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| Source: | Contracts Finder |
| Notice Type: | Award notice |
| Buyer: | BEIS |
| Main Category: | Services |
| Procurement Method: | Call-off from a dynamic purchasing system |
| Tender Status: |
Pipeline status
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Application Deadline
20 October 2023
Closed
Estimated Value
£82,000
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| Estimated Value (ex. VAT): | £82,000 |
| Release Date: | 12 December 2023 |
| Application Deadline: | 20 October 2023 |
| Contract Start Date: | 20 November 2023 |
| Contract End Date: | 29 February 2024 |
| Contract Duration: | 3 months |
| Procurement ID (OCID): | ocds-b5fd17-294c6864-213c-4a7f-8b09-d2501276aee3 |
| Notice Reference: | c8c753ba-1816-4663-be0f-0c3a0df24176-706483 |
View Original Notice
Access the full notice on the official portal
Awarded to
| Award value: | £82,000 |
| Award decision date: | 1 December 2023 |
| Award status: | Active |
**Please note this is an Award Notice and not a call for competition, this Contract has been awarded via the Crown Commercial Services - RM3764.3 - Lot 1: Cyber Security Services 3.** The Department for Science, Innovation and Technology has a requirement to appoint a supplier to conduct a study to comprehensively map the cyber risks to different AI technologies and their deployment. Purpose AI use is growing. In April 2023, an estimated 16% of all UK businesses had adopted at least one AI technology. However, this number is now likely to increase significantly with the growth of more accessible and powerful generative AI models. To inform our policy work in this space, the Department wants to improve its understanding of the cyber risks to AI models and systems. The Department would therefore like to commission a study to comprehensively map the cyber risks to different AI technologies and their deployment. Objectives The Department is commissioning this research primarily to develop a comprehensive mapping of the cyber security risks to AI models and systems. More specifically, the Department seeks to gain: - Comprehensive mapping of cyber security risks to AI across different AI technologies and across different parts of the AI life cycle. - An understanding of all AI risks with a delineation between those specific to broader software and those solely in relation to AI. - Identification of the impacts these vulnerabilities and risks can cause, including the scale of the damage/impact.
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