Ethical use of artificial intelligence in the workplace
To what extent do people who develop or deploy Artificial Intelligence innovations consider the impact on workers?
What is this research about?
Artificial Intelligence (AI) is fundamentally changing jobs across different industries and types of work. These developments have given rise to a new type of machine, a prediction machine, which can automate complex decision-making tasks. This technology provides many benefits, such as increasing productivity, streamlining processes and lowering the cost of making accurate predictions.
However, many businesses who are introducing this technology do not have a sufficient understanding of the limitations of these prediction machines. Ill-informed technology deployment decisions, which place too much trust in the integrity of machine predictions, can give rise to conflicting thoughts and behaviours in the workers required to use them.
The introduction of AI can have unintended consequences on a worker’s wellbeing, outside of what could traditionally be recognised as a harm. Attention needs to be paid to the appropriate ethical handling of AI technology.
What will the researchers do?
The researchers will seek to determine which principles are at the forefront of decision-makers’ minds and which tend to be overlooked. This knowledge will allow us to construct a scorecard that companies can use to track the degree to which their use of AI technology aligns with the wellbeing of their workers.
The study aims to assist businesses adopting AI technology while safeguarding workplace health and safety by developing a practical and readable guide outlining ethical approaches that champion wellbeing throughout the planning, implementation and continued use of AI technology.
Mapping the processes of conception, design and implementation of an AI application against AI ethics principles, the research team will explore the extent to which these different principles apply to each of these stages and the degree to which such application affects workplace health and safety.
Research partners and stakeholders
South Australian Centre for Economic Studies, Australian Institute for Machine Learning (University of Adelaide)/Australian Industrial Transformation Institute (Flinders University of South Australia)
Project commenced: June 2020
Project completion: Late 2021
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