Technological myopia

Crowther, David

doi:10.1108/techs-10-2022-0039

Cited by 2 publications

(1 citation statement)

References 45 publications

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“…We have argued that AI might well have a place in human endeavour but it is not going to replace humanity. Of course as Crowther (2023) argues it all depends upon humans anyway and how they choose to use the technology. Nevertheless AI is not able to truly innovate.…”

Section: Discussionmentioning

confidence: 99%

The mediocrity of AI

Crowther,

Hamdan

2024

TECHS

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PurposeThis paper aims to challenge the fashion of ubiquitous artificial intelligence (AI) and the effects which it will have upon society. In doing so it argues that the effects of AI will be minimal but important.Design/methodology/approachThis argument is based upon the Socratic method and explores the Utilitarian background in which AI is based while drawing upon classical literature and other examples to illustrate the argument.FindingsThe findings are encompassed in the argument and show that we need to be more open and careful when considering AI and its effects. We also need to be more realistic when considering potential benefits.Practical implicationsThis argument has significant implications for the adoption of AI.Social implicationsThe social implications are equally profound and will impact upon our application of AI solutions to current problems and upon humanity more generally.Originality/valueThis is the first paper which relates AI to human successes.

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Section: Discussionmentioning

confidence: 99%

The mediocrity of AI

Crowther,

Hamdan

2024

TECHS

Self Cite

View full text Add to dashboard Cite

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Artificial intelligence and unemployment dynamics: an econometric analysis in high-income economies

Masoud

2024

TECHS

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PurposeThe purpose of the study is to investigate the impact of artificial intelligence (AI), machine learning (ML), and data science (DS) on unemployment rates across ten high-income economies from 2015 to 2023.Design/methodology/approachThis study takes a unique approach by employing a dynamic panel data (DPD) model with a generalised method of moments (GMM) estimator to address potential biases. The methodology includes extensive validation through Sargan, Hansen, and Arellano-Bond tests, ensuring the robustness of the results and adding a novel perspective to the field of AI and unemployment dynamics.FindingsThe study’s findings are paramount, challenging prevailing concerns in AI, ML, and DS, demonstrating an insignificant impact on unemployment and contradicting common fears of job loss due to these technologies. The analysis also reveals a positive correlation (0.298) between larger government size and higher unemployment, suggesting bureaucratic inefficiencies that may hinder job growth. Conversely, a negative correlation (−0.201) between increased labour productivity and unemployment suggests that technological advancements can promote job creation by enhancing efficiency. These results refute the notion that technology inherently leads to job losses, positioning AI and related technologies as drivers of innovation and expansion within the labour market.Research limitations/implicationsThe study’s findings suggest a promising outlook, positioning AI as a catalyst for the expansion and metamorphosis of employment rather than solely a catalyst for automation and job displacement. This insight presents a significant opportunity for AI and related technologies to improve labour markets and strategically mitigate unemployment. To harness the benefits of technological progress effectively, authorities and enterprises must carefully evaluate the balance between government spending and its impact on unemployment. This proposed strategy can potentially reinvent governmental initiatives and stimulate investment in AI, thereby bolstering economic and labour market reliability.Originality/valueThe results provide significant perspectives for policymakers and direct further investigations on the influence of AI on labour markets. The analysis results contradict the common belief of technology job loss. The study’s results are shown to be reliable by the Sargan, Hansen, and Arellano-Bond tests. It adds to the discussion on the role of AI in the future of work, proposing a detailed effect of AI on employment and promoting a strategic method for integrating AI into the labour market.

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Technological myopia

Cited by 2 publications

References 45 publications

The mediocrity of AI

The mediocrity of AI

Artificial intelligence and unemployment dynamics: an econometric analysis in high-income economies

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