Within the scope of this study, great importance is attached to compliance with data protection regulations, the protection of privacy, and the confidentiality of the data. We strictly adhere to all applicable laws and regulations on data protection, including the EU General Data Protection Regulation (GDPR) and the Swiss Federal Act on Data Protection (FADP). With these notes we inform you about the processing of your personal data and the rights to which you are entitled.

Research team

This study is run by a research team based at ETH Zurich, The Wharton School of the University of Pennsylvania, Emory University (Goizueta Business School), and the University of St. Gallen.

Principal investigator: Max Gaerth, Emory University Goizueta Business School (maximilian.gaerth[at]emory.edu).
Data manager (contact for data-protection requests): Hauke Roggenkamp, ETH Zurich (hauke.roggenkamp[at]mtec.ethz.ch).


What data we collect

This study collects the following data:


How your recordings will be used

Your recordings are collected to study how people express preferences and confidence out loud when they decide with limited information. They will be analysed statistically. For example, we transcribe what was said and measure simple acoustic properties such as pitch and timing.


Legal basis for processing

The legal basis for processing your personal data is your freely given, informed consent (GDPR Art. 6(1)(a)). You may withdraw this consent at any time (see below).


Third-party data processors

To operate this study, your data is processed by the following third-party services:


Data retention and storage

Voice recordings will be transferred from Amazon S3 to a password-protected hard drive held at ETH Zurich within two weeks of data collection, after which they will be deleted from AWS. All study data, including recordings and survey responses, will be retained for as long as is necessary for the research and any resulting publications, in accordance with ETH Zurich's data retention policies.

Results of the analyses may be published at an aggregate level in an academic journal. Pseudonymised data (identified only by a random participant code, not by name or voice) may be shared with journal data editors as part of the peer-review process for a resulting publication. Raw voice recordings will not be made publicly available.


Confidentiality and pseudonymisation

Your responses are linked only to a randomly assigned participant code, not to your name. Voice recordings are potentially identifiable and are therefore not considered fully anonymous. Access to the raw data is restricted to members of the research team and, where required for publication, to journal data editors under equivalent confidentiality obligations.


Withdrawal from participation or consent

Participation in this research project is voluntary. You have the right at any time to withdraw from the study without stating a reason. You also have the right to withdraw your consent, which will result in your data being deleted so that it can no longer be linked to you. To exercise this right, contact the data manager, Hauke Roggenkamp (hauke.roggenkamp[at]mtec.ethz.ch), and provide your participant code: {{ participant.code }}


Your rights

Under applicable data protection law you have the right to:

To exercise any of these rights, contact the investigator by e-mail and provide your participant code: {{ participant.code }}


By agreeing to these terms you consent to the following statement:
"I am 18 years of age or older. I have read and understood this privacy policy. I consent to participate in this study and to the processing of my personal data, including voice recordings, as described above. I understand that my voice recordings are pseudonymous and potentially identifiable, and that they will be temporarily stored on Amazon AWS before being transferred to a secure hard drive at ETH Zurich. I understand that my recordings will be analysed statistically for research on decision-making and voice, that they will not be used to train or build any machine-learning model and will not be used to clone or synthesise my voice, and that I may request the deletion of my data at any time by contacting the data manager, Hauke Roggenkamp (hauke.roggenkamp[at]mtec.ethz.ch). I understand that I will not have any financial benefits that result from the commercial development of this research."