Policing

2017/3632
Sian Berry

What mechanisms are in place to ensure that the automatic facial recognition software in use by the Metropolitan Police Service is independently tested for racial accuracy biases?

2017/3631
Sian Berry

In 2015, the House of Commons Science and Technology Select Committee recommended that the Biometrics Commissioner is given responsibility for oversight of automatic facial recognition.  What independent oversight mechanism is responsible for the Metropolitan Police Service's use of automatic facial recognition technology?  

2017/3630
Sian Berry

The Home Office has not yet produced a biometrics strategy, which would include the use of automatic facial recognition. However, the Metropolitan Police Service is already using automatic facial recognition as a policing tactic. Is there any legal basis, strategy, policy or procedure that governs the way this capability is being used by the police in London?

2017/3629
Sian Berry

What is the retention period for footage and images recorded by the cameras involved in the automatic facial recognition capability at Notting Hill Carnival? Please specify if there are different retention periods for different sources of images. What are the criteria for further retention of images beyond this period?

2017/3628
Sian Berry

This year (2017) was the second time that the Metropolitan Police Service used automated facial recognition at Notting Hill Carnival. What consultation was carried out before the use of this intrusive tactic? What are your measurements of success for this capability?

2017/3627
Sian Berry

What criteria were used to place people on the 'watch lists' for a) human recognisers, and b) automatic facial recognition software, to monitor the attendees of Notting Hill Carnival 2017? What was the total number of people on a) both, and b) each of these watch lists?

2017/3626
Sian Berry

How many false positive matches highlighted on the automatic facial recognition software were identified after being checked by police officers a) checking against live images, and b) verification after further action was taken?

2017/3625
Sian Berry

How many false positive matches were made by the automatic facial recognition software used at Notting Hill Carnival in 2016 and 2017? Please provide a breakdown of the different age groups, gender and ethnicity of these false positives (with ethnicity also broken down by gender).

2017/3624
Sian Berry

How many of the positive matches identified using automatic facial recognition resulted in further action by the police? Please provide a breakdown of the total number of individuals identified who were a) stopped by police, b) stopped and searched, c) detained, d) arrested, e) cautioned, and f) other.

2017/3623
Sian Berry

How many positive matches were identified using automatic facial recognition at Notting Hill Carnival in 2017? Were all of these positive matches checked by a police officer before being considered for further action?

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