Siri Isaksson

About me:                                     

I am an Assistant Professor (tenure track) in Behavioral Economics at the FAIR group at the Norwegian School of Economics. I  got my PhD in Economics at the Stockholm School of Economics 2019. I spent the last three years of my PhD program as a research fellow at Harvard University, first with the Econ CS group at Harvard SEAS, and then with the Women and Public Policy Program at Harvard Kennedy School.   My primary research areas are experimental and behavioral economics.  Specifically, I am interested in understanding how gender differences in everyday decision-making translate into unequal outcomes for men and women.  My latest line of research is on gender differences in AI adoption and how these will affect professional as well as educational outcomes. 

I have four ongoing projects in this line of research.  The most finished project is currently under review. In a related project called "Will AI help or hurt learning?" we ask how access to generative AI affects learning outcomes. It is conceivable that students will use generative AI as a substitute for own effort, and end up learning less as a consequence. Another option is that students use AI as a complement to own effort and end up learning more when having access to it. In order to answer this question, we ran a controlled lab experiment (N=572) in which the access to AI is manipulated experimentally between subjects. Preliminary results will be presented at the 2025 rendition of the ASSA meeting in San Fransisco. In a separate paper, me Tatiana Celadin, Valeria Maggian and Fabio Galeotti are working on an experiment to test whether women can be trained in using AI, and whether competitiveness gaps can be closed by such training. The data-collection for this study will occur in the coming semester.  I also have an early stage project joint with co-authors on AI and beauty bias (more on this soon).

As a fellow with the Women and Science Chair at Dauphine I am also working on  a new project on the development on noncognitive skills with Sa-Kiera Hudson and Clementine van Effenterre. You can find more information about that project here we will run a first survey experiment shortly and preliminary results will be presented at the workshop of the chair in Feb 2025.

Previous work

 In my paper “It Takes Two: Gender Differences in Group Work”, I demonstrate that women consistently under-credit their contributions to shared work - and that this effect is strongest among women who contribute the most, and work on complex solutions. This paper introduces a novel experimental framework which has since been used to study related topics in gender and racial based discrimination, such as corrections and team work, whether incentives to exaggerate matter for the gender gap in claiming credit,  and whether race determines who you select as a tutor and subsequently whether this in turn determines learning outcomes. In a follow-up study I ask whether there is a gender bias in external attribution of credit for contributions to successful group work, and whether speaking up and claiming credit can reduce such a bias. The findings show that people who claim more credit, get more credit - this is true for both genders. Also interestingly, actual contribution does not matter for how much credit you get, instead claims seem to be determining this. These two projects are both awaiting a first submission after revising the drafts.

 Together with co-authors, I have studied gender differences in retaliation, and advice seeking. I have also collaborated on several replication studies. 

Teaching and Service

I am passionate about teaching, and have taught a wide variety of courses ranging from firm competition and strategy to behavioral economics. I've given guest lectures in a variety of courses including Gender Economics at Yale University and Fairness at NYUAD. My teaching philosophy is that students should come prepared and discuss various topics, rather than listen to a lecture passively. 

I'm was previously elected to serve on the board of the Norwegian School of Economics, and was part of the recruitment committee 2020 and 2021 for positions in labor and behavioral economics. 

I hold an M.Sc from the Stockholm School of Economics and a B.Sc. from Humboldt University of Berlin. I regularly refree for journals such as QJE, JPE:Micro, AER, AEJ: Applied, AEJ: Policy, AEJ: Micro, JHR, Management Science, Games and Economic Behavior, JEBO, Economic Journal, Science, European Economic Review, Scandinavian Journal of Economics, Revue Économique, Journal of the Economic Science Association, Economic Inquiry, Theory and Decision and others.

PUBLICATIONS:

Co-authored with: Colin F. Camerer and others:

"Evaluating the replicability of social science experiments in Nature and Science between 2010 and 2015", Nature Human Behaviour. 2018

Camerer CF, Dreber A, Forsell E, Ho TH, Huber J, Johannesson M, Kirchler M, Almenberg J, Altmejd A, Chan T, Heikensten E, Holzmeister F, Imai T, Isaksson S, Nave G, Pfeiffer T, Razen M, Wu H. “Evaluating replicability of laboratory experiments in economics.” Science. 2016

Dreber, Anna, Thomas Pfeiffer, Johan Almenberg, Siri Isaksson, Brad Wilson, Yiling Chen, Brian A. Nosek & Magnus Johannesson (in press). “Using Prediction Markets to Estimate the Reproducibility of Scientific Research”. Proceedings of the National Academy of Sciences.  2015

WORK IN PROGRESS:

 *NEW*[JOB MARKET PAPER] "Will Articifical Intelligence get in the way of achieving gender equality?" (with Daniel Carvajal and Catalina Franco) 

Abstract: We conduct two survey experiments to examine gender differences in generative AI adoption and potential labor market consequences. First, we document a substantial gender gap among students at a top business school in Norway, with female students, particularly top students, opting out of AI use. Second, a survey of managers shows acquiring AI skills significantly enhances job prospects for top female students currently opting out. Finally, we provide causal evidence on policy tools to close this gap. Our findings show generative AI could widen existing gender gaps in the labor market, but appropriate encouragement and policies can prevent this outcome. [UNDER REVIEW]

“Will AI Help or Hurt Learning?”(with Catalina Franco and Natalie Irmert) [Draft available upon request]

Abstract: As AI reshapes how students learn, it raises pressing concerns about ensuring equitable learning opportunities and outcomes. A key question is who benefits from AI and who may be left behind. We address this question through a preregistered lab experiment (N=572) examining AI’s impact on learning. Students were randomly assigned to one of three conditions: (1) Control (access to Google Search only), (2) AI-assisted (AI access), or (3) AI-guided (AI access with guidance), and were tasked with learning a novel topic that they had no prior knowledge of. At the end of the experiment, participants completed an exam without AI access, allowing us to causally estimate the effects of AI on learning outcomes. While AI has no overall effect on exam performance, this null masks a significant heterogeneous effect: high-GPA women benefit, while low-GPA men perform worse, raising concerns about whether AI will widen pre-existing educational inequalities. By analyzing participants’ prompt data, we gain insight into the mechanisms behind these effects and identify how different groups interact with AI and how this in turn affects learning outcomes. Our findings reveal that AI may exacerbate learning gaps, providing key insights for designing policies that can mitigate this risk.

“It Takes Two: Gender differences in in group work.- Part II” [Draft in progress]

Abstract:This study analyzes gender differences in two dimensions of attribution of credit for successful group work: 1. Are women attributed less than appropriate credit for their contributions to group work? 2. Does the fact that women claim less credit for their contributions to group work affect how much credit they end up getting? In addition, it explores mechanisms that may be driving results. I finf that female and male claims are evaluated equally, indicating that women should claim as much credit as their male counterparts for successful group-work. Pre-plan available here: OSF 

“It Takes Two: Gender differences in in group work.” 

Abstract This study tests for gender differences in credit claimed for individual contributions to group work. I introduce a novel experimental design in which two subjects work together on solving a computerized puzzle, by making alternating moves. Participants play nine rounds, each time with a new partner and puzzle. After each puzzle, they are asked to estimate their contributions towards the solution in incentivized questions. There are no gender differences in ability: women and men are equally good at solving the puzzle both individually and in teams. Despite their equal contribution, women consistently claim less credit than men. This effect is strongest among high contributing women, and women in groups that implemented more complex solutions. I also explore the propensity of participants to undo a partner's move, and I find that men are more likely to correct a partner when he or she made a move that was wrong. These results suggest that gender differences in claiming credit may contribute to the labor market gender gap.

Working paper: https://www.dropbox.com/s/hafhh70p3li9tij/1120jmp.pdf?dl=0 

“In favor of girls: A field study of adults' beliefs in children's ability.” (with Emma Heikensten). [UNDER REVIEW]

Abstract In this paper, we examine whether adults (N=123) engage in gender discrimination when seeking advice from children (N=38). To answer this question, we collect data from the five seasons of the Swedish Game Show  “Are you smarter than a 5th grader?” where adult contestants choose a boy or a girl from 5th grade to help them earn large amounts of money by answering questions from the primary school curriculum. We observe that girls are 9.5 percentage points more likely to be asked for advice than boys. This corresponds to a 18,1 percent gap in favor of girls. The favoritism is not rational since boys and girls perform equally well.

“Simon Says: Examining gender differences in advice seeking and influence in the lab.” (with Emma Heikensten). 

Abstract Advice seeking is an important part of both professional and personal decision making. In this paper, we investigate gender differences in the propensity to seek costly advice and if the gender of the advisor influences this decision. Over two treatments, we vary the amount of information that advisees receive about advisors on the quality of their advice. We also use two types of questions, mathematical and verbal, to test the effect of stereotyped domains. Our findings suggest that women seek less advice than men. This result is driven by men seeking more advice on verbal tasks, and women seeking less advice when information about it's quality is introduced. Furthermore, the advisor's gender does not influence the decision to seek advice and we do not find that advisees seek more (or less) advice from advisors of the same gender.

Working paper: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3273186 

“Gender differences in revenge and strategic play: a natural experiment.” (with Sirus Dehdari Emma Heikensten and Mateusz Myliwski).

Abstract This paper provides new evidence of gender differences in retaliatory behavior. Using game show data from a natural setting where stakes are high, we ask whether men are more likely to retaliate following an attack and whether the gender of the target matters for this decision. The behavior studied in this paper is the decision of whom to send the question to in a quiz show setting. We observe a 23 percent gender gap in the propensity to retaliate:  women are less likely to seek revenge. The gender of the target matters for women but not for men, with women being more likely to retaliate against men than women. In addition, we show that retaliation is a successful way to avert future attacks in the short term. This is especially true for women, yet we find that women seek less revenge than men.[R&R at GEB]

Working paper: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3378279 

TEACHING EXPERIENCE:

Behavioral Economics (Graduate) - 2021-2024 

Student Evaluation: 4-4.5/5

Firm Strategy and Competition (Undergraduate)- Fall 2021

Student Evaluation: 4.48/5

Human Capital, Mobility, and Diversity in Firms (Graduate) - Fall 2020-2022

Student Evaluation: 4.2-4.45/5

In addition, I have moderated class discussions in the Undergraduate course in International Trade 2020 - 2024.

During graduate studies:

Microeconomics II (PhD) - Fall 2015

International Economics (Undergraduate) - Fall 2014 

Introduction to LaTeX (at Humboldt Universität zu Berlin) - Fall 2010 

COLLABORATORS:

Adam Altmejd

Daniel Carvajal

Tatiana Celadin

Sirus Dehdari

Clémentine van Effenterre

Catalina Franco

Fabio Galeotti

Emma Heikensten

Astrid Hopfenstiz

Sa-Kiera Hudson

Natalie Irmert

Valeria Maggian

Mateusz Mysliwski

Ingvild Lindgren Skarpeid

Adam Zylbersztejn

SUPERVISION:

Nina Rapoport - I will serve on the defense committee

Pablo Soto Mota  I served as first opponent

Vegard Sjurseike Wiborg  (PhD 2022) - I served as 1st opponent

Yuki Takahashi (PhD 2022 ) - I serve on the evaluation committee

Master thesis: 

2025

Vilde Areklett and Ivar Lande

2024

Jan Nartley and Anders Jøsøk

Solveig Engen and Lise Mellefsen 

Torbjørg Synnøve and Elsie Baldishol 

Amanda Apolinario

2023

Hyunyi Um and Joelle Soumi 

Juni Holberg and Sara Sadeghi Khosroshahi  

Ada Hetland 

Ingeborg Kolstad and Hanne Skattemyr 

2022

Siri Sandnes and Marlen Garli 

COMMUNITY WORK:

I love contributing to culture and my community. I care deeply about and try to promote gender equality and diversity. Towards this end, I have served in various positions both voluntarily and as part of my job. 

I am also a founding board member of the first Jewish organization in Bergen.  I  frequently serve on panels  and other fora  to discuss how to promote gender equality.