Themen für Bachelorarbeiten

Beschreibung: Generative artificial intelligence provides powerful tools for creating images and videos from large datasets. With rapid technological advances, these tools have become so sophisticated that generated images and videos are increasingly difficult to distinguish from real photographs or video footage. At this turning point, the technology also provides dangerous opportunities to create so-called deepfakes and other fake images that can be used to deceive people into believing they are real.

The manipulation of images and videos is not new. Especially in political contexts, fake images have a long history of being used to influence public opinion and for propaganda purposes. However, the scale and accessibility of these new technologies are unprecedented.

From a psychological perspective, several important questions arise. Who is more likely to be deceived by fake images and videos? Are people more likely to believe fake media when it aligns with their prior beliefs and worldviews (motivated cognition)? Can the ability to identify fake media be trained?

The goal of this bachelor?s thesis is to (a) compile recent empirical findings on the psychological factors that determine the believability of AI-generated images and videos, (b) summarize these findings in a review article, and (c) discuss our current understanding of these mechanisms, including potential blind spots that could inspire further research.

Initial References:

Köbis, N. C., Dole?alová, B., & Soraperra, I. (2021). Fooled twice: People cannot detect deepfakes but think they can. iScience, 24(11).

Pennycook, G., & Rand, D. G. (2021). The psychology of fake news. Trends in Cognitive Sciences, 25(5), 388-402.

Nieweglowska, M., Stellato, C., & Sloman, S. A. (2023). Deepfakes: Vehicles for radicalization, not persuasion. Current Directions in Psychological Science, 32(3), 236-241.

Appel, M., & Prietzel, F. (2022). The detection of political deepfakes. Journal of Computer-Mediated Communication, 27(4), zmac008.

Mai, K. T., Bray, S., Davies, T., & Griffin, L. D. (2023). Warning: Humans cannot reliably detect speech deepfakes. PloS ONE, 18(8), e0285333.

Newman, E. J., & Schwarz, N. (2024). Misinformed by images: How images influence perceptions of truth and what can be done about it. Current Opinion in Psychology, 56, 101778.

Diel, A., Lalgi, T., Schröter, I. C., MacDorman, K. F., Teufel, M., & Bäuerle, A. (2024). Human performance in detecting deepfakes: A systematic review and meta-analysis of 56 papers. Computers in Human Behavior Reports, 16, 100538.

Groh, M., Sankaranarayanan, A., Singh, N., Kim, D. Y., Lippman, A., & Picard, R. (2024). Human detection of political speech deepfakes across transcripts, audio, and video. Nature Communications, 15(1), 7629.

Barari, S., Lucas, C., & Munger, K. (2025). Political deepfakes are as credible as other fake media and (sometimes) real media. The Journal of Politics, 87(2), 510-526.
Kontakt: Prof. Dr. Jörg Gross, E-Mail

Beschreibung: Cooperation and working together enable groups to achieve more than individuals alone could. Yet, achieving cooperation is far from straightforward. Cooperation can be defined as the willingness to incur personal costs, whether in terms of time, effort, or resources, to create benefits for all members of a group. While mutual cooperation generates welfare that exceeds what individuals could achieve alone, it also introduces the temptation to free-ride. If others are cooperating, why not simply free-ide on their efforts, enjoying the benefits without sharing the burden? Conversely, if others are free-riding, why pay the costs to create benefits for others, especially if those efforts are not reciprocated but exploited? This dilemma, comprehensively captured in game-theoretic models such as the Prisoner?s Dilemma and the Public Goods Game, raises a fundamental question: how does cooperation emerge?

One mechanism for sustaining cooperation that has been extensively discussed in the empirical literature is communication. Humans, compared to other social animals, have the unique ability to coordinate their actions, make promises, and issue demands to cooperate within groups through language. Yet, promises can be broken, people can use communication to deceive others into cooperating without reciprocating, and people may not put ?their money where their mouth is.? This raises the question if and why communication can enhance collective action and cooperation within groups.

The goal of this bachelor?s thesis is to (a) compile empirical findings on the effectiveness and conditions of communication in sustaining group cooperation, (b) summarize these findings in a review article, and (c) discuss our current understanding of this mechanism, including potential blind spots that could inspire further research.

Initial references:

Braver, S. L., & Wilson, L. A. (1986). Choices in social dilemmas: Effects of communication within subgroups. Journal of Conflict Resolution, 30(1), 51-62.

Isaac, R. M., & Walker, J. M. (1988). Communication and free?riding behavior: The voluntary contribution mechanism. Economic inquiry, 26(4), 585-608.

Wilson, R. K., & Sell, J. (1997). ?Liar, liar...? Cheap talk and reputation in repeated public goods settings. Journal of Conflict Resolution, 41(5), 695-717.

Belot, M., Bhaskar, V., & van de Ven, J. (2010). Promises and cooperation: Evidence from a TV game show. Journal of Economic Behavior & Organization, 73(3), 396-405.

Tavoni, A., Dannenberg, A., Kallis, G., & Löschel, A. (2011). Inequality, communication, and the avoidance of disastrous climate change in a public goods game. Proceedings of the National Academy of Sciences, 108(29), 11825-11829.

Oprea, R., Charness, G., & Friedman, D. (2014). Continuous time and communication in a public-goods experiment. Journal of Economic Behavior & Organization, 108, 212-223.

Feltovich, N., & Grossman, P. J. (2015). How does the effect of pre-play suggestions vary with group size? Experimental evidence from a threshold public-good game. European Economic Review, 79, 263-280.

Haruvy, E., Li, S. X., McCabe, K., & Twieg, P. (2017). Communication and visibility in public goods provision. Games and Economic Behavior, 105, 276-296.

Kontakt: Prof. Dr. Jörg Gross, E-Mail

Beschreibung: Insbesondere in der Arbeits- und Organisationspsychologie werden zunehmenden sog. star performers untersucht ? Arbeitnehmende, die hervorragende Leistungen erbringen und damit einen bedeutenden Mehrwert für Organisationen, Vorgesetzte, Mitarbeitende, etc. bedeuten können (e.g., Aguinis & O?Boyle, 2014; Barlow et al., 2023; Kehoe et al., 2023; O?Boyle & Götz, 2025; O?Boyle & Kroska, 2017; Zhou et al., 2025). Es stellen sich allerdings diverse Fragen, wie etwa: (1) Was genau macht einen star performer aus?, (2) Haben star performer ausschliesslich positive Effekte?, (3) Was passiert mit star performers, die keine mehr sind?, etc.

Vor diesem Hintergrund ist es das Ziel der Literaturarbeit, (1) einen konzeptionellen und methodischen interdisziplinären Überblick über star performer zu geben, (2) empirische Arbeiten zu identifizieren, die die Rolle von star performers empirisch illustrieren, sowie (3) eine konstruktiv-kritische Diskussion der Befunde zu führen.

Initiale Literatur:
Aguinis, H., & O?Boyle, E. H. (2014). Star performers in twenty-first century organizations. Personnel Psychology, 67(2), 313?350. https://doi.org/10.1111/peps.12054
Barlow, M. A., Hesterly, W. S., & Verhaal, J. C. (2023). Catching a falling star: Mobility of declining star performers, peer effects, and organizational performance in the National Football League. Journal of Business Research, 165, 114053. https://doi.org/10.1016/j.jbusres.2023.114053
Kehoe, R. R., Collings, D. G., & Cascio, W. F. (2023). Simply the best? Star performers and high?potential employees: Critical reflections and a path forward for research and practice. Personnel Psychology, 76(2), 585?615. https://doi.org/10.1111/peps.12558
O?Boyle, E. H., & Götz, M. (2025). Rethinking stardom: A relativistic approach to studying the absolute best performers. Annual Review of Organizational Psychology and Organizational Behavior. https://doi.org/10.1146/annurev-orgpsych-020924-065909
O?Boyle, E. H., & Kroska, S. (2017). Star performers. In D. G. Collings, K. Mellahi, & W. F. Cascio (Eds.), The Oxford handbook of talent management (pp. 43?65). Oxford University Press. https://doi.org/10.1093/oxfordhb/9780198758273.013.12
Zhou, J., Li, N., Xu, S., & Chi, W. (2025). High performers in the shadow: The adverse effect of star employees on their peers. Journal of Applied Psychology, 110(6), 776?797. https://doi.org/10.1037/apl0001254
Kontakt: Dr. Martin Götz, E-Mail

Beschreibung: Meta-Analysen gelten als zentrale Bestandteile der Wissenschaft, um in Primärstudien gesammeltes Wissen zu kondensieren (e.g., Cooper et al., 2019; Siddaway et al., 2019; Valentine et al., 2023). Insbesondere im Rahmen der Open Science-Bewegung in den Sozialwissenschaften sind allerdings auch Meta-Analysen hinterfragt worden (e.g., Aguinis et al., 2011; DeSimone et al., 2019; Ioannidis, 2016). Schliesslich lauern bei jedem Schritt einer Meta-Analyse (z.B. Suche, Kodierung, Analyse, Bericht) diverse Gefahren, die die Validität der Meta-Analyse an sich und damit auch der gezogenen Aussagen gefährden.

Vor diesem Hintergrund ist es das Ziel dieser Literaturarbeit, (1) einen klaren Überblick über das allgemeine Vorgehen bei einer Meta-Analyse zu geben, (2) kritische Punkte bzgl. einzelner Schritte und mögliche Lösungsmöglichkeiten zusammenzutragen und (3) eine kritische Diskussion der meta-analytischen Methode im Allgemeinen zu führen.

Initiale Literatur:
Aguinis, H., Dalton, D. R., Bosco, F. A., Pierce, C. A., & Dalton, C. M. (2011). Meta-analytic choices and judgment calls: Implications for theory building and testing, obtained effect sizes, and scholarly impact. Journal of Management, 37(1), 5?38. https://doi.org/10.1177/0149206310377113
Cooper, H. M., Hedges, L. V., & Valentine, J. C. (2019). Research synthesis as a scientific process. In H. M. Cooper, L. V. Hedges, & J. C. Valentine (Eds.), The handbook of research synthesis and meta-analysis (pp. 3?16). Russell Sage Foundation. https://doi.org/10.7758/9781610448864.4
DeSimone, J. A., Köhler, T., & Schoen, J. L. (2019). If it were only that easy: The use of meta-analytic research by organizational scholars. Organizational Research Methods, 22(4), 867?891. https://doi.org/10.1177/1094428118756743
Ioannidis, J. P. A. (2016). The mass production of redundant, misleading, and conflicted systematic reviews and meta-analyses. The Milbank Quarterly, 94(3), 485?514. https://doi.org/10.1111/1468-0009.12210
Siddaway, A. P., Wood, A. M., & Hedges, L. V. (2019). How to do a systematic review: A best practice guide for conducting and reporting narrative reviews, meta-analyses, and meta-syntheses. Annual Review of Psychology, 70(1), 747?770. https://doi.org/10.1146/annurev-psych-010418-102803
Valentine, J. C., Pigott, T. D., & Morris, J. (2023). Meta-analysis. In H. M. Cooper, M. N. Coutanche, L. M. McMullen, A. T. Panter, D. Rindskopf, & K. J. Sher (Eds.), APA handbook of research methods in psychology: Data analysis and research publication (2nd ed., Vol. 3, pp. 539?559). American Psychological Association. https://doi.org/10.1037/0000320-024
Kontakt: Dr. Martin Götz, E-Mail

Beschreibung: Fehlverhalten am Arbeitsplatz (engl. counterproductive work behavior; workplace deviance) umfasst ein breites Verhaltensspektrum (z.?B. Diebstahl, Sabotage, Mobbing, Regelverstösse), das Mitarbeitende zeigen können und stellt für Unternehmen ein potentiell sehr grosses Problem dar (e.g., Bennett et al., 2018; Carpenter et al., 2021; Götz et al., 2019). Wissenschaftliche Erkenntnisse zu Ursachen und wirksamen Präventionsstrategien sind jedoch nach wie vor fragmentiert (e.g., Carpenter & Berry, 2017; Liao et al., 2021; Mackey et al., 2021) ? so werden mögliche Prädiktoren von Fehlverhalten am Arbeitsplatz i.d.R. recht isoliert untersucht. Die ausgeschriebene Literaturübersicht soll dazu beitragen, theoretische Grundlagen zu konsolidieren und praxisrelevante Handlungsempfehlungen abzuleiten.

Vor diesem Hintergrund ist es das Ziel dieser Literaturarbeit, (1) einen klaren Überblick über das Phänomen des Fehlverhaltens am Arbeitsplatz zu geben, (2) aktuelle, empirische Belege bzgl. Definitionen und Prädiktoren zusammenzutragen und (3) eine kritische Diskussion der Ergebnisse zu führen, um deren Implikationen für die Praxis zu verstehen.

Initiale Literatur:
Bennett, R. J., Marasi, S., & Locklear, L. (2018). Workplace deviance. In R. J. Bennett, S. Marasi, & L. Locklear, Oxford research encyclopedia of business and management. Oxford University Press. https://doi.org/10.1093/acrefore/9780190224851.013.111
Carpenter, N. C., & Berry, C. M. (2017). Are counterproductive work behavior and withdrawal empirically distinct? A meta-analytic investigation. Journal of Management, 43(3), 834?863. https://doi.org/10.1177/0149206314544743
Carpenter, N. C., Whitman, D. S., & Amrhein, R. (2021). Unit-level counterproductive work behavior (CWB): A conceptual review and quantitative summary. Journal of Management, 47(6), 1498?1527. https://doi.org/10.1177/0149206320978812
Götz, M., Bollmann, G., & O?Boyle, E. H. (2019). Contextual undertow of workplace deviance by and within units: A systematic review. Small Group Research, 50(1), 39?80. https://doi.org/10.1177/1046496418790044
Liao, E. Y., Wang, A. Y., & Zhang, C. Q. (2021). Who influences employees? dark side: A multi-foci meta-analysis of counterproductive workplace behaviors. Organizational Psychology Review, 11(2), 97?143. https://doi.org/10.1177/2041386620962554
Mackey, J. D., McAllister, C. P., Ellen, B. P., & Carson, J. E. (2021). A meta-analysis of interpersonal and organizational workplace deviance research. Journal of Management, 47(3), 597?622. https://doi.org/10.1177/0149206319862612
Kontakt: Dr. Martin Götz, E-Mail

Beschreibung: Mit der rasanten Verbreitung von sog. künstlicher Intelligenz ist auch die Verbreitung von künstlich generierten Texten, Bildern, und Videos einhergegangen (e.g., Borges Do Nascimento et al., 2022; Farid, 2022; Mubarak et al., 2023). Während KI-generierte Selfies von vermeintlichen Treffen mit Filmstars oder Schlagzeug spielende Katzen noch lustig sein mögen, können KI-generierte Medien auch schnell als Mis- oder gar Disinformation (sog. Deepfakes) eingesetzt werden. Will man sicherstellen, dass Menschen gut zwischen realem und AI-generiertem Material unterscheiden können, braucht es zentrale Medienkompetenz. Um zu verstehen, wie diese Kompetenz geschult werden kann, muss man überhaupt erst einmal verstehen, welche Prädiktoren für die gelungene Differenzierung von realem und AI-generiertem Material relevant sind (e.g., Arechar et al., 2023; Hubeny et al., 2025; Sultan et al., 2024).

Vor diesem Hintergrund ist es das Ziel dieser Literaturarbeit, (1) einen klaren Überblick über AI-generierte Mis-, Dis- und echte Informationen zu geben, (2) empirische Befunde bzgl. der Prädiktoren der Unterscheidungskompetenz von realem und AI-generiertem Material zusammenzutragen und (3) eine kritische Diskussion der Ergebnisse zu führen, um deren Implikationen für die Praxis zu verstehen.

Initiale Literatur:
Arechar, A. A., Allen, J., Berinsky, A. J., Cole, R., Epstein, Z., Garimella, K., Gully, A., Lu, J. G., Ross, R. M., Stagnaro, M. N., Zhang, Y., Pennycook, G., & Rand, D. G. (2023). Understanding and combatting misinformation across 16 countries on six continents. Nature Human Behaviour. https://doi.org/10.1038/s41562-023-01641-6
Borges Do Nascimento, I. J., Beatriz Pizarro, A., Almeida, J., Azzopardi-Muscat, N., André Gonçalves, M., Björklund, M., & Novillo-Ortiz, D. (2022). Infodemics and health misinformation: A systematic review of reviews. Bulletin of the World Health Organization, 100(9), 544?561. https://doi.org/10.2471/BLT.21.287654
Farid, H. (2022). Creating, using, misusing, and detecting deep fakes. Journal of Online Trust and Safety, 1(4). https://doi.org/10.54501/jots.v1i4.56
Hubeny, T. J., Nahon, L. S., Ng, N. L., & Gawronski, B. (2025). Who falls for misinformation and why? Personality and Social Psychology Bulletin, 01461672251328800. https://doi.org/10.1177/01461672251328800
Mubarak, R., Alsboui, T., Alshaikh, O., Inuwa-Dutse, I., Khan, S., & Parkinson, S. (2023). A survey on the detection and impacts of deepfakes in visual, audio, and textual formats. IEEE Access, 11, 144497?144529. https://doi.org/10.1109/ACCESS.2023.3344653
Sultan, M., Tump, A. N., Ehmann, N., Lorenz-Spreen, P., Hertwig, R., Gollwitzer, A., & Kurvers, R. H. J. M. (2024). Susceptibility to online misinformation: A systematic meta-analysis of demographic and psychological factors. Proceedings of the National Academy of Sciences, 121(47), e2409329121. https://doi.org/10.1073/pnas.2409329121
Kontakt: Dr. Martin Götz, E-Mail