In with the new? Generational differences shape population technology adoption patterns in the age of self-driving vehicles K Ruggeri, O Kácha, IG Menezes, M Kos, M Franklin, L Parma, P Langdon, ... Journal of Engineering and Technology Management 50, 39-44, 2018 | 45 | 2018 |
Optimising nudges and boosts for financial decisions under uncertainty M Franklin, T Folke, K Ruggeri Humanities & Social Sciences Communications 5 (1), 1-13, 2019 | 43 | 2019 |
Blaming automated vehicles in difficult situations M Franklin, E Awad, D Lagnado Iscience 24 (4), 2021 | 34* | 2021 |
Recognising the importance of preference change: A call for a coordinated multidisciplinary research effort in the age of AI M Franklin, H Ashton, R Gorman, S Armstrong The AAAI-22 Workshop on AI For Behavior Change (AI4BC 2022), 2022 | 23 | 2022 |
A proposal for a definition of general purpose artificial intelligence systems CI Gutierrez, A Aguirre, R Uuk, CC Boine, M Franklin Digital Society 2 (3), 36, 2023 | 22 | 2023 |
The problem of behaviour and preference manipulation in AI systems H Ashton, M Franklin Proceedings of the Workshop on Artificial Intelligence Safety 2022 (SafeAI …, 2022 | 21 | 2022 |
Missing mechanisms of manipulation in the EU AI Act M Franklin, H Ashton, R Gorman, S Armstrong The International FLAIRS Conference Proceedings 35, 2022 | 16* | 2022 |
Causal framework of artificial autonomous agent responsibility M Franklin, H Ashton, E Awad, D Lagnado Proceedings of the 2022 AAAI/ACM Conference on AI, Ethics, and Society, 276-284, 2022 | 14 | 2022 |
A study protocol for testing the effectiveness of user-generated content in reducing excessive consumption A Herziger, A Benzerga, J Berkessel, NL Dinartika, M Franklin, ... Frontiers in Psychology 8, 241217, 2017 | 12 | 2017 |
Testing a definition of intent for AI in a legal setting H Ashton, M Franklin, D Lagnado Submitted manuscript, 2022 | 9 | 2022 |
Explanations that backfire: Explainable artificial intelligence can cause information overload AN Ferguson, M Franklin, D Lagnado Proceedings of the Annual Meeting of the Cognitive Science Society 44 (44), 2022 | 7 | 2022 |
Solutions to preference manipulation in recommender systems require knowledge of meta-preferences H Ashton, M Franklin arXiv preprint arXiv:2209.11801, 2022 | 6 | 2022 |
Designing memory aids for dementia patients using earables M Franklin, D Lagnado, C Min, A Mathur, F Kawsar Adjunct Proceedings of the 2021 ACM International Joint Conference on …, 2021 | 6 | 2021 |
Unpredictable robots elicit responsibility attributions. M Franklin, E Awad, H Ashton, D Lagnado Behavioral & Brain Sciences 46, 2023 | 5 | 2023 |
The Influence of Explainable Artificial Intelligence: Nudging Behaviour or Boosting Capability? M Franklin arXiv preprint arXiv:2210.02407, 2022 | 5 | 2022 |
Human-AI interaction paradigm for evaluating explainable artificial intelligence M Franklin, D Lagnado International Conference on Human-Computer Interaction, 404-411, 2022 | 4 | 2022 |
Virtual Spillover of preferences and behavior from extended reality M Franklin In the Conference on Human Factors in Computing Systems (CHI ’22) Workshop …, 2022 | 3 | 2022 |
A Mechanism-Based Approach to Mitigating Harms from Persuasive Generative AI S El-Sayed, C Akbulut, A McCroskery, G Keeling, Z Kenton, Z Jalan, ... arXiv preprint arXiv:2404.15058, 2024 | 2 | 2024 |
An International Consortium for AI Risk Evaluations R Gruetzemacher, A Chan, Š Los, K Frazier, S Campos, M Franklin, J Fox, ... Socially Responsible Language Modelling Research, 2023 | 2* | 2023 |
The corrupting influence of AI as a boss or counterparty H Ashton, M Franklin | 2 | 2022 |