What do we loose when machines take the decisions?

Bolander, Thomas

doi:10.1007/s10997-019-09493-x

Cited by 47 publications

(26 citation statements)

References 9 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…the machine) to act in all events of life the same way as our reason causes us to act.'' This is supported by Bolander (2019), who claims that humans and machines cannot be compared in intelligence, as they have different strengths and weaknesses. Moreover, some researchers find AI to be useful for special areas only, where no abstractions, knowledge transfer, or the analysis of unstructured tasks is needed (Sheil 1987;Surden 2019), and there are differing views on the potential that AI has for creativity, emotions, or empathy (Wamba et al 2015;Kaplan and Haenlein 2019).…”

Section: Introductionmentioning

confidence: 94%

“…Almost 30 years later, the number of AI applications has increased significantly. Therefore, the framework will be linked to the categories of bottomup and top-down approaches, following the majority of researchers (Nilsson 2010;Bolander 2019;Surden 2019). The former category refers to applications that are created implicitly, meaning that they all statistically learn from experience and are thus not completely predictable, error-free, or explainable.…”

Section: Ai Applicationsmentioning

confidence: 99%

“…The second cluster includes mathematical and statistical approaches, although researchers sometimes do not agree with or even mention them as being AI (e.g., Simon 1995;Welter et al 2013;Haruvy et al 2019). These applications are also called logical rules and knowledge representation, based on rules that human programmers provide to computers, often with the goal of automation (Surden 2019), leading to systems that are predictable and explainable with strict and known abilities (Bolander 2019). Figure 2 offers a framework relating the categories to the continuum of rational behavior (see Fig.…”

Section: Ai Applicationsmentioning

confidence: 99%

“…Specifying clear applications for the categories is unfortunately not possible, as researchers do not even agree on how to categorize traditional mathematical applications, while new applications for bottom-up AI are also not stipulated or agreed. The reason for this may be that most systems today, especially when it comes to decision making, are located in the middle, ''having a human in the loop'' (Bolander 2019;Surden 2019).…”

Section: Ai Applicationsmentioning

confidence: 99%

“…For this reason, in this article, Nilsson's (2010: 13) definition is adopted, as it encompasses Simon's view and all other above-mentioned aspects, while being precise enough to guide the further analysis: ''For me, AI is that activity devoted to making machines intelligent, and intelligence is that quality that enables an entity to function appropriately and with foresight in its environment.'' The capabilities necessary to ''function appropriately and with foresight'' range from perception to interpretation and the development of actions to interact with, react to, or even influence the environment to achieve individual goals (Legg and Hutter 2007;Bolander 2019). The specific capability that is needed depends on the environment and the type of problem.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

On the current state of combining human and artificial intelligence for strategic organizational decision making

Trunk

Birkel

Hartmann

2020

Bus Res

123

View full text Add to dashboard Cite

Strategic organizational decision making in today’s complex world is a dynamic process characterized by uncertainty. Therefore, diverse groups of responsible employees deal with the large amount and variety of information, which must be acquired and interpreted correctly to deduce adequate alternatives. The technological potential of artificial intelligence (AI) is expected to offer further support, although research in this regard is still developing. However, as the technology is designed to have capabilities beyond those of traditional machines, the effects on the division of tasks and the definition of roles established in the current human–machine relationship are discussed with increasing awareness. Based on a systematic literature review, combined with content analysis, this article provides an overview of the possibilities that current research identifies for integrating AI into organizational decision making under uncertainty. The findings are summarized in a conceptual model that first explains how humans can use AI for decision making under uncertainty and then identifies the challenges, pre-conditions, and consequences that must be considered. While research on organizational structures, the choice of AI application, and the possibilities of knowledge management is extensive, a clear recommendation for ethical frameworks, despite being defined as a crucial foundation, is missing. In addition, AI, other than traditional machines, can amplify problems inherent in the decision-making process rather than help to reduce them. As a result, the human responsibility increases, while the capabilities needed to use the technology differ from other machines, thus making education necessary. These findings make the study valuable for both researchers and practitioners.

show abstract

Section: Introductionmentioning

confidence: 94%

Section: Ai Applicationsmentioning

confidence: 99%