Lecturer of Applied AI Armando Vieira shares his thoughts on Medium, an online publishing platform. The dominant discourse on AI alignment rests on a quiet but catastrophic assumption: that morality can be imposed on systems that do not experience anything. The debate unfolds as if values were transferable objects — encoded, optimized, constrained — rather than lived […]

The dominant paradigm in modern AI rests on a deceptively simple premise: intelligence emerges from minimizing prediction error across vast datasets. We train neural networks to be accurate, to match patterns, to reduce loss functions. Yet this approach, for all its empirical success, may be fundamentally misaligned with the nature of intelligence itself. Here is […]

Protests and conflicts have become influential forces for bringing about change and shaping the political and social landscapes not only on a local demographic level but also on a global scale. In the modern Internet and online social media era, protests have increasingly utilized digital platforms to facilitate discussions, coordinate actions, and spread respective agendas. […]

With the development of Online Social Media (OSM) platforms like Twitter and Facebook, the way individuals connect and exchange information has changed dramatically. These platforms have, however, also led to the problem of misinformation, which can quickly spread on a global scale, and once it has been disseminated, it can be hard to stop. It […]

Introduction: Privacy-preserving computation is a crucial discipline that protects the privacy of confidential data while facilitating secure analysis. In graph problems, secure multiparty computation (SMC) presents a promising approach to performing these functionalities. This article delves into the notable advancements in privacy-preserving parallel algorithms recently introduced in a Ph.D. thesis. By integrating graph algorithms with […]

Machine Translation is a quickly growing field of Natural Language Processing (NLP) that automatically translates a text from one language to another without human involvement.  In recent years, the use of machine translation systems has increased dramatically. Today machine translation is used not only by translation agencies but also by people using online machine translation […]

The cornerstone of democracy is the right for voters to participate in free and fair elections. However, securing elections is a non-trivial task due to the conflicting security requirements.  On the one hand, to provide the freedom to vote, it should not be possible to coerce voters into voting for a specific candidate. Therefore, the […]

The original article (in Estonian) by Airika Harrik was published in Novaator. Estonia has used the ID card system as a means to identify its citizens for almost 20 years. During those years, several security issues have emerged. A new PhD dissertation from the University of Tartu has shed light on those issues and pointed […]

On December 21, Madis Vasser defended his PhD thesis „Testing a Computational Theory of Brain Functioning with Virtual Reality“. In his thesis, he investigated the concept of active inference (AI) using virtual reality (VR) devices. During the work they developed VR software, conducted experiments on human study participants and compiled a set of guidelines for […]

On Friday, August 28 Janno Siim defended his PhD thesis „Non-Interactive Shuffle Arguments„ A fundamental requirement for all democratic governments is a secure voting system. In recent years some countries, like Estonia and Switzerland, have adopted internet voting (i-voting), and many more have experimented (e.g., Norway and Australia) or have plans to adopt it in […]

On the 13th of August Karim Baghery defended his PhD thesis „Reducing trust and improving security in zk-SNARKs and commitments„ in which he studied the zk-SNARKs from two different perspectives, namely reducing trust in their setup phase and improving their security in different applications. On the need for proof systems People frequently are asked to […]

On the 21st of February, Faiz Ali Shah defended his PhD thesis on “Extracting information from app reviews to facilitate software development activities” which evaluates the existing Text Mining techniques for extracting developer-relevant information from app reviews at different levels of granularity, and then combined these techniques to develop a tool REVSUM for competitive analysis. […]