Studying the appearance of algorithms in popular culture and everyday life. By PlummerFernandez
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Pizza Palace - Ordering Pizza in 2015 (as speculated 20 years ago)

I just saw Roger Burrows give a lecture on what it is now like to live with algorithms, metrics and data governing our lives and he started the talk by illustrating the point with this pizza video. This was made in the mid-nineties and speculated that so much data about ourselves would be made available for commercial exploit. The female voice is clearly a human over a phone-line but it could easily be imagined that this would be the voice of recommendation algorithms at an algo-driven pizza service, perhaps a subsidiary business of Amazon or Google Shopping that has access to all that data. 




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Amazon’s recommendation algos may assume you’re a drug dealer
Upon ordering digital scales, Amazon recommended seal bags and filters to go with it. via Shardcore 

Algo-intelligence at it’s best: buy a scale on Amazon, Amazon will think you’re a drug dealer.

Amazon’s recommendation algos may assume you’re a drug dealer

Upon ordering digital scales, Amazon recommended seal bags and filters to go with it. via Shardcore 

Algo-intelligence at it’s best: buy a scale on Amazon, Amazon will think you’re a drug dealer.




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"I have a friend who works in physical rehabilitation at a clinic on Park Avenue. She feels that she needs a minimum of one hour to work with a patient. Recently she was sued for $200,000 by a health insurer, because her feelings exceeded their insurance algorithm. She was taking too long."

A Talk With Simon Head, Author of ‘Mindless: Smarter Machines Are Making Dumber Humans’.



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Welcome new followers! Especially all you bots, this tumblr is all about your kind. Your tumblr names are incredible, like extracts from the Library of Babel.  

Welcome new followers! Especially all you bots, this tumblr is all about your kind. Your tumblr names are incredible, like extracts from the Library of Babel.  




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The Fear Index by Robert Harris
A novel about High Frequency Trading/ Algo-Trading. I’ve just read this book and can now vouch for it. At first glance I found it intruiging that such a high profile author would even want to tell the story of how hedge-funds and quants deploy algorithms to do their trading, so I was surprised to discover that the story totally revolves around a fictional algorithm called Vixal-4 and its maker. Robert Harris actually spent time with quants when researching for his book, so the story does offer a good picture of what this secretive industry must be like behind the scenes. The story is also loosely based on the 2010 Flash Crash. The ending troubled me a little but I don’t want to elaborate on that to avoid spoilers!
Another HFT book that is making the headlines at the moment is Flash Boys, a non-fiction by Michael Lewis that strongly suggests that HFT is rigged. This has prompted investigations into whether this is true, including that of the FBI, the Securities and Exchange Commission, the Commodity Futures Trading Commission and the Justice Department. 

The Fear Index by Robert Harris

A novel about High Frequency Trading/ Algo-Trading. I’ve just read this book and can now vouch for it. At first glance I found it intruiging that such a high profile author would even want to tell the story of how hedge-funds and quants deploy algorithms to do their trading, so I was surprised to discover that the story totally revolves around a fictional algorithm called Vixal-4 and its maker. Robert Harris actually spent time with quants when researching for his book, so the story does offer a good picture of what this secretive industry must be like behind the scenes. The story is also loosely based on the 2010 Flash Crash. The ending troubled me a little but I don’t want to elaborate on that to avoid spoilers!

Another HFT book that is making the headlines at the moment is Flash Boys, a non-fiction by Michael Lewis that strongly suggests that HFT is rigged. This has prompted investigations into whether this is true, including that of the FBI, the Securities and Exchange Commission, the Commodity Futures Trading Commission and the Justice Department. 




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prostheticknowledge:

Apple Patents for Automatic 3D Avatar Creation and Emotional States

Something to expect in the future in regards to online identity (both of which were filed today):

A three-dimensional (“3D”) avatar can be automatically created that resembles the physical appearance of an individual captured in one or more input images or video frames. The avatar can be further customized by the individual in an editing environment and used in various applications, including but not limited to gaming, social networking and video conferencing.

I wonder if this will be connected to Apple’s purchase of depth sensor company Primesense [Link to patent file]

Methods, systems, and computer-readable media for creating and using customized avatar instances to reflect current user states are disclosed. In various implementations, the user states can be defines using trigger events based on user-entered textual data, emoticons, or states of the device being used. For each user state, a customized avatar instance having a facial expression, body language, accessories, clothing items, and/or a presentation scheme reflective of the user state can be generated.

[Link to patent file]




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RED - Reading Eye Dog, Onomy (2001) - via p-dpa

Red is a piece we did to try and explain what machine reading was. Hollywood set the bar really high for humanoid robots, C3PO knows 6000 languages and never makes a mistake. But then we settled on a dog, because a dog, even if it does make mistakes is still the smartest dog in the world, its reading! ”

Mounted in the dog’s eyes are two video cameras that capture the image of the material placed in front of it. It uses Optical Character Recognition software to detect letters and then puts these letters together to form words. Through a voice synthesizer, the dog speaks each word that it has read. 




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FOMO Algorithmic Journalism Machine - via Dezeen
Design studio Space Caviar have created a mobile unit that prints on-demand newspapers generated by their FOMO - Fear of Missing Out -Algorithm. Using voice recognition and web-scraping, the algorithm automatically translates these sources into text articles. The piece will be presented at the Milan design fair and so its activities will be centred around the social media and in-situ conversations regarding the event. The system will be following the hashtag #OnTheFlyMilan if you feel inclined to participate. Not to be confused with Jonas Lund’s Fear of Missing Out art generating algorithm.

FOMO Algorithmic Journalism Machine - via Dezeen

Design studio Space Caviar have created a mobile unit that prints on-demand newspapers generated by their FOMO - Fear of Missing Out -Algorithm. Using voice recognition and web-scraping, the algorithm automatically translates these sources into text articles. The piece will be presented at the Milan design fair and so its activities will be centred around the social media and in-situ conversations regarding the event. The system will be following the hashtag #OnTheFlyMilan if you feel inclined to participate. Not to be confused with Jonas Lund’s Fear of Missing Out art generating algorithm.




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Nest Labs’ Smoke Detector wave-detect fail - via NYT
Nest Labs have halted sales of their smoke detector because one of its algorithms has been found to accidentally switch the device off. A feature that lets you wave at the device to temporarily disable it has caused concern as the algorithm failed to distinguish other movements from a waving motion, potentially disabling the device when it is most needed. 

Nest Labs’ Smoke Detector wave-detect fail - via NYT

Nest Labs have halted sales of their smoke detector because one of its algorithms has been found to accidentally switch the device off. A feature that lets you wave at the device to temporarily disable it has caused concern as the algorithm failed to distinguish other movements from a waving motion, potentially disabling the device when it is most needed. 




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“As algorithmic systems become more prevalent, I’ve begun to notice of a variety of emergent behaviors evolving to work around these constraints, to deal with the insufficiency of these black box systems…The first behavior is adaptation. These are situations where I bend to the system’s will. For example, adaptations to the shortcomings of voice UI systems — mispronouncing a friend’s name to get my phone to call them; overenunciating; or speaking in a different accent because of the cultural assumptions built into voice recognition. We see people contort their behavior to perform for the system so that it responds optimally.”
Alexis Lloyd (NYTimes R&D) shares some interesting views under the title In the Loop: Designing Conversations with Algorithms.

As algorithmic systems become more prevalent, I’ve begun to notice of a variety of emergent behaviors evolving to work around these constraints, to deal with the insufficiency of these black box systems…The first behavior is adaptation. These are situations where I bend to the system’s will. For example, adaptations to the shortcomings of voice UI systems — mispronouncing a friend’s name to get my phone to call them; overenunciating; or speaking in a different accent because of the cultural assumptions built into voice recognition. We see people contort their behavior to perform for the system so that it responds optimally.”

Alexis Lloyd (NYTimes R&D) shares some interesting views under the title In the Loop: Designing Conversations with Algorithms.




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Quakebot, the LA Times earthquake reporter - via Wired

An Earthquake hit Los Angeles on the 17th March at 6.25am and eight minutes later the story was reported on the LA Times by a bot. Journalist and coder Ken Schwencke created Quakebot that takes information from the USGS Earthquake Notification Service and turns anything over a 3.0 magnitude into a readable story with a map and headline, queued and ready for publishing on the content management system. The system then pings Schwencke who, on this occasion, had to roll out of bed and approve the story for publishing. The bot continues to break the news for Earthquakes, see here for an example.

This type of automated reporting has some journalists worried about being replaced by algorithms, see here and here.




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Google / Boston Dynamics announce direction
Google announced plans for their Boston Dynamics robotic acquisition. After their encounter at TED, Sergey Brin personally wanted to improve Edward Snowden’s mobility. The solution has been revealed as a special teleconferencing version of their Big Dog robot that Snowden will be able to control remotely. Snowden has expressed initial delight for the project and it is rumoured that he may soon be roaming the fields of the Googleplex for testing.

Google / Boston Dynamics announce direction

Google announced plans for their Boston Dynamics robotic acquisition. After their encounter at TED, Sergey Brin personally wanted to improve Edward Snowden’s mobility. The solution has been revealed as a special teleconferencing version of their Big Dog robot that Snowden will be able to control remotely. Snowden has expressed initial delight for the project and it is rumoured that he may soon be roaming the fields of the Googleplex for testing.




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Computers dethrone humans in European stock trading - via reuters
European equity investors are placing more orders via computers than through human traders for the first time as new market rules drive more money managers to go high-tech and low cost. The widespread regulatory changes has made electronic trading spread across the industry.
Last year, European investors put 51 percent of their orders through computers directly connected to the stock exchange or by using algorithms, a study by consultants TABB showed. The TABB study revealed that of 58 fund managers controlling 14.6 trillion euros in assets, a majority intended to funnel much more of their business through electronic “low touch” channels, which can cut trade costs by two-thirds. Pioneer Investments, which trades 500 billion euros ($695 billion) worth of assets every year and has cut the number of brokers it uses from 300 to around 100. Thats a lot of money in the non-hands of algorithms.

Computers dethrone humans in European stock trading - via reuters

European equity investors are placing more orders via computers than through human traders for the first time as new market rules drive more money managers to go high-tech and low cost. The widespread regulatory changes has made electronic trading spread across the industry.

Last year, European investors put 51 percent of their orders through computers directly connected to the stock exchange or by using algorithms, a study by consultants TABB showed. The TABB study revealed that of 58 fund managers controlling 14.6 trillion euros in assets, a majority intended to funnel much more of their business through electronic “low touch” channels, which can cut trade costs by two-thirds. Pioneer Investments, which trades 500 billion euros ($695 billion) worth of assets every year and has cut the number of brokers it uses from 300 to around 100. Thats a lot of money in the non-hands of algorithms.




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internet-of-dreams:

For a while now, facial analysis software has been able to distinguish between the six “basic categories” of emotion—happiness, surprise, anger, sadness, fear, and disgust. If you asked me to do the same, I could probably do it. But when you drill down into complex, compound facial expressions such as “happily surprised,” “fearfully angry,” “appalled,” “hatred,” and “awed,” I’d probably blow a couple of them. This computer doesn’t. In fact, it can decipher between 21 different “complex emotions.” (via Computers Can Read Emotions Better Than You Can | Motherboard)

internet-of-dreams:

For a while now, facial analysis software has been able to distinguish between the six “basic categories” of emotion—happiness, surprise, anger, sadness, fear, and disgust. If you asked me to do the same, I could probably do it. But when you drill down into complex, compound facial expressions such as “happily surprised,” “fearfully angry,” “appalled,” “hatred,” and “awed,” I’d probably blow a couple of them. This computer doesn’t. In fact, it can decipher between 21 different “complex emotions.” (via Computers Can Read Emotions Better Than You Can | Motherboard)




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