John Zerilli

860 citations
19 papers · 518 · 1 hit paper · h-index 7

Impact in

Papers in

John Zerilli

13 papers receiving 461 citations

John Zerilli's Hit Papers

How transparency modulates trust in artificial intelligence 2022 · 116 citations
1160+1+2Years since publication255075100

Peers

John Zerilli
Comparison fields: 5 of 79
  • Health Informatics 96
  • Safety Research 245
  • Artificial Intelligence 202
  • General Decision Sciences 9
  • Cognitive Neuroscience 86
Replace Nina Grgić-Hlača with:
Nina Grgić-Hlača Germany
Maurice Jakesch United States
Hao-Fei Cheng United States
Hasan Mahmud Bangladesh
Anat Elhalal United Kingdom
Daniel Susser United States
Jason W. Burton United Kingdom
Jess Whittlestone United Kingdom
Janghee Cho United States
Pratyusha Kalluri United States
John Zerilli relative to Nina Grgić-Hlača Germany Nina Grgić-Hlača's profile →
Citations per field
00.5×1.5×1.8×
Nina Grgić-Hlača · 1×
Citations per year

Countries citing papers authored by John Zerilli

Since Specialization
Citations

This map shows the geographic impact of John Zerilli's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by John Zerilli with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites John Zerilli more than expected).

Fields of papers citing papers by John Zerilli

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by John Zerilli. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by John Zerilli. The network helps show where John Zerilli may publish in the future.

Co-authors

The 6 scholars most cited alongside John Zerilli, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with John Zerilli Line = papers co-authored together John Zerilli links everyone, so they are left out of the graph.

All Works

19 of 19 papers shown
#Work
1 2018252
2
How transparency modulates trust in artificial intelligence
Hit paper breakdown →
2022116
3 201984
4 202114
5
Government Use of Artificial Intelligence in New Zealand
201913
6 201711
7 20187
8 20225
9 20175
10 20213
11 20193
12 20142
13 20071
14 20211
15 20061
16 20210
17 20220
18 20220
19 20200

About John Zerilli

John Zerilli is a scholar working on Social Psychology, Safety Research, Cognitive Neuroscience, Experimental and Cognitive Psychology and Political Science and International Relations, having authored 19 papers that have together received 518 indexed citations. Recurring topics across this work include Ethics and Social Impacts of AI (5 papers), Artificial Intelligence in Law (3 papers), Embodied and Extended Cognition (3 papers), Action Observation and Synchronization (3 papers), Language and cultural evolution (2 papers), Law, Economics, and Judicial Systems (2 papers), Human-Automation Interaction and Safety (2 papers) and Philosophy and Theoretical Science (2 papers). The work is most often cited by research in Health Informatics (96 citations), Safety Research (245 citations), Artificial Intelligence (202 citations), General Decision Sciences (9 citations) and Cognitive Neuroscience (86 citations). John Zerilli has collaborated with scholars based in United Kingdom, New Zealand and Australia. Frequent co-authors include James Maclaurin, Alistair Knott, Colin Gavaghan, Umang Bhatt, Adrian Weller and John Danaher. Their work appears in journals such as Philosophy of Science, Biological Theory, Synthese, Philosophical Psychology and Minds and Machines.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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