AI & Society最新文献

Increasing attention is paid to ethical issues and values when designing and deploying artificial intelligence (AI). However, we do not know how those values are embedded in artificial artefacts or how relevant they are to the population exposed to and interacting with AI applications. Based on literature engaging with ethical principles and moral values in AI, we designed an original survey instrument, including 15 value components, to estimate the importance of these values to people in the general population. The article is based on representative surveys conducted in Estonia, Germany, and Sweden (n = 4501), which have varying experiences with implementing AI. The factor analysis showed four underlying dimensions of values embedded in the design and use of AI: (1) protection of personal interests to ensure social benefit, (2) general monitoring to ensure universal solidarity, (3) ensuring social diversity and social sustainability, and (4) efficiency. We found that value types can be ordered along the two dimensions of resources and change. The comparison between countries revealed that some dimensions, like social diversity and sustainability evaluations, are more universally valued among individuals, countries, and domains. Based on our analysis, we suggest a need and a framework for developing basic values in AI.

This paper endeavors to appraise scholarly works from the 1940s to the contemporary era, examining the scientific quest to transpose human cognition and consciousness into a digital surrogate, while contemplating the potential ramifications should humanity attain such an abstract level of intellect. The discourse commences with an explication of theories concerning consciousness, progressing to the Turing Test apparatus, and intersecting with Damasio’s research on the human cerebrum, particularly in relation to consciousness, thereby establishing congruence between the Turing Test and Damasio’s notions of consciousness. Subsequently, the narrative traverses the evolutionary chronology of transmuting human cognition into machine sapience, and delves into the fervent endeavors to metamorphose human minds into synthetic counterparts. Additionally, theoretical perspectives from the domains of philosophy, psychology, and neuroscience provide insight into the constraints intrinsic to AI implementations, contentious hypotheses, the perils concealed within artificial networks, and the ethical considerations necessitated by AI frameworks. Furthermore, contemplation of prospective repercussions facilitates the refinement of strategic approaches to safeguard our future Augmented Age Realities within AI, circumventing the prospect of inhabiting an intimidating technopolis where a mere 30% monopolize the intellect and ingenuity of the remaining 70% of human minds.

As AI technologies are rolled out into healthcare, academia, human resources, law, and a multitude of other domains, they become de-facto arbiters of truth. But truth is highly contested, with many different definitions and approaches. This article discusses the struggle for truth in AI systems and the general responses to date. It then investigates the production of truth in InstructGPT, a large language model, highlighting how data harvesting, model architectures, and social feedback mechanisms weave together disparate understandings of veracity. It conceptualizes this performance as an operationalization of truth, where distinct, often-conflicting claims are smoothly synthesized and confidently presented into truth-statements. We argue that these same logics and inconsistencies play out in Instruct’s successor, ChatGPT, reiterating truth as a non-trivial problem. We suggest that enriching sociality and thickening “reality” are two promising vectors for enhancing the truth-evaluating capacities of future language models. We conclude, however, by stepping back to consider AI truth-telling as a social practice: what kind of “truth” do we as listeners desire?

The AI world was rocked with controversy when Blake Lemoine, an AI researcher at Google claimed that their new LaMDA model was sentient. This Curmudgeon’s Corner article explores his claims critically by contrasting them to the original LaMDA paper released by the team of researchers at Google. The piece explores the human tendency for anthropomorphization via historical chatbots such as Eliza and potential reasons why we developed this propensity. It addresses the potential causes for the model’s choice of words. Subsequently, using the scoring criteria of the language model, I provide an explanation for the model’s behavior in the conversation with Lemoine. Finally, I explore some of Lemoine’s assertions and break down the logical gaps they hold. I conclude on a potential reorientation of the debate in view of our unfortunate tendency.

In our ever technologically driven and mediatized society, we face the existential risk of falling into an info-calypse as much as an eco-calypse. To complement the list of values of a progressive culture put forth by Harrison (Natl Interest 60:55–65, 2000) and Vuong (Econ Bus Lett 10(3):284–290, 2021), this short essay proposes cultivating a new cultural value of protecting the infosphere. It argues rewarding practices and products that strengthen the integrity of infosphere as part of the newly emerged corporate social responsibility (CSR) practices are highly beneficial for the fight against contaminations of the infosphere, i.e., misinformation, disinformation, damaging contents, etc.

If I decide to disclose information about myself, this act may undermine other people’s ability to conceal information about them. Such dependencies are called privacy dependencies in the literature. Some say that privacy dependencies generate moral duties to avoid sharing information about oneself. If true, we argue, then it is sometimes justified for others to impose harm on the person sharing information to prevent them from doing so. In this paper, we first show how such conclusions arise. Next, we show that the existence of such a dependency between the moral significance you are inclined to attribute to privacy dependencies and judgments about permissible self-defense puts pressure on at least some ways of spelling out the idea that privacy dependencies ought to constrain our data-sharing conduct.

Well-being is an important policy concept including in discussions around the use of artificial intelligence, machine learning and robotics. Disabled people experience challenges in their well-being. Therefore, the aim of our scoping review study of academic abstracts employing Scopus, IEEE Xplore, Compendex and the 70 databases from EBSCO-HOST as sources was to better understand how academic literature focusing on AI/ML/robotics engages with well-being in relation to disabled people. Our objective was to answer the following research question: how and to what extent does the AI/ML/robot literature we covered include well-being in relation to disabled people? We found 2071 academic abstracts covering AI/ML and well-being, and 1055 covering robotics and well-being. Within these abstracts, only 39 covered AI/ML and 48 robotics and well-being in relation to disabled people. The tone of the coverage was techno-positive and techno-optimistic arguing that AI/ML/robotics could improve the well-being of disabled people in general or improve well-being by helping disabled people overcome their ‘disability’ or make tasks easier. No negative effects that AI/ML/robotics could have or has had on the well-being of disabled people were mentioned. Disabled people were portrayed only within patient, client, or user roles but not in their roles as stakeholders in the governance of AI/ML/robotics discussions. This biased and limited coverage of the impact of AI/ML/robotics on the well-being of disabled people disempowers disabled people.