ARTIFICIAL INTELLIGENCE (AI) AND ETHICAL ARTIFICIAL INTELLIGENCE (EAI) Medical Decision Support System, Medical Sapiens (MS)

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Published Sep 3, 2021
Claudio Garuti

Abstract

The concept of AI is a relatively new concept that is being used with increasing frequency. The importance of this concept has to do in general with the increased capacity of what we understand as intelligence. However, it is a delicate concept and easy to misuse and / or misinterpret. This requires a good understanding of what AI is, what it is based on or should be based on and its forms of practical operation.

I would like to make a point regarding the difference between IA and IAE. AI in general is thought of as a program or machine capable of answering difficult questions by generating relationships related to the question within large relational databases. This, in general, leads to obtaining results about which it is not clear how they were obtained (what was the "reasoning" behind). This, in the long term, can bring important problems of understanding and dependency. Ultimately, we would be obeying a machine based on its eventual high predictive capacity. But, in this case, who is really the decision-maker and who is the operator?

How to Cite

Garuti, C. (2021). ARTIFICIAL INTELLIGENCE (AI) AND ETHICAL ARTIFICIAL INTELLIGENCE (EAI): Medical Decision Support System, Medical Sapiens (MS). International Journal of the Analytic Hierarchy Process, 13(2). https://doi.org/10.13033/ijahp.v13i2.896

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Keywords

AHP, ANP, COMPATIBILITY INDEX G, SEMIOLOGY, AI, AEI

References
Garuti C., (2021). Set theory justification of G-compatibility index. Generalization of Jaccard index working within weighted environment. Journal of Multicriteria Decision Analysis, 27, 1-2. Doi: 10.1002/mcda.1667

Garuti, C. (2016). Measuring in weighted environments: Moving from metric to order topology (knowing when close really means close). In De Felice, F., Petrillo, A. & Saaty, T. (Eds.) Applications and Theory of Analytic Hierarchy Process- Decision Making for Strategic Decisions. InTech. Doi: 10.5772/63670

Garuti, C. (2014). Compatibility of AHP/ANP vectors with known results. Presentation of a suggested new index of compatibility in weighted environments. ISAHP2014 International Symposium of the Analytic Hierarchy Process.

Garuti, C., & Escudey, M. (2005). Decision making in complex environments. (1st ed.), Santiago, Chile: Universidad de Santiago.

Jaccard P. (1901). Distribution de la flore Alpine dans le bassin des dranses et dans quelques régions voisines. Bulletin de la Société Vaudoise des Sciences Naturelles 37, 241-272.

Saaty, T.L. (2001). The Analytic Network Process: Decision making with dependence and feedback. (1st ed). Pittsburgh, PA: RWS Publications.

Saaty, T.L. (2010). The Analytic Network Process: Decision making with dependence and feedback. (2nd ed). Pittsburgh, PA: RWS Publications.

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Essays, Reviews & Comments