AISEC: AI Secure and Explainable by Construction
AISEC: AI Secure and Explainable by Construction
批准号:
EP/T026952/1
负责人:
Ekaterina Komendantskaya
金额:
$102.85万
依托单位:
依托单位国家:
英国
项目类别:
Research Grant
财政年份:
2020
资助国家:
英国
项目状态:
未结题
起止时间:
2020 至 --
中文摘要
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英文摘要
AI applications have become pervasive: from mobile phones and home appliances to stock markets, autonomous cars, robots and drones. As AI takes over a wider range of tasks, we gradually approach the times when security laws, or policies, ultimately akin to Isaac Asimov's "3 laws of robotics" will need to be established for all working AI systems. A homonym of Asimov's first name, the project AISEC (``Artificial Intelligence Secure and Explainable by Construction"), aims to build a sustainable, general purpose, and multidomain methodology and development environment for policy-to-property secure and explainable by construction development of complex AI systems.We will create and deploy a novel framework for documenting, implementing and developing policies for complex deep learning systems by using types as a unifying language to embed security and safety contracts directly into programs that implement AI. The project will produce a development tool AISEC with infrastructure (user interface, verifier, compiler) to cater for different domain experts: from lawyers working with security experts to verification experts and system engineers designing complex AI systems. AISEC will be built, tested and used in collaboration with industrial partners in two key AI application areas: autonomous vehicles and natural language interfaces.AISEC will catalyse a step change from pervasive use of deep learning in AI to pervasive use of methods for deep understanding of intended policies and latent properties of complex AI systems, and deep verification of such systems.
期刊论文(9)
专著(0)
科研奖励(0)
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DOI:
10.1017/9781108775038.018
发表时间:
2022
期刊:
影响因子:
--
作者:
[Bogani R]
通讯作者:
Bogani R
A type- and scope-safe universe of syntaxes with binding: their semantics and proofs
具有绑定的类型和范围安全的语法宇宙:它们的语义和证明
DOI:
10.1017/s0956796820000076
发表时间:
2021
期刊:
Journal of Functional Programming
影响因子:
1.1
作者:
[ALLAIS G]
通讯作者:
ALLAIS G
DOI:
10.18653/v1/2023.emnlp-main.290
发表时间:
2023
期刊:
影响因子:
--
作者:
[Abercrombie G]
通讯作者:
Abercrombie G
DOI:
10.1145/3573105.3575674
发表时间:
2023-01
期刊:
Proceedings of the 12th ACM SIGPLAN International Conference on Certified Programs and Proofs
影响因子:
--
作者:
[M. Daggitt;R. Atkey;Wen Kokke;Ekaterina Komendantskaya;Luca Arnaboldi-]
通讯作者:
M. Daggitt;R. Atkey;Wen Kokke;Ekaterina Komendantskaya;Luca Arnaboldi-
DOI:
10.1007/978-3-031-13185-1_11
发表时间:
2021-04
期刊:
ArXiv
影响因子:
--
作者:
[Marco Casadio;Ekaterina Komendantskaya;M. Daggitt;Wen Kokke;Guy Katz;Guy Amir;Idan Refaeli]
通讯作者:
Marco Casadio;Ekaterina Komendantskaya;M. Daggitt;Wen Kokke;Guy Katz;Guy Amir;Idan Refaeli
共 7 条
COALGEBRAIC LOGIC PROGRAMMING FOR TYPE INFERENCE: Parallelism and Corecursion for New Generation of Programming Languages
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批准号:EP/K031864/2
-
项目类别:Research Grant
-
资助金额:$8.32万
-
财政年份:2016
-
负责人:Ekaterina Komendantskaya
-
依托单位:
COALGEBRAIC LOGIC PROGRAMMING FOR TYPE INFERENCE: Parallelism and Corecursion for New Generation of Programming Languages
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批准号:EP/K031864/1
-
项目类别:Research Grant
-
资助金额:$35.75万
-
财政年份:2013
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负责人:Ekaterina Komendantskaya
-
依托单位:
MACHINE LEARNING COALGEBRAIC AUTOMATED PROOFS
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批准号:EP/J014222/1
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项目类别:Research Grant
-
资助金额:$12.78万
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财政年份:2012
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负责人:Ekaterina Komendantskaya
-
依托单位:
Computational Logic in Artificial Neural Networks
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批准号:EP/F044046/2
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项目类别:Fellowship
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资助金额:$0.0万
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财政年份:2010
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负责人:Ekaterina Komendantskaya
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依托单位:
Computational Logic in Artificial Neural Networks
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批准号:EP/F044046/1
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项目类别:Fellowship
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资助金额:$30.82万
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财政年份:2008
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负责人:Ekaterina Komendantskaya
-
依托单位:
国内基金
海外基金
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