Just like me but not exactly: AI, anthropomorphism & the human-technology gap
type: CreativeWork
description: While artificial intelligence (AI) design continues to aspire towards romanticised visions of intelligence and human-likeness, the increasing dichotomy between its technological and social facets has given rise to tangible evidence of surveillance, inequality and discrimination. This evidence emphasises a pressing need for systems more aligned with human expectations and values, but computationally, it remains extremely difficult to embed concepts as fundamentally fluid and situational as value and meaning. Such difficulty has led present-day research to formalise these intricate principles of human behaviour, in all their complexity, through predictive machine learning models built on data extracted from how people behave not in relationship to AI but in the absence of it. This research proposes that the inseparability of the AI social artefact from the Human entails, foremost, an understanding of the interaction between concept (humanlike design) and percept (anthropomorphism). Consequently, the effect of these variables on each other is explored in two stages: first by reviewing whether our mental models of humanlike AI are built on pre-existing knowledge and schemas of other people (Just Like Me), and second, by probing their homogeneity with respect to their corresponding human counterparts (But Not Exactly). Building on the results of these initial investigations, this study demonstrates that the locus of the interaction, in practice, cannot be neatly extracted from manipulating the correlation of these variables, but rather by looking at how it is continuously constituted in the dynamic between the two. With combinations of effects born in the fleeting concept-perception interaction, it is concluded that very few behavioural patterns and mental models can truly be universalised, and for the most part, one context cannot be neatly applied to the next. To address this epistemological limitation, the present study proposes a novel methodological approach – takin…
abstract: While artificial intelligence (AI) design continues to aspire towards romanticised visions of intelligence and human-likeness, the increasing dichotomy between its technological and social facets has given rise to tangible evidence of surveillance, inequality and discrimination. This evidence emphasises a pressing need for systems more aligned with human expectations and values, but computationally, it remains extremely difficult to embed concepts as fundamentally fluid and situational as value and meaning. Such difficulty has led present-day research to formalise these intricate principles of human behaviour, in all their complexity, through predictive machine learning models built on data extracted from how people behave not in relationship to AI but in the absence of it. This research proposes that the inseparability of the AI social artefact from the Human entails, foremost, an understanding of the interaction between concept (humanlike design) and percept (anthropomorphism). Consequently, the effect of these variables on each other is explored in two stages: first by reviewing whether our mental models of humanlike AI are built on pre-existing knowledge and schemas of other people (Just Like Me), and second, by probing their homogeneity with respect to their corresponding human counterparts (But Not Exactly). Building on the results of these initial investigations, this study demonstrates that the locus of the interaction, in practice, cannot be neatly extracted from manipulating the correlation of these variables, but rather by looking at how it is continuously constituted in the dynamic between the two. With combinations of effects born in the fleeting concept-perception interaction, it is concluded that very few behavioural patterns and mental models can truly be universalised, and for the most part, one context cannot be neatly applied to the next. To address this epistemological limitation, the present study proposes a novel methodological approach – takin…
author: Ionescu, Iulia
keywords: Design studies, Design Practice, Industrial/Product Design
identifier: Ionescu, Iulia <https://ualresearchonline.arts.ac.uk/view/creators/Ionescu=3AIulia=3A=3A.html> (2022) Just like me but not exactly: AI, anthropomorphism & the human-technology gap. PhD thesis, Royal College of Art / Microsoft Research Cambridge.
date published: 2022-12-11
date modified: 2026-07-24T01:00:50Z
provider: University of the Arts London
publisher: Networked Digital Library of Theses and Dissertations
type: WebPage
source organization: University of the Arts London