AIOS Midterm Exam Prep
INFO-AIOS — Friday, May 29, 2026 at 11:00–13:00, EDUC-BETA (Rupert D for extra time). Laptops provided. 9 essay questions, 2 hours.
Resources: Schedule | Flashcards | Mock Exam | Slides (PDFs)
Lectures
| # | Topic | Coverage |
|---|---|---|
| L1 | Intro & IOS | Open Society (4 elements), institutions (formal/informal), IOS framework (3 pillars / 15 platforms), Elliott et al. 2021 (TRUST + CDR) |
| L2 | Decision Making | Newell time scales, three levels of cognitive integration, ACT-R smart fact learning, Linear Ballistic Accumulator, Palada et al. 2016 (workload + ATC) |
| L3 | Autonomy | Rahwan et al. 2019 Machine Behaviour (3 scales × 4 domains), digital traces, Kosinski 2013, Hinds & Joinson 2019, Matz 2017, Kramer 2014 |
| L4 | Collective Patterns | Emergence, Coleman bathtub, five analytic concepts, Hegselmann-Krause bounded confidence, Douven & Hegselmann 2021 (3 agent types) |
| L5 | Linguistic Models | NLP basics, Perspective API, dictionary NLP, van der Vegt 2023, Dutch politicians study, Baele 2024 incels, CTAP-25 |
| L6 | Medical AI & Digital Twins | Classification vs stratification, Van Rooij's three topics, Bontje digital twins SWOT, Wang et al. 2023 federated edge |
| L7 | Trust in AI | ⚠️ paper-only. Trust components, algorithm aversion vs appreciation, Grimmelikhuijsen & Meijer 2022 (six threats + calibrated response), toeslagenaffaire |
| L8 | Synthesis | Includes in-class mock + model answers, plus the four-level scaling framework (cognition→psychology→networks→society) |
Key warning
Lecture 7 (Grimmelikhuijsen + Liefooghe) has no slide deck in the course folder — summary is built from the obligatory paper + general literature. Verify against any slides shared on Teams. Paper 7 (Wang et al.) was summarised from title + general federated-learning knowledge, not the full PDF.