We’re looking for a Policy Economist to tease smart answers to hard questions out of big data
Uber is a fascinating enterprise. I think they are going to change cities globally. Not just reform the sclerotic taxi monopoly. Here is an example:
Urban transportation has looked the same for a long time – a really long time – thanks in large part to regulatory regimes that don’t encourage innovation. We think it’s time for change. We’re a tech company sure, and we’re working in the transportation space, but at the end of the day we’re disrupting very old business models. Our Public Policy team prefers winning by being right over some of the darker lobbying arts, and so we’re looking for a Policy Economist to tease smart answers to hard questions out of big data. How do the old transportation business models impact driver income? What effect if any is Uber having on the housing market or drunk driving or public transit? To what extent are the different policy regimes in New York City and Taipei responsible for different transportation outcomes? Just a few of the questions we want you to dig on.
Read their placement ad for the full description of the opportunity. And note the Perks:
- Travel like a European diplomat: employees are showered with Uber credits
- Ground floor opportunity at a fast growing company that is changing the face of transportation worldwide
- As an early member of our business operations team, you’ll shape the business direction of the company
- We’re not just another social web app: we’re moving real assets and real people around their cities
- We have access to an amazing list of advisors and investors that we actively engage
If I were a young economist that would look like a big chance.
From my iPad library of “images from forgotten sources”.
Michael B Sullivansees the implementation of Amazon PrimeAir much the way I do, as the last part of integrated logistics:
Taking as the basis for conversation a world in which both drones and driverless vehicles are technically possible and easy-to-use (I don’t think either are right around the corner), then I think you use both for your delivery.
Forget last-mile delivery, this is more about “last 15ish miles” and “last quarter mile.” You send your driverless big old truck out with hundreds of packages. It has with it a small fleet (maybe 5-10) of drones that handle the last quarter mile of the delivery. Your truck trundles along on big streets that can accommodate it; the drones blitz out with packages and back over short distances, charging up from the big batteries of the truck on a rotation. This allows you to deliver far heavier packages (the drones don’t need a battery capable of delivering X kg over 15km, they need a battery capable of delivering X kg over 0.5km), at overall lower cost (the majority of your trip is via low-energy rolling along roads, not high-energy helicoptering), but with the same convenience of the actual delivery (no giant truck moving along narrow residential streets, no need for some kind of klutzy mechanical linkage between a robotic vehicle and your drop-box at your house). It’s probably less legitimately awful in terms of aviation control, too.
This is pure speculation – but it is an exciting spec. Not all of this will happen, but possibly other big opportunities will emerge. This is just a sample:
So, step one: Take over taxi industry. Step two: Kill ownership. From there, who knows what could happen in the long term? Uber could start using self-driving cars made by Google (one of its investors) to eliminate the need for human drivers, driving down its costs even more. It could introduce a near-instantaneous delivery service to rival Amazon’s drones. It could roll out a subscription service, akin to Amazon Prime, that would include perks like predictive transportation, so that, for example, when Uber sees an appointment on your Google calendar for a cross-town meeting, it sends a car to your office automatically at the right time. There’s no reason that other companies couldn’t try to do these things, too. But Uber has first-mover advantage, and it’s got most of the kinks – customer interface, payment, fleet management, supply-and-demand considerations – worked out already, making it a prime candidate to beat competitors to new product areas.
The result of Uber’s efforts, in other words, could be the creation of a techno-metropolis, in which people and goods are ferreted around seamlessly and, perhaps, automatically. It would be like something out of a sci-fi movie. And Uber would be standing at the center of it all, collecting a cut of every transaction.
Let’s say 30-minute drone delivery to your home were legal, well-run, and, for purposes of argument, free or done at very low cost. You would buy smaller size packages and keep smaller libraries at home and in your office. Bookshelf space would be freed up, you would cook more with freshly ground spices, the physical world would stand a better chance of competing with the rapid-delivery virtual world, and Amazon Kindles would decline in value. Given that the storage costs for goods would fall (more storage by specialists, accompanied by later delivery), expected inflation would more likely be converted into price hikes today. The liquidity premium of money (NB: not currency) would rise and the liquidity premium of goods would fall. Some drug markets would be taken off the streets and the importance of gang “turf” would fall.
Addendum: What do we know about network economies in drone delivery systems? FedEx and UPS and USPS, taken together, dominate the market for physical delivery of parcels to homes. How much room would there be in the market for “lone drone” operators?
Amazon is developing Amazon PrimeAir .
There are two Google courses on Power Searching and Advanced Power Searching. The course is an efficient, very high return on your attention investment. You are guaranteed to learn methods and “tricks” that will make you a better student or researcher.
Here are a few examples:
The deadly curse on King Tutankhamen’s tomb
Mimicking presidential voices [From Kee Malesky, of National Public Radio]
Searching your own web history
The course is in both video and text-transcript form – to suit your preferred learning modality.
The latest Android, iOS data from OpenSignal makes my head hurt. There is much more analysis in the report – but these two figures capture some of the pain that Android developers suffer. The graphic below shows the variety of screen sizes/resolutions that full Android support requires.
The bottom line is that Android devices are pushed by carriers – who have NO incentive to keep their customers up to date on the latest OS version.
This is so totally the innovative Adams. Scott has to decided to “crowd blurb” his new book titled How to Fail Almost Every Time and Still Win Big: Kind of the Story of My Life. Here's your chance to appear on the back cover:
After Dilbert became a big deal, people started asking how I was able to beat such long odds. Was it simply a case of hard work plus extraordinary luck, or did I have some sort of secret method?
The interesting answer is that my career unfolded according to a written strategy that I created after I graduated from college. I still have it. And on top of the strategy I have several systems designed to make it easier for luck to find me.
This is where you come in.
My publisher has agreed to print blurbs from you, my blog readers, knowing that none of you have read the actual book. What's in it for you is that you might see your name on the back cover of the book.
The trick is to write your review in a way that addresses my general writing/thinking qualities as seen on this blog. You won't be reviewing the book so much as reviewing me as a writer. Keep your reviews to a few sentences at most, and don't be so overboard that it looks disingenuous. The trick is to say something positive that isn't over the top. And don't pretend you actually read the book.
I'll select several winners from what I see in the comments and stick them on the book.
(…snip…) While once the flow of data across the Internet appeared too overwhelming for N.S.A. to keep up with, the recent revelations suggest that the agency’s capabilities are now far greater than most outsiders believed. “Five years ago, I would have said they don’t have the capability to monitor a significant amount of Internet traffic,” said Herbert S. Lin, an expert in computer science and telecommunications at the National Research Council. Now, he said, it appears “that they are getting close to that goal.”
Thanks to Tyler Cowen for the link to this NYT piece by James Risen and Eric Lichtblau. I've been casually following Palantir Technologies for some time. They are arguably one of the “new disruptors” and by chance happen to be headquartered next to the Phillz Coffee that we favor in Palo Alto (Phillz is of course full of Palantir and other denizens of the brain-powered companies based around Palo Alto). From listening to a couple of podcast interviews with CEO Dr. Alex Karp, I understood Palantir's specialty was to help clients such as drug developers or intelligence agencies discern patterns in mountains of data. Palantir is not an automated data-mining algorithms company. Their secret sauce is enabling human brainpower to analyze enormous and often separate data sets. So visualization of relationships is an important part of their solutions.
Palantir has a large number of YouTube videos - conference lectures, demos, and “Palantir 101″ type overviews.
I'll close with an apt Alex Karp quote from the Palantir website:
“There is no point in having a war on terrorism if civil liberties are being undermined to the extent that we aren’t willing to fight that war.”
Further to the cognitive computing topic, I'll also note that IBM Research Director John Kelly is speaking tonight at the Computer History Museum in nearby Mountain View. We immediately tried to reserve seats, but Kelly's talk is already sold out. His book Smart Machines: IBM’s Watson and the Era of Cognitive Computing , will be published in the fall by Columbia University Press. You can read a free chapter here.