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Your search keyword '"Bahník, Štěpán"' showing total 456 results
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456 results on '"Bahník, Štěpán"'

1. Advances in Machine Learning for the Behavioral Sciences

Author

Kliegr, Tomáš, Bahník, Štěpán, and Fürnkranz, Johannes

Subjects
Computer Science - Machine Learning, Computer Science - Computation and Language, Statistics - Machine Learning
Abstract

The areas of machine learning and knowledge discovery in databases have considerably matured in recent years. In this article, we briefly review recent developments as well as classical algorithms that stood the test of time. Our goal is to provide a general introduction into different tasks such as learning from tabular data, behavioral data, or textual data, with a particular focus on actual and potential applications in behavioral sciences. The supplemental appendix to the article also provides practical guidance for using the methods by pointing the reader to proven software implementations. The focus is on R, but we also cover some libraries in other programming languages as well as systems with easy-to-use graphical interfaces.

Published
2019
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3. A review of possible effects of cognitive biases on the interpretation of rule-based machine learning models

Author

Kliegr, Tomáš, Bahník, Štěpán, and Fürnkranz, Johannes

Subjects
Statistics - Machine Learning, Computer Science - Artificial Intelligence, Computer Science - Machine Learning
Abstract

While the interpretability of machine learning models is often equated with their mere syntactic comprehensibility, we think that interpretability goes beyond that, and that human interpretability should also be investigated from the point of view of cognitive science. The goal of this paper is to discuss to what extent cognitive biases may affect human understanding of interpretable machine learning models, in particular of logical rules discovered from data. Twenty cognitive biases are covered, as are possible debiasing techniques that can be adopted by designers of machine learning algorithms and software. Our review transfers results obtained in cognitive psychology to the domain of machine learning, aiming to bridge the current gap between these two areas. It needs to be followed by empirical studies specifically focused on the machine learning domain.

Published
2018
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9. Same data, different conclusions: Radical dispersion in empirical results when independent analysts operationalize and test the same hypothesis

Author

Schweinsberg, Martin, Feldman, Michael, Staub, Nicola, van den Akker, Olmo R., van Aert, Robbie C.M., van Assen, Marcel A.L.M., Liu, Yang, Althoff, Tim, Heer, Jeffrey, Kale, Alex, Mohamed, Zainab, Amireh, Hashem, Venkatesh Prasad, Vaishali, Bernstein, Abraham, Robinson, Emily, Snellman, Kaisa, Amy Sommer, S., Otner, Sarah M.G., Robinson, David, Madan, Nikhil, Silberzahn, Raphael, Goldstein, Pavel, Tierney, Warren, Murase, Toshio, Mandl, Benjamin, Viganola, Domenico, Strobl, Carolin, Schaumans, Catherine B.C., Kelchtermans, Stijn, Naseeb, Chan, Mason Garrison, S., Yarkoni, Tal, Richard Chan, C.S., Adie, Prestone, Alaburda, Paulius, Albers, Casper, Alspaugh, Sara, Alstott, Jeff, Nelson, Andrew A., Ariño de la Rubia, Eduardo, Arzi, Adbi, Bahník, Štěpán, Baik, Jason, Winther Balling, Laura, Banker, Sachin, AA Baranger, David, Barr, Dale J., Barros-Rivera, Brenda, Bauer, Matt, Blaise, Enuh, Boelen, Lisa, Bohle Carbonell, Katerina, Briers, Robert A., Burkhard, Oliver, Canela, Miguel-Angel, Castrillo, Laura, Catlett, Timothy, Chen, Olivia, Clark, Michael, Cohn, Brent, Coppock, Alex, Cugueró-Escofet, Natàlia, Curran, Paul G., Cyrus-Lai, Wilson, Dai, David, Valentino Dalla Riva, Giulio, Danielsson, Henrik, Russo, Rosaria de F.S.M., de Silva, Niko, Derungs, Curdin, Dondelinger, Frank, Duarte de Souza, Carolina, Tyson Dube, B., Dubova, Marina, Mark Dunn, Ben, Adriaan Edelsbrunner, Peter, Finley, Sara, Fox, Nick, Gnambs, Timo, Gong, Yuanyuan, Grand, Erin, Greenawalt, Brandon, Han, Dan, Hanel, Paul H.P., Hong, Antony B., Hood, David, Hsueh, Justin, Huang, Lilian, Hui, Kent N., Hultman, Keith A., Javaid, Azka, Ji Jiang, Lily, Jong, Jonathan, Kamdar, Jash, Kane, David, Kappler, Gregor, Kaszubowski, Erikson, Kavanagh, Christopher M., Khabsa, Madian, Kleinberg, Bennett, Kouros, Jens, Krause, Heather, Krypotos, Angelos-Miltiadis, Lavbič, Dejan, Ling Lee, Rui, Leffel, Timothy, Yang Lim, Wei, Liverani, Silvia, Loh, Bianca, Lønsmann, Dorte, Wei Low, Jia, Lu, Alton, MacDonald, Kyle, Madan, Christopher R., Hjorth Madsen, Lasse, Maimone, Christina, Mangold, Alexandra, Marshall, Adrienne, Ester Matskewich, Helena, Mavon, Kimia, McLain, Katherine L., McNamara, Amelia A., McNeill, Mhairi, Mertens, Ulf, Miller, David, Moore, Ben, Moore, Andrew, Nantz, Eric, Nasrullah, Ziauddin, Nejkovic, Valentina, Nell, Colleen S, Arthur Nelson, Andrew, Nilsonne, Gustav, Nolan, Rory, O'Brien, Christopher E., O'Neill, Patrick, O'Shea, Kieran, Olita, Toto, Otterbacher, Jahna, Palsetia, Diana, Pereira, Bianca, Pozdniakov, Ivan, Protzko, John, Reyt, Jean-Nicolas, Riddle, Travis, (Akmal) Ridhwan Omar Ali, Amal, Ropovik, Ivan, Rosenberg, Joshua M., Rothen, Stephane, Schulte-Mecklenbeck, Michael, Sharma, Nirek, Shotwell, Gordon, Skarzynski, Martin, Stedden, William, Stodden, Victoria, Stoffel, Martin A., Stoltzman, Scott, Subbaiah, Subashini, Tatman, Rachael, Thibodeau, Paul H., Tomkins, Sabina, Valdivia, Ana, Druijff-van de Woestijne, Gerrieke B., Viana, Laura, Villesèche, Florence, Duncan Wadsworth, W., Wanders, Florian, Watts, Krista, Wells, Jason D, Whelpley, Christopher E., Won, Andy, Wu, Lawrence, Yip, Arthur, Youngflesh, Casey, Yu, Ju-Chi, Zandian, Arash, Zhang, Leilei, Zibman, Chava, and Luis Uhlmann, Eric

Published
2021
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11. Taking Algorithmic (Vs. Human) Advice Reveals Different Goals to Others

Author

Efendić, Emir, Van de Calseyde, Philippe P.F.M., Bahník, Štěpán, Vranka, Marek A., Efendić, Emir, Van de Calseyde, Philippe P.F.M., Bahník, Štěpán, and Vranka, Marek A.

Abstract

People are increasingly likely to obtain advice from algorithms. But what does taking advice from an algorithm (as opposed to a human) reveal to others about the advice seekers’ goals? In five studies (total N = 1927), we find that observers attribute the primary goal that an algorithm is designed to pursue in a situation to advice seekers. As a result, when explaining advice seekers’ subsequent behaviors and decisions, primarily this goal is taken into account, leaving less room for other possible motives that could account for people’s actions. Such secondary goals are, however, more readily taken into account when (the same) advice comes from human advisors, leading to different judgments about advice seekers’ motives. Specifically, advice seekers’ goals were perceived differently in terms of fairness, profit-seeking, and prosociality depending on whether the obtained advice came from an algorithm or another human. We find that these differences are in part guided by the different expectations people have of the type of information that algorithmic- vs. human advisors take into account when making their recommendations. The presented work has implications for (algorithmic) fairness perceptions and human-computer interaction.

Published
2024

13. Perspective-Taking Does Not Reduce Victim Blaming in Work-Related Situations.

Author

Houdek, Petr, Bahník, Štěpán, Vrbová, Lucie, and Hájek, Jiří

Abstract

According to the just-world theory, people tend to blame innocent victims for the misfortune they experienced to preserve the belief in a just world. Our preregistered experimental study (N = 404; a university participants pool) employed work-related scenarios to test the possibility of reducing victim-blaming by taking a victim’s perspective. We also explored whether “victim-blaming” occurs for both undeserved negative and positive outcomes, i.e. attributions of blame or virtue in scenarios including demotions, dismissals, public reprimands, and removal of responsibilities as negative outcomes; and bonuses, promotions, salary raises, and job hirings as positive outcomes. We found that victim-blaming followed from the just-world belief only in scenarios where an individual gains unjust benefit. The belief in a just world could thus lead to the misattribution of positive work outcomes and could result in biased human resources management. Taking the victim’s perspective did not reduce attributions of blame and virtue. However, participants considered the outcomes more deserved when they took the perpetrator’s perspective. This finding may be a warning that if a perpetrator’s perception framework is more accessible for assessing a particular situation, the victims will be blamed more. [ABSTRACT FROM AUTHOR]

Published
2024
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25. sj-docx-1-eab-10.1177_00139165231163547 – Supplemental material for Pro-Environmental Behavior Triggers Moral Inference, Not Licensing by Observers

Author

Urban, Jan, Bahník, Štěpán, and Braun Kohlová, Markéta

Subjects
FOS: Psychology, 170199 Psychology not elsewhere classified
Abstract

Supplemental material, sj-docx-1-eab-10.1177_00139165231163547 for Pro-Environmental Behavior Triggers Moral Inference, Not Licensing by Observers by Jan Urban, Štěpán Bahník and Markéta Braun Kohlová in Environment and Behavior

Published
2023
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28. Investigating variation in replicability: A 'Many Labs' Replication Project

Author

Klein, Richard, Ratliff, Kate, Nosek, Brian, Vianello, Michelangelo, Pilati, Ronaldo, Cemalcilar, Zeynep, Chandler, Jesse, Devos, Thierry, Galliani, Elisa, Brandt, Mark, van 't Veer, Anna, Levitan, Carmel, Kurtz, Jaime, Joy-Gaba, Jennifer, Ehrlinger, Joyce, Bernstein, Michael, Morris, Wendy, Vaughn, Leigh Ann, Wichman, Aaron, Rutchick, Abraham, Kappes, Heather, Brumbaugh, Claudia, Nelson, Anthony, Eisner, Matthew, Smith, Robert, Woodzicka, Julie, Bocian, Konrad, Frankowska, Natalia, Schmidt, Kathleen, Skorinko, Jeanine, Storbeck, Justin, Thompson, Donna, Packard, Grant, van Swol, Lyn, Nier, Jason, Cheong, Winnee, Davis, William, Mallett, Robyn, Huntsinger, Jeffrey, Bahník, Štěpán, Vranka, Marek, Hasselman, Fred, IJzerman, Hans, and Krueger, Lacy

Subjects
replication, psychology
Abstract

We will attempt to replicate 12 effects in a single experimental package across numerous labs. Variations between lab conditions and sample characteristics will be analyzed to investigate how these factors might influence replication success.

Published
2022
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32. Direct replication and extension of Mazar and Zhong’s (2010, experiment 3) moral licensing experiment with environmental attitude as moderator of moral regulation processes

Author

Braun Kohlová, Markéta, Bahník, Štěpán, and Urban, Jan

Subjects
health care economics and organizations, humanities
Abstract

This study aims to conduct direct replication of Mazar and Zhong’s (2010, experiment 3) moral licensing experiment and extend it by including environmental attitude as a moderator of moral regulation processes and by including a control group.

Published
2022
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33. Analysis Scripts

Author

Vianello, Michelangelo, Klein, Richard, Ratliff, Kate, Nosek, Brian, Pilati, Ronaldo, Devos, Thierry, Galliani, Elisa, Brandt, Mark, van 't Veer, Anna, Rutchick, Abraham, Schmidt, Kathleen, Bahník, Štěpán, Vranka, Marek, IJzerman, Hans, Hasselman, Fred, Joy-Gaba, Jennifer, Chandler, Jesse, Vaughn, Leigh Ann, Brumbaugh, Claudia, van Swol, Lyn, Wichman, Aaron, Packard, Grant, Brooks, Beach, Cemalcilar, Zeynep, Storbeck, Justin, Bocian, Konrad, Levitan, Carmel, Bernstein, Michael, Krueger, Lacy, Eisner, Matthew, Davis, William, Nier, Jason, Nelson, Anthony, and Steiner, Troy

Published
2022
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34. In your facebook

Author

Bahník, Štěpán, Henkel, Maureen, Schulz, Daniel, Keklik, Malik, Stanean, Antonia, Tsvetkova, Antoniya, Stevic, Milan, and Witucki, Fina

Published
2022
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39. Data

Author

Klein, Richard, Ratliff, Kate, Nosek, Brian, Vianello, Michelangelo, Pilati, Ronaldo, Devos, Thierry, Galliani, Elisa, Brandt, Mark, van 't Veer, Anna, Rutchick, Abraham, Schmidt, Kathleen, Bahník, Štěpán, Vranka, Marek, IJzerman, Hans, Hasselman, Fred, Joy-Gaba, Jennifer, Chandler, Jesse, Vaughn, Leigh Ann, Brumbaugh, Claudia, van Swol, Lyn, Wichman, Aaron, Packard, Grant, Brooks, Beach, Cemalcilar, Zeynep, Storbeck, Justin, Bocian, Konrad, Levitan, Carmel, Bernstein, Michael, Krueger, Lacy, Eisner, Matthew, Davis, William, Nier, Jason, Nelson, Anthony, and Steiner, Troy

Published
2022
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40. RRR - Finkel - Vranka

Author

Vranka, Marek, Bahník, Štěpán, and Houdek, Petr

Subjects
ComputerSystemsOrganization_COMPUTER-COMMUNICATIONNETWORKS
Abstract

Our implementation of the Finkel RRR protocol.

Published
2022
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42. Methods and Study Materials

Author

Klein, Richard, Ratliff, Kate, Nosek, Brian, Vianello, Michelangelo, Pilati, Ronaldo, Devos, Thierry, Galliani, Elisa, Brandt, Mark, van 't Veer, Anna, Rutchick, Abraham, Schmidt, Kathleen, Bahník, Štěpán, Vranka, Marek, IJzerman, Hans, Hasselman, Fred, Joy-Gaba, Jennifer, Chandler, Jesse, Vaughn, Leigh Ann, Brumbaugh, Claudia, van Swol, Lyn, Wichman, Aaron, Packard, Grant, Brooks, Beach, Cemalcilar, Zeynep, Storbeck, Justin, Bocian, Konrad, Levitan, Carmel, Bernstein, Michael, Krueger, Lacy, Eisner, Matthew, Davis, William, Nier, Jason, Nelson, Anthony, and Steiner, Troy

Published
2022
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44. Mock Session Videos

Author

Klein, Richard, Ratliff, Kate, Nosek, Brian, Vianello, Michelangelo, Pilati, Ronaldo, Devos, Thierry, Galliani, Elisa, Brandt, Mark, van 't Veer, Anna, Rutchick, Abraham, Schmidt, Kathleen, Bahník, Štěpán, Vranka, Marek, IJzerman, Hans, Hasselman, Fred, Joy-Gaba, Jennifer, Chandler, Jesse, Vaughn, Leigh Ann, Brumbaugh, Claudia, van Swol, Lyn, Wichman, Aaron, Packard, Grant, Brooks, Beach, Cemalcilar, Zeynep, Storbeck, Justin, Bocian, Konrad, Levitan, Carmel, Bernstein, Michael, Krueger, Lacy, Eisner, Matthew, Davis, William, Nier, Jason, Nelson, Anthony, and Steiner, Troy

Published
2022
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48. Methods

Author

Braun Kohlová, Markéta, Bahník, Štěpán, and Urban, Jan

Abstract

Methods and Measures

Published
2022
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