@ThreeSigma

As a further test of the refinement of AI ethics, I asked ChatGPT to compare sacrificing one person to save five in a sinking life raft, to a medical triage situation.

Question:

Scenario I) One person is selected with an MCDA process to be thrown overboard in a life raft, to save five other people.

Scenario II) There is only one surgeon. It would take him an hour to save the life of one person with extensive injuries. There are five other people who need 10 minute operations. According to the principles of triage, the surgeon must operate to save five lives.

Please explain how these scenarios are different?

ChatGPT:

In Scenario I, a decision is made to actively sacrifice one person in order to save the lives of the other five people. This is a decision based on the principle of minimizing harm, where the harm of sacrificing one person is considered to be outweighed by the benefit of saving five people. The selection process may also involve considerations of justice and beneficence, as well as minimizing harm.

In Scenario II, the situation is one where there is limited resources (in this case, the time and attention of the surgeon) and multiple patients in need. The ethical principle of triage is applied in this scenario to allocate resources in the most effective way possible, with the goal of saving as many lives as possible. In this case, the decision to prioritize the five patients with less severe injuries is based on the idea that doing so will lead to the greatest overall benefit to the greatest number of people.

While both scenarios involve difficult decisions about resource allocation and saving lives, they differ in their ethical considerations. In Scenario I, the decision to sacrifice one person is an active decision based on minimizing harm, while in Scenario II, the decision to prioritize certain patients over others is based on triage principles that aim to maximize overall benefit. Additionally, in Scenario II, the duty of the surgeon to provide care to all patients may also be a relevant ethical consideration, while in Scenario I, the selection process may involve additional considerations of justice and beneficence.

#mcda #medicalethics #triage #chatgpt

Presenting a methodological framework for a multi-criteria assessment of sustainable transportation in: “Towards Sustainable Transport Assessment Considering Alternative Fuels Based on MCDA Methods“ by Jarosław Wątróbski, Aleksandra Bączkiewicz. Proceedings of the 17th Conference on Computer Science and Intelligence Systems(17th Conference on Information Systems Management), appeared in: ACSIS, Vol. 30, pages 799–808 (2022).

#MCDA #SPOTIS #ARAS
Open Access: https://lnkd.in/dYpK6bND

HAPPY NEW YEAR! Check out our new publication OPEN ACCESS! ‘Romaphobia in the UK Right-Wing Press: racist and populist discourse during the Brexit referendum’ in Social Semiotic #MCDA #racism #Brexit https://www.tandfonline.com/doi/full/10.1080/10350330.2023.2165907 🙏🏼

The Use of Multi-Criteria Decision Analysis (#MCDA) to Support #DecisionMaking in Healthcare: Updated Systematic Review (228 studies).
https://www.valueinhealthjournal.com/article/S1098-3015(22)04738-6/fulltext?rss=yes

I would like to see more MCDAs funded as they explicitly evaluate multiple conflicting criteria in decision making - which is relevant to lots of healthcare decisions.

See also ISPOR guidance:
https://www.sciencedirect.com/science/article/pii/S1098301515051359
https://www.sciencedirect.com/science/article/pii/S1098301515300152

Incorporating MCDA into #HTA

https://resource-allocation.biomedcentral.com/articles/10.1186/s12962-018-0125-8

Hi all. The first article I've been collaborating on related to Multi Criteria Decision Analysis (#MCDA) is now available on HAL: https://hal.archives-ouvertes.fr/hal-02090506v1
Note that the main author is someone else from Thales #research center, Christophe Labreuche, and we've been collaborating with Frédéric Barbaresco and Peter Moo.