I know this is intended to be funny but it is part of the problem. Too many people focus on presidential elections and candidates rather than the House and Senate. 

Algorithms, the Internet, STEAM, and the Continuing Struggle for Justice

Beautiful Day is a feel good, uplifting pop rock song that serves as a reminder to all of us that it is always possible to be optimistic.

Its a Beautiful Day

Its A Beautiful Day

CORRECTED DESCRIPTION 13 May 2024

This is a piece created by Duncan Chapman from recordings of forced rhubarb growing at David Westwood & Son rhubarb farm, near Wakefield. You can hear the rhubarb buds popping as they burst and also some mud as we squelched around in the dark. The audio has been cleaned up as much as possible to remove the sound of both the M62 and M1 motorways which are nearby!

A mass of popping rhubarb - forced rhubarb growing at DWS Farm

Dorothy Roberts is an award-winning author and expert on the interplay of gender, race, and class in legal issues concerning reproduction, bioethics, and child welfare. She is a professor of law and sociology at the University of Pennsylvania. Chuck Mertz interviews Roberts about her latest book, TORN APART: How the child welfare system destroys black families—and how abolition can build a safer world. 

TORN APART available Now at Basic Books https://www.basicbooks.com/titles/dorothy-roberts/torn-apart/9781541675445/

Family Policing Punishes Poor Families and Protects White Supremacy  / Dorothy Roberts

This song was inspired by gangster and florist Charles Dean O'Banion (shot dead in his flower shop on November 10, 1924) and the long defunct Chicago punk bar named after him.

Blood On The Roses (remix)

Sometimes when we say an algorithm discriminates, we mean it can tell the difference between two types of items.  But in this episode, we'll talk about another, more troublesome side to discrimination: algorithms can be... racist?  Sexist?  Ageist?  Yes to all of the above.  It's an important thing to be aware of, especially when doing people-centered data science.  We'll discuss how and why this happens, and what solutions are out there (or not).

Relevant Links:
http://www.nytimes.com/2015/07/10/upshot/when-algorithms-discriminate.html
http://techcrunch.com/2015/08/02/machine-learning-and-human-bias-an-uneasy-pair/
http://www.sciencefriday.com/segments/why-machines-discriminate-and-how-to-fix-them/
https://medium.com/@geomblog/when-an-algorithm-isn-t-2b9fe01b9bb5#.auxqi5srz




Discriminatory Algorithms


Algorithms have become a powerful force in the world, but for all the impressive good they do, they sometimes show some worrying tendencies. Algorithms that discriminate are a problem that nobody's found a solution for yet. This week, we discuss why some algorithms appear to be racist, and whether there's anything that can be done about it.

The Techdirt Podcast

Is Your Algorithm Racist?

In this week's podcast InfoQ’s editor-in-chief Charles Humble talks to Data Scientist Cathy O’Neil. O'Neil is the author of the blog mathbabe.org. She was the former Director of the Lede Program in Data Practices at Columbia University Graduate School of Journalism, Tow Center and was employed as Data Science Consultant at Johnson Research Labs. O'Neil earned a mathematics Ph.D. from Harvard University. Topics discussed include her book “Weapons of Math Destruction,” predictive policing models, the teacher value added model, approaches to auditing algorithms and whether government regulation of the field is needed.

Why listen to this podcast:

 - There is a class of pernicious big data algorithms that are increasingly controlling society but are not open to scrutiny.
 - Flawed data can result in an algorithm that is, for instance, racist and sexist.  For example, the data used in predictive policing models is racist. But people tend to be overly trusting of algorithms because they are mathematical.
 - Data scientists have to make ethical decisions even if they don’t acknowledge it. Often problems stem from an abdication of responsibility.
 - Auditing for algorithms is still a very young field with ongoing academic research exploring approaches.
 - Government regulation of the industry may well be required.

Notes and links can be found on http://bit.ly/2eYVb9q

Weapons of math destruction

0m:43s - The central thesis of the book is that whilst not all algorithms are bad, there is a class of pernicious big data algorithms that are increasingly controlling society.
1m:32s - The classes of algorithm that O'Neil is concerned about - the weapons of math destruction - have three characteristics: they are widespread and impact on important decisions like whether someone can go to college or get a job, they are somehow secret so that the people who are being targeted don’t know they are being scored or don’t understand how their score is computed; and the third characteristic is they are destructive - they ruin lives.
2m:51s - These characteristics undermine the original intention of the algorithm, which is often trying to solve big society problems with the help of data.

More on this:

Quick scan our curated show notes on InfoQ. http://bit.ly/2eYVb9q

You can also subscribe to the InfoQ newsletter to receive weekly updates on the hottest topics from professional software development. bit.ly/24x3IVq

InfoQ Podcast

Show Notes

Cathy O'Neil on Pernicious Machine Learning Algorithms and How to Audit Them

When we covered the Word2Vec algorithm for embedding words, we mentioned parenthetically that the word embeddings it produces can sometimes be a little bit less than ideal--in particular, gender bias from our society can creep into the embeddings and give results that are sexist. For example, occupational words like "doctor" and "nurse" are more highly aligned with "man" or "woman," which can create problems because these word embeddings are used in algorithms that help people find information or make decisions. However, a group of researchers has released a new paper detailing ways to de-bias the embeddings, so we retain gender info that's not particularly problematic (for example, "king" vs. "queen") while correcting bias.

Debiasing Word Embeddings

Writer Sara Wachter-Boettcher explains how racial and sexual bias finds its way from society into digital products (and back into society) as a result of the tech industry's unwillingness to examine its own values, and they way their work engages with and shapes society beyond the mostly white, male corporate campuses of Silicon Valley.

Sara is author of "Technically Wrong: Sexist Apps, Biased Algorithms, and Other Threats of Toxic Tech" from W.W. Norton: http://books.wwnorton.com/books/978-0-393-63463-1/

Social inequality is coded deep within the devices of Silicon Valley.

Released on Linear Obsessional's free download label, my album The Terminal Beach was first conceived in the early 80's.  It is a personal story as much as an attempt to capture JG Ballard's short story.  

A man maroons himself upon a former nuclear test atoll in the Pacific.  The small landscape is festooned with concrete structures.  Lakes, bunkers and two thousand blocks.  Wrecked bombers and more structures than even Ballard gets time to write about.  A story written in the shadow of the cold war, it perfectly captured who and what I was in my early 20's.  Come with me here, and see the sights?

07 The dark, undersea organ

VENUS PELLAGATTI XTRAVAGANZA
ROBERT BROOKS
SAM NORDQUIST
AARON BUSHNELL
ELIJAH MCCLAIN
ANTEO ZAMBONI 
SUMMER TAYLOR
AHMED EREKAT
DOMINIQUE REM'MIE FELLS
SARAH GROSSMAN
JAMES SCURLOCK
DAVID MCATEE
EYAD AL-HALAQ
HECTOR GARCIA MENDOZA
GEORGE FLOYD
BREONNA TAYLOR
VICENTE RAMON GUERRERO
MARCI WISE
JOSEPH ROSENBAUM
ANTHONY HUBER
RIAH MILTON
TONY MCDADE 
EUGUI ROY
AHMAUD ARBERY
ASHLYNN LISBY
OLUWATOYIN SALAU 
VICTORIA SIMS
JOHANNA METZGER
ZEZICO GUAJAJARA
ISABEL CABANILLAS
DAVID GLEN WARD
TONY MCDADE
TIFFANY M. MOFIELD
KENNY RICHIE MARTY "MYLEZ" MITCHELL
NÉHÉMIE JOSEPH
NICOLA SACCO
BARTOLOMEO VANZETTI
ANNA LOPIZZO
ATATIANA KOQUICE JEFFERSON
CARY BALL JR.
ROXANA HERNANDEZ
JAKELIN CAAL MAQUIN
FELIPE ALONZO-GOMEZ
DREASJON "SEAN" REED
MCHALE ROSE
JANA LANGE
WILLIE MCCOY
MARIEE JUAREZ
OSMAR EPIFANIO GONZALEZ-GADBA
JEANCARLO JIMENEZ-JOSEPH
HUY CHI TRAN
KALIEF BROWDER
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SERGIO ALONSO LOPEZ
KAMYAR SAMIMI
JOSHUA BROWN
GEMMEL MOORE
TIMOTHY DEAN
SAHAR KHODAYARI
DE'VON BAILEY
TONY TIMPA
MARIA DEL PILAR HURTADO
EMILSEN MANYOMA
MOISÉS MOSQUERA MORENO
TEMISTOCLES MACHADO 
ELEAZAR TEQUÍA VITUCAY
HECTOR WILLIAM MINA
ELIJAH AL-AMIN
NINA POP
JENNIFER LAUDE
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CHYNAL LINDSEY
JOYCE FIENBERG
RICHARD GOTTFRIED
ROSE MALLINGER 
JERRY RABINOWITZ 
CECIL ROSENTHAL 
DAVID ROSENTHAL 
BERNICE SIMON 
SYLVAN SIMON 
DANIEL STEIN 
MOHAMMED ABU KHUDAIR
MOHAMMAD RAMIZ BAKR
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MELVIN WAX 
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EMANTIC “EJ” BRADFORD, JR.
TENIYA JONES 
THURMAN BLEVINS
ALEX NIETO
WALTER LUEBCKE
ARMANDO FRANK
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LINUS PHILLIP
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DANA MARTIN
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MUHLAYSIA BOOKER
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PHILANDO CASTILE
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VIOLA LIUZZO
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RICKY JOHN BEST
TALIESIN MYRDDIN NAMKAI MECHE
FREDDIE GRAY 
ALTON STERLING
JORDAN EDWARDS
OSCAR RAMIREZ, JR.
LIGE DANIELS
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ELTON MITCHELL
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WILLIAM LITTLE
JEFF BROWN
KEITH BOWEN
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DOROTHY DORSEY
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SEAN BELL 
ANTHONY LAMAR SMITH
HENRY GLOVER
RONALD MADISON
TIMOTHY STANSBURY
ALBERTA SPRUILL
DEBORAH DANNER
OUSMANE ZONGO
ORLANDO BARLOW
PRINCE JONES
RONALD BEASLEY
EARL MURRAY
PATRICK DORISMOND
MALCOLM FERGUSON
JONATHAN FERRELL
DONTRE HAMILTON
JOHN CRAWFORD III
EZELL FORD
AIYANA JONES
OSCAR GRANT
DANTE PARKER
TANISHA ANDERSON
TYREE WOODSON
VICTOR WHITE III
YVETTE SMITH
MCKENZIE COCHRAN
JORDAN BAKER
ANDY LOPEZ
MIRIAM CAREY
DEION FLUDD
KIMANI GRAY
REYNALDO QUEVAS
SHANTEL DAVIS
TAMON ROBINSON 
SHEREECE FRANCIS
REKIA BOYD 
TROY DAVIS 
AMADOU DIALLO
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LAQUAN MCDONALD
KENDRICK JOHNSON
LAVENA JOHNSON
MEDGER EVERS
ANDREW GOODMAN 
MICHAEL SCHWERNER 
JAMES CHANEY 
JOHN EARL REESE 
WILLIE EDWARDS JR 
MACK CHARLES PARKER 
MARSH COOK
JOHN BROWN
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WILLIAM LEWIS MOORE 
ADDIE MAE COLLINS 
DENISE MCNAIR 
CAROLE ROBERTSON 
CYNTHIA WESLEY 
VIRGIL WARE 
HENRY HEZEKIAH DEE 
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LEMUEL PENN 
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JAMES REEB 
ONEAL MOORE 
WILLIE BREWSTER
JONATHAN DANIELS 
VERNON DAHMER 
BEN CHESTER WHITE 
WHARLEST JACKSON
BENJAMIN BROWN 
SAMUEL HAMMOND JR 
DELANO MIDDLETON 
HENRY EZEKIAL SMITH 
NAT TURNER 
ANDY BURKE 
JOHNSON WHITTAKER 
ROBERT ROBINSON 
FRED ALEXANDER 
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L.B. REED 
CLINTON BRIGGS 
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BUD JOHNSON 
LUCIUS MCCARTY 
POWELL GREEN 
EARNEST MCGOWAN 
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PRECIOUS GRANT 
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EUGENE BELLS 
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JAMES STEPHENSON 
ALONZA BROOKS 
DEJUAN GUILLORY 
ROCRAST MACK JR. 
JUSTIN THOMPSON 
DARRIUS STEWART

Social inequality is coded deep within the devices of Silicon Valley.

This Is Hell!

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