"Next:Economy" entries

Four short links: 22 April 2016

Four short links: 22 April 2016

Unicorn Hazards Ahead, Brainprinting for Identity, Generating News Headlines, and Anthropic Capitalism

  1. Why The Unicorn Financing Market Just Became Dangerous to Everyone — read with Fortune’s take on the Tech IPO Market. “They profess to take a long-term view, but the data shows post-IPO stocks are very volatile in the case of tech IPOs, and that is not a problem the underwriters try to address.” Damning breakdown of the current state. As Bryce said, Single-horned, majestic, Weapons of Mass Extraction.
  2. Brainprints (Kurzweil) — 50 subjects, 500 images, EEG headset, 100% accuracy identifying person from their brain’s response to the images. We’ll need much larger studies, but this is promising.
  3. Generating News Headlines with Recurrent Neural NetworksWe find that the model is quite effective at concisely paraphrasing news articles.
  4. Anthropic Capitalism And The New Gimmick Economy — market capitalism struggles with “public goods” (those which are inexhaustible and non-excludable, like infinitely copyable bits that any number of people can have copies of at once), yet much of the world is being recast as an activity where software manipulates information, thus becoming a public good. Capitalism and Communism, which briefly resembled victor and vanquished, increasingly look more like Thelma and Louise; a tragic couple sent over the edge by forces beyond their control. What comes next is anyone’s guess and the world hangs in the balance.

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Four short links: 31 March 2016

Four short links: 31 March 2016

Accountable Machines, Forbidden Gaming, Make Things, and Crypto Monoculture

  1. Accountable MachinesSome of the proposals discussed at our workshop included having machine learning processes verify the outcomes of algorithmic decisions and provide transparency, and that systems should be designed to permit auditing as well as to audit other related systems. To me this appeared as an especially accountable version of bureaucracy, where results from each system’s accounting dynamically report up through an iterative (but still accountable) chain of command. This is not bureaucratic in the sense of inventing process for its own sake, but it is bureaucratic in the sense that it establishes many processes of accountability that are the responsibility of entities who report to one another through a structure where trust is related to the capacity to validate decisions.
  2. Russia Bans Queue — banned the Polish board game that recreates the experience of life under Communism. Games that are simulations are effective educational experiences, too effective for Russia.
  3. Tech Economies Must Still Make Things (Vaclav Smil) — Bill Gates’s favorite scientist/policy analyst weighs in on the next economy. Take away manufacturing and you’re left with…selfies.
  4. On the Impending Crypto Monoculture (Peter Gutmann) — A number of IETF standards groups are currently in the process of applying the second-system effect to redesigning their crypto protocols. A major feature of these changes includes the dropping of traditional encryption algorithms and mechanisms like RSA, DH, ECDH/ECDSA, SHA-2, and AES, for a completely different set of mechanisms, including Curve25519 (designed by Dan Bernstein et al), EdDSA (Bernstein and colleagues), Poly1305 (Bernstein again) and ChaCha20 (by, you guessed it, Bernstein). What’s more, the reference implementations of these algorithms also come from Dan Bernstein (again with help from others), leading to a never-before-seen crypto monoculture in which it’s possible that the entire algorithm suite used by a security protocol, and the entire implementation of that suite, all originate from one person. How on earth did it come to this?
Four short links: 29 March 2016

Four short links: 29 March 2016

SNES Code Injection, World Without Work, Spectrum Collaboration, and Mass Surveillance

  1. SNES Code Injection (YouTube) — this human exploited various glitches in Super Mario World to inject the code for Flappy Bird. Wow.
  2. Will Life be Worth Living in a World without Work? — new paper published in the Science and Engineering Ethics journal. Two distinct ethical/social issues would seem to arise. The first is one of distributive justice: how will the (presumed) efficiency gains from automated labour be distributed through society? The second is one of personal fulfilment and meaning: if people no longer have to work, what will they do with their lives? In this article, I set aside the first issue and focus on the second. In doing so, I make three arguments. First, I argue that there are good reasons to embrace non-work and that these reasons become more compelling in an era of technological unemployment. Second, I argue that the technological advances that make widespread technological unemployment possible could still threaten or undermine human flourishing and meaning, especially if (as is to be expected) they do not remain confined to the economic sphere. And third, I argue that this threat could be contained if we adopt an integrative approach to our relationship with technology.
  3. Spectrum Collaboration Challenge — DARPA’s next big challenge is based on the idea that wireless devices would work better if they cooperated with one another rather than fought for bandwidth. Since not all devices are active at all times, the agency says, it should be possible through the use of artificial intelligence machine-learning algorithms to allow them to figure out how to share the spectrum with a minimum of conflict.
  4. Mass Surveillance Silences Minority Opinions (PDF) — This study explores how perceptions and justification of surveillance practices may create a chilling effect on democratic discourse by stifling the expression of minority political views. Using a spiral of silence theoretical framework, knowing one is subject to surveillance and accepting such surveillance as necessary act as moderating agents in the relationship between one’s perceived climate of opinion and willingness to voice opinions online. Theoretical and normative implications are discussed. (via Washington Post)
Four short links: 22 February 2016

Four short links: 22 February 2016

Immersive Flood, Human Jobs, Anonymous Security, and Chrome Speed

  1. Facebook Creates Social VR Team (FT) — Facebook said that users had uploaded 20,000 videos in VR-friendly 360-degree format. At same time as HTC Vive VR Headset price is announced, LG 360 VR is announced, the new Samsung handsets come with a Gear VR headset, and Samsung’s Gear 360 camera is announced. There’s a heap of immersive hardware coming.
  2. AAAI-16 Panel on Future of Work (Tech Republic) — “It’s hard to argue that there will be new jobs for humans,” said Vardi. “It’s a vacuous promise.”
  3. Security Without Identification (PDF) — a David Chaum paper from 1985. Digital pseudonyms, handheld signing devices, Current systems emphasize the one-sided security of organizations attempting to protect themselves from individuals; the new approach allows all parties to protect their own interests. The new approach relies on individuals keeping secret keys from organizations and organizations devising other secret keys that are kept from individuals. During transactions, parties use these keys to provide each other with specially coded confirmation of the transaction details, which can be used as evidence.
  4. Killing Slow Chrome Tabs (Medium) — There is one not-so-well known tool in Chrome, that allows you to analyse how much resources the individual tabs consume. It is called Task Manager and you can find it in Menu > More Tools > Task Manager.
Four short links: 15 February 2016

Four short links: 15 February 2016

Deep Learning Analogies, IoT Privacy, Robot Numbers, and App Economy

  1. Deep Visual Analogy-Making (PDF) — In this paper, we develop a novel deep network trained end-to-end to perform visual analogy making, which is the task of transforming a query image according to an example pair of related images. Open source code from the paper also available.
  2. Samsung’s TV and Privacy Gets More AwkwardSamsung has now issued a new statement clarifying how the voice activation feature works. “If a consumer consents and uses the voice recognition feature, voice data is provided to a third party during a requested voice command search,” Samsung said in a statement. “At that time, the voice data is sent to a server, which searches for the requested content then returns the desired content to the TV.” It only seems creepy until you give in and nothing bad happens, then you normalise the creepy.
  3. 2015 Robot Numbers (RoboHub) — The Robotic Industries Association (RIA), representing North American robotics, reported […] 2015 set new records and showed a 14% increase in units and 11% in dollars over 2014. The automotive industry was the primary growth sector, with robot orders increasing 19% year over year. Non-automotive robot orders grew at 5%.
  4. Mozilla, Caribou Digital Release Report Exploring the Global App Economy (Mark Surman) — The emerging markets are the 1% — meaning, they earn 1% of total app economy revenue. 95% of the estimated value in the app economy is captured by just 10 countries, and 69% of the value is captured by just the top three countries. Excluding China, the 19 countries considered low- or lower-income accounted for only 1% of total worldwide value. Developers in low-income countries struggle to export to the global stage. About one-third of developers in the sample appeared only in their domestic market.

Four short links: 11 January 2016

Four short links: 11 January 2016

Productivity Mystery, Detecting Bullshit, Updating Cars, and Accountable Algorithms

  1. Why Americans Can’t Stop Working (The Atlantic) — summary of a paywalled economics paper on the mystery of increasing productivity yet increasing length of the work week. (via BoingBoing)
  2. On the Reception and Detection of Pseudo-Profound Bullshit (PDF) — These results support the idea that some people are more receptive to this type of bullshit and that detecting it is not merely a matter of indiscriminate skepticism but rather a discernment of deceptive vagueness in otherwise impressive sounding claims. (via Rowan Crawford)
  3. Tesla Model S Can Now Drive Without You (TechCrunch) — the upside of the Internet of Things is that objects get smarter while you sleep. (In fairness, they can also be pwned by Ukrainian teenagers while you sleep.)
  4. Replacing Judgement with Algorithms (Bruce Schneier) — We can get the benefits of automatic algorithmic systems while avoiding the dangers. It’s not even hard. Transparency and oversight with accountability.
Four short links: 17 November 2015

Four short links: 17 November 2015

Remix Contest, Uber Asymmetry, Language Learning, and Continuous Delivery

  1. GIF It Up — very clever remix campaign to use heritage content—Friday is your last day to enter this year’s contest, so get creating! My favourite.
  2. Uber’s Drivers: Information Asymmetries and Control in Dynamic WorkOur conclusions are two-fold: first, that the information asymmetries produced by Uber’s system are fundamental to its ability to structure indirect control over its workers; and second, that Uber relies heavily on the evolving rhetoric of the algorithm to justify these information asymmetries to drivers, riders, as well as regulators and outlets of public opinion.
  3. ANNABELL — unsupervised language learning using artificial neural networks, install your own four year old. The paper explains how.
  4. Spinnakeran open source, multi-cloud continuous delivery platform for releasing software changes with high velocity and confidence.
Four short links: 3 November 2015

Four short links: 3 November 2015

Quantum Architectures, Gig Economy Size, Networking Truths, and Twitter's Decay

  1. Australians Invent Architecture for Full-Scale Quantum Computer (IEEE) — still research paper, so I’ll believe it when it can glitch Hangouts just like a real computer.
  2. How Big is the Gig Economy? (Medium) — this is one example in which the Labor Department and Bureau of Labor Statistics really have shirked their responsibility to try and assess the size and growth of this dynamic shift to our economy.
  3. The Twelve Networking Truths — RFC1925 is channeling the epigram-leaking protagonist of Robert Heinlein’s Time Enough for Love. It is easier to move a problem around (for example, by moving the problem to a different part of the overall network architecture) than it is to solve it. This is true for most areas of life: generally easier to make it someone else’s problem than to solve it.
  4. The Decay of Twitter (The Atlantic) — In other words, on Twitter, people say things that they think of as ephemeral and chatty. Their utterances are then treated as unequivocal political statements by people outside the conversation. Because there’s a kind of sensationalistic value in interpreting someone’s chattiness in partisan terms, tweets “are taken up as magnum opi to be leapt upon and eviscerated, not only by ideological opponents or threatened employers but by in-network peers.”

Improving Uber’s surge pricing

Should algorithmic pricing be the norm rather than the exception?

The Newport Wedge by Tom Walker on Flickr. Used under a public domain license.

Request an invitation to Next:Economy, our event aiming to shed light on the transformation in the nature of work now being driven by algorithms, big data, robotics, and the on-demand economy.

Companies want a bigger share of the pie than their competitors, capital wants a bigger share than labor (and labor wants right back), countries want a bigger share than their rivals, but true wealth comes when we make a bigger pie for everyone. Well run markets are a proven way to do that.

Surge pricing is one of Uber’s most interesting labor innovations. Faced with the problem that they don’t have enough drivers in particular neighborhoods or at particular hours, they use market mechanisms to bring more drivers to those areas. If they need more drivers, they raise the price to consumers until enough drivers are incented by the possibility of higher earnings to fill the demand. Pricing is not set arbitrarily. It is driven algorithmically by pickup time — the goal is to have enough cars on the road that a passenger will get a car within 3–5 minutes. (Lyft’s Prime Time pricing is a similar system.) Uber keeps raising the price until the pickup time falls into the desired range.

This is clearly an imperfect system. In one case, surge pricing gouged customers during a crisis, and even in more prosaic situations like bad weather, the end of a sporting event, or a holiday evening, customers can see enormous price hikes. This uncertainty undercuts the fundamental promise of the app, of cheap, on-demand transportation. If you don’t know how much the ride will cost, can you rely on it?

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A world of continous partial employment

Managers and workers benefit when both have access to data and control.

Photo illustration showing Lyft car in front of a Walmart

Request an invitation to Next:Economy, our event aiming to shed light on the transformation in the nature of work now being driven by algorithms, big data, robotics, and the on-demand economy.

Our future workplaces are increasingly managed by apps and algorithms. Is technology empowering workers, or making them ever more helpless cogs in a corporate profit machine?

When we talk about the “on-demand economy,” we are really talking about two things: the ability of a consumer to summon a vehicle, their lunch, or their groceries with the touch of an app or a few words to Siri, Cortana, or Google Now; and the lives of the workers who respond to those summons. Instant on-demand consumer services mean workers must also be available on demand.

As Logan Green of Lyft noted, his company provides “transportation as a service.” Perhaps the more general point is that it provides labor as a service. At least for now, the car comes with a driver.

Companies such as Lyft, Uber, TaskRabbit, Postmates, Upwork (and too many other new startups to count) all depend on a large pool of workers who make no set work commitments, who are bound to no schedule, but simply turn on an app when they want to work, and compete with other workers for whatever jobs are available.

These apps have gotten a lot of attention. But focusing that attention merely on “Next Economy companies” misses many of the deeper changes in the labor economy.

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