Why Artificial Intelligence Will Not Outsmart Complex Knowledge Work

2018 ◽  
Vol 33 (6) ◽  
pp. 1058-1067 ◽  
Author(s):  
Lene Pettersen
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
Potential Role ◽  
Knowledge Work ◽  
Complex Problem ◽  
Complex Problem Solving ◽  
The 1960S ◽  
Complex Knowledge ◽  
Artificial Intelligence Systems

The potential role of artificial intelligence in improving organisations’ performance and productivity has been promoted regularly and vociferously since the 1960s. Artificial intelligence is today reborn out of big business, similar to the occurrences surrounding big data in the 1990s, and expectations are high regarding AI’s potential role in businesses. This article discusses different aspects of knowledge work that tend to be ignored in the debate about whether or not artificial intelligence systems are a threat to jobs. A great deal of knowledge work concerns highly complex problem solving and must be understood in contextual, social and relational terms. These aspects have no generic nor universal rules and solutions and, thus, cannot be easily replaced by artificial intelligence or programmed into computer systems, nor are they constructed based on models of the rational brain. In this respect, this article draws on philosopher Herbert Dreyfus’ thesis regarding artificial intelligence.

scholarly journals Out of the loop? On the radical and the routine in urban big data

Urban Studies ◽  
2021 ◽  
pp. 004209802110140
Author(s):  
Sarah Barns
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
Computational Models ◽  
Data Driven ◽  
Urban Systems ◽  
Out Of The Loop ◽  
Urban Futures ◽  
Urban Behaviour ◽  
The City

This commentary interrogates what it means for routine urban behaviours to now be replicating themselves computationally. The emergence of autonomous or artificial intelligence points to the powerful role of big data in the city, as increasingly powerful computational models are now capable of replicating and reproducing existing spatial patterns and activities. I discuss these emergent urban systems of learned or trained intelligence as being at once radical and routine. Just as the material and behavioural conditions that give rise to urban big data demand attention, so do the generative design principles of data-driven models of urban behaviour, as they are increasingly put to use in the production of replicable, autonomous urban futures.

The Role of Strategy Knowledge for the Application of Strategies in Complex Problem Solving Tasks

2014 ◽  
Vol 19 (1-2) ◽  
pp. 127-146 ◽  
Author(s):  
Sascha Wüstenberg ◽  
Matthias Stadler ◽  
Jarkko Hautamäki ◽  
Samuel Greiff
Keyword(s):  
Problem Solving ◽  
Complex Problem ◽  
Complex Problem Solving

scholarly journals Rethinking Development Strategy –The Importance of the Rural Non Farm Economy in Growth and Poverty Reduction in Pakistan

2008 ◽  
Vol 13 (Special Edition) ◽  
pp. 189-204 ◽  
Author(s):  
Sohail Jehangir Malik
Keyword(s):  
Development Strategy ◽  
Poverty Reduction ◽  
Potential Role ◽  
Development Theory ◽  
Investment Climate ◽  
Agricultural Growth ◽  
Services Sector ◽  
Agriculture Sector ◽  
The 1960S

The structural transformation of Pakistan’s economy has not been accompanied by a concomitant decline in the proportion of labor employed in agriculture. While this transformation has resulted in a non-farm sector that is large and growing it has not lead to the rapid absorption of the pool of relatively low productivity labor away from the agriculture sector, as predicted by conventional development theory embodied in the models of the 1960s. Despite the obvious importance of the role of a vibrant rural non-farm economy (RNFE), and in particular, a vibrant non-farm services sector to address the challenges of poverty, food security, agricultural growth and rural development, this sector has received inadequate attention in the debate in Pakistan. Based on a review of literature and data from two large surveys – the Rural Investment Climate Survey of Pakistan 2005 and the Surveys of Domestic Commerce 2007 – this paper attempts to analyze the factors underlying the low level of development of the rural non farm economy and the potential role it can play in Pakistan’s economic development.

Big Data, Artificial Intelligence, and the Internet of Things in Cross-Border E-Commerce

2021 ◽  
pp. 257-272
Author(s):  
Aboobucker Ilmudeen
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
Internet Of Things ◽  
Economic Globalization ◽  
The Internet ◽  
Technological Revolution ◽  
Cross Border ◽  
Wide Range ◽  
The Internet Of Things

Today, the terms big data, artificial intelligence, and internet of things (IoT) are many-fold as these are linked with various applications, technologies, eco-systems, and services in the business domain. The recent industrial and technological revolution have become popular ever before, and the cross-border e-commerce activities are emerging very rapidly. As a result, it supports to the growth of economic globalization that has strategic importance for the advancement of e-commerce activities across the globe. In the business industry, the wide range applications of technologies like big data, artificial intelligence, and internet of things in cross-border e-commerce have grown exponential. This chapter systematically reviews the role of big data, artificial intelligence, and IoT in cross-border e-commerce and proposes a conceptually-designed smart-integrated cross-border e-commerce platform.

Smart Technology for Smart Response During Pandemic Times

2022 ◽  
pp. 261-278
Keyword(s):  
Artificial Intelligence ◽  
Social Media ◽  
Big Data ◽  
Smart City ◽  
Critical Role ◽  
Communication Strategy ◽  
Smart Technology ◽  
Information And Communication ◽  
Remote Learning

The formal response to COVID-19 through ICT is presented with a focus on testing COVID-19, ICTs and tracking COVID-19, ICTs and COVID-19 treatment, and policies and strategies. The chapter highlights the critical role of ICTs and e-government for technologies to fight coronavirus. It covers delivery of remote learning, ICT trends, artificial intelligence (AI), and big data in fighting the pandemic, in addition to social media application for awareness of citizens such as emergencies, protection, and pandemic news. The notion of developing an information and communication strategy for redesigning smart city transformation in a pandemic is highlighted.

scholarly journals Artificial intelligence, real-time feedback and workplace learning analytics to support in situ complex problem-solving: a commentary

2020 ◽  
Vol 37 (5) ◽  
pp. 267-277
Author(s):  
Maarten de Laat ◽  
Srecko Joksimovic ◽  
Dirk Ifenthaler
Keyword(s):  
Artificial Intelligence ◽  
Problem Solving ◽  
Real Time ◽  
Workplace Learning ◽  
Learning Analytics ◽  
Complex Problem ◽  
Complex Problem Solving ◽  
Feedback Systems ◽  
Content Type

PurposeTo help workers make the right decision, over the years, technological solutions and workplace learning analytics systems have been designed to aid this process (Ruiz-Calleja et al., 2019). Recent developments in artificial intelligence (AI) have the potential to further revolutionise the integration of human and artificial learning and will impact human and machine collaboration during team work (Seeber et al., 2020).Design/methodology/approachComplex problem-solving has been identified as one of the key skills for the future workforce (Hager and Beckett, 2019). Problems faced by today's workforce emerge in situ and everyday workplace learning is seen as an effective way to develop the skills and experience workers need to embrace these problems (Campbell, 2005; Jonassen et al., 2006).FindingsIn this commentary the authors argue that the increased digitization of work and social interaction, combined with recent research on workplace learning analytics and AI opens up the possibility for designing automated real-time feedback systems capable of just-in-time, just-in-place support during complex problem-solving at work. As such, these systems can support augmented learning and professional development in situ.Originality/valueThe commentary reflects on the benefits of automated real-time feedback systems and argues for the need of shared research agenda to cohere research in the direction of AI-enabled workplace analytics and real-time feedback to support learning and development in the workplace.

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