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

Algorithms make many decisions for users in the marketplace of ideas. They dictate our search results, the ads we see, and the news stories that reach us. As journalists, we need to learn to hold algorithms -- and their designers -- accountable for the ethical implications they create.

Algorithms Are The New Gatekeepers

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

Machines are making a lot of decisions that used to be made by humans. Computer-driven algorithms can determine everything from which friends we keep up with on Facebook, to the prices that we pay for goods and services, to which neighborhoods get more attention from political candidates. But how do we hold machines accountable for the decisions they make? What’s at stake when it comes to algorithmic injustice and accountability?

Algorithmic Accountability: When Machines Make Our Decisions


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

Cathy O’Neil, data scientist and author of the new book Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy, discussed how some algorithms can have an invisible, but important and destructive impact on people’s lives.

Media and Politics Podcast

Cathy O'Neil: How Big Data Increases Inequality and Threatens Democracy

Cathy O'Neil, author of Math Destruction:&nbsp;How Big Data Increases Inequality and Threatens Democracy, explains how data can be bias. Who Defines success and algorithms. Big data hype and being "beyond morals". Data and the war on teachers. Targeting teachers through data. Data-driven models to predictive policing and sentencing. The myth that numbers don't mislead and algorithms and job discrimination. On The Fun Half: The Republican civil war. Trump's most amazing spokesperson yet. A Trump supporter says Hillary Clinton is&nbsp;hypocrite&nbsp;because she listens to Beyonce. Sean Hannity calls Republican leaders "feckless". Alex Jones says Clinton is possessed by demons. Ben Carson defends Trump in the most amazing way. Why the mainstream still does not understand the Republican Party even in the age of Trump and your calls and IMs. Check out today’s sponsors: Texture: Texture.com/majority and Harry’s.com use promo code MAJORITYREPORT Members make the Majority Report possible. Please join us by becoming a MEMBER. Go to https://majority.fans.fm/memberships/new. &nbsp;You can also show your support by going to http://majority.fm/about/donate-to-the-majority-report/&nbsp;Thanks!

1441 - Cathy O’Neil: Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy

Our dangerous reliance on big data: in an episode recorded before the election, Rich and Paul talk to Cathy O’Neil, author of  Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy. They discuss Cathy’s origins in the math world, her years at a hedge fund on the brink of the 2008 financial crisis, the lack of transparency in the Department of Education’s data, and the various examples of “weapons of math destruction” in her book—all the ways that data is used to harm.

#0039: Cathy O'Neil on “Weapons of Math Destruction”

interview with joy buolamwini, winner of the search for hidden figures grand prize and founder of the algorithmic justice league

learn more about algorithmic justice at http://www.ajlunited.org
learn more about the center for civic media at https://civic.mit.edu

interview by allan ko for http://mitadmissions.org
see also http://mitadmissions.org/blogs/entry/interview-joy-buolamwini

interview: joy buolamwini

ThePLUG Data 4 Black Lives Interview with Cathy O'Neil

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.

Snippets of TED Radio Hour episode 'Can We Trust The Numbers', 'Do Algorithms Perpetuate Human Bias?' for English imitation practice.
https://www.npr.org/2018/01/26/580617998/cathy-oneil-do-algorithms-perpetuate-human-bias

Do Algorithms Perpetuate Human Bias6

Do Algorithms Perpetuate Human Bias5

Do Algorithms Perpetuate Human Bias4

Do Algorithms Perpetuate Human Bias3

Do Algorithms Perpetuate Human Bias2

Do Algorithms Perpetuate Human Bias1

In this episode, Kira Allmann (Virginia & Magdalen 2010) discusses how injustice can be tackled in the real and the virtual world with Rhodes Scholars Jennifer Haverkamp (Ohio & Somerville 1979), Jen Robinson (Australia-at-Large & Balliol 2006), and Joy Buolamwini (Tennessee & Jesus 2013).

Supported by: The Rhodes Trust (rhodeshouse.ox.ac.uk)
Produced by: Dr Kira Allmann (kiraallmann.com)
Music by: Conor Molloy (conormolloymusic.com)

Rhodes Women Series: Episode 2- Rhodes Women Take On Injustice

Healthcare and our digital trail are two things vital in our society. In this podcast you will notice and learn about the generated systems that are piecing together information to know who we are. Tax Companies such as Experian do a lot more than just your taxes.

Algorithmic Justice For Health Care Data

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
MI'CHANCE DUNLAP-GITTENS
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
LAYLEEN POLANCO
PAMELA TURNER
CHYNAL LINDSEY
JOYCE FIENBERG
RICHARD GOTTFRIED
ROSE MALLINGER 
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CECIL ROSENTHAL 
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BERNICE SIMON 
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MOHAMMED ABU KHUDAIR
MOHAMMAD RAMIZ BAKR
AHED ATEF BAKR
ZAKARIYA AHED BAKR
ISMAIL MAHMOUD BAKR
MELVIN WAX 
TIMOTHY CAUGHMAN
LARNELL BRUCE JR
OSCAR JOSE FIGUERA
EMANTIC “EJ” BRADFORD, JR.
TENIYA JONES 
THURMAN BLEVINS
ALEX NIETO
WALTER LUEBCKE
ARMANDO FRANK
RACHEL ALIENE CORRIE
ANTWON ROSE, JR.
LINUS PHILLIP
DIANTE BUTCHIE YARBER
SAHEED VASSEL
DANA MARTIN
ASHANTI CARMON
CLAIRE LEGATO
RACHEL CORRIE
MUHLAYSIA BOOKER
KENNETH CHAMBERLAIN SR.
ADAMA TRAORE
MICHELLE "TAMIKA" WASHINGTON
JAQUARRIUS HOLLAND
DANNY RAY THOMAS
STEPHON CLARK
MARIELLE FRANCO
TOVEET RADCLIFFE
HEATHER HEYER
FRED HAMPTON
LAVENA LYNN JOHNSON
PHILANDO CASTILE
TAMIR RICE
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TALIESIN MYRDDIN NAMKAI MECHE
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HENRY GLOVER
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TYREE WOODSON
VICTOR WHITE III
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KENDRICK JOHNSON
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MEDGER EVERS
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JAMES CHANEY 
JOHN EARL REESE 
WILLIE EDWARDS JR 
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ROMAN DUCKSWORTH JR 
WILLIAM LEWIS MOORE 
ADDIE MAE COLLINS 
DENISE MCNAIR 
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CYNTHIA WESLEY 
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LEMUEL PENN 
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WILLIE BREWSTER
JONATHAN DANIELS 
VERNON DAHMER 
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SAMUEL HAMMOND JR 
DELANO MIDDLETON 
HENRY EZEKIAL SMITH 
NAT TURNER 
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JOHNSON WHITTAKER 
ROBERT ROBINSON 
FRED ALEXANDER 
ROBERT TRUETT
L.B. REED 
CLINTON BRIGGS 
FRANK LIVINGSTON 
BUD JOHNSON 
LUCIUS MCCARTY 
POWELL GREEN 
EARNEST MCGOWAN 
LEE SNELL 
PRECIOUS GRANT 
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EUGENE BELLS 
TIMOTHY HOOD 
JAMES STEPHENSON 
ALONZA BROOKS 
DEJUAN GUILLORY 
ROCRAST MACK JR. 
JUSTIN THOMPSON 
DARRIUS STEWART

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

dialectical integrities