-
Springer, M.: Schwarzer Schwan im Internet (2020)
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- Source
- Spektrum der Wissenschaft. 2020, H.7, S.29
-
Müller, P.: Text-Automat mit Tücken (2023)
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- Source
- Pirmasenser Zeitung. Nr. 29 vom 03.02.2023, S.2
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Jaeger, L.: Wissenschaftler versus Wissenschaft (2020)
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- Date
- 2. 3.2020 14:08:22
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Ibrahim, G.M.; Taylor, M.: Krebszellen manipulieren Neurone : Gliome (2023)
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- Spektrum der Wissenschaft. 2023, H.10, S.22-24
-
Kurz, C.: Womit sich Strafverfolger bald befassen müssen : ChatGPT (2023)
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- Abstract
- Ein Europol-Bericht widmet sich den Folgen von ChatGPT, wenn Kriminelle die Fähigkeiten des Chatbots für sich ausnutzen: Es drohe vermehrt Phishing und noch mehr Desinformation. Ein Problem für die Strafverfolgung könne auch automatisiert erzeugter bösartiger Quellcode sein.
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Meineck, S.: ¬Das Hype-Theater um moderne Chatbots : Olimpias Augen (2022)
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- Abstract
- Die Debatte um Künstliche Intelligenz und ChatGPT führt dramatisch in die Irre. In seiner Ringvorlesung für die Universität Erfurt fächert der Autor zehn Gefahren aktuell gehypter KI-Systeme auf und argumentiert: Nicht etwa intelligente Maschinen sind das Problem, sondern der menschliche Blick auf Technologie.
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Pekar, V.; Binner, J.; Najafi, H.: Early detection of heterogeneous disaster events using social media (2020)
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- Abstract
- This article addresses the problem of detecting crisis-related messages on social media, in order to improve the situational awareness of emergency services. Previous work focused on developing machine-learning classifiers restricted to specific disasters, such as storms or wildfires. We investigate for the first time methods to detect such messages where the type of the crisis is not known in advance, that is, the data are highly heterogeneous. Data heterogeneity causes significant difficulties for learning algorithms to generalize and accurately label incoming data. Our main contributions are as follows. First, we evaluate the extent of this problem in the context of disaster management, finding that the performance of traditional learners drops by up to 40% when trained and tested on heterogeneous data vis-á-vis homogeneous data. Then, in order to overcome data heterogeneity, we propose a new ensemble learning method, and found this to perform on a par with the Gradient Boosting and AdaBoost ensemble learners. The methods are studied on a benchmark data set comprising 26 disaster events and four classification problems: detection of relevant messages, informative messages, eyewitness reports, and topical classification of messages. Finally, in a case study, we evaluate the proposed methods on a real-world data set to assess its practical value.
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Jörs, B.: Wider eine Überschätzung der gegenwärtigen Leistungen der deutschsprachigen Informationswissenschaft : Keine fehlende Fundierung? Doch mit gesellschaftlicher Relevanz ausgestattet? (2020)
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- Abstract
- In einem aktuellen Beitrag von Open Password (#664, 19. November ) zu einer Veranstaltung des Berliner Arbeitskreises Information unter dem Titel "Zukunft der Informationswissenschaft. Hat die Informationswissenschaft eine Zukunft?" nimmt der Herausgeber des gleichnamigen Buches, Dr. Willi Bredemeier, die Rolle eines Berichterstatters ein. Vorgestellt werden die Inhalte eines Vortrages des Hamburger HAW-Referenten, Prof. Dr. Dirk Lewandowski, zum Thema: "Warum die Frage nach der Zukunft der Informationswissenschaft falsch gestellt ist". Dem Bericht darüber in Open Password wurde der Titel "Die Informationswissenschaft hat ein strukturelles, kein inhaltliches Problem. Ein Sechs-Punkte-Programm, um aus dem Status eines kleinen Faches herauszukommen" gegeben.
- Content
- Erwiderung auf: Lewandowski, D.: Die Informationswissenschaft hat ein strukturelles, kein inhaltliches Problem: Ein Sechs-Punkte-Programm, um aus dem Status eines kleinen Faches herauszukommen. In: Open Password. Nr. 664 vom 19.11.2019, [https://www.password-online.de/?wysija-page=1&controller=email&action=view&email_id=822&wysijap=subscriptions&user_id=1045]. Zweiter Teil als: Doch einen angemessenen Praxisbezug und einen ausreichenden gesellschaftlichen Nutzen? In: Open Password. Nr. 701 vom 06. Februar 2020 [Unter: https://www.password-online.de/?mailpoet_router&endpoint=view_in_browser&action=view&data=WzIwLDAsNjI2NCwiMTIxdHVlYm51bnMwa2tnZ2Nnd3dnNDgwdzg4MGs0c2MiLDE5LDBd]. Vgl. auch die vorangegangenen Beiträge von Lewandoski und Jörs.
-
MacFarlane, A.; Missaoui, S.; Frankowska-Takhari, S.: On machine learning and knowledge organization in multimedia information retrieval (2020)
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- Abstract
- Recent technological developments have increased the use of machine learning to solve many problems, including many in information retrieval. Multimedia information retrieval as a problem represents a significant challenge to machine learning as a technological solution, but some problems can still be addressed by using appropriate AI techniques. We review the technological developments and provide a perspective on the use of machine learning in conjunction with knowledge organization to address multimedia IR needs. The semantic gap in multimedia IR remains a significant problem in the field, and solutions to them are many years off. However, new technological developments allow the use of knowledge organization and machine learning in multimedia search systems and services. Specifically, we argue that, the improvement of detection of some classes of lowlevel features in images music and video can be used in conjunction with knowledge organization to tag or label multimedia content for better retrieval performance. We provide an overview of the use of knowledge organization schemes in machine learning and make recommendations to information professionals on the use of this technology with knowledge organization techniques to solve multimedia IR problems. We introduce a five-step process model that extracts features from multimedia objects (Step 1) from both knowledge organization (Step 1a) and machine learning (Step 1b), merging them together (Step 2) to create an index of those multimedia objects (Step 3). We also overview further steps in creating an application to utilize the multimedia objects (Step 4) and maintaining and updating the database of features on those objects (Step 5).
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Zhang, Y.; Zhang, C.; Li, J.: Joint modeling of characters, words, and conversation contexts for microblog keyphrase extraction (2020)
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- Abstract
- Millions of messages are produced on microblog platforms every day, leading to the pressing need for automatic identification of key points from the massive texts. To absorb salient content from the vast bulk of microblog posts, this article focuses on the task of microblog keyphrase extraction. In previous work, most efforts treat messages as independent documents and might suffer from the data sparsity problem exhibited in short and informal microblog posts. On the contrary, we propose to enrich contexts via exploiting conversations initialized by target posts and formed by their replies, which are generally centered around relevant topics to the target posts and therefore helpful for keyphrase identification. Concretely, we present a neural keyphrase extraction framework, which has 2 modules: a conversation context encoder and a keyphrase tagger. The conversation context encoder captures indicative representation from their conversation contexts and feeds the representation into the keyphrase tagger, and the keyphrase tagger extracts salient words from target posts. The 2 modules were trained jointly to optimize the conversation context encoding and keyphrase extraction processes. In the conversation context encoder, we leverage hierarchical structures to capture the word-level indicative representation and message-level indicative representation hierarchically. In both of the modules, we apply character-level representations, which enables the model to explore morphological features and deal with the out-of-vocabulary problem caused by the informal language style of microblog messages. Extensive comparison results on real-life data sets indicate that our model outperforms state-of-the-art models from previous studies.
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Skulimowski, A.M.J.; Köhler, T.: ¬A future-oriented approach to the selection of artificial intelligence technologies for knowledge platforms (2023)
0.00
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- Abstract
- This article presents approaches used to solve the problem of selecting AI technologies and tools to obtain the creativity fostering functionalities of an innovative knowledge platform. The aforementioned selection problem has been lagging behind other software-specific aspects of online knowledge platform and learning platform development so far. We linked technological recommendations from group decision support exercises to the platform design aims and constraints using an expert Delphi survey and multicriteria analysis methods. The links between expected advantages of using selected AI building tools, AI-related system functionalities, and their ongoing relevance until 2030 were assessed and used to optimize the learning scenarios and in planning the future development of the platform. The selected technologies allowed the platform management to implement the desired functionalities, thus harnessing the potential of open innovation platforms more effectively and delivering a model for the development of a relevant class of advanced open-access knowledge provision systems. Additionally, our approach is an essential part of digital sustainability and AI-alignment strategy for the aforementioned class of systems. The knowledge platform, which serves as a case study for our methodology has been developed within an EU Horizon 2020 research project.
-
Dachwitz, I.: ¬Das sind 650.000 Kategorien, in die uns die Online-Werbeindustrie einsortiert : Microsofts Datenmarktplatz Xandr (2023)
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- Content
- Umfang und Detailtiefe dieser Datensammlung sind erschreckend. Es gibt kaum eine menschliche Eigenschaft, die Werbetreibende nicht für Werbung ausnutzen wollen. Sie wollen Menschen aus Dänemark erreichen, die einen Toyota gekauft haben? Kein Problem. Sie wollen Menschen erreichen, die gerade finanzielle Probleme haben? Oder keine Krankenversicherung? Kein Problem. Minderjährige? Schwangere? Homosexuelle? Depressive? Politiker:innen? Alles kein Problem. "Diese Liste ist das gewaltigste Dokument über den globalen Datenhandel, das ich je gesehen habe", sagt der Wiener Tracking-Forscher Wolfie Christl. Er hat die Datei aufgestöbert und mit netzpolitik.org sowie The Markup geteilt. Das US-Medium berichtet heute unter anderem über die zahlreichen sensiblen Daten und macht sie mit einem interaktiven Tool einfach durchsuchbar. Xandr hat auf mehrere Presseanfragen nicht reagiert. Die Liste ist auf Mai 2021 datiert, sie stand bis zu unserer Anfrage auf einer Dokumentationsseite von Xandr offen im Netz. Heute ist sie nicht mehr erreichbar, aber beim Internet Archive gibt es eine archivierte Version der Seite und der Datei [23 MB]. Laut von uns befragten Jurist:innen zeige die Liste, dass das derzeitige Werbegeschäft strukturell unvereinbar mit Datenschutzanforderungen ist."
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Rötzer, F.: Droht bei einer Verschmelzung des Gehirns mit KI der Verlust des Bewusstseins? (2020)
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- Date
- 29. 6.2019 17:46:17
-
Lewis, T.: Woher stammt Sars-CoV-2? (2023)
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- Date
- 25. 9.2023 18:29:02
-
Koch, C.: Was ist Bewusstsein? (2020)
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- Date
- 17. 1.2020 22:15:11
-
Wagner, E.: Über Impfstoffe zur digitalen Identität? (2020)
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- Date
- 4. 5.2020 17:22:40
-
Engel, B.: Corona-Gesundheitszertifikat als Exitstrategie (2020)
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- Date
- 4. 5.2020 17:22:28
-
Arndt, O.: Totale Telematik (2020)
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- Date
- 22. 6.2020 19:11:24
-
Arndt, O.: Erosion der bürgerlichen Freiheiten (2020)
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- Date
- 22. 6.2020 19:16:24
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Baecker, D.: ¬Der Frosch, die Fliege und der Mensch : zum Tod von Humberto Maturana (2021)
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- Date
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