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"To date, all stakeholders are working intensively on policy design for
artificial intelligence. All initiatives center around the requirement
that AI algorithms should be fair. But what exactly does it mean? And
how algorithmic fairness can be translated to legal and policy terms?
These are the main questions that this paper aims to explore."
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Showing posts with label predictive algorithms. Show all posts
Showing posts with label predictive algorithms. Show all posts
Big Data and Criminal Justice - What Canadians Should Know
"On its surface, the term ‘big data’ refers both to very large data sets, as well as the tools used to manipulate and analyze them. This concept, however, does not just refer to the harvested information – it also refers to the motivations behind what harvesting that information is supposed to achieve. When data is collected en masse, and algorithms (a series of instructions that tell a computer what to do) cross reference data both within and between datasets, the computational software processing the data identifies patterns within them. It is this notion of “identifying patterns” that serves
as the backbone of predictive justice.
Predictive justice uses data on past occurrences or behaviours to make decisions about the future, such as who and where will be policed, how an individual should be sentenced given the risk they pose to others, and when someone should be released from prison....
Unfortunately, there has been a lack of both awareness and scholarship regarding how this technology is being employed across Canadian police departments, justice agencies, and courts....
These predictive technologies are appealing because they claim to make justice a speedier, more egalitarian affair; they take complicated and potentially-biased discretionary decisions – such as who to police and who to assess as “higher-risk offenders” - and reduce these decisions to scores, numbers, or dots on a map. In so doing, these technologies can incur greater costs than benefits."
Read on...
as the backbone of predictive justice.
Predictive justice uses data on past occurrences or behaviours to make decisions about the future, such as who and where will be policed, how an individual should be sentenced given the risk they pose to others, and when someone should be released from prison....
Unfortunately, there has been a lack of both awareness and scholarship regarding how this technology is being employed across Canadian police departments, justice agencies, and courts....
These predictive technologies are appealing because they claim to make justice a speedier, more egalitarian affair; they take complicated and potentially-biased discretionary decisions – such as who to police and who to assess as “higher-risk offenders” - and reduce these decisions to scores, numbers, or dots on a map. In so doing, these technologies can incur greater costs than benefits."
Read on...
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