IB Digital Society 3.2 Algorithms Questionbank

Sentencing criminals using artificial intelligence (AI)

In 10 states in the United States, artificial intelligence (AI) software is used for sentencing criminals. Once criminals are found guilty, judges need to determine the lengths of their prison sentences. One factor used by judges is the likelihood of the criminal re-offending*.

The AI software uses machine learning to determine how likely it is that a criminal will re-offend. This result is presented as a percentage; for example, the criminal has a 90 % chance of re-offending. Research has indicated that AI software is often, but not always, more reliable than human judges in predicting who is likely to re-offend.

There is general support for identifying people who are unlikely to re-offend, as they do not need to be sent to prisons that are already overcrowded.

Recently, Eric Loomis was sentenced by the state of Wisconsin using proprietary AI software. Eric had to answer over 100 questions to provide the AI software with enough information for it to decide the length of his sentence. When Eric was given a six-year sentence, he appealed and wanted to see the algorithms that led to this sentence. Eric lost the appeal.

On the other hand, the European Union (EU) has passed a law that allows citizens to challenge decisions made by algorithms in the criminal justice system.

* re-offending: committing another crime in the future

In criminal justice, "black box" algorithms are increasingly used to make decisions about bail, parole, and sentencing. However, the lack of transparency and potential for bias raise serious ethical concerns about fairness and accountability.

Facial recognition algorithms, used for security in airports, rely on large datasets and are sometimes criticized for algorithmic bias. For instance, these algorithms have been known to misidentify individuals of certain racial backgrounds, raising fairness and transparency issues.