Unleashing the Power of AI: Explainability and Transparency are the Keys to Promote Ethics, Trust and Inclusion in Digital Policing

Since Artificial Intelligence is inherently neither good nor bad, it can be used in improper ways—even unintentionally—causing significant harm and infringing on fundamental rights, but it also holds great promise to promote individual wellbeing and solve societal problems. The development and use of AI require ethical values to ensure that AI tools are developed and […]

The ACM Conference Highlights: Fairness, Accountability, and Transparency in Socio-Technical Systems

Fairness, accountability, and transparency in socio-technical systems is a research area that has attracted growing interest. Socio-technical systems shape our day-to-day experience; therefore, it is essential to address the problems they may cause from different perspectives (e.g., legal, philosophical, educational among others). The work and workshops at this year’s ACM Conference on Fairness, Accountability, and […]

Bias in machine learning: How to measure fairness in algorithms?

ProPublica, a nonprofit media organisation, published a seminal article in 2016, entitled Machine Bias. In this piece, they claim that the risk assessment software used by the US judiciary to classify future defendants was biased against the black community. The algorithm underpinning the risk assessment, COMPAS, analysed past convicts ‘historical data in order to assess […]