The final speaker in this session at the IAMCR 2025 conference in Singapore is Peichi Chung, whose focus is on digital labour in the context of e-sports. This is a rapidly growing area of digital entertainment, with an inaugural e-sports Olympics to be held in Dubai in 2027.
Past work on e-sports has focussed on e-sports as fan-based digital labour, and linked this to emerging worker identities in the gig economy. This is further disrupted by the rise of artificial intelligence and its embedding into video games, and the gamification of digital work; overall, video gaming becomes a form of digital labour (or ‘playbour’), and digital labour takes on aspects of computational gaming.
This human-machine hybridisation represents a shift towards competitive playing, giving labour increasing control over the machine and enabling new modes of production that involve autonomous creativity – but does this result in new autonomy for labour mobility?
How, then, has artificial intelligence changed working conditions in the e-sports gaming environment? Has digital labour evolved and been reflected in computational gaming?
This paper conducted expert interviews with professional e-sports players, game developers, team and tournament managers, data analysts, and other industry stakeholders in Hong Kong; these highlighted the increasing datafication and metrification of personalised and competitive play, and such datafication is also used to support player engagement in immersive gaming.
This includes the availability of AI-powered playing coaches and AI tournament referees; increasingly complex data analytics presented through gaming leaderboards, performance reviews, and other features; the emergence of dedicated e-sports data analytics companies; and the use of such data to make games more enjoyable, inclusive, and addictive.
Games data are also being used to create more realistic AI opponents (or ‘v-rivals’) in games; conversely, professional players also test and train themselves against an aggregate of leading competitors’ data. They learn to ‘think like a system’: to internalise the rules of the game and its AI features. This does not necessarily increase their autonomy, but rather datafies their digital labour as professional e-sports players.
