activity
20242026
collaborators

5 papers

cs.HC2026

Beyond AI advice -- independent aggregation boosts human-AI accuracy

Julian Berger, Pantelis P. Analytis, Ville Satopää +1

Artificial intelligence (AI) is broadly deployed as an advisor to human decision-makers: AI recommends a decision and a human accepts or rejects the advice. This approach, however,…

cs.HC2026

The hybrid confirmation tree: A robust strategy for hybrid intelligence

Julian Berger, Pantelis P. Analytis, Frederik Andersen +3

Combining human and artificial intelligence (AI) is a potentially powerful approach to boost decision accuracy. However, few such approaches exist that effectively integrate both t…

cs.HC2025

Human learning is an understudied but promising lever for boosting human--AI synergy

Julian Berger, Jason W. Burton, Ralph Hertwig +9

Humans collaborating with artificial intelligence (AI) hold the promise of achieving superior outcomes compared to either acting alone (i.e., human--AI synergy). However, the condi…

cs.AI2024

Human-AI collectives produce the most accurate differential diagnoses

N. Zöller, J. Berger, I. Lin +10

Artificial intelligence systems, particularly large language models (LLMs), are increasingly being employed in high-stakes decisions that impact both individuals and society at lar…

cs.GT2024

Strategic Network Creation for Enabling Greedy Routing

Julian Berger, Tobias Friedrich, Pascal Lenzner +2

Today we rely on networks that are created and maintained by smart devices. For such networks, there is no governing central authority but instead the network structure is shaped b…