Cogs in the machine shows that using AI to manage people has serious negative consequences for workers.
Algorithmic management involving automated management decision making, intensive surveillance of workers and the collection and use of vast amounts of workers’ personal data, is becoming widespread in all sorts of industries.
AI tools are being used to augment and replace human workforce management, including for hiring and firing, directing and controlling workers, and measuring and evaluating their performance at work.
This report draws together international and Australian evidence to show how algorithmic management practices are undermining fairness and accountability, intensifying work and intruding into workers’ private lives.
The research identified negative outcomes for workers, including that algorithmic management:
- causes increased mental and physical health risks, due to work intensity and surveillance
- undermines privacy and dignity due to loss of autonomy, including no longer being able to exercise judgement and have control of work
- leads to reduced opportunity for collaboration and participation in the workplace
- causes loss of opportunity and discrimination due to biases in and misuse of personal data
- reduces trust in the workplace.
Existing regulation is not preventing the serious risks and harms of algorithmic management practices.
Report author, Dr Fiona Macdonald, said:
‘Most of the economic benefits of AI for the Australian economy are expected to come from organisations adopting and embedding imported technologies into their business practices, rather than from data centres or use of home-grown AI tools. But, as this report shows, where organisations are embedding AI technologies to manage their workforces, benefits are uncertain. However, there is no question of the serious risks and harms to workers.
‘There is no good reason to delay regulating to place clear limits on automated monitoring and decision-making practices, including drawing red lines through some particularly damaging practices.
‘Regulation should also ensure greater transparency and provide guarantees of worker involvement in planning, implementation and impact assessment of AI applications in the workplace.’