In an effort to clean up my reading list, this page catalogues papers that caught my eye but that I never got around to reading.

I’d love to read all of these some day; like I said, they caught my eye at least once before. But, being realistic with myself, I think it’s important to accept that I can’t get around to everything; I have limited time and energy. Rather than maintain an indefinite list of “laters,” I choose to put these papers to rest on this page.

I liken this to closing my browser tabs. If something is truly engaging, I’ll come back to it later. But for now, I am accepting that I have no plans to read these, as great as they probably are.

CHI 2020

When looking for papers to read, I used the following sources:

And these all looked interesting to me:

ICWSM 2020

I identified these by looking through the proceedings at:

Communal Quirks and Circlejerks: A Taxonomy of Processes Contributing to Insularity in Online Communities by Kimberley Allison, Kay Bussey

Higher Ground? How Groundtruth Labeling Impacts Our Understanding of Fake News about the 2016 U.S. Presidential Nominees by Lia Bozarth, Aparajita Saraf, Ceren Budak

Toward a Better Performance Evaluation Framework for Fake News Classification by Lia Bozarth, Ceren Budak

No Robots, Spiders, or Scrapers: Legal and Ethical Regulation of Data Collection Methods in Social Media Terms of Service by Casey Fiesler, Nathan Beard, Brian C. Keegan

Towards Measuring Adversarial Twitter Interactions against Candidates in the US Midterm Elections by Yiqing Hua, Thomas Ristenpart, Mor Naaman

Detecting Troll Behavior via Inverse Reinforcement Learning: A Case Study of Russian Trolls in the 2016 US Election by Luca Luceri, Silvia Giordano, Emilio Ferrara

The Structure of U.S. College Networks on Facebook by Jan Overgoor, Bogdan State, Lada A. Adamic

Other papers

I don’t plan to read these any time soon; but again, these all looked interesting at some point.

On the Utility of Learning about Humans for Human-AI Coordination from BAIR, NeurIPS 2019

Towards fairer datasets: filtering and balancing the distribution of the people subtree in the ImageNet hierarchy from FAT* 2020

Gelman: progress from the past decade is a list of tons of papers on his blog

Beyond near and long term: something about AI ethics and society from Import AI

The stealth media? Groups and targets behind divisive issue campaigns on Facebook from Network Propaganda

Weaponizing the digital influence machine: the political perils of online ad tech on digital political advertising

ICML papers

From the participatory design workshop:

  • Fairness, Equality, and Power in Algorithmic Decision-Making
  • Measuring Non-Expert Comprehension of Machine Learning Fairness Metrics (Encore: ICML 2020)
  • The Hidden Assumptions Behind Counterfactual Explanations and Principal Reasons (Encore: FAccT 2020)
  • Metric-Free Individual Fairness in Online Learning

Blog posts, websites, etc.

Most things on this course project page, found from the author of the Skynet Today article

The coming software apocalypse from The Atlantic. I’ve already read this, but worth revisiting.

FAIR blog post on insta recommendations, from Miranda

An epidemic of AI misinformation from Data Elixir

Overcooked blog post by BAIR, from Judah