The Supreme Court provides cover for private actors who anonymously call 911 to report suspicious Black people to the police, and for the police who arrive with guns blazing.

Justice Marshall* delivered the opinion of the Court.

In this case, we decide whether it is consistent with the Fourth Amendment for a police officer who observed a traffic violation to use that violation as the justification to perform a racially-selective traffic stop, or as the pretext to investigate a crime for which the officer does not have probable cause. We answer that question in the negative.

Argued December 12, 1967.Decided June 10, 1968.

Mr. Chief Justice WARREN1 delivered the opinion of the Court.

Is the police practice known as “stop and frisk” constitutional? This case presents frisky questions about the power of police to cop a feel. Our decision is a minstrelsy in three acts, with elements of burlesque.

Argued November 2, 1999.Decided January 12, 2000.

Justice L. SONG RICHARDSON delivered the opinion of the Court*

The issue in this case is whether a person’s sudden and unprovoked flight from a clearly identifiable police officer, who is patrolling a high crime area, is sufficiently suspicious, without more, to justify a temporary investigatory stop pursuant to Terry v. Ohio. We hold that it is not.

Technological progress could constitute a huge benefit for law enforcement: greater efficiency, effectiveness and speed of operations as well as more precise risk analyses, including the discovery of unexpected correlations, which could feed nourish profiles. A number of new tools entail new scenarios for information gathering, as well as the monitoring, profiling and prediction of individual behaviours, thus allegedly facilitating crime prevention: algorithms, artificial intelligence, machine learning and data mining. Law enforcement authorities have already embraced the assumed benefits of big data. However, there is a great need for an in-depth debate about the appropriateness of using algorithms in machine-learning techniques in criminal justice, assessing how the substance of legal protection may be weakened. Given that big data, automation and artificial intelligence remain largely under-regulated, the extent to which data-driven surveillance societies could erode core criminal law principles such as reasonable suspicion and the presumption of innocence, ultimately depends on the design of the surveillance infrastructures. This contribution first addresses the so-called rise of the algorithmic society and the use of automated technologies in criminal justice to assess whether and how the gathering, analysis and deployment of big data are changing law enforcement activities. It then examines the actual or potential transformation of core principles of criminal law and whether the substance of legal protection may be weakened in a ‘data-driven society’.

Chapter 3 examines the challenges of applying the cost–benefit analysis theory given the current legal stanrads used by courts. The cost–benefit analysis theory requires quantified costs and benefits, while the current legal system uses broad, descriptive standards to evaluate searches. The chapter notes that the current legal standards are inconsistently applied, and thus provide inadequate guidance to police who are attempting to follow these standards. The chapter also points out a dissonance between how judges apply the current standards and how lay people believe the standards should be applied. The solution is to quantify the legal standards, thus making the standards more transparent, allowing for a greater range of standards, and allowing the judges to use data from predictive algorithms as formal factors in deciding whether to allow a certain type of surveillance. This will also allow courts and policymakers to use the cost–benefit analysis theory more accurately and efficiently.