Goal

High Quality AI aims to address the quality challenges that come with the current AI race. AI systems should be safe, robust, understandable, verifiable and auditable. AI systems should also be privacy proof, bias-free and fair.

85%

85 percent of AI projects will deliver erroneous outcomes due to bias in data, algorithms, or the teams responsible for managing them

47%

47 percent will choose a “robot doctor” over a human doctor

24

cases have been tested for data quality

OPPORTUNITIES and Challenges

High Quality AI aims to address the quality challenges that came with the current AI race. There are examples of poorly designed AI systems, inadequate use or availability of data to train the systems and undesirable consequences as a result of that.

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“High-Stakes algorithms
should not be crappy”

Cathy O’Neill

Theme In Action

  • RESEARCH

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  • ROUND TABLES

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  • CO-CREATION

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  • MEETUPS

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CONTACT

welkom@allai.nl