---
title: "Explainability for Vulnerability Identification in AI Systems"
ocid: "ocds-b5fd17-00a2575c-79f5-4d35-9d5f-abc8fa2c317c"
canonical_url: "https://d3tenders.com/contract/?ocid=ocds-b5fd17-00a2575c-79f5-4d35-9d5f-abc8fa2c317c"
markdown_url: "https://d3tenders.com/contract/ocds-b5fd17-00a2575c-79f5-4d35-9d5f-abc8fa2c317c.md"
json_url: "https://d3tenders.com/contract/ocds-b5fd17-00a2575c-79f5-4d35-9d5f-abc8fa2c317c.json"
source: "Contracts Finder"
current_stage: "Award"
buyer: "DEFENCE SCIENCE AND TECHNOLOGY LABORATORY"
published: "2022-08-24"
---

# Explainability for Vulnerability Identification in AI Systems

Buyer: DEFENCE SCIENCE AND TECHNOLOGY LABORATORY  
Current stage: Award  
OCID: ocds-b5fd17-00a2575c-79f5-4d35-9d5f-abc8fa2c317c

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## Summary

The procurement process for the contract titled "Explainability for Vulnerability Identification in AI Systems" was managed by the Defence Science and Technology Laboratory from Porton Down, SALISBURY, England. This award falls under the industry category of "Software package and information systems." The procurement stage was completed with a contract value of 149,717 GBP. The procurement method used was a direct procurement method with single tender action. The contract period spans from September 1, 2022, to August 31, 2023.

This tender presents an opportunity for businesses, particularly those involved in developing AI technologies and software solutions, to engage with the Defence Science and Technology Laboratory. Small and medium-sized enterprises (SMEs) would be well-suited for this opportunity. Understanding and exploiting artificial intelligence explainability methodologies is the focus of this contract, aimed at identifying and exposing vulnerabilities in neural network-based machine vision algorithms. Businesses interested in advancing AI technology in security and defence contexts could benefit from competing in this procurement process.

## Notice

The Research and Development submission to the Strategic Review (SR20) recognised the need to advance MOD's ability to adopt critical and game-changing technology, enabling autonomous systems on the battlefield and in the command space through the use of artificial intelligence. It proposed to do this by establishing a Defence AI Centre with the science and technology component delivered by a Defence AI Centre Experimentation hub (DAIC-X) led by Dstl. A key objective for DAIC-X is to understand and develop good practice in managing AI verification, validation, vulnerabilities as well as wider issues including trust and transparency and legal and ethical considerations. This task will research the potential to exploit artificial intelligence explainability (XAI) methodologies to identify and expose vulnerabilities in neural network-based machine vision algorithms. Please see the attached Tasking Form for further information regarding this award.

## Key Details

| Field | Value |
| --- | --- |
| Publication source | Contracts Finder |
| Latest notice | https://www.contractsfinder.service.gov.uk/Notice/32b71324-c3b8-4715-a708-db4659db552a |
| Notice type | Award Notice |
| Procurement type | Standard |
| Procurement category | Goods |
| Procurement method | Direct |
| Procurement method details | Single tender action (below threshold) |
| Tender suitability | SME |
| Awardee scale | Large |
| All stages | Award |

## Dates

| Field | Value |
| --- | --- |
| Publication date | 24 Aug 2022 |
| Submission deadline | 8 Jul 2022 |
| Future notice date | Not specified |
| Award date | 3 Aug 2022 |
| Contract period | 31 Aug 2022 - 31 Aug 2023 |
| Recurrence | Not specified |

## Values

| Field | Value |
| --- | --- |
| Tender value | £149,717 |
| Lots value | Not specified |
| Awards value | £149,717 |
| Contracts value | Not specified |

## Status

| Field | Value |
| --- | --- |
| Tender status | Complete |
| Lots status | Not specified |
| Awards status | Active |
| Contracts status | Not specified |

## Buyer

| Field | Value |
| --- | --- |
| Main buyer | DEFENCE SCIENCE AND TECHNOLOGY LABORATORY |
| Locality | SALISBURY |
| Post town | Salisbury |
| Postcode | SP4 0JQ |
| Country | England |
| ITL 1 | TLK South West (England) |
| ITL 2 | TLK7 Gloucestershire and Wiltshire |
| ITL 3 | TLK72 Wiltshire |
| Local authority | Wiltshire |
| Electoral ward | Winterslow & Upper Bourne Valley |
| Westminster constituency | Salisbury |
| Delivery location | Not specified |

## Supplier

| Field | Value |
| --- | --- |
| Number of suppliers | 1 |
| Supplier names | CITY, UNIVERSITY OF LONDON |

## CPV Codes

### Divisions

- 48 - Software package and information systems

### Codes

- 48000000 - Software package and information systems

## Release History

- 24 Aug 2022 at 12:49 - Award - Award Notice - https://www.contractsfinder.service.gov.uk/Notice/32b71324-c3b8-4715-a708-db4659db552a

## Documents

- https://www.contractsfinder.service.gov.uk/Notice/32b71324-c3b8-4715-a708-db4659db552a
  24th August 2022 - Awarded contract notice on Contracts Finder
- https://www.contractsfinder.service.gov.uk/Notice/Attachment/eb642f68-14ae-436b-9ccf-80e8e3384b44
  Part A of the Tasking Form giving the basic details of the requirement.
- https://www.contractsfinder.service.gov.uk/Notice/Attachment/d863edca-d9f7-4a2c-a0eb-aa4f6feb48e4
  This document details the requirements of the tasking.
- https://www.contractsfinder.service.gov.uk/Notice/Attachment/f43d8645-706a-4938-a944-5734231ce298
  Transparency Annex C.

## Provenance

This Markdown file is an alternate public rendering of the D3 Tenders contract record. The canonical page is https://d3tenders.com/contract/?ocid=ocds-b5fd17-00a2575c-79f5-4d35-9d5f-abc8fa2c317c. The underlying structured data is available as OCDS JSON at https://d3tenders.com/contract/ocds-b5fd17-00a2575c-79f5-4d35-9d5f-abc8fa2c317c.json.