No AI After Auschwitz? Bridging AI and Memory Ethics in the Context of Information Retrieval of Genocide-Related Information

The growing application of artificial intelligence (AI) in the field of information retrieval (IR) affects different domains, including cultural heritage. By facilitating organisation and retrieval of large volumes of heritage-related content, AI-driven IR systems inform users about a broad range of historical phenomena, including genocides (e.g. the Holocaust). However, it is currently unclear to what degree IR systems are capable of dealing with multiple ethical challenges associated with the curation of genocide-related information. To address this question, this chapter provides an overview of ethical challenges associated with the human curation of genocide-related information using a three-part framework inspired by Belmont criteria (i.e. curation challenges associated with respect for individuals, beneficence and justice/fairness). Then, the chapter discusses to what degree the above-mentioned challenges are applicable to the ways in which AI-driven IR systems deal with genocide-related information and what can be the potential ways of bridging AI and memory ethics in this context.Comment: 17 page

Algorithmic Auditing, the Holocaust, and Search Engine Bias

The ongoing digitisation of individual and collective remembrance results in the growing role of algorithmic curation of information about the past by web search engines. This process, however, raises multiple concerns, in particular considering that performance of complex algorithmic systems, including the ones dealing with web search, is often subjected to bias. In this guest post, Mykola Makhortykh shares his experience of studying biases in visual representation of the Holocaust across six major search engines, and discusses its implications for Holocaust remembrance

Animating the subjugated past: Digital greeting cards as a form of counter-memory

This article discusses how popular culture products – digital greeting cards – interact with hegemonic historical narratives in the context of war remembrance. It employs the Foucauldian concept of counter-memory to analyse how user-generated mnemonic content interacts with historical power relations. Using content analysis to examine a sample of amateur greeting cards, the authors investigate how these cultural products engage with official and counter-official memory practices in Russia related to the Soviet victory in the Second World War. Specifically, the article explores how different visual elements are employed to (de)construct specific narratives about the Soviet victory and it discusses how the use of computer graphics, in particular animation, influences the potential role of greeting cards as a means of resurrecting the subjugated past

There can be only one truth: Ideological segregation and online news communities in Ukraine

The paper examines ideological segregation among Ukrainian users in online environments, using as a case study partisan news communities on Vkontakte, the largest online platform in post-communist states. Its findings suggest that despite their insignificant numbers, partisan news communities attract substantial attention from Ukrainian users and can encourage the formation of isolated ideological cliques – or ‘echo chambers’ – that increase societal polarisation. The paper also investigates factors that predict users’ interest in partisan content and establishes that the region of residence is the key predictor of selective consumption of pro-Ukrainian or pro-Russian partisan news content

Sociotechnical imaginaries of algorithmic governance in EU policy on online disinformation and FinTech

Datafication and the use of algorithmic systems increasingly blur distinctions between policy fields. In the financial sector, for example, algorithms are used in credit scoring, money has become transactional data sought after by large data-driven companies, while financial technologies (FinTech) are emerging as a locus of information warfare. To grasp the context specificity of algorithmic governance and the assumptions on which its evaluation within different domains is based, we comparatively study the sociotechnical imaginaries of algorithmic governance in European Union (EU) policy on online disinformation and FinTech. We find that sociotechnical imaginaries prevalent in EU policy documents on disinformation and FinTech are highly divergent. While the first can be characterized as an algorithm-facilitated attempt to return to the presupposed status quo (absence of manipulation) without a defined future imaginary, the latter places technological innovation at the centre of realizing a globally competitive Digital Single Market

Blame It on the Algorithm? Russian Government-Sponsored Media and Algorithmic Curation of Political Information on Facebook

Previous research highlighted how algorithms on social media platforms can be abused to disseminate disinformation. However, less work has been devoted to understanding the interplay between Facebook news curation mechanisms and propaganda content. To address this gap, we analyze the activities of RT (formerly, Russia Today) on Facebook during the 2020 U.S. presidential election. We use agent-based algorithmic auditing and frame analysis to examine what content RT published on Facebook and how it was algorithmically curated in Facebook News Feeds and Search Results. We find that RT’s strategic framing included the promotion of anti-Biden leaning content, with an emphasis on antiestablishment narratives. However, due to algorithmic factors on Facebook, individual agents were exposed to eclectic RT content without an overarching narrative. Our findings contribute to the debate on computational propaganda by highlighting the ambiguous relationship between government-sponsored media and Facebook algorithmic curation, which may decrease the exposure of users to propaganda and at the same time increase confusion

You are how (and where) you search? Comparative analysis of web search behavior using web tracking data.

In this article, we conduct a comparative analysis of web search behaviors in Switzerland and Germany. For this aim, we rely on a combination of web tracking data and survey data collected over a period of 2 months from users in Germany (n = 558) and Switzerland (n = 563). We find that web search accounts for 13% of all desktop browsing, with the share being higher in Switzerland than in Germany. In over 50% of cases users clicked on the first search result, with over 97% of all clicks being made on the first page of search outputs. Most users rely on Google when conducting searches, with some differences observed in users' preferences for other engines across demographic groups. Further, we observe differences in the temporal patterns of web search use between women and men, marking the necessity of disaggregating data by gender in observational studies regarding online information seeking behaviors. Our findings highlight the contextual differences in web search behavior across countries and demographic groups that should be taken into account when examining search behavior and the potential effects of web search result quality on societies and individuals

Can Filter Bubbles Protect Information Freedom? Discussions of Algorithmic News Recommenders in Eastern Europe

The increasing use of recommender systems to provide personalized news delivery influences media systems worldwide. Using different data sources to predict what content will be interesting for specific readers, recommender systems can better accommodate individual information needs, but also raise concerns about potential audience fragmentation. However, current assessments of the effects of news personalization are predominantly based on observations from Western democracies. This Western-centric approach raises concerns about these assessments’ applicability to other contexts, in particular non-democratic ones, and brings to question the influence of prevalent Western conceptualisations of news personalization (e.g., filter bubbles) on attitudes towards it in non-Western countries. To address this gap, we scrutinize discussions of the promises and threats of news personalization in countries characterized by limited press freedom: Belarus, Russia and Ukraine. Using document analysis, we examine how three categories of actors—academics, journalists and IT specialists—discuss news personalization and the ways it can affect the public sphere. Through our analysis we uncover how Western conceptualisations of news personalization interact with discussions about it in non-democratic media systems and scrutinize whether existing concerns about personalization are applicable to non-Western contexts

#Azovsteel: Comparing qualitative and quantitative approaches for studying framing of the siege of Mariupol on Twitter

Social media platforms play a major role in shaping how the public around the world perceives contemporary wars, including the ongoing Russian invasion of Ukraine. However, there are multiple challenges in studying how exactly these platforms represent violence and what aspects of it are made more salient by their users. One of these challenges concerns the broad range of qualitative and quantitative approaches used to study platform-based war framing and their different capabilities in tackling the large volume of available data. To address this challenge, the authors compare the performance of qualitative and quantitative approaches – i.e. qualitative content analysis and topic modelling – for studying how one of the key episodes of the Russian–Ukrainian war, the siege of Mariupol in 2022 was framed on Twitter over time. Their findings demonstrate that both approaches show the prevalence of human interest and conflict frames that aligns with earlier research on war framing in journalistic media. At the same time, they observe differences in the estimated visibility of less common frames, such as morality and responsibility frames, depending on what method is used

How transparent are transparency reports? Comparative analysis of transparency reporting across online platforms

Over the last decade, transparency reports have been adopted by most large information technology companies. These reports provide important information on the requests tech companies receive from state actors around the world and the ways they respond to these requests, including what content the companies remove from platforms they own. In theory, such reports shall make inner workings of companies more transparent, in particular with respect to their collaboration with state actors. They shall also allow users and external entities (e.g., researchers or watchdogs) to assess to what extent companies adhere to their own policies on user privacy and content moderation as well as to the principles formulated by global entities that advocate for the freedom of expression and privacy online such as the Global Network Initiative or Santa Clara Principles. However, whether the current state of transparency reports actually is conducive to meaningful transparency remains an open question. In this paper, we aim to address this through a critical comparative analysis of transparency reports using Santa Clara Principles 2.0 (SCP 2.0) as the main analytical framework. Specifically, we aim to make three contributions: first, we conduct a comparative analysis of the types of data disclosed by major tech companies and social media platforms in their transparency reports. The companies and platforms analyzed include Google (incl. YouTube), Microsoft (incl. its subsidiaries Github and LinkedIn), Apple, Meta (prev. Facebook), TikTok, Twitter, Snapchat, Pinterest, Reddit and Amazon (incl. subsidiary Twitch). Second, we evaluate to what degree the released information complies with SCP 2.0 and how it aligns with different purposes of transparency. Finally, we outline recommendations that could improve the level of transparency within the reports and beyond, and contextualize our recommendations with regard to the Digital Services Act (DSA) that received the final approval of the European Council in October 2022