![]() ![]() Managing one’s online history becomes critical for crowdworkers, even though ratings are not necessarily impartial or free from collusion or retaliation. The presence of algorithmic computation means that continuous appraisal and evaluation generates a level of pressure about job performance that is of such magnitude, it is completely out of synch with the activity or task. Workers become functionaries in an ‘algorithmically-mediated work environment’ (Iperiotis 2012) of ruthless objectification (Ekbia and Nardi 2014). Furthermore, the growth of inbuilt performance management techniques for relentless technological filtering of good from bad work represents an extreme example of surveillance and control, as each worker has an ‘invisible supervisor’ (Elliott and Long 2016) monitoring every keystroke. Algorithmic outcomes are seen to embody meritocratic ideals and assumed to capture the essence of a workers’ performance, yet in the absence of human intervention and interpretation, they display inadequate levels of accountability and lack transparency (Diakopoulos 2016). They play an important role in the viability of crowdwork since they enable effective and efficient searching, matching, scheduling, and levels of remuneration: in the absence of management they are non-negotiable. ![]() Some authors view this positively and suggest that the evolving ‘digital trust infrastructure’ (Sundararajan 2016) represents a paradigm shift (Botsman 2015), operating as an ‘invisible hand’ that rewards good workers while punishing poor ones (Goldman 2011).Īlgorithmic objectivity is seen to be fundamental to the operation of platforms, and they are bestowed with legitimacy, accuracy and a technologically-inflicted promise of neutrality (Gillespie 2014). Consequently, platforms comprise complex algorithms which monitor and assess workers performance. Given that the terms and conditions of crowdsourcing effectively absolve platform-owners of any responsibility for transactions, interactions require a semblance of quality assurance. Online recommendation systems, which have become ubiquitous for grading films (Netflix), holidays (TripAdvisor), and books (Amazon), are now being applied to evaluate workers. This issue remains just as relevant today, as crowdwork poses interesting challenges for labour-capital relations. In 1987, Richard Hyman posed the question as to how far microprocessor-based systems have been integrated with a widespread strategy for the control of labour (Hyman 1987).
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