14th November 2023
Room “Sala Seminari” – Abacus Building (U14)
Preserving Human Agency in Hybrid Decision-Making via “Frictional” Decision Support Systems
Designing in the field of Artificial Intelligence (AI) goes beyond simple programming: it is a process that shapes the way we make decisions, interact and think about these advanced systems. But how can we design an ethical collaboration between humans and AI, fostering a form of hybrid intelligence?
In her talk, Chiara Natali will present her research on the risks of over-reliance on AI systems, presenting insights and proposals to protect our decision-making autonomy through a conscious, “frictional” design of our interaction with intelligent systems. This talk will also be an opportunity to reflect on the impact, both individual and collective, of only apparently neutral design choices.
Data Structures for SMEM-Finding in the PBWT
The positional Burrows–Wheeler Transform (PBWT) was presented as a means to find set-maximal exact matches (SMEMs) in haplotype data via the computation of
the divergence array. Although run-length encoding the PBWT has been previously considered, storing the divergence array along with the PBWT in a compressed
manner has not been as rigorously studied. In this talk, I will present two queries that can be used in combination to compute SMEMs, allowing us to define smaller data structures that support one or both of these queries. I will explain how we combine these data structures, enabling the PBWT and the divergence array to be stored in a manner that allows for finding SMEMs. Finally, I will discuss the memory usage of these data structures, leading to μ-PBWT, the data structure that is most memory efficient. To prove these
results, I will show some results on two real datasets: the 1000 Genomes Project data and the UK Biobank data.