TY - GEN
T1 - Error-Correction for AI Safety
AU - Aliman, Nadisha Marie
AU - Elands, Pieter
AU - Hürst, Wolfgang
AU - Kester, Leon
AU - Thórisson, Kristinn R.
AU - Werkhoven, Peter
AU - Yampolskiy, Roman
AU - Ziesche, Soenke
PY - 2020/1/1
Y1 - 2020/1/1
N2 - The complex socio-technological debate underlying safety-critical and ethically relevant issues pertaining to AI development and deployment extends across heterogeneous research subfields and involves in part conflicting positions. In this context, it seems expedient to generate a minimalistic joint transdisciplinary basis disambiguating the references to specific subtypes of AI properties and risks for an error-correction in the transmission of ideas. In this paper, we introduce a high-level transdisciplinary system clustering of ethical distinction between antithetical clusters of Type I and Type II systems which extends a cybersecurity-oriented AI safety taxonomy with considerations from psychology. Moreover, we review relevant Type I AI risks, reflect upon possible epistemological origins of hypothetical Type II AI from a cognitive sciences perspective and discuss the related human moral perception. Strikingly, our nuanced transdisciplinary analysis yields the figurative formulation of the so-called AI safety paradox identifying AI control and value alignment as conjugate requirements in AI safety. Against this backdrop, we craft versatile multidisciplinary recommendations with ethical dimensions tailored to Type II AI safety. Overall, we suggest proactive and importantly corrective instead of prohibitive methods as common basis for both Type I and Type II AI safety.
AB - The complex socio-technological debate underlying safety-critical and ethically relevant issues pertaining to AI development and deployment extends across heterogeneous research subfields and involves in part conflicting positions. In this context, it seems expedient to generate a minimalistic joint transdisciplinary basis disambiguating the references to specific subtypes of AI properties and risks for an error-correction in the transmission of ideas. In this paper, we introduce a high-level transdisciplinary system clustering of ethical distinction between antithetical clusters of Type I and Type II systems which extends a cybersecurity-oriented AI safety taxonomy with considerations from psychology. Moreover, we review relevant Type I AI risks, reflect upon possible epistemological origins of hypothetical Type II AI from a cognitive sciences perspective and discuss the related human moral perception. Strikingly, our nuanced transdisciplinary analysis yields the figurative formulation of the so-called AI safety paradox identifying AI control and value alignment as conjugate requirements in AI safety. Against this backdrop, we craft versatile multidisciplinary recommendations with ethical dimensions tailored to Type II AI safety. Overall, we suggest proactive and importantly corrective instead of prohibitive methods as common basis for both Type I and Type II AI safety.
KW - AI ethics
KW - AI safety paradox
KW - Error-correction
UR - http://www.scopus.com/inward/record.url?scp=85088498789&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-52152-3_2
DO - 10.1007/978-3-030-52152-3_2
M3 - Conference contribution
AN - SCOPUS:85088498789
SN - 9783030521516
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 12
EP - 22
BT - Artificial General Intelligence
A2 - Goertzel, Ben
A2 - Potapov, Alexey
A2 - Panov, Aleksandr I.
A2 - Yampolskiy, Roman
PB - Springer
T2 - 13th International Conference on Artificial General Intelligence, AGI 2020
Y2 - 16 September 2020 through 19 September 2020
ER -