1,720,958 research outputs found
Understanding Choice Independence and Error Types in Human-AI Collaboration
No full textThe ability to make appropriate delegation decisions is an important prerequisite of effective human-AI collaboration. Recent work, however, has shown that people struggle to evaluate AI systems in the presence of forecasting errors, falling well short of relying on AI systems appropriately. We use a pre-registered crowdsourcing study (N = 611) to extend this literature by two underexplored crucial features of human AI decision-making: choice independence and error type. Subjects in our study repeatedly complete two prediction tasks and choose which predictions they want to delegate to an AI system. For one task, subjects receive a decision heuristic that allows them to make informed and relatively accurate predictions. The second task is substantially harder to solve, and subjects must come up with their own decision rule. We systematically vary the AI system's performance such that it either provides the best possible prediction for both tasks or only for one of the two. Our results demonstrate that people systematically violate choice independence by taking the AI's performance in an unrelated second task into account. Humans who delegate predictions to a superior AI in their own expertise domain significantly reduce appropriate reliance when the model makes systematic errors in a complementary expertise domain. In contrast, humans who delegate predictions to a superior AI in a complementary expertise domain significantly increase appropriate reliance when the model systematically errs in the human expertise domain. Furthermore, we show that humans differentiate between error types and that this effect is conditional on the considered expertise domain. This is the first empirical exploration of choice independence and error types in the context of human-AI collaboration. Our results have broad and important implications for the future design, deployment, and appropriate application of AI systems.Web Information System
Frauen gehen in Führung - Frauen als Unternehmerinnen im Handwerk, unter besonderer Berücksichtigung des Handwerkskammerbezirks Düsseldorf
No full textDie Kurzstudie, die im Auftrag der Handwerkskammer Düsseldorf erstellt worden ist, untersucht die Rolle von Frauen als Inhaberinnen im Handwerk. Zwar hat sich in den letzten Jahren der Frauenanteil im Handwerk etwas erhöht, so dass derzeit etwa jeder vierte Handwerksbetrieb von einer Frau geleitet wird, dieser Anteil ist aber immer noch niedriger als in der Gesamtwirtschaft. Der Grund liegt primär darin, dass Frauen eher in Dienstleistungsbranchen gründen, die im Handwerk unterrepräsentiert sind. Darüber hinaus stehen Frauen eher kleineren Betrieben vor und üben ihre Selbstständigkeit relativ häufig in Teilzeit oder im Nebenerwerb aus. So können Beruf und Familie einerseits besser miteinander vereinbart werden; andererseits fällt das Einkommen geringer aus. Bei Frauen ist die Risikobereitschaft geringer; sie gründen daher sehr viel vorsichtiger, wobei sie viel häufiger als Männer eine Doppelbelastung von Familie und Beruf auf sich nehmen. Hier kommt den traditionellen Rollenbildern immer noch ein hoher Stellenwert zu. Am Ende des Kurzgutachtens werden einige Handlungsempfehlungen aufgezeigt, wie Frauen vermehrt für eine Selbstständigkeit im Handwerk interessiert werden können. In erster Linie sind die Rollenbilder aufzubrechen, um zu zeigen, dass im männerdominierten Handwerk auch Inhaberinnen Erfolg haben können. Darüber hinaus ist mit speziellen Informationsangeboten auf das besondere Gründungsverhalten von Frauen einzugehen. Als letztes ist eine Vernetzung zu fördern, damit Frauen bei ihren Gründungsplänen den notwendigen Rückhalt bekommen.This compact study about the role of female company owners in the skilled crafts sector was commissioned by the crafts chamber in Düsseldorf. The share of female company owners has risen in recent years. One out of four crafts companies is headed by a woman, which is lower than the fraction in the overall economy. The main reason for this disparity is the tendency of women to start businesses in the service sector, which is underrepresented in the crafts. Women also tend to be self-employed in smaller companies and they engage in part-time work more frequently than men. On the one hand this enables women to care for children and actively participate in the labor force at the same time. On the other, incomes are generally lower. Women are more risk averse and tend to be more cautious in their entrepreneurial endeavors. They are more likely to bear the double responsibility of company owners as well as caretakers within their own family. Traditional gender roles are still prevalent. At the end of this study there are a number of policy recommendations with regard to the question of how women could be more successfully motivated to become self-employed in the crafts. First of all, traditional gender roles need to be overcome in order to show that women can be successful in traditionally male dominated crafts trades. Entrepreneurship consulting should incorporate gender typical concerns and cater to the specific informational requirements of women. Finally, female entrepreneur networks can support women in their commercial endeavors
For What It's Worth: Humans Overwrite Their Economic Self-interest to Avoid Bargaining With AI Systems
No full textAs algorithms are increasingly augmenting and substituting human decision-making, understanding how the introduction of computational agents changes the fundamentals of human behavior becomes vital. This pertains to not only users, but also those parties who face the consequences of an algorithmic decision. In a controlled experiment with 480 participants, we exploit an extended version of two-player ultimatum bargaining where responders choose to bargain with either another human, another human with an AI decision aid or an autonomous AI-system acting on behalf of a passive human proposer. Our results show strong responder preferences against the algorithm, as most responders opt for a human opponent and demand higher compensation to reach a contract with autonomous agents. To map these preferences to economic expectations, we elicit incentivized subject beliefs about their opponent's behavior. The majority of responders maximize their expected value when this is line with approaching the human proposer. In contrast, responders predicting income maximization for the autonomous AI-system overwhelmingly override economic self-interest to avoid the algorithm.Web Information System
Handwerk als Vertrauensgut - ein theoretischer Rahmen zur experimentellen Forschung
No full textDas Handwerk befindet sich in einem tiefgreifenden Prozess der digitalen Transformation, der sowohl Leistungsangebote als auch Marktstrukturen nachhaltig verändert. Diese Entwicklungen erzeugen einen erheblichen Forschungsbedarf für ein "Handwerk der Zukunft". Die vorliegende Studie beschreibt das Konzept der Vertrauensgütermärkte und begründet, warum dieses einen in der Verhaltensökonomik etablierten und theoretisch tragfähigen Analyserahmen für den Handwerksmarkt der Zukunft bietet. Vertrauensgütermärkte erfassen die Informationsasymmetrie zu Gunsten von Experten (Handwerkern) gegenüber den Kunden, welche häufig auch nach Leistungserbringung nicht oder nur unzureichend die Qualität der Leistung beurteilen können. So können die Wirkungen von Verhaltensänderungen der Betriebe und der Kunden sowie institutioneller und marktlicher Veränderungen präzise analysiert werden. Zukünftig von besonderem Forschungsinteresse ist der Bereich der Digitalisierung im Kontext der Konsumenteninformation, in dem große Veränderungen und potenziell tiefgreifende Verschiebungen der Informationsasymmetrien zugunsten der Konsumenten zu erwarten sind. Beispielsweise steigt der Informationsgrad der Kunden durch KI-Tools, die Einholung zweiter Meinungen wird erleichtert, und Bewertungen zu Experten können breit geteilt werden. Gleichwohl ist die Wirkung der Digitalisierung auf die Informationslage der Experten bisher wenig erforscht, obwohl das daraus resultierende Investitions- und Innovationsverhalten für zukünftige Handwerksmärkte entscheidend sein dürfte. Vor diesem Hintergrund leitet die Studie vier zentrale Forschungsfelder ab: (1) die Entscheidungsrolle des Kunden im Kontext der digitalen Transformation und ihre heterogenen Effekte auf Marktprozesse im Handwerk, (2) die Dynamik technologischer Investitionen und Adaptionen von Handwerkern, insbesondere unter dem Einfluss algorithmischer Empfehlungen, (3) das Explorationsverhalten im Sinne von "learning by doing-using-interacting" und seine Implikationen für Qualitätssicherung und Informationsasymmetrien sowie (4) die Gestaltung regulatorischer Anforderungen, um Transparenz, Verlässlichkeit und Vertrauen in einem sich rasch wandelnden Marktumfeld zu gewährleisten
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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