Fahad Diwan logs in and fills out the details of a person facing a bail hearing. Date of birth. Current charges. Pending charges. Past convictions.
Once his SmartBail program is done, he says, an algorithm trained on a mountain of data will be able to assess whether that suspect is a good candidate for pretrial release. Unlikely to be a flight risk. Unlikely to commit offences. Likely to comply with the conditions of release.
Suspects in custody are “legally innocent people,” said Diwan, 30, who hopes to one day put his software to use in Ontario’s bail courts. “We just want to find a way to make the system better, faster, economical.”
Proponents of this kind of program say machine learning would save time and money by quickly identifying people who should be released, speeding up bail hearings, reducing the number of people in jails and freeing up courts to focus on defendants who should have a full, contested hearing. All that with less bias and without affecting the crime rate.