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Dr. Martin Cunneen

Biography

I am a lecturer in Data Analytics and Risk Governance in the Accounting and Finance dept. in the Kemmy Business School, University of Limerick. My research focuses on investigating the science of Data Analytics in terms of societal relations. This often concerns questions and topics relating to Explainable AI (XAI), Algorithmic Bias, Black Box decision making, Data Profiling, Data Commodification and Risk, Autonomous Vehicle Decision making, InsurTech, AI in Education, AI Assistants (Language theory & NLP) and Societal Risks due to Data Profiling. I am also interested in AI and technology for social good and especially the use of innovation to support climate risk mitigation.

Research Interests

    Dr Martin Cunneen investigates the societal impacts of Machine Intelligence applications under the umbrella of Data Analytics, AI, ML and Robotics. His research focuses on the challenge to anticipate and provide informed and timely 'Governance' instruments in response to commercial applications of these technologies. With years of professional tech sector experience from sustainable technology initiatives, EdTech, community programming projects to Big Data, his research continually examines the complexities of socio-technological relations. In developing his research, he has fashioned a unique framework to support multi-stakeholder engagement in terms of socio-technological risk and ethics. His research is also supported by years of teaching applied ethics, analytical philosophy, and philosophy of AI & technology. He is a senior member of the Emerging Risk Group (ERG) and a member of the Accountability Research Cluster (ARC) at The University of Limerick. Over the past years, he has developed important networks with international academics in Germany, Spain, Turkey and the UK. Through domestic and international networks, he continues to collaborate with large research consortia, including a number of SFI, EU H2020 research projects. Over several years he has been part of the successful completion of two H2020 EU funded projects, Vision Inspired Driver Assistance Systems (VI-DAS) and Cloud Large Scale Video Analysis (Cloud-LSVA). His research takes a cross-discipline approach by combining technical and social science research on AI and Data innovation to respond to commercial and social orientated research demands.

Teaching Interests

Data Governance, Data Risk and Regulation, Privacy, Explainable AI, Machine Decision making, Insurtech, Data Ethics, AI Principles and Frameworks, Data Markets and Data centred circular economies, and Sustainable AI

Professional Activities

Association

  • Irish Software Foundation, SFI LERO

Outreach

  • I have worked and supported community coding projects aimed at providing technology access and coding (MIT Scratch) to economically disadvantaged areas.

Committee

  • APEX, UL Apex (Academic and Professional Empowerment Network) Advisory Committee. The role of the Advisory Committee will be to: This network aims to be inclusive of all staff academic, professional, administrative, research, technical and support roles at all levels and ALL GENDERS

Publications

Book Chapters

2020

Could Autonomous Vehicles Become Accidental Autonomous Moral Machines?
Martin Cunneen
(2020) Could Autonomous Vehicles Become Accidental Autonomous Moral Machines?
In Culturally Sustainable Social Robotics; Marco Nørskov, Johanna Seibt, Oliver Santiago Quick(Ed.) Germany : IOS Press pp. 563-569
DOI: 10.3233/FAIA200958

2018

Framing risk, the new phenomenon of data surveillance and data monetisation; from an ‘always on' culture to ‘always on' artificial intelligence assistants
Martin Cunneen, Martin Mullins and Finbarr Murphy
(2018) Framing risk, the new phenomenon of data surveillance and data monetisation; from an ‘always on' culture to ‘always on' artificial intelligence assistants
In Hybrid Worlds: Societal and Ethical Challenges CLAWAR Association Series on Robot Ethics and Standards; Mohammad O. Tokhi Maria Isabel A. Ferreira Naveen S. Govindarajulu Manuel Silva Gurvinder S. Virk Endre E. Kadar Sarah R. Fletcher(Ed.) London : CLAWAR pp. 65-76
DOI: https://doi.org/10.13180/icres.2018.20-21.08.009

Peer Reviewed Journals

2021

Connected and autonomous vehicle injury loss events: Potential risk and actuarial considerations for primary insurers
Shannon, D., Jannusch, T., David‐Spickermann, F., Mullins, M., Cunneen, M., & Murphy, F
(2021) Connected and autonomous vehicle injury loss events: Potential risk and actuarial considerations for primary insurers
In Risk Management And Insurance Review; pp. 5-35
DOI: https://doi.org/10.1111/rmir.12168
[ULIR]

2019

From semi to fully autonomous vehicles: New emerging risks and ethico-legal challenges for human-machine interactions
Bellet T.;Cunneen M.;Mullins M.;Murphy F.;Pütz F.;Spickermann F.;Braendle C.;Baumann M.
(2019) From semi to fully autonomous vehicles: New emerging risks and ethico-legal challenges for human-machine interactions
In Transportation Research Part F: Traffic Psychology And Behaviour; pp. 153-164
DOI: 10.1016/j.trf.2019.04.004
[ULIR]

2019

Autonomous Vehicles and Avoiding the Trolley (Dilemma): Vehicle Perception, Classification, and the Challenges of Framing Decision Ethics
Cunneen M.;Mullins M.;Murphy F.;Shannon D.;Furxhi I.;Ryan C.
(2019) Autonomous Vehicles and Avoiding the Trolley (Dilemma): Vehicle Perception, Classification, and the Challenges of Framing Decision Ethics
In Cybernetics And Systems;
DOI: 10.1080/01969722.2019.1660541
[ULIR]

2019

Autonomous Vehicles and Embedded Artificial Intelligence: The Challenges of Framing Machine Driving Decisions
Cunneen M.;Mullins M.;Murphy F.
(2019) Autonomous Vehicles and Embedded Artificial Intelligence: The Challenges of Framing Machine Driving Decisions
In Applied Artificial Intelligence;
DOI: 10.1080/08839514.2019.1600301

2019

Artificial intelligence assistants and risk: framing a connectivity risk narrative
Cunneen M.;Mullins M.;Murphy F.
(2019) Artificial intelligence assistants and risk: framing a connectivity risk narrative
In Ai And Society;
DOI: 10.1007/s00146-019-00916-9
[ULIR]

2018

Artificial Driving Intelligence and Moral Agency: Examining the Decision Ontology of Unavoidable Road Traffic Accidents through the Prism of the Trolley Dilemma
Cunneen M.;Mullins M.;Murphy F.;Gaines S.
(2018) Artificial Driving Intelligence and Moral Agency: Examining the Decision Ontology of Unavoidable Road Traffic Accidents through the Prism of the Trolley Dilemma
In Applied Artificial Intelligence;
DOI: 10.1080/08839514.2018.1560124

Other Journals

2021

Creating Ethics Guidelines for Artificial Intelligence (AI) and Big Data Analytics: The Case of the European Consumer Insurance Market
Professor Chris Holland, Professor Martin Mullins and Dr Martin Cunneen
(2021) Creating Ethics Guidelines for Artificial Intelligence (AI) and Big Data Analytics: The Case of the European Consumer Insurance Market
In SSRN; Online : SSRN
DOI: http://dx.doi.org/10.2139/ssrn.3808207

2021

Algorithmic Trading, High-frequency Trading: Implications for MiFID II and Market Abuse Regulation (MAR) in the EU
Rabeea Sadaf, Orla McCullagh, Barry Sheehan, Colette Grey, Erin King, Martin Cunneen
(2021) Algorithmic Trading, High-frequency Trading: Implications for MiFID II and Market Abuse Regulation (MAR) in the EU
In SSRN; Online :

Conference Contributions

2020

Electronomous International Mobility
Martin Cunneen
(2020) Electronomous International Mobility
Online

2020

Robophilosophy
Martin Cunneen
(2020) Robophilosophy
Aarhus University

2019

5th International Conference on the History and Philosophy of Computing
Martin Cunneen
(2019) 5th International Conference on the History and Philosophy of Computing
University of Bergamo, Italy

2018

Anticipatory technologies – data and disorientation
Martin Cunneen and Martin Mullins
(2018) Anticipatory technologies – data and disorientation
Faculty of Arts and Social Sciences, Maastricht, The Netherlands

Other Publications

2017

The Issue of Agency in AI; The Case of Automated Driving
Martin Cunneen
(2017) The Issue of Agency in AI; The Case of Automated Driving