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Hyperpartisan Facebook Pages Are Publishing False And Misleading Information At An Alarming Rate
Analyzing the partisanship and veracity of claims posted on public facebook news pages.
hcds  data_journalism 
may 2018 by jaimoe
Four AI composition tools easy enough to soundtrack your film masterpiece | Ars Technica
AI-driven tools for musical composition. Interesting UX and UI considerations.
aiux  hcds  google  machine_learning  infoviz  music 
march 2018 by jaimoe
The UX of AI - Library - Google Design
As was the case with the mobile revolution, and the web before that, machine learning will cause us to rethink, restructure, and reconsider what’s possible in virtually every experience we build. In the Google UX community, we’ve started an effort called “human-centered machine learning” to help focus and guide that conversation. Using this lens, we look across products to see how machine learning (ML) can stay grounded in human needs while solving for them—in ways that are uniquely possible through ML. Our team at Google works across the company to bring UXers up to speed on core ML concepts, understand how to best integrate ML into the UX utility belt, and ensure we're building ML and AI in inclusive ways.
aiux  hcds  machine_learning  data_science  ux  google 
february 2018 by jaimoe
How DNA Testing Botched My Family's Heritage, and Probably Yours, Too
When we talk about “ancestry,” we also don’t always mean the same thing. Ancestry just implies people you’re descended from. But when? In America, we often mean whenever our relatives came to the U.S. On my dad’s side, I expected to see a lot of Scandinavian, because just a few generations ago my great grandparents came from Norway to North Dakota. On my mom’s side, my grandmother has a relative that came to America on the Mayflower. Both are what come to mind when I think of my “ancestors,” but they are separated by several generations and hundreds of years in time. Rutherford pointed out that if we went 5oo years back, my ancestors were probably from all over Europe.
hcds  genetics  statistics  algorithmic_transparency  data_science 
january 2018 by jaimoe
Analytics/AQS/Pageviews/Pageviews by country - Wikitech
This page documents the implications and decisions taken regarding user privacy in the Pageviews by country data set.
hcds  data_privacy  anonymization  infosec  ethics  research_ethics  analytics 
january 2018 by jaimoe
Facebook Ditches ‘Disputed' News Tag After It Totally Backfired
In the wake of the 2016 US presidential election, the way Facebook and other sites helped amplify fake news was found to have had a profound impact on how people reacted to current events. So earlier this year, Facebook implemented a new system to mark inaccurate stories with a “disputed” tag to help alert readers to potentially false stories. Well it seems that was a mistake, too, because now Facebook is doing away with the disputed tags.
lvg  hcds  ethical_ai  transparency 
december 2017 by jaimoe
Facebook (Still) Letting Housing Advertisers Exclude… — ProPublica
After ProPublica revealed last year that Facebook advertisers could target housing ads to whites only, the company announced it had built a system to spot and reject discriminatory ads. We retested and found major omissions.
facebook  ethical_ai  hcds  algorithmic_bias  algorithmic_transparency 
december 2017 by jaimoe
Facebook Lets Advertisers Exclude Users by Race — ProPublica
Imagine if, during the Jim Crow era, a newspaper offered advertisers the option of placing ads only in copies that went to white readers.

That’s basically what Facebook is doing nowadays.

The ubiquitous social network not only allows advertisers to target users by their interests or background, it also gives advertisers the ability to exclude specific groups it calls “Ethnic Affinities.” Ads that exclude people based on race, gender and other sensitive factors are prohibited by federal law in housing and employment.
facebook  ethical_ai  algorithmic_bias  hcds 
december 2017 by jaimoe
People at Facebook Don’t Know How Facebook Works
Facebook is a vast and bewildering operation, working with visible and invisible data streams via opaque algorithms on a scale larger than humans can readily comprehend. Many of us have been baffled, for example, by the social network’s ability to figure out who we know in real life, as reflected by the suggestions that pop up in its “People You May Know” box.

That confusion, it’s now clear, extends to Facebook’s own communications department. Judging by my experiences reporting on the feature, even Facebook is confused about exactly how it works.
facebook  privacy  ethical_ai  hcds  recsys_eval  auditing 
december 2017 by jaimoe
Ethics in data project design: It’s about planning - O'Reilly Media
When I explain the value of ethics to students and professionals alike, I refer it as an “orientation.” As any good designer, scientist, or researcher knows, how you orient yourself toward a problem can have a big impact on the sort of solution you develop—and how you get there. As Ralph Waldo Emerson once wrote, “perception is not whimsical, but fatal.” Your particular perspective, knowledge of, and approach to a problem shapes your solution, opening up certain paths forward and forestalling others.

Data-driven approaches to business help optimize measurable outcomes—but the early planning of a project needs to account for the ethical (and in many cases, the literal) landscape to avoid ethically treacherous territory. Several recent cases in the news illustrate this point and show the type of preparation that enables a way to move forward in both a data-driven and ethical fashion: Princeton Review’s ZIP-code-based pricing scheme, which turned out to unfairly target Asian-American families, and Amazon’s same-day-delivery areas, which neglect majority-Black neighborhoods.
data  ethics  hcds  ethical_ai  data_science 
december 2017 by jaimoe
My vision of a possible strategy. – Christian Kleineidam – Medium
Given the recent growth in the number of items inside Wikidata there was the idea voiced that we might need tools for dealing with more data. One effect that the recent FactGrid workshop had on me was the appearance that different people have quite a different idea of how Wikidata works despite them spending serious amounts of time with it.
wikidata  hcds  structured_data  wikipedia 
december 2017 by jaimoe
Passing Notebooks in Class: West Big Data Innovation Hub’s UC Berkeley and UW partner with Microsoft on shared data science infrastructure | Division of Data Sciences
In a similar vein, the new DATA 512: Human-Centered Data Science(link is external) (link is external) course at UW aims to enable reproducible workflows and foster community dialogue. “I expect that Jupyter notebooks and the course infrastructure we are piloting for the first time will be great teaching and communication tools for reinforcing best practices and supporting experimentation,” notes instructor Jonathan T. Morgan, Senior Design Researcher at the Wikimedia Foundation. The notebooks will help guide students in sharing the story of their research using various tools, from code and data to prose and visualizations, with the goal of making the projects more accessible and impactful for a wider variety of audiences.
hcds  berkeley  data_science  blog 
december 2017 by jaimoe
Testing AI concepts in user research – uxdesign.cc
step by step workflow for prototyping and user testing AI-driven experiences (seems to focus on chatbots)
aiux  machine_learning  hcds  prototype  ux  user_experience 
november 2017 by jaimoe
YouTube's Creepy Kid Problem Was Worse Than We Thought
YouTube says that it’s removed ads from some 2 million videos and over 50,000 channels that featured disturbing content aimed at kids. Some of that content actually exploited children in videos. And while we’ve long known that YouTube struggles to keep bad stuff off of its platform, the fact that tens of thousands of channels involved doing bad things to children feels chilling.
hcds  ethical_ai 
november 2017 by jaimoe
It’s time to stop trusting Google search already - The Verge
Last weekend, in the hours after a deadly Texas church shooting, Google search promoted false reports about the suspect, suggesting that he was a radical communist affiliated with the antifa movement. The claims popped up in Google’s “Popular on Twitter” module, which made them prominently visible — although not the top results — in a search for the alleged killer’s name. Of course, the was just the latest instance of a long-standing problem: it was the latest of multiple similar missteps. As usual, Google promised to improve its search results, while the offending tweets disappeared. But telling Google to retrain its algorithms, as appropriate as that demand is, doesn’t solve the bigger issue: the search engine’s monopoly on truth.
algorithmic_bias  search  hcds  ethical_ai 
november 2017 by jaimoe
Gender by Wikipedia Language | WHGI
This plot shows the top 40 Wikipedia Languages (by number of gendered biographies), and compares their number of gendered biographies to female percentage of those biographies. This cutoff is arbitrary for the sake of clearly visualizing the distribution across major Wikipedia languages. For a comprehensive coverage, one can fetch the complete data from the data repository.
wigi  gender_gap  wikipedia  tools__addons_and_dashboards  wmflabs  research  hcds 
november 2017 by jaimoe

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