Effective implementation of existing law can protect us from the risks posed by AI algorithms.
Articles on algorithms at work
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Antisemitism today does not always appear in the form of traditional hate speech. It manifests in GIFs, memes, vlogs, comments and reactions on social media platforms.
A UK controversy about school leavers’ marks shows algorithms can get things wrong. To ensure algorithms are as fair as possible, how they work and the trade-offs involved must be made clear.
Our review of 45 studies on machines as managers shows we generally hate being slaves to algorithms.
The Fair Work Commission’s ruling that delivery rider Diego Franco was an employee of Deliveroo is a major legal win for Australia’s gig workers.
Employees at Amazon knew they were under constant surveillance and that the company had a history of sacking those who were pro-union.
Food-ordering platform Menulog has declared it will break with the standard contractor business model. But let’s not get too excited yet.
The departure of AI ethics researcher Timnit Gebru from Google highlights attempts to make algorithmic decision-making accountable.
Handing management to algorithms creates ‘black-box bosses" whose decision-making is hard to understand or question.
A tale of two leaders on Twitter in the age of COVID-19.
Computer capabilities have boosted our decryption technology to great heights. How will the future compare to a past, one in which codes were thought to be a means of communicating after death?
Automated tools could help encourage access to justice in areas such as divorce, owners corporation disputes and small value contracts.
High grades might be awarded to papers that show the structural features of highly persuasive writing – papers that follow the “persuasion script”, so to speak.
There are good reasons why business has not been as successful as sports teams at implementing algorithmic decision-making.
Creating an ethical machine learning system is no simple task, but maths can help.
On balance, computers may make better judges of risk than people.
This is how marketers are taking advantage of customer data to build predictive algorithms, and even tailor their products and offerings.
Top contributors
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Senior Lecturer, Management and Organisations, The University of Western Australia
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Senior Lecturer, Management and Organisations, UWA Business School, The University of Western Australia
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Associate professor, University of Sydney
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Sessional Lecturer, Australian Catholic University
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Senior Lecturer of Marketing, Swinburne University of Technology
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Professor in Business Information Systems, University of Sydney
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Professor of Mathematics, Toronto Metropolitan University
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Research Fellow, Humanising Machine Intelligence Grand Challenge, Australian National University
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Australian Research Council Laureate Fellow, Curtin University
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Professor and ARC Future Fellow, Education & Social Work, Education Futures Studio, University of Sydney
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Senior lecturer in Law, Brunel University of London
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Head of School at the School of Accounting, Curtin University
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PhD candidate, University of Sydney
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Postdoctoral Fellow, Bonavero Institute of Human Rights, University of Oxford
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Research Fellow, School of Information Technology and Electrical Engineering, The University of Queensland