Domestic Abuse Bill

Debate between Baroness Garden of Frognal and Baroness Grey-Thompson

Committee stage & Committee: 2nd sitting (Hansard) & Committee: 2nd sitting (Hansard): House of Lords
Wednesday 27th January 2021 Lords Chamber

[The Deputy Chairman of Committees (Baroness Garden of Frognal) (LD)]

The noble and learned Baroness, Lady Butler-Sloss, has withdrawn, so I now call the noble Baroness, Lady Grey-Thompson.

[Baroness Grey-Thompson (CB) [V]]

My Lords, I shall speak to Amendments 23, 28 and 62 in this group, to which my name is attached. I thank the noble Lord, Lord Hunt, for moving the first of these amendments and for comprehensively covering their purpose. I draw your Lordships’ attention to my entry in the register of interests in that I am a vice-chair of the Local Government Association.

Amendments 23 and 28, supported by London School of Economics research, make explicit the importance of utilising data and technology in the prevention, reporting and detection of domestic abuse and the commissioner’s important role in supporting this. Examples include encouraging the use of new “silent” methods of reporting abuse—especially important during lockdown—and using artificial intelligence methods, alongside better data usage, to determine the likelihood of repeated abuse.

Amendment 62, again based on LSE research, would ensure that, when the need for a handing out a domestic abuse protection notice was being considered, senior police officers could take into account any previous related criminality and convictions held by the alleged perpetrator. LSE research has shown that previous convictions can be a key indicator of the potential for future incidents of domestic abuse and yet are not currently taken into account when they should be regarded as a priority by any police officer considering handing out a DAPN.

Having access to the criminal history of the alleged perpetrator should be a crucial aspect of decision-making. The amendment would improve data sharing to strengthen the ability of the police to make informed, and potentially life-saving, decisions. It would enable immediate protection for survivors following a domestic abuse incident; for example, by requiring a perpetrator to leave the victim’s home for up to 48 hours.

Currently, there are many significant issues with data sharing that can have serious effects on police forces’ ability to identify, prevent and tackle domestic abuse. Not having a systematic way of recording the same person, victim or perpetrator often means that repeat victims or perpetrators are not spotted or that no action is taken to protect and prevent.

Moreover, police forces do not share data systematically, apart from the police national computer, and that only records charges. Even more concerning, there is no data or systematic information exchange between non-profit and police, so abusers are able to be invisible to the police. That is a particular worry right now, when many people are hidden from sight.

There are many examples of where better use of technology and data can help tackle abuse, including helping to determine what level of danger someone may be in so that they can receive help as quickly as possible, and prioritising police resources and responding to domestic abuse calls accordingly. Using machine-learning prediction will go a long way to supporting those who desperately need it.