Machine learning models increasingly make high-stakes decisions affecting people’s lives—determining who gets hired, who receives loans, who qualifies for parole, and who gets access to healthcare. Yet these systems can perpetuate and amplify societal biases, systematically disadvantaging certain groups whilst privileging others. The consequences are serious. Biased hiring algorithms exclude qualified candidates based on protected…
The integration of Artificial Intelligence into academia promises unprecedented efficiency, but it also introduces critical ethical challenges. For researchers and institutions, it’s no longer enough to simply use AI; we must use it responsibly and ethically. Operationalising ethical AI in research means moving past abstract discussions and applying tangible tools and processes to identify, mitigate,…