Sentencing dangerous offenders in an era of predictive technologies: New skin, same old snake?

Abstract

Predictive technologies are now used across the criminal justice system to inform risk-based decisions regarding bail, sentencing and parole as well as offender-management in prisons and in the community. However, public protection and risk considerations also provoke enduring concerns about ensuring proportionality in sentencing and about preventing unduly draconian, stigmatising and marginalising impacts on particular individuals and communities. If we are to take seriously the principle of individualised justice as desert in the liberal retributive sense, then we face serious (potentially intractable) difficulties in justifying any sort of role for predictive risk profiling and assessment, let alone sentencing based on automated algorithms drawing on big data analytics. In this respect, predictive technologies present us, not with genuinely new problems, but merely a more sophisticated iteration of established actuarial risk assessment (ARA) techniques. This chapter describes some of the reasons why principled and social justice objections to predictive, risk-based sentencing make so elusive any genuinely synthetic resolution or compromise. The fundamental question as regards predictive technologies therefore is how it might even be possible to conceive such a thing without seriously undermining fundamental principles of justice and fairness.

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ORCID for David Gurnham: orcid.org/0000-0002-6807-7587

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