Titlebook: Keeping Your AI Under Control; A Pragmatic Guide to Anand Tamboli Book 2019 Anand Tamboli 2019 Artificial intelligence.liability.insurance.

愛國(guó)者

杠桿

Ardent

certain

Anand TamboliLearn from a pragmatic and usable risk evaluation framework.Study a brand-new concept of AI insurance with actionable steps.Examine the process through which you can quantitative score AI vendors to i

痛苦一下

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刺穿

Learning Lessons from Past FiascoesWhenever we are set to improve something, what is the first thing we do? If you are thinking of assessing the past, you are correct. It is the most convenient and sure-shot method of understanding improvement areas and fixes that are required for better future outcomes.

我不死扛

強(qiáng)行引入

Good AI in the Hands of Bad UsersUntil now, we have discussed generic and specific risks of AI solutions that were either applicable at a macro level or were specific to the solution design. In this chapter, we will talk about risks arising out of the interaction of the AI system with other systems and human users or operators.

珍奇

A Systematic Approach to Risk MitigationRisk mitigation is not an easy task; instead, it is even harder if there is no quantifiable measure attached to it. In this chapter, we will discuss a systematic approach to risk mitigation. There are four types of risk mitigation strategies one could use, namely, risk avoidance, acceptance, transference, and risk control or reduction.

泄露

When Working with Emerging TechnologiesThroughout this book, I have attempted to explain the various possible risks related to AI solutions and ways to mitigate most of these risks or control them. Once these controls are in place, the world should be a better place. But as the technology adapts and changes, there could be new risks in the future, which are unpredictable at this point.