Artificial intelligence (AI) is commonly offered as a potentially beneficial application towards bettering the future of people, organisations and society. However, AI can have a dark side, where, for example, ideologically driven AI decision-making is directed at political ends involving the impoverishing of the poorest in society to further neoliberal individual and collective political ambitions and careers. This paper aims to examine this ideologically driven dark side use of AI and to answer the research question of whether algorithmic and AI-enabled decision-making can be used by ruthless actors for dark purposes.
The current research adopts a case study approach to explore the algorithm-enabled immoral and unethical neoliberal governmental approach to welfare provision in Australia. This exploration is achieved via an examination of the report from the Australian “Royal Commission into the Robo-debt Scheme” and the related academic and other literature.
Robo-debt was an Australian AI-driven debt recovery system motivated by a neoliberal political agenda that aimed to capture overpayments from welfare benefit recipients. Findings include that AI misapplied faulty algorithms based on inappropriate timescales to assign and claim back overpayments to welfare recipients who had not necessarily been overpaid. The full power of the state was used to chase alleged debtors, resulting in huge amounts of stress, anxiety, panic and worry for those in the most vulnerable groups of Australian society.
The current paper is the first to examine the report from the Royal Commission concerning this ethical scandal in Australia through the lens of corporate psychopathy. According to the report, up to $1.73 billion in wrongly attributed debts were attributed to about 433,000 Australians. These people included victims of abuse, those with mental health issues, single mothers and their children, those with disabilities and the educationally disadvantaged. The use of algorithm-driven AI caused considerable societal hardship and upheaval.
