This sort of picture of a margin of view curve being the demand curve shifting will not always hold. It only holds for certain functional forms. Mostly we'll use functional forms for where it holds.


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[Assistant] The main lesson is the marginal revenue curve has to be at or below the demand curve.


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[Assistant] Shifted in relationship, that depends very much on functional form.


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[Assistant] But what is absolutely true is the marginal rev curve is always everywhere at or below the demand curve.


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[Assistant] Why? Because the demand curve, because by selling an X unit, you're gonna make less to this poisoning effect. So the marginal revenue curve is always below, uh, the demand curve. Alright, questions about that?


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[Assistant] And let's talk about the critical relationship, which I just developed intuitively, let's do it mathematically.


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[Assistant] Oh, p plus p- I'm sorry, nope. I did this wrong. My bad. Don't write that down. Gotta look more at my notes.


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[Assistant] I'm gonna write it as, I'm gonna multiply and divide by p, p plus p times, yeaah, delta p, delta q, times q over p, I skipped a step, okay? So I just multiply and divide it by p, multiply and divide by p, p plus p times delta q, delta p over delta q, times q over p, okay? Now,


[User] Please transcribe this text

[Assistant] If you look at this expression, delta P over delta Q times Q over P, that is the inverse of the elasticity of demand. So you can rewrite this as P plus P times 1 over the elasticity of demand. Or, we're writing it one more time,


[User] Please transcribe this text

[Assistant] That marginal revenue equals p times 1 plus 1 over the elasticity of demand. Marginal revenue equals p times 1 plus 1 over the elasticity of demand. Okay? So think about this for a second. This gets the intuition we just talked about. If e is, if the elasticity of demand is negative infinite, is negative infinity. Okay, I had it wrong with zero. If the elasticity of demand is negative infinity, then you have a competitive market. Perfectly competitive market is elasticity of demand negative infinity.


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[Assistant] So you get a competitive market. Okay?


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[Assistant] Uh, if the elasticity of a man goes, like the elasticity of a man is negative 1, let's do that case. So negative infinity is perfectly competitive. Okay, what about negative 1?


[User] Please transcribe this text

[Assistant] What's special about the elasticity demand of negative one in this case? What's the margin of revenue? Zero. That's the case going back to figure 11-2 where B and C exactly cancel out.


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[Assistant] So you probably thought about this when you looked at this graph. You probably quickly asked yourself, well, should the monopolists try to sell more or not? Well, the answer is the elasticity demand is minus one, they're indifferent.


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[Assistant] So this is sort of the important insight. With elasticity of demand of minus one, the monopolist is indifferent about selling another unit. Because what they gain from selling the unit, they lose on the previous units. If the elasticity of demand is greater than minus one absolute value, then they're gonna lose money by selling additional units. If the elasticity of demand is less than one, uh, then they're gonna make money.


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[Assistant] By, uh, by- by- by selling additional units. But let's- I- I'm skipping ahead. Let's go on and talk about profit maximization. Okay?


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[Assistant] Imagine a monopolist cost function curves of the form.


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[Assistant] 12 plus q squared. Let's take the same monopolist and write down cost function of 12 plus q squared. Okay? So with this cost function, marginal cost equals 2q. Okay, that's marginal cost with this cost function. Okay? So what's the profit maximization rule? It's that marginal revenue equals marginal cost. Well marginal revenue, we wrote down here, is 24 minus 2q.


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[Assistant] Equals marginal cost. Now we're monopolists, here's the trick, little q and big q are the same. So I wrote little q here, but if you're the only firm in the market, little q and big q are the same. Right? It's only one firm in the market.


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[Assistant] So, 24 minus 2q equals, I'll make this a big q now, equals 2q. So, so the optimization point


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[Assistant] That's the profit maximizing sale on quantity for the monopolist.


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[Assistant] Is where 24 minus 2q, where marginal revenue equals marginal cost, we derive marginal revenue. Okay? Marginal cost, we know how to derive from a cost function. We set them equal and we get the optimizing quantity. Okay? And you can see this in figure 11-4.


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[Assistant] Shows what's going on here. So I've driven all the, I've drawn all the various cost curves for this cost function. Okay? I've driven all the various cost curves for this cost function. You can see the marginal cost curve.


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[Assistant] And then you can see it intersects the marginal revenue curve at a quantity of 6. Intersects the marginal revenue curve at a quantity of 6. Okay. What is the price? Somebody raise their hand and tell me, tell me why. The quantity is 6. What's, what's the price of the monopolist set? Yea.


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[Assistant] 18. Why? You're supposed to get that wrong. You didn't follow my instructions. You didn't get it wrong. Uh, you got it right. I'm just joking. How did you know it was 18 and not 12?


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[Assistant] They have to choose a price such that people want to buy six units. So your intuition, which is my fault, I've always said look where the curves intersect, do a quantity and a price. Your quick intuition, which was to look and say the price was 12, which was the wrong answer I usually get, okay, is wrong.


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[Assistant] So a monopolist solves for the optimal quantity, but then to get the optimal price, he has to plug this back into the man curve. Well, what's demand? Demand is 24 minus P.


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[Assistant] So, I'm sorry, it's p equals 24 minus q, that's what I meant. So if q star is 6,


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[Assistant] Then price is 24 minus 6, or 18. P star is 18. And that is what you will get wrong on, when you, when you do this. If you're gonna get anything wrong in Monopoly problems, this is what you're gonna get wrong.


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[Assistant] Okay, which is remembering, you can't just, at the end, you have to do an extra step here. To get the price, you have to solve for quantity, but then respect the demand curve to get the price. That's a question somewhere. Okay, you have a question?


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[Assistant] It's pretty much, yeaah, it's pretty much meaningless. Basically that intersection used to pin down the quantity, but price has to come for demand curve, because you have to respect, you can't sell something consumers don't want to buy. Okay? So you've got to respect that demand curve. Okay? And in fact, you can show yourself, uhm, so, so basically, uhm,


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[Assistant] Uh, okay, so basically, uhm, that's the pro- pro- pro- pro- pro- pro- pro- pro- pro- pro- pro- pro- pro- pro- pro- pro- pro- pro- pro- pro- pro- pro- pro- pro- pro- pro- pro- pro- pro- pro- pro- pro- pro- pro- pro- pro- pro- pro- pro- pro- pro- pro- pro- pro- pro- pro- pro- pro- pro- pro- pro- pro- pro- pro- pro- pro- pro- pro- pro- pro- pro- pro- pro- pro- pro- pro- pro- pro- pro- pro- pro- pro- pro- pro-


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[Assistant] In the short run, we still have to spec the shutdown rules, so you still have to check.


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[Assistant] Is price less than average variable cost. Now once again, in this function,


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[Assistant] Okay, in, in this, you have to check if it's a price. So, even if profits are negative, you're still gonna have to check if price is greater than average variable cost. Now here, at six units, the average variable cost is six.


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[Assistant] You see, you see the dashed line. If we sell 6 units, the average variable cost is 6.


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[Assistant] So clearly price is greater than the average per hour cost, you wouldn't shut down. You're making positive profits in fact. You're making profits of 60. Okay, so you wouldn't shut down, but you always do have to check the shutdown rule. Okay, so that's how you do a monopoly problem. Okay, just to go back, how do you do a monopoly problem?


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[Assistant] You'll be given a cost function. You know what to do those in your sleep. And a demand function.


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[Assistant] The demand function gets turned into a marginal revenue function simply through these couple of steps. So the demand function gives you a marginal revenue function.


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[Assistant] If you have marginal revenue and marginal cost, then you know how to solve for optimal quantity.


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[Assistant] If you have optimal quantity and you respect the demand curve, you know how to solve for price. Once you have a price,


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[Assistant] Okay, and an average cost curve, you can both check the shutdown rule and compute profits. Profits are simply the price you get minus average costs. So we can compute the profit and check the shutdown rule. Okay, so the only thing we did here that's new,


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[Assistant] That we need to think about that comes to the question you might have asked yourself at some point. You might have said, well, if monopolists are the only firm in the market, why don't they discharge whatever they want? Why do they have to, why are they sort of constrained by the sort of mathematics we've done before?


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[Assistant] And to answer this, let's turn to the concept of market power.


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[Assistant] The market power of monopolists we will define as their ability to charge price greater than marginal cost.


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[Assistant] Your bill to charge price greater than marginal cost is your market power. In other words, competitive firms have no market power. They have to charge a price that's the same as their marginal cost. And that's why they make no money. Monopolists have market power.


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[Assistant] Okay, so now let's return to the condition for profit maximization. We said that marginal revenue can be rewritten


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[Assistant] As price times one plus one over the elasticity of demand.


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[Assistant] Okay, so we can rewrite this as marginal cost over price.


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[Assistant] Equals 1 plus 1 over the elasticity of demand.


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[Assistant] Casually we can call it profits, but technically it's the markup, okay, as the percentage markup a monopolist can make as P minus MC over P. How much of the price is actually a markup over costs? It's sort of an intuitive concept. So basically, how much of the money you get for the unit is a markup as a share of the money you get? Then that is simply, that is equal to minus


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[Assistant] 1 over the elasticity of demand. So the monopolist markup is equal to 1 over the, minus 1 over the elasticity of demand.


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[Assistant] Okay, so if the elasticity of demand is negative infinity, that is a perfectly competitive market, then the markup is what? Zero. Just like competitive firm. Competitive firms have to charge marginal cost. But as demand gets more inelastic,


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[Assistant] The monopolist gains power to mark up the price and make money.


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[Assistant] And this answers our question of why monopolists aren't infinitely powerful.


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[Assistant] What is the limiting factor on monopolists? It's not other firms producing their good. What's the limiting factor on monopolists? Yeaah.


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[Assistant] Yeah, it's other products. So think about a monopolist in insulin. They can charge however the hell they want. Right? Because basically there's nothing else to buy. That may be multiple insulin products, but imagine one insulin product. Okay?


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[Assistant] So nothing constrains him enough. He should charge an infinite price up to like what Congress will put up with. Okay?


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[Assistant] But if you think about a monopolist in a good with as a substitute, so if I'm the monopolist in, uhm, gum, if I'm a gum-opolist, okay,


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[Assistant] Then I'm constrained by how much people eventually will just substitute to candy. Okay?


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[Assistant] Anything, so I'm constrained, not by competitors in my market.


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[Assistant] But by the fact that consumers can substitute to other goods. So what's the limit on monopolists? Consumers.


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[Assistant] We're the limit on monopolists. Our willingness to put up with that good relative to other goods, i.e. our elasticity of demand, is the only thing limiting monopolists. Okay?


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[Assistant] So basically, there is market discipline in monopolists. Even though they're the only provider of a good, they're still subject to market discipline. It's just the discipline doesn't come from other firms. It comes from consumers. Okay? So a great example of this is let's look, if you go on, at least as of last year, if you go on Amazon and look at the prices of two goods that you've probably had to consume in high school,


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[Assistant] Huckleberry Finn and Great Gatsby. Two books. Okay, that many of you had to consume in high school. You had to read Huckleberry Finn, you had to read Great Gatsby. They're both


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[Assistant] Comparable lengths, great grats, these are a little shorter I think, but they're both comparable lengths. The production cost, the marginal cost of producing them is probably pretty comparable.


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[Assistant] Okay, but if you go on Amazon, Hawkfin costs $4, and the Great Gatsby costs $16.


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[Assistant] Why is this? Anyone know? Why does Great Gatsby cost four times much?


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[Assistant] Only people who get permission from the great, from William F., from William Scott Fitzgerald's descendants, F. Scott Fitzgerald, I'm sorry, descendants get to produce it. They have a monopoly on the good that is the great Gatsby. Huck Finn


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[Assistant] It turns out that 75 years after an author's death, copyright protection expires. F. Scott Fitzgerald hasn't been dead for 75 years. Mark Twain has.


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[Assistant] So we think probably Hawkfin should be produced in a pretty competitive market.


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[Assistant] That is, basically the four dollars you pay for Huck Finn should be roughly the cost of producing a book. Okay, now no mark is perfectly competitive. A little markup, but not much. Whereas the Great Gatsby, it's not limited by competition.


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[Assistant] But it is limited by the fact that if they tried to charge 500 bucks for Great Gatsby, teachers would have signed something else.


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[Assistant] Okay. There's still a limit. It's only $16. That's not a whole lot for one of the great works of literature. Okay.


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[Assistant] It's only $16, so why is it only $16? Because it's limited by the fact that there are other great works of literature people can turn to.


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[Assistant] Probably pretty close to a perfectly competitive market, right? It's pretty easy to just set up a shop and produce Huck Finn. Whereas the Great Gatsby has this extra effect.


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[Assistant] Which is copyright protected, so it's only limited by, by the elasticity of demand. Yeah.


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[Assistant] That, that's a great point. So the last of this demand, I should say the last of this demand for that good, where one of the substitutes could be an illegal substitute. That's a good point.


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[Assistant] Okay, so let's go on and talk about the next topic I want to cover today, which is


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[Assistant] How do we, cause now we have a new set of tools we've developed that's really cool, which lets us ask the question, not just what do monopolies do, but how do we feel about it. That is, we can now turn to talking about the welfare effects of monopoly.


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[Assistant] What are the welfare effects of monopoly? How do we feel about monopoly? Well let's start with the standard case.


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[Assistant] That is the case we've covered so far as opposed to a case I'll cover in a minute. Okay? And let's look at figure 11-5, which is the example we just solved for.


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[Assistant] Okay, the example where, uh, demand equals 24 minus q, and cost is 12 plus q squared. Okay, so here we sh-


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[Assistant] Once again, what do we do? We set marginal cost equal to marginal revenue. So they sell six units.


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[Assistant] We then say what price permits them to sell 6 units at a price of 18. So the equilibrium is at a price of a, is at e little m, e for, e little m for monopoly. Okay. They sell 6 units at a price of 18. Well, at that equilibrium, what's consumer surplus? It's A.


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[Assistant] For which the marginal, for which the willingness to pay is above the willingness to supply. And what do we call those units? Units that are not sold. Someone raise their hand and tell me. Units that are not sold, for which the willingness to pay is above the willingness to supply. Yeaah. Deadweight loss. Those are units that's an inefficiency. Those units that are not sold, that


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[Assistant] Efficiently should be. That is, we've broken this, our first example ever. This is a super exciting moment of breaking the first fundamental theorem of welfare economics.


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[Assistant] The first fundamental theory of welfare economics was that the equilibrium, the competitive equilibrium, okay, maximizes welfare. Well, that's no longer true. Here we have an equilibrium that comes out of competition, okay, it's what the market delivers, but it doesn't maximize welfare.


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[Assistant] There's a deadweight loss. And that's because the market's imperfectly competitive.


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[Assistant] This is our first ever example of what we call a market failure.


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[Assistant] Okay. And that's what, from my perspective, makes economics fun.


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[Assistant] Okay, if there were no market failures, if all markets functioned the way we said they functioned, then basically we could have been largely done with the course by now.


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[Assistant] Okay, what makes this all interesting is markets don't function the way we said they function in that extreme case. And therefore markets, a market failure is defined as a case where the market equilibrium does not maximize social welfare. So whenever the market equilibrium does not maximize social welfare, you've got a market failure. In the perfectly competitive case, we didn't have a failure because the market equilibrium maximized welfare. That's not true here.


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[Assistant] Now the market equilibrium does not maximize welfare, therefore it's a market failure. Hint, what's exciting about that to me, is that means there might be a potential role for policy.


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[Assistant] Okay, so far in this course, the government's just been a bad guy. It's done nothing but set mean minimum wages and things like that. And terrible price ceilings.


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[Assistant] But in fact, as we'll see next time, this starts to introduce the role for the government as a good guy. Okay? Now, what makes, to drive this into a show and make this more interesting, let's contrast that to the more realistic case of price discrimination. Or potentially more realistic case.


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[Assistant] Of price discrimination. Now, what happens if we don't force the monopolist to only charge one price?


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[Assistant] What if we allow the monopolist to charge different prices to different consumers?


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[Assistant] If monopolists can perfectly price discriminate, that is that they can sell a separate price for every consumer, then monopoly is welfare maximizing.


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[Assistant] If monopolists can set a perfect price for every consumer, then monopoly does maximize social welfare. To see that, simply look at figure 11-6.


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[Assistant] Now let's take a perfectly priced discriminating monopolist. Let's think about what this price is they set. Well, essentially what they're gonna do is set price where?


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[Assistant] A Pervil's Criminine Monopolis is going to set the price for each unit. To what? Yeah.


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[Assistant] The demand, the willingness to pay. If you're perfectly price discriminating, you will screw consumers to the max.


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[Assistant] And how do you do that? By delivering them no surplus.


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[Assistant] By taking all the surplus for yourself. So for the first unit.


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[Assistant] You charge five. For the second unit you charge four. And for the sixth unit you charge eighteen. Now!


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[Assistant] Now the priest monopolist stopped at 6. Why did he stop at 6? Because to sell the 7th unit would have lost him money.


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[Assistant] He would have had to lower the price on all previous units. But the price scheme monopolist has no poisoning effect, because he doesn't have to lower the price on the previous units. He can say for that seventh unit, I'm gonna sell that one at 17.


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[Assistant] I'm gonna make 17 and I'm not gonna lose any money because I can keep the other prices the same.


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[Assistant] So with a perfectly priced discriminating monopolist, you get rid of the poisoning effect, they just march their way down the demand curve, charging every consumer exactly their willingness to pay.


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[Assistant] Therefore, they will continue to produce until the competitive equilibrium. They will continue to produce until willingness to pay equals willingness to supply.


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[Assistant] But they will capture all the surplus. So the new equilibrium will be EC.


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[Assistant] The competitive equilibrium, but the entire surplus goes to the monopolist.


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[Assistant] This is a fascinating case. There's, we maximize social welfare, but only because we define social welfare in this peculiar way, which is the simple sum of consumer, producer, surplus.


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[Assistant] Here, producers get all the surplus, therefore, welfare is maximized. So a perfectly price-iscreting monopolist, okay, gets, uh, maximized social welfare. Okay? Now, there's two interesting points that come out of this.


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[Assistant] And think about why the perfectly priced screening monopolist gets to sell another unit and the regular monopolist doesn't. Because the regular monopolist has the poisoning effect and the perfectly priced screening monopolist does not. So it's a good way to sort of think about that intuition of the poisoning effect. That's lesson one.


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[Assistant] Lesson two is, gee, we may want to think about definition of welfare that's not just a sum of consumer-producer surplus.


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[Assistant] A model of welfare that delivers the fact that a producer that can screw every single consumer out of any of their surplus is the best possible outcome might not be a model we're so happy with. Okay?


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[Assistant] There was a controversy a number of years ago where Amazon would set your price according to your, uhm, what's the little string of numbers address? IP address. They literally would set prices by IP address.


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[Assistant] They'd literally say, well, you know, you're coming for an IP address. That's for example, you're in a high, high income area. I'm going to charge you more. You're in a university. Therefore you need this book for a course. Therefore I'm going to charge you more, et cetera. That, they got busted and that was found illegal.


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[Assistant] Just because you can't perfectly price discriminate doesn't mean we don't have lots of examples of partial price discrimination. So what are examples in the real world of price discrimination? What do firms do?


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[Assistant] And what's the general, let me ask, the, the, tell me what firms do, and also I want to know what's the general principle. What's the basic idea that firms, if you want to price discriminate, what do you want to figure out? What is your goal to figure out? Yeaah.


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[Assistant] They have to go. If you're gonna buy two days before, you gotta go. Okay, if you're buying six months before,


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[Assistant] You know, you might have to go that day, you might not have to go that day, you might have to, but if you're buying last minute, you gotta go. So your elasticity's lower.


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[Assistant] So, price discriminating monopolists look for signals of elasticity.


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[Assistant] That's their search. They can't literally know your willingness to pay. Amazon tried, but even Amazon couldn't perfectly know your willingness to pay. So they're looking for signals that are correlated with your willingness to pay. One signal,


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[Assistant] Uh, they don't, I don't know if they actually use that. How long have you been on the website? They could, that'd be kind of interesting.


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[Assistant] Yeah, I don't know, but that's pretty subtle. What's a more blunt one than even the four websites? So, yeah.


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[Assistant] I know you guys grew up with the internet, but there was life before the internet. And even before the internet, airlines price discriminated. What did they, what did they do in the back? Yea.


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[Assistant] Yeah, different levels of flight, right? Why is a first class ticket more than a coach ticket? Because rich guys are less elastic than poor guys.


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[Assistant] Okay, so basically another way of price discriminating within the same flight is by having different quality. So what they do is they say, we're gonna give you a higher quality product, but look, first class,


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[Assistant] Okay, but it raised the price figure from $1,000 to $2,500. Now, it was better, but it wasn't $1,500 better.


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[Assistant] Okay, or a certain length of this, let me rephrase that. It cost more, but it certainly didn't cost $1,500 more. I got a bigger seat and like, you know, people slaved over me. But like,


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[Assistant] It certainly did not cost them $1,500 to provide that service. They clearly made more of a markup on the business class seat than they did in the coach seat. Because I was less elastic. Why? Because someone else was paying for my flight.


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[Assistant] Okay, so I was less elastic, and that's if you talk to people in business class, none of them are paying for their own flights. They're either super rich or their company's paying. Okay?


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[Assistant] So the bottom line, that's another way airlines discriminate. So let's get away from airlines. What are other examples of price discrimination?


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[Assistant] Exactly. Or, that's exactly right. Restaurants are supermarkets.


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[Assistant] Now here's what's interesting. If you look at McDonald's,


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[Assistant] Okay, it's prices, uh, no, it's true for both. Basically, if you look like, like, if, if I buy Mc-, when I buy McDonald's on the highway out in the suburbs, it's more expensive than I would buy it here in Cambridge. Why's that? Why's, why's, why's a big so-, yeah.


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[Assistant] So that's an example. Inner-city price-higher supermarkets charge much higher prices in the city than out of the city. Now you might think that's sort of strange.


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[Assistant] Okay, but that's because in the city people have to walk to get there. They don't have a lot of options. There's not a lot of shopping. I'll see if they can drive from supermarket to supermarket. Okay, so there's all these complicated things that go into it.


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[Assistant] One of my, let me sort of show you my, uhm, couple of my favorite examples. One of my favorite examples is early bird specials. You guys might not know about this, but you might have hung out with your grandparents.


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[Assistant] It's cheaper. Or if you go to a matinee movie, a movie during the day is cheaper than a movie at night. Same movie. Why? Why is a movie during the day cheaper than a movie at night?


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[Assistant] You're more elastic during the day because basically you're an old retired person who's got nothing but time in their hands.


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[Assistant] It's like you can shop around movie theaters, you can decide to go to the movie or take a nap, etc. Okay? Same thing with early dinner specials.


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[Assistant] People who have more time to shop are more elastic. At night, you're going out to see the movie. These are people, you know.


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[Assistant] In some sense, it's sort of interesting. You think midnight movies, I don't know if this is true.


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[Assistant] Midnight movies should charge them most of all. Cause that's a bunch of insane fans, right, who have to see the movie first.


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[Assistant] Seems like the midnight showing should charge the most. I don't know if that's true. That'd be interesting to look at.


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[Assistant] Okay, that's one example. Another example I love is Disneyland.


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[Assistant] Disneyland and Disney World charge less if you live within 20 or so miles of the park. Why?


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[Assistant] Because you can go whenever. So, when I took my kids to Disney World, if I went up and said, oh I'm sorry kids, it was $10 more than I thought we're not going. Okay, I would have had a riot on my hands. Once you're there, you're in elastic. You're going to Disney World. There's nothing else to do in Orlando. I mean, but there's other parks, I guess. But like, but if you live locally, you can decide if you're going or not.


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[Assistant] Okay, and then probably the most interesting recent example is Tesla. So during, I feel like, did I tell you guys the Tesla hurricane story yet? I don't think so, right? Okay, so during the hurricane in Florida, erm, I guess it was, uh, in Florida,


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[Assistant] Tesla, so Tesla sold two cars, two models. The cheaper model and the more expensive model. And the more expensive model had some nice doodads, but most importantly the engine, the battery lasted longer.


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[Assistant] The cheaper model is like 300 miles, the more expensive model is like 500 miles.


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[Assistant] During Hurricane Irma, Tesla, as a good gesture of goodwill,


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[Assistant] Okay, said, hey, guys who drive the cheap car, you can now drive 500 miles. And they're like, what the hell? It's the same battery. Tesla said, well, it turns out it's the, it's the same battery. The only difference is a piece of software that we could turn off or on. So why did Tesla do that? Why did Tesla have a piece of software


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[Assistant] They turn off or on and turn it off for some people to make them drive less. Why did they do that? Did someone else involve?


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[Assistant] Anyone tell me about what Tesla thought? Besides Elon Musk being an asshole. What else? What's the other, what's the kind of, what sort of Tesla thought process? Actually it was perfect economics. Yea. Price discrimination. Right, price discrimination, but how? How are you price discriminating? By making some people, yea.


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[Assistant] Exactly. It's like first class. You're basically saying, I want to charge more for a better product.


[User] Please transcribe this text

[Assistant] I can't charge more for the same product. So if I give everyone 500 miles, I can't charge more. But by making one product better, I can separate demand.


[User] Please transcribe this text

[Assistant] I can sell the expensive products to the low elasticity demand consumers and the less expensive the high elasticity demand. But it's actually the same damn product. I just did it as a way to price discriminate. So Tesla, in an effort to be nice, screwed themselves by revealing that they had been actually falsely screwed, you know,


[User] Please transcribe this text

[Assistant] Screwing consumers, it's not, it's good economics, it makes total sense. Okay, this actually follows one last example. When the first laser printers came out, okay, it turned out that you could buy one for home that was like half the price of one for office.


[User] Please transcribe this text

[Assistant] And someone took them apart and found the one for home was the one for the office plus an extra piece that made it go slower.


[User] Please transcribe this text

[Assistant] Okay, and they did that simply because they knew the office guys were less price-elastic than the home guys. So they wanted an expensive one, so they said the office one's faster, isn't this cool? It was faster because they didn't add an extra piece that made it go slower.


[User] Please transcribe this text

[Assistant] Neurotransmission speeds under one nanosecond. Faster than signals travel inside the brain. Never mind to an external prosthesis. We did it, Peter.


[User] Please transcribe this text

[Assistant] And your work on the neural web was the key. But we haven't even tested it yet.


[User] Please transcribe this text

[Assistant] I'll keep at it. Work out some bugs.


[User] Please transcribe this text

[Assistant] Adventure 6 The Adventure of Black Peter


[User] Please transcribe this text

[Assistant] I have never known my friend to be in better form, both mental and physical, than in the year 95. His increasing fame had brought with it an immense practice, and I should be guilty of an indiscretion if I were even to hint at the identity of some of the illustrious clients who crossed our humble threshold in Baker Street.


[User] Please transcribe this text

[Assistant] Holmes, however, like all great artists, lived for his art's sake.


[User] Please transcribe this text

[Assistant] And, save in the case of the Duke of Holderness, I have seldom known him claim any large reward for his inestimable services.