Algorithms become the arbiters of determinations about individuals (e.g. government benefits, granting licenses, pre-sentencing and sentencing, granting parole). Whilst AI tools may be used to mitigate human biases and for speed and lower costs of trials, there is evidence that it may enforce biases by using characteristics such as postcode or social economic level as a proxy for ethnicity.
The use of commercial AI tools such speech recognition – which have been shown to be less reliable for non-white speakers – can actively harm some groups when criminal justice agencies use them to transcribe courtroom proceedings.
When it comes to decision making, it might seem that computers are less biased than humans. But algorithms can be just as biased as the people who create the… Quick, […]Read More
Dartmouth professor Dr. Hany Farid reverse engineers the inherent dangers and potential biases of recommendations engines built to mete out justice in today’s criminal justice system. In this video, he […]Read More
Whilst some believe AI will increase police and sentencing objectivity, others fear it will exacerbate bias. For example, the over-policing of minority communities in the past has generated a disproportionate […]Read More
A study on the discriminatory impact of algorithms in pre-trial bail decisions.Read More
Racial disparities in automated speech recognition Automated speech recognition (ASR) systems are now used in a variety of applications to convert spoken language to text, from virtual assistants, to closed […]Read More
Sophisticated computational techniques, known as machine-learning algorithms, increasingly underpin advances in business practices, from investment banking to product marketing and self-driving cars. Machine learning—the foundation of artificial intelligence—portends vast changes […]Read More