Lieto Antonio
Dipartimento di Informatica, Università di Torino, Torino, Italy.
Istituto di Calcolo e Reti ad Alte Prestazioni del Consiglio Nazionale delle Ricerche, ICAR-CNR, Palermo, Italy.
Front Robot AI. 2022 May 30;9:888199. doi: 10.3389/frobt.2022.888199. eCollection 2022.
In this article, I argue that the artificial components of hybrid bionic systems do not play a direct explanatory role, i.e., in simulative terms, in the overall context of the systems in which they are embedded in. More precisely, I claim that the internal procedures determining the output of such artificial devices, replacing biological tissues and connected to other biological tissues, cannot be used to directly explain the corresponding mechanisms of the biological component(s) they substitute (and therefore cannot be used to explain the local mechanisms determining an overall biological or cognitive function replicated by such bionic models). I ground this analysis on the use of the Minimal Cognitive Grid (MCG), a novel framework proposed in Lieto (Cognitive design for artificial minds, 2021) to rank the epistemological and explanatory status of biologically and cognitively inspred artificial systems. Despite the lack of such a direct mechanistic explanation from the artificial component, however, I also argue that the hybrid bionic systems can have an indirect explanatory role similar to the one played by some AI systems built by using an overall structural design approach (but including the partial adoption of functional components). In particular, the artificial replacement of part(s) of a biological system can provide i) a local functional account of that part(s) in the context of the overall functioning of the hybrid biological-artificial system and ii) global insights about the structural mechanisms of the biological elements connected to such artificial devices.
在本文中,我认为混合仿生系统的人工组件并不发挥直接的解释作用,也就是说,从模拟的角度来看,在它们所嵌入的系统的整体背景中并非如此。更确切地说,我主张,决定此类人工装置输出的内部程序,这些装置替代生物组织并与其他生物组织相连,不能用于直接解释它们所替代的生物组件的相应机制(因此不能用于解释决定此类仿生模型所复制的整体生物或认知功能的局部机制)。我基于最小认知网格(MCG)的运用进行这一分析,最小认知网格是列托(《人工思维的认知设计》,2021年)提出的一个新颖框架,用于对受生物和认知启发的人工系统的认识论和解释地位进行排名。然而,尽管人工组件缺乏这种直接的机制性解释,但我也认为混合仿生系统可以具有类似于某些采用整体结构设计方法构建的人工智能系统所发挥的间接解释作用(但包括部分采用功能组件)。特别是,生物系统部分的人工替代可以提供:i)在混合生物 - 人工系统整体功能背景下该部分的局部功能说明;ii)关于与此类人工装置相连的生物元素结构机制的全局见解。