Technology, Artificial Intelligence, and the Future of Sport and Physical Activity

Introduction

This chapter concludes the book by summarizing the main contributions.

In recent years, understanding of performance in sport, as well as the capacity to track data of people engaged in recreational-level physical activity and exercise, has rapidly developed (Couceiro et ah, 2016). In co-authoring this book, we sought to understand how AI can be used to enhance and enrich participation in sport and physical activity from the perspectives of high performance and lifelong recreational engagement. The chapters of this book examined different aspects of artificial intelligence, which require digital technologies to provide support for tasks - such as education, coaching, teaching, and supporting learning and performance in sport and physical activities - that have traditionally challenged humans. The book indicates how the current focus of attention in AI research has been to create and develop hardware and software systems that can record, classify, analyse, and interpret large amounts of data. In sport, there has been a considerable amount of effort undertaken for providing a wide range of ever-improving technological solutions designed to extract data about key aspects of performance during training and competition, including kinematics of movement, collective system behaviours, and physiological data on outputs of different sub-systems.

An important take-home message from the book is that the AI system implementation and exploitation stages require teams of specialists working in a transdisciplinary organization to act on data, for the purposes of continuously enhancing athlete learning, development, and performance preparation from augmented information provided from AI systems (Rothwell, Davids, Stone, Araujo, & Shuttleworth, 2020). The implementation of new digital tools for recording, analysing, and tracking of information on individual’s performance, progression, and health has enhanced the use of artificial intelligence systems to augment the (re)design of selection, training, and practice activities, supporting an individualization of such processes as never before. Summarizing the technical engineering advances in sport, Couceiro et al. (2016) noted how such intelligence systems provided data and feedback to regulate athlete behaviours by enhancing: (i) development of innovative technological solutions to estimate the changing location of wearable mobile devices in a performance setting, supporting individual tracking with multi-lateration techniques and wireless propagation measures; (ii) design of multi-sensor fusion algorithms to provide real-time and fault-tolerant information about an individual’s organizational state (i.e., position and orientation), integrating wireless propagation measures with data coming from attached inertial measurement units; (iii) integration of physiological sensors during exercise and training (e.g., heart rate monitors) within wearable devices for non-invasive remote bio-signal monitoring of the active individual’s performance state and design of data mining procedures to improve data reliability from the sensing units; and (iv) with regard to sport performance, mathematical formulations of software systems for online performance analysis and predictions based on player actions, locations, and physiological data monitored over time.

In this chapter, we overview the key ‘take-home’ messages that may be highlighted from reading this text. At one level of analysis, an important message is to warn against technological determinism: considering new technological advances as an immutable over-arching force that imposes irresistible and unavoidable changes on the functional behaviours of individuals, organizations, communities, and societies. Despite the enormous amounts of funding devoted to finding technological solutions to planning and predicting outcomes of competitive events, sports still have a significant amount of uncertainty. This sentiment is captured by Brazil’s assistant national coach, Sylvinho, discussing how the margins between winning and losing can be wafer-thin (https:// www.theguardian.eom/football/2020/aug/03/sylvinho-winning-a-treble- with-barcelona-was-spectacular-arsenal-wenger-guardiola-manager). Here, he discussed how some of the greatest coaches in association football including Pep Guardiola, Tite national coach ofBrazil, and Roberto Mancini could never guarantee winning competitions:

Guardiola used to always say: ‘Lads, we’re going to do everything, everything, everything, everything. But I don't know if we’ll win, I can’t guarantee that.’ Tite’s the same: he studies all... day ... long. Locked away, studying. Mancini too, moving with the game. I see Diego Simeone, a great coach, lose two European Cup finals. Sometimes, the difference between winning or not is tiny. We won a treble getting there via Stamford Bridge with the last kick. Bloody hell. Pffff. How do you explain that?

Furthermore, it is important to recognize that the rapid proliferation of digital technologies in physical education, sport, and physical activity also risks an over-reliance on its use. For more effective implementation of technology, it needs to be integrated into a methodology for enhancing performance and enriching the development of athletes and teams (Stone, Strafford, North, Toner, & Davids, 2018).