What we owe to decision-subjects: beyond transparency and explanation in automated decision-making

Grant, David Gray; Behrends, Jeff; Basl, John

doi:10.1007/s11098-023-02013-6

Cited by 4 publications

(2 citation statements)

References 72 publications

(90 reference statements)

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“…The disadvantage of the study is the lack of calculation of indicators that will help make this or that decision (there is no ranking of threats). The work [22] explores machine learning methods for creating automated systems for processing huge amounts of data. The proposed results can be used to create automated decision-making systems.…”

Section: Research Materials and Methodsmentioning

confidence: 99%

Development of the automated decision-making system synthesis method in the management of information security channels

Shmatko,

Herasymov,

Lysetskyi

et al. 2023

EEJET

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In the process of transmission channels functioning, the results of the work of bodies for detecting and blocking information leakage channels are not sufficiently taken into account. Management of information protection channels is actually the collection and display of data followed by the assignment of influence on each information channel separately and is carried out in manual mode. In decision support systems, the tasks of identifying information leakage channels are not solved. There is a contradiction between the requirements for the automation of the management of information protection channels and the possibility of meeting these requirements at the expense of the available automation tools. Classical theory considers the decision-making process as a choice of one of many alternatives. The development of rational forms and methods of managing information protection channels should prevent threats and challenges. Therefore, the object of research is the process of ensuring security during data transmission through information channels. The main threats and challenges are man-made and natural cataclysms, terrorism, aggression by a number of states or individual groups of people, which are not taken into account in the complex in the decision-making system during the management of information protection channels. A structural diagram of information exchange based on the description of a weakly formalized process under conditions of non-stochastic uncertainty is proposed. It is proposed to use the logical-linguistic production model. For a hierarchically organized structure based on classification features, it is proposed to build a hierarchy tree that takes into account the relationships of partially ordered sets. The formed production rules for determining appropriate strategies for the planned detection of information leakage channels based on predicted values allow to proceed to knowledge processing for the synthesis of an automated decision-making system during the management of protection channels

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Section: Research Materials and Methodsmentioning

confidence: 99%

Development of the automated decision-making system synthesis method in the management of information security channels

Shmatko,

Herasymov,

Lysetskyi

et al. 2023

EEJET

View full text Add to dashboard Cite

show abstract

“…Likewise, outside of journalism, there are growing calls for disclosure around the use of AI generally due to the opaque nature of AI systems and the ways by which these systems arrive at results (see, e.g. Grant et al, 2023). However, at present, the available literature around modes of disclosure of AI-generated content is limited.…”

Section: Disclosure Of Ai-generated Contentmentioning

confidence: 99%

“Or they could just not use it?”: The Paradox of AI Disclosure for Audience Trust in News

Toff,

Simon

2023

Preprint

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The adoption of artificial intelligence (AI) technologies in the production and distribution of news has generated theoretical, normative, and practical concerns around the erosion of journalistic authority and autonomy and the spread of misinformation. With trust in news already low in many places worldwide, both scholars and practitioners are wary of how the public will respond to news generated through automated methods, prompting calls for labeling of AI-generated content. In this study, we present results from a novel survey-experiment conducted using actual AI-generated journalistic content. We test whether audiences in the US, where trust is particularly polarized along partisan lines, perceive news labeled as AI- generated as more or less trustworthy. We find on average that audiences perceive news labeled as AI-generated as less trustworthy, not more, even when articles themselves are not evaluated as any less accurate or unfair. Furthermore, we find that these effects are largely concentrated among those whose pre-existing levels of trust in news are higher to begin with and among those who exhibit higher levels of knowledge about journalism. We also find that negative effects associated with perceived trustworthiness are largely counteracted when articles disclose the list of sources used to generate the content. As news organizations increasingly look toward adopting AI technologies in their newsrooms, our results hold implications for how disclosure about these techniques may contribute to or further undermine audience confidence in the institution of journalism at a time in which its standing with the public is especially tenuous.

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On the scope of the right to explanation

Fritz

2024

AI Ethics

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As opaque algorithmic systems take up a larger and larger role in shaping our lives, calls for explainability in various algorithmic systems have increased. Many moral and political philosophers have sought to vindicate these calls for explainability by developing theories on which decision-subjects—that is, individuals affected by decisions—have a moral right to the explanation of the systems that affect them. Existing theories tend to suggest that the right to explanation arises solely in virtue of facts about how decision-subjects are affected by opaque systems. But this ignores an important part of the normative landscape: sometimes, facts about a decision-maker’s rights and freedoms can make a difference to whether she owes anyone explanations of her decisions. I illustrate the point by calling attention to examples of artistic, romantic, and supererogatory altruistic decisions; in at least some cases of this sort, even highly influential decisions can legitimately be kept entirely private and opaque,

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What we owe to decision-subjects: beyond transparency and explanation in automated decision-making

Cited by 4 publications

References 72 publications

Development of the automated decision-making system synthesis method in the management of information security channels

Development of the automated decision-making system synthesis method in the management of information security channels

“Or they could just not use it?”: The Paradox of AI Disclosure for Audience Trust in News

On the scope of the right to explanation

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