Google Introduces SAIF, a Framework for Secure AI Development and Use

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Aug 17, 2017
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All new technologies bring new opportunities, threats, and risks. As business concentrates on harnessing opportunities, threats and risks can be overlooked. With AI, this could be disastrous for business, business customers, and people in general. SAIF offers six core elements to ensure maximum security in AI.

Many existing security controls can be expanded and/or focused on AI risks. A simple example is protection against injection techniques, such as SQL injection. “Organizations can adapt mitigations, such as input sanitization and limiting, to help better defend against prompt injection style attacks,” suggests SAIF.

Traditional security controls will often be relevant to AI defense but may need to be strengthened or expanded. Data governance and protection becomes critical to protect the integrity of the learning data used by AI systems. The old concept of ‘rubbish in, rubbish out’ is magnified manyfold by AI, but made critical where business and people decisions are based on that rubbish.
 

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