Partly in response to the so-called ‘reproducibility crisis’ in science, researchers are embracing a set of practices that aim to make the whole endeavor more transparent, more reliable – and better.
Crime data reflect only what crimes are identified by the police – not all the crimes that occur. So decisions based on crime data are necessarily biased and incompletely informed.
Algorithms can have enormous consequences on people’s lives, yet a federal law prevents us from studying whether they may be biased, unfair or discriminatory.
A European Union law will require human-understandable explanations for algorithms’ decisions. A team of researchers has found a way to provide that, even for complex calculations.
South Africa’s mining industry is on an unsustainable trajectory and needs to undergo fundamental transformation that emphasises transparency, equity, and community participation.
China will have to play by international rules on transparency and accountability if it wants to secure its place as a leader for economic development in Asia.
The financial products offered by the shadow banking sector allow investors to be further removed from their investments and banks to escape regulation, increasing the risk in the sector overall.
Data-driven algorithms drive decision-making in ways that touch our economic, social and civic lives. But they contain inherent biases and assumptions that are too often invisible to the public.