Advances in Project Management
SERIES ARTICLE
By Prof Darren Dalcher
School of Management, University of Lancaster
Lancaster, United Kingdom
Is artificial intelligence the long-awaited answer to all our problems?
Artificial Intelligence (AI) has been described as the most important and disruptive general-purpose technology of our era, especially for large organisations (Benbya et al., 2020; Brynjolfsson & McAfee, 2017). The technology is concerned with building intelligent entities, capable of computing how to act effectively and safely in a wide variety of novel situations, by perceiving, understanding, predicting and manipulating a complex external world (Russell & Norvig, 2022: 19). A preoccupation with such intelligent prediction and engagement within an increasingly turbulent and complex world offers an appealing notion. Indeed, Davenport (2019: xii) maintains that 25% to 30% of large US companies are aggressively pursuing AI, with hundreds, or even thousands of projects under way – many other nations and different business sectors are following suit.
Where does AI come from?
The fascination with the creation of intelligent machines and autonomous agents represents a long-standing craving and desire for the human race. The field of AI traces its roots back to the pioneering work of John McCarthy (Andresen, 2002; Mitchell, 2019). McCarthy selected the term Artificial Intelligence in 1955 to distinguish it from the somewhat related area of work known as cybernetics and put together a proposal for a Dartmouth Summer Research Project in 1956 focused on the new area, together with leading scientists Marvin Minsky, Nathanial Rochester and Claude Shannon (see, original proposal, republished as: McCarthy et al., 2006). The proposal endeavours to bring together computer, information and neural scientists and engineers to determine if learning, or any other feature of intelligence can be so precisely described so that a machine could be made to simulate it. Nowadays, this has morphed into a more significant question of whether machines and their computational intelligence can replace, or even improve upon the performance of human agents, particularly in data rich, demanding contexts. Particularly appealing in this context is the machines’ potential to trawl through voluminous data at tremendous speed, and to keep improving and learning how to perform tasks better (i.e. to evolve and transform over time).
To be considered intelligent, a system must not only model a task, but also model the embedded context in which that task is undertaken; this implies sensing the environment and then modifying and adjusting actions accordingly—requiring an ability to make decisions in an uncertain environment (New Scientist, 2020: 8). The original ambition of the scientists around the creation of fully intelligent machines is yet to be realised: Nonetheless, Mitchell (2019) observes that progress has been made on two main fronts. On the scientific side, AI researchers are investigating the mechanisms of natural, or biological, intelligence by trying to embed it in computers (p. 7). On the practical side, significant effort has been devoted to creating computer programs that can outperform humans, without worrying about whether or not such programmes ‘think’ in the same way as their human counterparts (ibid.).
The relative success of deep learning, represented by deep neural networks has (inaccurately) resulted in the use of the term AI to depict this subclass of approaches in the popular media, ignoring large swaths of the discipline of artificial intelligence. Such deep learning is but one type of approach amongst many in the field of machine learning, which itself is a subfield of AI in which machines learn from data or from their own experiences (Brynjolfsson & McAfee, 2017; Mitchell, 2019; Alpaydin, 2020).
Taking its cue from the popular media, management has similarly embraced and adopted deep learning techniques as a proxy for the much wider discipline, perspectives, richness and range of approaches that make up artificial intelligence. It is fair to say that the label of AI has been changing rapidly, but the growing interest in its applicability and wide relevance has encouraged the new prevailing view that AI may be the new IT.
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Editor’s note: The PMWJ Advances in Project Management series includes articles by authors of program and project management books published by Routledge publishers. Each month an introduction to the current article is provided by series editor Prof Darren Dalcher, who is also the editor of the Routledge Advances in Project Management series of books on new and emerging concepts in PM. Prof Dalcher’s article is an introduction to the invited paper this month in the PMWJ.
How to cite this paper: Dalcher, D. (2021). The quest for artificial intelligence in projects, Advances in Project Management Series, PM World Journal, Volume XI, Issue III, March. Available online at https://pmworldlibrary.net/wp-content/uploads/2022/03/pmwj115-Mar2022-Dalcher-the-quest-for-artificial-intelligence-in-projects.pdf
About the Author
Darren Dalcher, PhD
Author, Professor, Series Editor
School of Management
University of Lancaster, UK
Darren Dalcher, Ph.D., HonFAPM, FRSA, FBCS, CITP, FCMI, SMIEEE, SFHEA, MINCOSE is Professor in Strategic Project Management at the University of Lancaster, and founder and Director of the National Centre for Project Management (NCPM) in the UK. He has been named by the Association for Project Management (APM) as one of the top 10 “movers and shapers” in project management and was voted Project Magazine’s “Academic of the Year” for his contribution in “integrating and weaving academic work with practice”. Following industrial and consultancy experience in managing IT projects, Professor Dalcher gained his PhD in Software Engineering from King’s College, University of London.
Professor Dalcher has written over 300 papers and book chapters on project management and software engineering. He is Editor-in-Chief of Journal of Software: Evolution and Process, a leading international software engineering journal. He is the editor of the book series, Advances in Project Management, published by Routledge and of the companion series Fundamentals of Project Management. Heavily involved in a variety of research projects and subjects, Professor Dalcher has built a reputation as leader and innovator in the areas of practice-based education and reflection in project management. He works with many major industrial and commercial organisations and government bodies.
Darren is an Honorary Fellow of the APM, a Chartered Fellow of the British Computer Society, a Fellow of the Chartered Management Institute, and the Royal Society of Arts, a Senior Member of the Institute of Electrical and Electronic Engineers, a Senior Fellow of the Higher Education Academy and a Member of the Project Management Institute (PMI), the British Academy of Management and the International Council on Systems Engineering. He is a Chartered IT Practitioner. He sits on numerous senior research and professional boards, including The PMI Academic Insight Team, the CMI Academic Council and the APM Group Ethics and Standards Governance Board as well as the British Library Management Book of the Year Panel. He is the Academic Advisor, author and co-Editor of the highly influential 7th edition of the APM Body of Knowledge. Prof Dalcher is an academic advisor for the PM World Journal. He can be contacted at d.dalcher@lancaster.ac.uk
To view other works by Prof Darren Dalcher, visit his author showcase in the PM World Library at http://pmworldlibrary.net/authors/darren-dalcher/
