Benjamin M. Abdel-Karim
Goethe University Frankfurt
WelfareData securityDecision support systemDeep learningInternet privacyEconomic efficiencyMachine learningEmpirical researchInformation technologyInformation asymmetryCollaborative learningEconometricsDownstream (petroleum industry)Artificial intelligenceRisk perceptionEmpirical evidenceMicroeconomicsGame theoryInformation systemExpectancy theorySurvey data collectionInstitutional investorData scienceRelation (database)Matrix (music)Stock market predictionContradictionAction (philosophy)Open researchElectronic marketsInvestment decisionsLOOP (programming language)Stock marketSocial network analysis (criminology)PopulationGynecologyHuman learningEconomic consequencesBusiness practicePredictive valueHot topicsField (computer science)Computer scienceSample (statistics)Medical diagnosisSocial WelfareIntelligent decision support systemStock (geology)Data Protection Act 1998Counterfactual conditionalMedicine
8Publications
2H-index
7Citations
Publications 8
Newest
#1Benjamin M. Abdel-Karim (Goethe University Frankfurt)H-Index: 2
#2Nicolas Pfeuffer (Goethe University Frankfurt)H-Index: 3
Last. Oliver Hinz (Goethe University Frankfurt)H-Index: 22
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Artificial Intelligence (AI) and Machine Learning (ML) are currently hot topics in industry and business practice, while management-oriented research disciplines seem reluctant to adopt these sophisticated data analytics methods as research instruments. Even the Information Systems (IS) discipline with its close connections to Computer Science seems to be conservative when conducting empirical research endeavors. To assess the magnitude of the problem and to understand its causes, we conducted a...
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#2Alexander BenlianH-Index: 33
Last. Oliver HinzH-Index: 22
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Optimal investment decisions by institutional investors require accurate predictions with respect to the development of stock markets. Motivated by previous research that revealed the unsatisfactory performance of existing stock market prediction models, this study proposes a novel prediction approach. Our proposed system combines Artificial Intelligence (AI) with data from Virtual Investment Communities (VICs) and leverages VICs’ ability to support the process of predicting stock markets. An em...
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Using a novel theoretical framework and data from a comprehensive field study we conducted over a period of three years, we outline the causal effects of algorithmic discrimination on economic efficiency and social welfare in a strategic setting under uncertainty. We combine economic, game-theoretic, and applied machine learning concepts allowing us to overcome the central challenge of missing counterfactuals, which generally impedes showcasing economic downstream consequences of algorithmic dis...
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#1Benjamin M. Abdel-Karim (Goethe University Frankfurt)H-Index: 2
#2Katharina Keller (Goethe University Frankfurt)H-Index: 3
Last. Daniel FranzmannH-Index: 1
view all 3 authors...
#1Benjamin M. Abdel-Karim (Goethe University Frankfurt)H-Index: 2
#2Nicolas Pfeuffer (Goethe University Frankfurt)H-Index: 3
Last. Oliver Hinz (Goethe University Frankfurt)H-Index: 22
view all 4 authors...
This article discusses the counterpart of interactive machine learning, i.e., human learning while being in the loop in a human-machine collaboration. For such cases we propose the use of a Contradiction Matrix to assess the overlap and the contradictions of human and machine predictions. We show in a small-scaled user study with experts in the area of pneumology (1) that machine-learning based systems can classify X-rays with respect to diseases with a meaningful accuracy, (2) humans partly use...
5 CitationsSource
Aufgrund der hohen Morbiditat sowie Mortalitat von Lungenerkrankungen steht die Pravention, Diagnostik und die adaquate Behandlung im Zentrum der modernen Medizin. Die Bildgebung mittels Thorax-Rontgenaufnahme ist hierbei Goldstandard. Die automatisierte Auswertung von Thorax-Rontgenaufnahmen konnte eine optimale Grundlage fur die Auswertung mittel kunstlicher Intelligenz (KI) darstellen. Allerdings ist die Thorax-Rontgenklassifikation keine triviale Aufgabe fur ein reines KI-basiertes System. D...
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Using experimental data from a comprehensive field study, we explore the causal eects of algorithmic discrimination on economic eciency and social welfare. We harness economic, game-theoretic, and state-of-the-art machine learning concepts allowing us to overcome the central challenge of missing counterfactuals, which generally impedes assessing economic downstream consequences of algorithmic discrimination. This way, we are able to precisely quantify downstream eciency and welfare ramifications...
#1Katharina Keller (Goethe University Frankfurt)H-Index: 3
#2Kim Valerie Carl (Technische Universität Darmstadt)H-Index: 1
Last. Oliver Hinz (Goethe University Frankfurt)H-Index: 22
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Personal smart assistance systems make people's lives easier and enable exceptional convenience, e.g. by supporting users during bothersome tasks. While personal intelligent assistants offer a lot of comfort to their users, there are also worries about data protection and data security since personal data about users is collected, aggregated and analyzed for ubiquitous assistance systems. Smart assistance systems can for example be found in cars. Connected to other internet of things devices, th...
1 CitationsSource