Select committee: Public Accounts Committee
Recommendation 38
6th Report - DWP Customer Service and Accounts 2023-24
Published 31 Jan 2025
Addressed to HM Treasury
Public Accounts Committee DWP Customer Service and Accounts 2023-24 All items in this report Report on parliament.uk ↗ Inquiry on parliament.uk ↗
Recommendation (the committee's words)
We stressed that we would like to be satisfied that DWP’s use of machine learning is fair and consistent. DWP highlighted its main safeguard, which is that it would never stop benefit payments to a customer due to an AI tool. It said that what AI helped it to do was to direct the work of its staff to investigate more effectively. DWP also committed to work with us and the National Audit Office to find a way to provide the necessary further assurance as to the fairness of its machine learning techniques. It reiterated this commitment in subsequent correspondence.74 74 Qq 52-54; Letter from DWP to the Public Accounts Committee dated 23 December 2024 18
From: Public Accounts Committee, 6th Report - DWP Customer Service and Accounts 2023-24 (HC 354), 31 January 2025
Government response
The government responded to the whole report on 6 May 2025.
Summary written by Accountability Index from the government's response. It is not the government's own words.The government agrees with most of the Committee's recommendations in this response, but disagrees with the recommendation that it set out when it expects to meet its PIP processing target.
- On PIP claim times, the government disagrees with the recommendation, stating the department "has to balance speed against the risk of inaccuracy". It says the Health Transformation Programme will modernise PIP "in the longer-term".
- On ESA calls, the government agrees and says it is recruiting 160 colleagues by March 2025. It states that customer wait times for ESA enquiries "will be improved by September 2025".
- On counter fraud, the government agrees and says that from April 2025 the department "will begin progressive deployment of an additional 3,000 staff", expecting the full number to be in role by 2027-28.
- On machine learning, the government agrees and gives a target implementation date of summer 2025. It says the department "will support an in-confidence session" on the 2024 fairness analysis assessment.