Nabídka expertů z Boloňské univerzity - právní aspekty datové ekonomiky, jazykové technologie, AI a společnost

Podrobnosti naleznete níže. Pro zprostředkování kontaktů se obraťte na NCP Lenku Švejcarovou (svejcarova@tc.cz).

- Legal aspects of the data economy, fintech, consumer protection, and data protection law.

- Human performance/interaction assessment in truly mixed human AI scenarios. Expertise in neurophysiological bases of perception, action, goal achievement. We are interested in achieving common goals between humans and AI systems working together as partners to achieve common goals, sharing mutual understanding and learning of each other’s abilities.

- Language technologies, especially argument mining, that is the automatic detection of evidence/claims from textual corpora and the extraction of the underlying structure of argumentation. Applications in debating technologies and decision-support systems helping context interpretation, dealing with uncertainty and multiple possibly conflicting viewpoints of topics, identification of keypoints and their relations, serving transparent, fair and accurate human-centric planning and decision-making.

- Artificial Intelligence (e.g. Machine Learning, Constraint Programming), Optimization methods (e.g. Mathematical Programming, meta-heuristics), and their integration (e.g. joint prediction and optimization problems, constraints and domain knowledge in learning, optimization under uncertainty); Scheduling, energy systems, maintenance of industrial components, optimization for computing systems (both low-power and High Performance Computing), decision support in a smart-city context, and a few health topics. Possible contributions along this topic: 1) User-specified constraints in Machine Learning; 2) Using ML method to model human goals, and update such models based on feedback; 3) Integrating symbolic and sub-symbolic methods to improve fairness and safety of decision support systems.

- Social and public perception of AI: how citizens acceptance of AI technology could influence and shape acceptance, uses and further technological development. Relevant links with digital divide and digital inequalities research. Narratives, expressed through hopes and fears, about AI can influence user adoption and awareness. Bias in algorithm and Ai-based system: especially how gender and race are in-built biases that reproduce existing inequalities by design (eg. facial recognition systems; algorithms used in policing, insurance and banking decisions). Smart city and inequality: how a top down model of designing a smart city can create lock-ins and reproduce social and economic inequalities at the urban level (also in the new concept of twin city). The platformization of the economy and society: how platforms - as new social arrangements and a new organizational principle - can relate to a more Humane AI.

- Multidisciplinary approach integrating research methods and theoretical frameworks focusing on health-centred research. Research in behavioural, psychosocial, cognitive, neuropsychological, psychophysiological (skin conductance, heart rate, electromyography) approaches that have been used to develop cognitive models for the understanding and the evaluation of non-pharmacological strategies of preventions and interventions. End-user analysis and central design principle were the basis of two EU funded projects. The groups capitalise on the co-design approach in developing technologies: the act of creating with stakeholders within the design development process to ensure the results meet their needs and are usable. Expertise in patients and public involvement (PPI), where patients and caregiver’s involvement foster products development by bringing into question naive insights, realistic problems and real-life experiences. Evaluation of people’s acceptance in terms of perceived utility, ease of use, acceptability and adequacy of the proposed solution.