Artificial wisdom: a philosophical framework
- PDF / 630,086 Bytes
- 8 Pages / 595.276 x 790.866 pts Page_size
- 47 Downloads / 246 Views
OPEN FORUM
Artificial wisdom: a philosophical framework Cheng‑hung Tsai1 Received: 13 December 2019 / Accepted: 6 February 2020 © Springer-Verlag London Ltd., part of Springer Nature 2020
Abstract Human excellences such as intelligence, morality, and consciousness are investigated by philosophers as well as artificial intelligence researchers. One excellence that has not been widely discussed by AI researchers is practical wisdom, the highest human excellence, or the highest, seventh, stage in Dreyfus’s model of skill acquisition. In this paper, I explain why artificial wisdom matters and how artificial wisdom is possible (in principle and in practice) by responding to two philosophical challenges for building artificial wisdom systems. The result is a conceptual framework that guides future research on creating artificial wisdom. Keywords Practical wisdom · Artificial narrow intelligence · Artificial general intelligence · Specificationism · Well-being
1 Introduction Human excellences such as intelligence, morality, and consciousness are investigated by philosophers as well as artificial intelligence (AI) researchers. AI researchers ask whether it is possible to create artificial superintelligence (Bostrom 2014), artificial morality (Moor 2006; Wallach and Allen 2008; Anderson and Anderson 2011; Leben 2019), and artificial consciousness (Gamez 2008; Reggia 2013), among others. One excellence that has not been widely discussed by AI researchers is practical wisdom, the highest human excellence, or the highest, seventh, stage in Dreyfus’s model of skill acquisition (Dreyfus 2001). If AI researchers aim to build machines to mimic humans with almost every aspect of human excellence, then practical wisdom is likely to be of the utmost interest. Some researchers (Goertzel 2008; Casacuberta 2013; Marsh et al 2016; Kim and Mejia 2019) have tried to develop artificial wisdom (AW) systems, aiming to “design computational systems that can model at least some relevant aspects of human wisdom” (Casacuberta 2013: 199), or to “[explore] how the very human notion of wisdom can be incorporated in the different behavior and ultimately reasonings of our computational systems” (Marsh et al 2016: * Cheng‑hung Tsai [email protected] 1
Institute of European and American Studies, Academia Sinica, No. 128, Sec. 2, Academia Road, Nankang, Taipei 115, Taiwan
137).1 However, unanticipated philosophical challenges are emerging from building AW systems, showing that AW is impossible either in principle or in practice. In this paper, I shall examine two philosophical challenges (Sects. 3 and 5) and offer responses to them (Sects. 4 and 6). The result is a conceptual framework that guides future research on creating artificial wisdom. Before examining and responding to the challenges, I would explain why AW matters.
1
Davis (2019: 51) claims that “there is no … prospect for artificial wisdom”. But he did not delve deeply into (artificial) wisdom in his essay, the focus of which is (artificial) morality. Davis’s argument
Data Loading...
