"Queere Betriebssysteme anwenden" (talk in German) - Elisa Linseisen (University of Hamburg)

UNFORTUNATELY THE LECTURE IS CANCELED DUE TO ILLNESS!
AN ALTERNATIVE DATE WILL BE ANNOUNCED SOON.

(19 June 2024: 15:00-16:30 CEST, hybrid)
Room: E - 1.022
Zoom: https://tuhh.zoom.us/j/84912361967?pwd=L1dnZWFIVVhaNDRvSElPZXZObTN4QT09

Abstract: 2016 veröffentlicht eine Gruppe von (Medien-)Wissenschaftler*innen, Theoretiker*innen und Künstler*innen ein IT-Handbuch mit dem Titel „Queer OS. A User’s Manual“. In diesem führen die Autor*innen spekulativ und von Wünschen geleitet aus, wie Computertechnologie diskriminierungsfrei eingesetzt werden kann. Der leitenden Frage des Manuals, nämlich wie Computertechnologie aussehen würde, die auf einem queeren Betriebssystem, einem Queer OS, läuft, möchte ich in meinem Vortrag mit dem Konzept der „App(lication)“ begegnen. App(lication) - die (computertechnische) Anwendung ermöglicht es, so meine These, Medientechnik in ihrer Verschränkung mit Medienkultur zu erfassen und damit die vergeschlechtlichten, rassifizierten, ableistischen und klassenbezogenen Dimensionen des Computings aufzuzeigen.

Elisa Linseisen is Professor for digital and audiovisual media at the Institute for Media and Communication at the University of Hamburg. Her research focuses on the aesthetics and episteme of digital media. For more information: https://elisalinseisen.com

"A Minimalist Account of the Right to Explanation" - Thomas Grote (University of Tübingen) (joint work with N. Paulo)

08 May 2024: 16:00-17:30 CEST (hybrid)
Room: E - 1.022

Abstract. Critiques of opaque machine learning models, used to guide consequential decisions, are getting traction in moral philosophy. According to the received view, the legitimacy of algorithmic decisions is threatened on the grounds that they undermine the rights of decision-subjects to informed self-advocacy (Vredenburgh, 2022). The appropriate mitigation strategy, in turn, is to grant decision-subjects a right to explanation (via explanation of the model output). This paper challenges the received view. More precisely, we have two objectives. The first is a critical one: we argue that existing accounts of the right to explanation prove unsatisfactory to ameliorate concerns about the moral illegitimacy of algorithmic decision-making. This is in particular due to their individualist framing, overburdening decision-subjects in a two-fold way: (i) the relevant explanations are likely to be epistemically over-demanding since their correct interpretation will require a combination of domain-knowledge and statistical proficiency that cannot be presumed for laypersons; and (ii) shifting the task to detect inadequacies to decision-subjects makes scrutinizing explanations very costly for them. Weakening the epistemic requirements of the right to explanation also lays the ground for our positive contribution. If providing explanations to decision-subjects turns out to be an inadequate amelioration strategy for opaque algorithmic decision-making, alternative moral guardrails are necessary. We outline the basic features of our proposal by discussing literature on model auditing in machine learning.

Thomas Grote is a research fellow at the Cluster of Excellence: “Machine Learning: New Perspectives for Science” at the University of Tübingen. He is also Co-PI in a project on certification and safety of ML models in healthcare, funded by the Carl-Zeiss Stiftung.

"On the Quest for Effectiveness in Human Oversight" - Kevin Baum (CERTAIN, DFKI)

10 April 2024: 10:00 CEST (hybrid)
Room: E - 1.022

Abstract: Human oversight is currently discussed as a potential safeguard to counter some of the negative aspects of high-risk AI applications. This prompts a critical examination of the role and conditions necessary for what is prominently termed effective or meaningful human philosophical, and technical domains. Based on the claim that the main objective of human oversight is risk mitigation, we propose a viable understanding of effectiveness in human oversight: for human oversight to be effective, the human overseer has to have (a) sufficient causal power with regards to the system and its effects, (b) suitable epistemic access to relevant aspects of the situation, (c) self-control over their own actions, and (d) fitting intentions for their role. Furthermore, we argue that this is equivalent to saying that a human overseer is effective if and only if they are morally responsible and have fitting intentions. Against this backdrop, we suggest facilitators and inhibitors of effectiveness in human oversight when striving for practical applicability and scrutinize the upcoming AI Act of the European Union – in particular Article 14 on Human Oversight – as an exemplary regulatory framework in which we study the practicality of our understanding of effective human oversight.

Kevin Baum is a philosopher and computer scientist. He is currently head of the Center for European Research in Trusted AI (CERTAIN) at the German Research Center for Artificial Intelligence (DFKI), one of the six German competence centers for AI. He is part of the NGO Algoright e.V., a think tank for good digitalization and interdisciplinary science communication. In his talk, Kevin will present current interdisciplinary work from the Center for Perspicuous Computing (CPEC), to which he is associated.

Do Large Language Models Have Credences? - Geoff Keeling (Google)

28 February 2024, 16:00 - 17:30 (CET) (online)

Abstract: Do Large Language Models (LLMs) have credences or degrees of belief? This question matters because a growing body of empirical research aims at quantifying LLM confidence in propositions with downstream implications for calibrating user trust in LLM assertions and combatting LLM-generated misinformation. Here an important question is whether techniques for quantifying confidence in LLMs are measuring degrees of belief on the part of the LLM; and if not, what is being measured and how it relates to credences. These questions are especially significant in relation to empirical studies which compare LLM confidence scores with human degrees of belief. In this paper we argue against the view that LLMs have credences. We consider three plausible accounts of what makes it the case that an LLM has a credence in a proposition: the reported confidence view, the output probabilities view, and the logits view. We argue that each account fails to adequately capture what it means to have a credence. The upshot is to clarify the interpretation of quantitative metrics for LLM confidence by providing a philosophical basis for denying that LLMs have credences. In doing so we not only put question to empirical comparisons between measurements of LLM confidence and reported degrees of belief in humans, but also orient discourse on confidence measurement in LLMs towards a non-mentalistic interpretation of confidence measures.

Bio: Geoff Keeling is a senior research scientist at Google, specialising in machine learning ethics. Prior to this role, Geoff served as a bioethicist at Google Health. His academic background includes a postdoctoral position at Stanford University, where he was part of the Institute for Human-Centered AI and the McCoy Family Center for Ethics in Society, and at the Leverhulme Centre for the Future of Intelligence at the University of Cambridge.

"Ubuntu as our Pathway to Inner Development" - Wakanyi Hoffman (The New Institute, Hamburg)

07 December 2024, 16:00 - 17:30  

Venue: Institute for Ethics in Technology, TUHH. Am Schwarzenberg Campus 3, 21073 Hamburg. Building E, 1st floor.

Wakanyi Hoffman, Research Fellow at The New Institute Hamburg, explores the transformative concept of Ubuntu and its pivotal role in shaping our approach to the climate and moral crises facing our world. In a world intricately woven with diverse narratives, Africa's rich heritage presents the profound concept of "Ubuntu" - a philosophy emphasising our interconnected humanity. Ubuntu, a term that resonates beyond mere words, is encapsulated in the African ethos as "I am because we are." This concept highlights the interconnectedness of all life and the belief that our individual and collective well-being are inextricably linked.

Popularised by Archbishop Desmond Tutu in post-apartheid South Africa, Ubuntu serves as a unifying cry across various African cultures. Its essence lies in the ethical principles of survival, solidarity, compassion, respect, dignity, and the pivotal concept of reciprocity. Reciprocity, or treating all life as we wish to be treated, is a universal principle found in numerous disciplines and indigenous worldviews.

Hoffman delves into the three levels of inner development under Ubuntu: Independence, Interdependence, and Interconnectedness. These stages guide us toward a deeper understanding of our role in the natural world and emphasise the need for a new moral framework in addressing the current climate and inner climate crises.

This talk is not just a presentation of an idea; it's an invitation to embrace a new operating system, a logic of the heart, that aligns with the shared principles of Ubuntu and reciprocity.