The Datafication of Travel in SARS-CoV-2 Times: Perceptions of Graduates in Estonia towards the Use of Passenger Locator Forms and Reinforcement Learning System EVA

digital

Article

Magazine

Fascicle

COMUNICAZIONI SOCIALI - 2022 - 2. Sustainable Screenings: Economic, Touristic and Cultural Impact of Audiovisual Productions on the Host Locations in the Post-Lockdown Era

Title

The Datafication of Travel in SARS-CoV-2 Times: Perceptions of Graduates in Estonia towards the Use of Passenger Locator Forms and Reinforcement Learning System EVA

Authors

Anu Masso, Olga Reili

Publisher

Vita e Pensiero

Format

Article |

Pdf

Online from

11-2022

Doi

10.26350/001200_000160

Issn

0392-8667 (print) | 1827-7969 (digital)

Write a comment for this product

€ 6.00

Ebook format Pdf readable on these devices:

Computer
with Software:
- Adobe PDF Reader
Android
iPhone/Ipad
with App:
- Adobe PDF Reader
E-Book Reader
Ibs Tolino
Kobo

Description Readers' comments

The Covid-19 pandemic provoked greater digitalisation of personal data and deepened the ongoing process of algorithmic governance. In order to reopen to tourism and balance the spread of the virus while keeping travellers and locals safe, countries established various rules for border crossing, such as digital passenger locator forms (PLFs), while some countries, such as Greece, implemented an algorithm (EVA) to analyse these PLFs. This transfer of data raises important questions about personal data privacy rights and informed consent. This study explored the perceptions of travellers towards these new rules, the sharing of additional personal data, and their imaginaries of the possible algorithmic work behind it. Qualitative interviews were conducted with ethnic Estonian and Russian-speaking Estonian graduates in Estonia (n=14) regarding their insights on (1) the perceived norms of sharing personal data and the use of the data by governmental authorities while travelling and (2) the perceptions of datafied/algorithmically controlled travel during the pandemic, with additional insight on the differences between the two groups. The interviewees weren’t against the PLFs or algorithmic processing in principle, but where they saw poor implementation or design, or where they felt that things had been done in semi-secrecy. According to the interviewees, datafication and algorithmic governance require deeper consideration of transparency, clarity, and communication to achieve truly informed consent and resolve unease with the creeping influence of algorithms.