Sirvi Autor "Leets, Peeter" järgi

Nüüd näidatakse 1 - 3 3

listelement.badge.access-status Avatud juurdepääs ,
Augmenting public sector data-driven decision support systems with expert knowledge: case of OTT
(Tartu Ülikool, 2022) Leets, Peeter; Solvak, Mihkel, juhendaja; Võrk, Andres, juhendaja; Tartu Ülikool. Sotsiaalteaduste valdkond; Tartu Ülikool. Johan Skytte poliitikauuringute instituut
Public sector data-driven decision support systems are uniquely challenging to design due to the ramifications they have on the societal level. Accountability and ethical considerations require these systems to arrive at an equilibirium between accuracy and interpretability amid various implementation and data constraints. While these systems need to contribute to legitimate governance through reasoned and explainable decision-making, they also need to accurately model the policy outcomes they were designed to support. Inopportunely, inductive data-driven systems struggle to solve problems that rely on heuristic input. In this thesis, a particular knowledge engineering technique was adopted to augment a public sector Machine Learning decision support tool with domain expert knowledge. The case in question is OTT – a job-seeker profiling tool used by the Estonian Unemployment Insurance Fund to predict the long-term unemployment risks of their clients. Upon augmenting it with knowledge from caseworkers and data scientists associated with the project, some evidence was found that accounting for expert knowledge in probabilistic data-driven models can lead to a model that performs better on new out-of-sample data and is more in line with underlying domain rules. This yields important implications on the future of Machine Learning in the public sector as it opens up new potential use cases in avenues where 1) labelled training data is hard to come by, 2) a more generalizable model is preferred due to frequent changes in the surrounding context, 3) a model has to perfectly mimic domain logic for interpretability and explainability reasons.
listelement.badge.access-status Avatud juurdepääs ,
Individuaalse hääle verifitseerimise võimaluse mõju usaldusele e-valimiste vastu
(Tartu Ülikool, 2020) Leets, Peeter; Solvak, Mihkel, juhendaja; Tartu Ülikool. Sotsiaalteaduste valdkond; Tartu Ülikool. Johan Skytte poliitikauuringute instituut
Individuaalse hääle verifitseerimine on komponent turvalisest e-valimissüsteemist, millel on kaks põhilist ülesannet: süsteemivastaste rünnete tuvastamine ning e-hääletaja usalduse tõstmine e-valimiste vastu. Käesolev uurimus keskendub viimasele ning püüab empiirilistele andmetele tuginedes seletada, kas ja mil määral on Eestis 2013. aastal kasutusele võetud verifitseerimine valija usaldustaset mõjutanud. Usalduse ja verifitseerimise vahelist seost uurisid 2016. aastal põgusalt Mihkel Solvak ja Kristjan Vassil. Toona kolme üleriigilise valimise põhjal tehtud uuring näitas, et verifitseerimise kasutamine usaldusele olulist mõju ei avaldanud, sest rakendust kasutas väga väike ja unikaalne grupp e-hääletajaid, keda iseloomustas muuhulgas kõrge arvutikasutusoskus ning kalduvus e-valimisi juba eos usaldada. Kuna tehnoloogia areneb tänapäeval kiiresti, oli paslik nüüd, neli aastat hiljem, verifitseerimise ja valija usalduse vaheline seos taas luubi alla võtta. Käesolevas töös analüüsiti valimisjärgseid läbilõikeküsitlusi ja tõlgendati tulemusi tehnoloogia usaldust ja difusiooni seletavate teooriatega. Selgus, et verifitseerimine on varajases innovatsioonijärgus ning seda kasutab endiselt väga spetsiifiliste tunnuste ja kõrge usaldustasemega e-valijate grupp, mistõttu efekt valija usaldustasemele tegelikkuses praktiliselt puudub. Asjaolu, et verifitseerimine ei ole kuute valimiste jooksul laiema kasutajaskonna seas levima hakanud, võib tähendada seda, et rakendus ei pruugi sellisel kujul ka tulevikus valija usaldustaset mõjutama hakata.
listelement.badge.access-status Avatud juurdepääs ,
State versus Technology: What drives trust in and usage of internet voting, institutional or technological trust?
(Elsevier, 2025-09-05) Romanov, Bogdan; Duenas Cid, David; Leets, Peeter
This study examines the combined influence of technological and institutional trust on citizens’ perceptions of and engagement with Internet voting, addressing gaps in the literature on digital governance and trust. While prior research often treats these trust dimensions separately, this article explores their interplay within the context of Estonia, which has utilized Internet voting for two decades. By constructing composite indices for technological and institutional trust through factor analysis, the study offers a novel methodological approach to operationalizing trust in digital governance (within the article, digital governance and e-governance are used interchangeably) research in general and Internet voting in particular, based on post-electoral survey data. Applying linear and logistic regression analyses, the study explicitly examines how these trust dimensions affect citizens’ trust in Internet voting systems and their actual use of such technology. The findings reveal that institutional trust is significantly more influential than technological trust, consistently emerging as the primary driver for both trusting Internet voting and engaging in its usage. Technological trust, in contrast, demonstrates only marginal predictive strength, highlighting the greater importance citizens place on institutional legitimacy, transparency, and accountability. These results emphasize the compensatory nature of institutional trust, suggesting that robust institutional frameworks allow citizens to confidently engage with complex technological systems despite limited technical understanding. Consequently, this research enhances theoretical insights into trust dynamics within digital governance, particularly in contexts where political sensitivity and institutional credibility significantly impact technology adoption.