- September 27, 2018
- Posted by: admin
- Category: Uncategorized
Can intelligent robots bribe govt officials for contracts? Asking for… a friend
SAP claims- SAP has created an AI ethics panel to guide its use of machine-learning technology. If only it had a similar committee for fraud allegations: it might have avoided the corruption scandal engulfing it in South Africa.
The German ERP giant – which is accused of kicking back $2m to secure state contracts – claimed it is the first European biz to create a external artificial intelligence ethics board: a five-person committee that includes technical experts and specialists in public policy, ethics, and bioethics. However, while several of them possess solid IT credentials, there’s no one with a background in AI.
Rather, expertise in the evolving field will come from inside SAP. Specifically, the panel will work alongside the software house’s internal technology ethics steering group – which includes people working in the field of machine learning as well as folks in corporate strategy, design, digital government, and data protection.
The ethics panel will dish out advice on how its specific use cases of AI technology may be affected by internationally accepted human rights principles and its own guiding principles for artificial intelligence.
That seven-point plan aims to demonstrate the firm’s commitment to do more than just what is legally required, and follows similar plans drawn up by Microsoft and Google.
“Bias can negatively impact AI software and, in turn, individuals and our customers,” SAP’s Corinna Machmeier explained on Tuesday. “This is particularly the case when there is a risk of causing discrimination or of unjustly impacting underrepresented groups.”
To address this, SAP said technical teams will be required to “gain a deep understanding of the business problems they are trying to solve,” and think hard about the quality of data required. The biz is also investigating technical ways to mitigate biases, as well as increase the diversity and interdisciplinarity of its techies. The wider the backgrounds of its developers, the better it will be at catching social and cultural biases in training data and algorithms, we assume.
The software house is also committed to ensuring its AI code undergoes rigorous testing in the real world, and making the input, capabilities, intended purpose, and limitations of its systems clear to customers so no one is duped by hype – or tries to use the software for naughty purposes.
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Article Credit: The Register
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