Weizenbaum Journal of the Digital Society

Permanent URI for this collectionhttps://www.weizenbaum-library.de/handle/id/1115

The Weizenbaum Journal of the Digital Society (WJDS) is an interdisciplinary, diamond open access journal that investigates processes of digitalization in society from the perspectives of different research areas.

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Subject: search.filters.subject.004 Informatik

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Now showing 1 - 9 of 9
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    AI Literacy for the Common Good
    (Weizenbaum Institute, 2024-07-16) Ullrich, Stefan; Messerschmidt, Reinhard
    Artificial Intelligence (AI) does not provide solutions to pressing social questions, such as those pertaining to a peaceful, sustainable, and socially acceptable world. However, when employed in a purposeful and critically reflective manner, it can assist in formulating more effective inquiries that can enable a better understanding of the terms “AI” and “common good.” Through implementation in response to sustainability issues and given its potential as an inclusive technology, AI could be a powerful and useful tool for the common good. Despite the possibility of useful machine learning applications in terms of a positive cost-benefit calculation for its life cycle energy and resources, the majority of AI is far too energy-hungry for model training and to scale inferences. Despite the considerable variation observed in terms of certain aspects, it is evident that AI is currently neither sustainable in itself nor primarily used for sustainability purposes to address the grand challenges of global society in a world characterized by rapid acceleration. This demands a critical understanding of how AI systems work to enable society to decide upon the areas in which we should, can, or even definitely must not use AI. Based on the UNESCO Framework for AI Competency and the Dagstuhl Declaration of the German Informatics Society, we advocate for a type of critical AI literacy that can be best taught through practical use, that is, “learning by making.” This approach leads to a concise overview of existing options that facilitate a more reflective approach to using and understanding AI, including its potential and limitations. We conclude with a practical example.
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    Too Far Away from the Job Market – Says Who? Linguistically Analyzing Rationales for AI-based Decisions Concerning Employment Support
    (Weizenbaum Institute, 2024-07-03) Berman, Alexander
    This paper describes an AI-based decision-support system deployed by the Swedish Public Employment Service to assist decisions concerning jobseekers’ enrolment in an employment support initiative. Informed by previous research concerning explanations in relation to trust, appealability, and procedural fairness, as well as jobseekers’ needs and interests in relation to algorithmic decision-making, the study linguistically analyses the extent to which the system enables affected jobseekers to understand the basis of decisions and to appeal or take other actions in response to automated assessments. The study also analyses the degree to which rationales behind decisions accurately reflect the actual decision-making process. Several weaknesses in these regards are highlighted, largely resulting from the opacity of the statistical model and the linguistic choices behind the design of explanations. Potential strategies for increasing the explainability of the system as a means to meet the needs and interests of affected jobseekers are also discussed. More broadly, the study contributes to a better understanding of how the linguistic design of AI explanations can affect normative dimensions, such as trust and appealability.
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    Comparative Analysis of the Essential Factors for the Adoption of Massive Open Online Courses in Higher Education of a Developing Country: Pre and Post COVID-19
    (Weizenbaum Institute, 2024-06-27) Chavoshi, Amir; Jandaghi Shahi, Sara
    Although massive open online courses (MOOCs) offer numerous benefits to students, developing countries are still in the early stages of promoting their implementation. This study aims to investigate how the factors influencing MOOC adoption have evolved in response to the increased usage of online courses during the pandemic. The proposed model is based on the Technology Acceptance Model, and research hypotheses are presented based on six different factors: Perceived Usefulness, Perceived Ease of Use, Openness, Self-Efficacy, Quality of Service, and Reputation of the MOOC Provider. To test these hypotheses two surveys were conducted, one before and one after the COVID-19 period. Analyzing the data from these two time periods provides insight into the level of influence each of these factors has had on increased MOOC usage. Survey data was tested using the novel Partial Least Squares-Artificial Neural Network approach, which can effectively analyze complex human decisions. The findings indicate that Perceived Usefulness was the most influential factor in the adoption of MOOCs both before and after the COVID-19 pandemic. Interestingly, changes have been observed in the impact of Openness between the pre-pandemic and post-pandemic periods.
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    Unlocking AI’s Potential: Human Collaboration as the Catalyst
    (Weizenbaum Institute, 2024-05-27) Buxmann, Peter; Ellenrieder, Sara
    Rapid advances in artificial intelligence (AI) have fueled high expectations for the technology’s potential to fundamentally transform our economy and society through automation. However, given the inscrutability and, sometimes, susceptibility to error of AI systems, we argue that the focus should shift towards fostering effective human-AI collaboration rather than pursuing automation alone. In this context, system decisions must be made available to decision-makers in an explainable and understandable manner, as further required by the EU’s recently passed AI Act. Research shows that there is potential for humans to learn from explainable AI systems and improve their own performance over time. Meanwhile, in addition to enabling humans to benefit from working with AI systems on various everyday tasks, such collaboration ensures the safe and reliable use of AI systems, especially in high-risk areas such as medicine, where human oversight remains paramount.
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    Promises and Myths of Artificial Intelligence
    (Weizenbaum Institute, 2024-02-19) Hirsch-Kreinsen, Hartmut; Krokowski, Thorben
    The development dynamics of any new technology are usually associated with promises of its special performance and completely new application possibilities. This is especially true for artificial intelligence (AI), prompting this contribution to inquire into which particular special features the technology promises. However, the imprecise rhetoric of that promise becomes apparent. Although it appears simple, clear, and convincing, it is fundamentally difficult to dispute and introduces multitudes of ambiguity, relying on fuzzy conceptual metaphors, very unspecific assessments, implicit misconceptions, technological determinism, and exaggerations of the future opportunities AI offers for economic and social progress. Ultimately, the promises of AI nourish their lasting persuasive power with notions from the old myth of the intelligent machine.
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    The Limits of Computation: Joseph Weizenbaum and the ELIZA Chatbot
    (Weizenbaum Institute, 2023) Berry, David M.
    Developed in the 1960s by Joseph Weizenbaum, ELIZA is arguably among the most influential computer programs ever written. ELIZA – and especially its most famous persona DOCTOR – continues to inspire programmers, wider discussions about AI, and imitations. This original ancestor of all conversa-tional interfaces and chatbots maintains a special fascination for engineers, historians, and philosophers of artificial intelligence (AI) and computing. With its ability to produce human-like responses using a relatively small amount of computer code, ELIZA has paved the way for a multitude of similar programs. These take the form of conversation agents and other human-computer inter-faces that have inspired entire new fields of study within computer science. This paper examines Weizenbaum’s contribution to AI and considers his more critical writings in the context of contemporary developments in generative AI, such as ChatGPT. Examining how ELIZA has been discussed can provide insights into current debates surrounding machine learning and AI.
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    The Image of Man in Artificial Intelligence: A Conversation with Joseph Weizenbaum
    (Weizenbaum Institute, 2023) Pörksen, Bernhard
    Joseph Weizenbaum fled from the Nazis to the USA, later studying mathematics and becoming a professor of computer science at the Massachusetts Institute of Technology (MIT). He became famous for the Eliza program, which simulates a psychotherapist who—apparently at least—tries to understand its client psychologically, and which became a very early example of chatbots simulating human language. His research led Weizenbaum to a critical attitude toward the possibilities, limits and uses of computers. His main work, “The Power of Computers and the Powerlessness of Reason”, dealt with the effects of computers on the world of human experience—at that time a new and, in its explosiveness, still largely unknown topic. This text makes available in English for the first time an interview with Joseph Weizenbaum conducted in 1998. The interview focuses on the development of artificial intelligence, arguments about analogies between human and artificial intelligence, and perspectives on critical thinking about the relationship between humans and computers.
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    How Should We Regulate AI?
    (Weizenbaum Institute, 2023) Zech, Herbert
    In the last decade, artificial intelligence (AI) – which describes the mimicking of human intelligence using technology – has made significant progress. Driven by algorithmic design, computing power and large amounts of training data, machine learning has transformed information technology, which can now augment and replace human intelligence, something that was thought impossible just a decade ago. In 2018, the European Commission labelled AI a transformative technology with the potential to raise new ethical and legal questions. Now, with the advent of generative AI, which can create content that could previously only be created by human beings, this potential has become visible to the wider public. At the same time, the European Commission’s proposal for an Artificial Intelligence Act (AIA) (which is now entering the final legislative stage) indicates its intentions to regulate AI. This comment wishes to highlight some key points regarding the regulation of artificial intelligence and, in doing so, comment on the current proposal.
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    Making Arguments with Data: Resisting Appropriation and Assumption of Access/Reason in Machine Learning Training Processes
    (Weizenbaum Institute, 2023) Savic, Selena; Martins, Yann Patrick
    This article presents an approach to practicing ethics when working with large datasets and designing data representations. Inspired by feminist critique of technoscience and recent problematizations of digital literacy, we argue that machine learning models can be navigated in a multi-narrative manner when access to training data is well articulated and understood. We programmed and used web-based interfaces to sort, organize, and explore a community-run digital archive of radio signals. An additional perspective on the question of working with datasets is offered from the experience of teaching image synthesis with freely accessible online tools. We hold that the main challenge to social transformations related to digital technologies comes from lingering forms of colonialism and extractive relationships that easily move in and out of the digital domain. To counter both the unfounded narratives of techno-optimismand the universalizing critique of technology, we discuss an approachto data and networks that enables a situated critique of datafication and correlationism from within.
The WJDS is a Diamond Open Access journal, with content open to anyone to read and reuse. It is free of any publication fees or charges to either author or reader. All contributions are published under a Creative Commons (CC BY 4.0) license. Publication rights remain with the authors, with unlimited use and reuse of articles.