I2SC Lecture Series

Policy Impact: From AI Regulation to Academic Inclusion

This talk examines how policies affect people across multiple domains. I analyze surveillance loopholes in the EU AI Act introduced by German regulators that potentially compromise civil liberties. The discussion then critiques academic name-change policies that create unnecessary barriers for transgender and queer scholars. Finally, I evaluate academic publishing frameworks that exclude underrepresented communities and propose practical reforms to create more equitable spaces. Throughout, I demonstrate how seemingly neutral policies can cause harm when developed without input from marginalized communities. 

TBD

TBD

Six Degrees of Slavery:  Measuring Slave-Ownership and Elite Persistence in Britain

Although the legacies of slavery in Britain have received increasing attention in recent years, little evidence exists on how such legacies have shaped the country’s political elite. This project seeks to quantify and chart these ties over time, using a novel computational technique harnessing Wikidata, a knowledge graph closely connected to Wikipedia, as a means of operationalizing historical proximity between individuals. This technique enables the measurement of personal proximity to slavery, including via familial and social connections. Aggregating this data for politicians across a series of historical parliaments demonstrates how links to slavery persisted via dynastic and other social ties into the 20th Century and the extent to which ties to slavery still exist among contemporary politicians. We demonstrate how slavery-backed networks have persisted more thoroughly in the Conservative Party and the House of Lords than in other institutions, and explore the robustness of this persistence to historical periods of reform. The results emphasize the extent to which slavery and its legacies continue to play an active role in British politics, as well as offering an efficient and reliable new method for measuring social proximity using online data. 

TBD

TBD

How to reinforce democratic values in language systems? 

Two key values in democratic societies are to facilitate easy access to a broad range of information, and in parallel, to foster an environment where a diverse range of opinions can thrive. In this presentation, I will talk about two sides of my research that touch on these aspects: investigating how to diversify news recommendations and understanding the stakes of accessing information through language systems such as ChatGPT. I will present ways to provide users with different perspectives and its challenges. Finally, I will present initial results on how users look for information via language systems in contrast with traditional web search engines.

Is machine learning a Woke, Neutral, or Fascist technic?

Since the mid-2010s there have been concerns about the social biases that are embedded in the representational space of machine learning models which has led to a flourishing field of addressing the social harms of machine learning. This, in turn, has led to conflicting claims of machine learning being discriminatory, "woke," and value-neutral. In this lecture I will discuss the history of natural language processing and machine learning; and examine methods for developing machine learning tools for human and social data. I argue that claims of wokeness or even neutrality inherently misunderstand (a) the methods used by machine learning and (b) the social and historical contexts under which machine learning technologies are developed. Finally, I will close with a discussion on how machine learning infrastructures maintain and reify colonial legacies of displacing costs onto colonial bodies while centralizing benefits in the heart of the empire. 

Society-centered AI: An Integrative Perspective on Algorithmic Fairness

In this talk, I will share my never-ending learning journey on algorithmic fairness. I will give an overview of fairness in algorithmic decision-making, reviewing the progress and wrong assumptions made along the way, which have led to new and fascinating research questions. Most of these questions remain open to this day and become even more challenging in the era of generative AI. Thus, this talk will provide only a few answers but many open challenges to motivate the need for a paradigm shift from owner-centered to society-centered AI. With society-centered AI, I aim to bring the values, goals, and needs of all relevant stakeholders into AI development as first-class citizens to ensure that these new technologies are at the service of society.