Reading List

289 words self,

This is a page of things I’m hoping to read “soon” (for some value of soon). It’s some cross between a digital bookshelf and public bookmarks, where I drop papers that cross my radar or blog posts, talks, or other ideas.

Some of these I’ve printed out and carry around with me. Others are unlikely to ever be read because they’re so far out of my areas of expertise or interest. While this page is mostly for my own reference, it also pretty broadly shows the types of work I’m interested in.


Generalizable and robust TV advertising effects linked from the correspondent

Lessons from Archives: Strategies for Collecting Sociocultural Data in Machine Learning by Eun Seo Jo & Timnit Gebru (from FAT* 2020)

Exposure to ideologically diverse news and opinion on Facebook from Science - study out of Facebook research (short)

The small effects of political advertising are small regardless of context, message, sender, or receiver: Evidence from 59 real-time randomized experiments tl;dr ads bad don’t work

Fairness and Accountability Design Needs for Algorithmic Support in High-Stakes Public Sector Decision-Making

Auditing local news presence on Google News (get the PDF from, Twitter)

Datasheets for datasets

Election emails project

Learning Representations of Hierarchical Slates in Collaborative Filtering - RecSys 2020, out of Netflix

Characterizing Communication Patterns between Audiences and Newsbots

Lots of papers from Koustuv Saha’s page

NeurIPS keynote

Anticipatory ethics and the role of uncertainty from NeurIPS workshop

Extracting training data from large language models (Twitter; on GPT-2)

Data Leverage: A Framework for Empowering the Public in its Relationship with Technology Companies (Twitter; FAccT 2021)

Where Responsible AI meets Reality: Practitioner Perspectives on Enablers for shifting Organizational Practices (Twitter; CSCW 2021)


See Reading List Archive #1.