Intelligent recruitment: how to identify, select, and retain talents from around the world using artificial intelligence.

This research analyzes how digital technologies contribute to improving the successive stages of the recruitment process: identifying, selecting, and retaining talented people. E-recruitment is an emerging and polymorphous phenomenon that starts with identification of candidates on social networks, continues through gamification of recruitment and job interviews with chatbots, and ends by matching a candidate and a job using artificial intelligence. These technologies are particularly useful for social businesses looking to recruit not only skilled people, but above all employees who have behaviors and values that match their mission. The methodology is based on grounded theory, participant observation, and qualitative data collection. A multiple case study is designed to analyze, compare, and combine several technologies dedicated to recruitment: (1) a social network with LinkedIn, (2) a MOOC with Udacity, (3) a serious game called Reveal from L'Oréal, (4) a chatbot called Ari from TextRecruit, and (5) a massive data analysis matching system with Randstad.tech. The discussion examines the respective performance and limits of these tools and their convergence via a progressive integration that leads to an uberization of recruitment. Managerial recommendations are formulated to support recruiters in their adoption of e-recruitment

AI as a Methodology for Supporting Educational Praxis and Teacher Metacognition

Evidence-based practice (EBP) is of critical importance in education where emphasis is placed on the need to equip educators with an ability to independently generate and reflect on evidence of their practices in situ – a process also known as praxis. This paper examines existing research related to teachers’ metacognitive skills and, using two exemplar projects, it discusses the utility and relevance of AI methods of knowledge representation and knowledge elicitation as methodologies for supporting EBP. Research related to technology-enhanced communities of practice as a means for teachers to share and compare their knowledge with others is also examined. Suggestions for the key considerations in supporting teachers’ metacognition in praxis are made based on the review of literature and discussion of the specific projects, with the aim to highlight potential future research directions for AIEd. A proposal is made that a crucial part of AIEd’s future resides in its curating the role of AI as a methodology for supporting teacher training and continuous professional development, especially as relates to their developing metacognitive skills in relation to their practices

Looking for c(l)ues. How visual cues can help predict personality traits in video interviews.

There is an ongoing trend that asynchronous video interviews are used more and more frequently for their efficiency gain (Brenner, 2019), especially in large scale selection processes (Brandt, Justenhoven & Schöffel, 2020). Visual cues that are present during those video recordings are not yet systematically processed and used, which is a miss under the argument of further efficiency gain (e.g. to measure personality traits). However, in a first step, a framework as well as a systematic visual cue analyses needs to be completed to establish the available data source that can – in a second step – be further used in an automatic scoring process. The purpose of the present study exactly that first step: to outline an approach to capture, categorize and systematically process visual cues to then link them to personality traits which are captured in various other forms as well. As an approach to this topic, the work from Gosling and colleagues (2005) is leveraged and with it Brunswik’s lens model (1956). Ultimately, and postulated as a research question, the aim of this body of research is to find functional achievement between self-rated and observer rated personality traits using the visual cues as elements of the lens. The body of research is structured in three steps. In step 1 visual cues present in research are catalogued, enriched with visual cues captured through various studies with asynchronous video interview data and categorized in five categories: Face, Body, Appearance, Media Properties, and Environment. In step 2 a visual cue inventory is developed that allows a manual systematic cue coding process of the 236 visual cues that are used in this work. In step 3, a dataset with n = 99 participants is generated that includes coding for all of the visual cues, as well as self and observer ratings on the video respondee’ s personality traits. Contrary to the hypotheses, however, little evidence is found that suggest visual cues can be linked both to self-ratings and observer ratings of personality traits. The cues seem to be either valid (i.e. linked to self-ratings) or used (i.e. linked to observer ratings) but generally the results show a very confound picture. Given the present results, it is not recommended to proceed further with the approach to leverage visual cues as a predictor for personality traits in asynchronous video interviews.Es gibt einen anhaltenden Trend, dass asynchrone Videointerviews wegen ihres Effizienzgewinns immer häufiger eingesetzt werden (Brenner, 2019), insbesondere in groß angelegten Auswahlverfahren (Brandt, Justenhoven & Schöffel, 2020). Visuelle Hinweisreize, die während dieser Videoaufnahmen vorhanden sind, werden noch nicht systematisch verarbeitet und verwendet, was unter dem Argument der weiteren Effizienzsteigerung (z. B. zur Messung von Persönlichkeitsmerkmalen) ein Versäumnis ist. In einem ersten Schritt muss jedoch ein Rahmenwerk sowie eine systematische Analyse der visuellen Hinweise geschaffen werden, um die verfügbare Datenquelle zu ermitteln, die in einem zweiten Schritt in einem automatischen Scoring-Prozess weiterverwendet werden kann. Das Ziel der vorliegenden Studie ist genau dieser erste Schritt: einen Ansatz zur Erfassung, Kategorisierung und systematischen Verarbeitung visueller Hinweise zu skizzieren, um diese dann mit Persönlichkeitsmerkmalen zu verknüpfen, die auch in verschiedenen anderen Formen erfasst werden. Als Grundlage zu diesem Thema wird die Arbeit von Gosling und Kollegen (2005) genutzt und damit das Linsenmodell von Brunswik (1956). Letztlich, und als Forschungsfrage postuliert, ist das Ziel der vorliegenden Forschung, die funktionale Leistung zwischen selbst- und beobachterbewerteten Persönlichkeitsmerkmalen – unter Verwendung der visuellen Hinweise als Elemente der Linse – zu finden. Die Forschungsarbeit ist in drei Schritte gegliedert. In Schritt 1 werden die in der Forschung vorhandenen visuellen Anhaltspunkte katalogisiert, mit visuellen Anhaltspunkten angereichert, die in verschiedenen Studien mit asynchronen Videointerviewdaten erfasst wurden, und in fünf Kategorien kategorisiert: Gesicht, Körper, Erscheinungsbild, Medieneigenschaften und Umgebung. In Schritt 2 wird ein Inventar visueller Hinweisreize entwickelt, das einen manuellen systematischen Kodierungsprozess der 236 visuellen Hinweisreize ermöglicht, die in dieser Arbeit verwendet werden. In Schritt 3 wird ein Datensatz mit n = 99 Teilnehmern generiert, der die Kodierung aller visuellen Hinweisreize sowie Selbst- und Beobachtereinschätzungen zu den Persönlichkeitsmerkmalen des Video-Respondenten enthält. Im Gegensatz zu den Hypothesen finden sich jedoch nur wenige Hinweise darauf, dass visuelle Hinweisreize sowohl mit Selbst- als auch mit Fremdeinschätzungen von Persönlichkeitsmerkmalen verknüpft werden können. Die Hinweisreize scheinen entweder gültig zu sein (d. h. mit Selbsteinschätzungen korrelierend) oder verwendet zu werden (d. h. mit Beobachtereinschätzungen korrelierend), aber im Allgemeinen zeigen die Ergebnisse ein sehr diffuses Bild auf. In Anbetracht der vorliegenden Ergebnisse wird nicht empfohlen, den Ansatz weiter zu verfolgen, visuelle Hinweise als Prädiktor für Persönlichkeitsmerkmale in asynchronen Videointerviews zu nutzen

Sistemas de diálogo: una revisión

Spoken dialogue systems are computer programs developed to interact with users employing speech in order to provide them with specific automated services. The interaction is carried out by means of dialogue turns, which in many studies available in the literature, researchers aim to make as similar as possible to those between humans in terms of naturalness, intelligence and affective content. In this paper we describe the fundaments of these systems including the main technologies employed for their development. We also present an evolution of this technology and discuss some current applications. Moreover, we discuss development paradigms, including scripting languages and the development of conversational interfaces for mobile apps. The correct modelling of the user is a key aspect of this technology. This is why we also describe affective, personality and contextual models. Finally, we address some current research trends in terms of verbal communication, multimodal interaction and dialogue management.Los sistemas de diálogo son programas de ordenador desarrollados para interaccionar con los usuarios mediante habla, con la finalidad de proporcionarles servicios automatizados. La interacción se lleva a cabo mediante turnos de un tipo de diálogo que, en muchos estudios existentes en la literatura, los investigadores intentan que se parezca lo más posible al diálogo real que se lleva a cabo entre las personas en lo que se refiere a naturalidad, inteligencia y contenido afectivo. En este artículo describimos los fundamentos de esta tecnología, incluyendo las tecnologías básicas que se utilizan para implementar este tipo de sistemas. También presentamos una evolución de la tecnología y comentamos algunas aplicaciones actuales. Asimismo, describimos paradigmas de interacción, incluyendo lenguajes de script y desarrollo de interfaces conversacionales para aplicaciones móviles. Un aspecto clave de esta tecnología consiste en realizar un correcto modelado del usuario. Por este motivo, discutimos diversos modelos afectivos, de personalidad y contextuales. Finalmente, comentamos algunas líneas de investigación actuales relacionadas con la comunicación verbal, interacción multimodal y gestión del diálogo

Investigating Technologically Advanced Job Interview Approaches

Die technologische Entwicklung stellt Unternehmen vor die Herausforderung informierte Entscheidungen über technologische Lösungen für organisationale Prozesse zu treffen. Besonders auffällig ist das im Falle von Bewerbungsgesprächen, bei denen in der Praxis wenig erforschte Technologien verwendet werden. Infolgedessen können Unternehmen über die Einflüsse technologiegestützter Bewerbungsgespräche (z.B. digitale Interviews) auf den Interviewprozess nur spekulieren. Meine Doktorarbeit soll die Forschung zu technologiegestützen Bewerbungsgesprächen in vier Schritten modernisieren. Erstens entwickle ich eine psychometrisch fundierte Skala zur Messung von Creepiness. Diese soll die Forschung zur Akzeptanz neuer Technologien unterstützen. Zweitens vergleiche ich digitale Interviews mit Videokonferenz-Interviews. Die Ergebnisse zeigen, dass digitale Interviews weniger akzeptiert und dass Bewerbende in digitalen Interviews besser bewertet werden. Drittens antizipiere ich die Zukunft des Bewerbungsgesprächs und untersuche ein algorithmusbasiertes Bewerbungsgespräch. Das algorithmusbasierte Bewerbungsgespräch führte zu negativeren Bewerberreaktionen als ein Videokonferenz-Interview. Im vierten Schritt erweitern zwei weiteren Studien die vorangegangenen Erkenntnisse indem versucht wird, negative Bewerberreaktionen durch Informationen zu technologisch fortschrittlichen Bewerbungsgesprächen vorzubeugen. Die Ergebnisse zeigen eine komplexe Beziehung zwischen Informationen und Akzeptanz. Weiterhin scheinen rechtfertigende Informationen besser als Prozessinformationen zu sein, um Bewerberreaktionen zu verbessern. Zusammengefasst zeigt meine Dissertation, dass die Anwendung neuer Technologien für die Personalauswahl wohl durchdacht sein sollte und dass Forschung zu klassischen Bewerbungsgesprächen möglicherweise nicht auf technologisch fortschrittliche Bewerbungsgespräche übertragbar ist. Schlussendlich ruft meine Dissertation zu weiterer Forschung bezüglich des Einflusses neuer Technologien in der Personalauswahl auf.Technology and its use has an immense effect on our daily lives. For instance, the recent rapid technological evolution has led to a myriad of technological solutions for organizational procedures. This challenges organizations to stay up-to-date and to make informed decisions about implementing and investing in technologically advanced procedures. In the context of job interviews, the technology that is used in practice has outpaced the research on the use of these technologies. As a consequence, researchers and practitioners can only speculate about how modern job interviews (e.g., digital interviews) affect outcomes such as applicant reactions and interview performance ratings. My dissertation therefore aims to update the research on technologically advanced job interviews in four steps. First, I provide a study on the development of a psychometrically sound measure of creepiness as a new perspective on research involving acceptance of technology-based situations. Second, I present a study comparing the emerging interview form of digital interviews with videoconference interviews showing that digital interviews can impair applicants’ reactions but increase applicants’ performance ratings. Third, I attempt to foreshadow the future of job interviewing technology by investigating an algorithm-based job interview with a virtual agent as the interviewer; results showed diminished applicant reactions compared to videoconference interviews. Fourth, two additional studies incorporate the aforementioned findings and attempt to buffer negative applicant reactions with information preceding technologically advanced job interviews. The results indicate a complex relation between information and acceptance and that justification information is better than process information to improve applicant reactions. All things considered, my dissertation implies that careful design is needed for personnel selection technology, that previous research in non-technological job interview settings might not translate to situations including novel technologies, and it calls for further research to investigate the influence of technology on personnel selection.Bundesministerium für Bildung und Forschung, Projekt Empa

Asynchronous video interviews in selection: A systematic review and five empirical investigations

It has become very popular to conduct employment interviews using new digital technologies, including synchronous and even asynchronous video interviews. In contrast to this wide usage in practice, less is known about how these technologies influence psychometric properties and selection outcomes. Findings gained from traditional face-to-face interviews cannot easily be transferred to digital interview formats. In addition, scholars have recently called for increased theory development to overcome the numerous limitations of cross-media comparisons and explain why and how technology should influence selection outcomes. While a variety of theories on media usage, media choice and media adaption exist, their applicability and explanatory value for technology usage in the area of employment interviews is rarely addressed. The present dissertation addresses this notable gap in the literature through both a systematic review of conceptional frameworks on technology usage in employment interviews as well as empirical results on understudied digital interview formats. In doing so, it identifies promising avenues for future research and provides information for HR practitioners about how to design their selection systems. More specifically, the current dissertation encompasses a comprehensive review of technology usage in employment interviews and five empirical studies on the specific format of asynchronous video interviews. The review integrates several theoretical perspectives on the topic, including the unitary perspective on technology-enhanced interviews, major theoretical directions in media research, and research on differences in psychometric properties and selection outcomes due to technology, into a comprehensive working model. The empirical portion of the dissertation presents five exploratory studies on asynchronous video interviews that explore research questions on blind spots in the literature or address urgent issues concerning the use of technology in today’s selection practice. The first study addresses interrater agreement and the importance of structured evaluation formats in a nonapplicant sample of N = 111 participants. The second study investigates the influence of social bandwidth on the accuracy of interview ratings in a sample of non-applicants with N = 279 participants. The third study provides first results on the validity of asynchronous video interviews in the field of high-stakes selection with N = 899 real applicants. The fourth study assesses the impact of personalized communication via video messages on applicant reactions in asynchronous video interviews with a non applicant sample of N = 98 participants. Finally, the fifth study explores rating inflation due to preparation time in a non-applicant sample of N = 51 participants. This dissertation contributes to the literature in several ways: The review provides an up-to-date, multi-perspective overview of the field and integrates several previous research strands into a single framework on technology usage in employment interviews. The empirical studies provide promising initial results concerning the psychometric properties of asynchronous video interviewing, specifically with respect to reliability and validity, but also highlight possible pitfalls--like rating inflation--that might appear when preparation time is introduced into the process design. In addition, the studies further highlight the extraordinary importance of structure in interviews, even though further study is required to better understand the exact nature of the relationship between structure and technology in employment interviews

Analytics and Intuition in the Process of Selecting Talent

In management, decisions are expected to be based on rational analytics rather than intuition. But intuition, as a human evolutionary achievement, offers wisdom that, despite all the advances in rational analytics and AI, should be used constructively when recruiting and winning personnel. Integrating these inner experiential competencies with rational-analytical procedures leads to smart recruiting decisions