Meta-narratives on machinic otherness: beyond anthropocentrism and exoticism

Kim, Min-Sun

doi:10.1007/s00146-022-01404-3

Cited by 6 publications

(4 citation statements)

References 19 publications

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“…To do this, reflection on the relative nature and trends in storytelling; e.g., relative to groups of people, (Yee 2017 ), place (Dihal et al 2021 ), time and panorama, as illustrated above, is vital. As Kim ( 2022 ) recently stated, the field must “broaden the purview of intelligent machines”, taking into account cultural and historical forces which shape public understanding of AI. To return to the concept of optimisation of ‘the wrong thing’, our participants stress the need to interrogate who decides what the wrong thing is – who is telling the story, what is the genre and the communicative purpose of the story.…”

Section: Discussionmentioning

confidence: 99%

“…They suggest that socio-technical imaginaries (Jasanoff and Kim 2015 ) should include an explicit account of the important role that narratives play and assert the need for further investigation into the ways narratives impact upon the public. This is supported by a growing body of research into the critical value of AI narratives (Kim 2022 ; Coeckelbergh 2021 ). We add to this critical line and Cave et al’s work by focusing on novel, nuanced and niche AI narratives.…”

Section: Introductionmentioning

confidence: 96%

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Expert views about missing AI narratives: is there an AI story crisis?

2022

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Stories are an important indicator of our vision of the future. In the case of artificial intelligence (AI), dominant stories are polarized between notions of threat and myopic solutionism. The central storytellers—big tech, popular media, and authors of science fiction—represent particular demographics and motivations. Many stories, and storytellers, are missing. This paper details the accounts of missing AI narratives by leading scholars from a range of disciplines interested in AI Futures. Participants focused on the gaps between dominant narratives and the untold stories of the capabilities, issues, and everyday realities of the technology. One participant proposed a “story crisis” in which these narratives compete to shape the public discourse on AI. Our findings indicate that dominant narratives distract and mislead public understandings and conceptions of AI. This suggests a need to pay closer attention to missing AI narratives. It is not simply about telling new stories, it is about listening to existing stories and asking what is wanted from AI. We call for realistic, nuanced, and inclusive stories, working with and for diverse voices, which consider (1) story-teller; (2) genre, and (3) communicative purpose. Such stories can then inspire the next generation of thinkers, technologists, and storytellers.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 96%

Expert views about missing AI narratives: is there an AI story crisis?

2022

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“…This could even include cases where the limitations of the inferential capabilities of the human prevent them from correctly anticipating the effects. This inability to correctly model the robot lies at the heart of the value alignment problem, in fact, [Kim, 2022] presents a human interaction with a modern AI agent to that of interacting with an alien intelligence. Now coming back to the plan π H , even if we allow for the possibility that in the human mental model that the plan could achieve the true goal, there is no reason to believe that the robot can execute it or even that executing it will result in the same goal state.…”

Section: Goal Alignment Problemmentioning

confidence: 99%

Goal Alignment: A Human-Aware Account of Value Alignment Problem

Mechergui¹,

Sreedharan²

2023

Preprint

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Value alignment problems arise in scenarios where the specified objectives of an AI agent don't match the true underlying objective of its users. The problem has been widely argued to be one of the central safety problems in AI. Unfortunately, most existing works in value alignment tend to focus on issues that are primarily related to the fact that reward functions are an unintuitive mechanism to specify objectives. However, the complexity of the objective specification mechanism is just one of many reasons why the user may have misspecified their objective. A foundational cause for misalignment that is being overlooked by these works is the inherent asymmetry in human expectations about the agent's behavior and the behavior generated by the agent for the specified objective. To address this lacuna, we propose a novel formulation for the value alignment problem, named goal alignment that focuses on a few central challenges related to value alignment. In doing so, we bridge the currently disparate research areas of value alignment and human-aware planning. Additionally, we propose a first-of-its-kind interactive algorithm that is capable of using information generated under incorrect beliefs about the agent, to determine the true underlying goal of the user.

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“…This points to an existence of a double empathy problem between AI systems and their users. However, in the context of AI systems, the problem is even more pronounced as the users may be forced to work with a truly alien intelligence (Kim 2022).…”

Section: Double Empathy Problemmentioning

confidence: 99%

Human-Aware AI – A Foundational Framework for Human-AI Interaction

Sreedharan

2023

AAAI

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We are living through a revolutionary moment in AI history. We are seeing the development of impressive new AI systems at a rate that was unimaginable just a few years ago. However, AI's true potential to transform society remains unrealized, in no small part due to the inability of current systems to work effectively with people. A major hurdle to achieving such coordination is the inherent asymmetry between the AI system and its users. In this talk, I will discuss how the framework of Human-Aware AI (HAAI) provides us with the tools required to bridge this gap and support fluent and intuitive coordination between the AI system and its users.

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Meta-narratives on machinic otherness: beyond anthropocentrism and exoticism

Cited by 6 publications

References 19 publications

Expert views about missing AI narratives: is there an AI story crisis?

Expert views about missing AI narratives: is there an AI story crisis?

Goal Alignment: A Human-Aware Account of Value Alignment Problem

Human-Aware AI – A Foundational Framework for Human-AI Interaction

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