As SAS CEO Jim Goodnight posted on 28 January 2023 on LinkedIn, “SAS is committed to developing, implementing and promoting trustworthy AI systems that help ensure sustainable improvements and responsible innovation for our customers, the economy and society.”
Specifically, SAS has committed to six trustworthy AI principles, as shown in the graphic below from the SAS web site:
Human-centricity indicates that human well being and human agency must remain first and foremost. Not exactly like the Hippocratic Oath by doctors “First, do no harm,” but similar. Any AI that does nothing for the benefit of humans (and by extension the health of the planet we live in) should be questioned as to what is its purpose. As part of human centricity is the tenet of equity. AI should improve equity and should not exacerbate inequities.
AI should be fully inclusive. This means that it must ensure accessibility for all. It also means that its developers and managers should include a diverse set of perspectives and experiences. SAS is committed to maintaining a diverse, inclusive, equitable and satisfied work force. We also work diligently to ensure that our software is accessible. See my article on Accessibility.
Anyone who creates AI or builds applications that use AI will not be able to 100% control the irresponsible use of that AI. Therefore, to be responsible we must proactively identify adverse impacts and mitigate those impacts. To identify adverse impacts, we must first decide what impacts are adverse versus beneficial. See my previous blog on AI Ethics Part 1: Bots to read a discussion of this.
The best surrogate that we have for ethics is laws. Unfortunately, laws surrounding AI are sadly lagging behind the AI technology itself. Nonetheless, we must make ourselved aware of and in compliance with laws that exist and also be engaged in guiding those conversations. SAS leadership is involved at highest levels of US AI ethics conversations. For example, Reggie Townsend, Director of the SAS Data Ethics Practice, serves on the US National Artificial Intelligence Advisory Committee. This committee advises the US President Biden and the US National AI Initiative Office on topics related to the development and use of AI.
Transparency is important. We must openly communicate the intended use and potential risks of AI applications. In addition, how the AI makes decisions such as denying loans or identifying possible fraudsters must be as transparent as possible. In some cases explainability is legislated, as in the financial sector. SAS Viya provides interpretability aids out of the box, including:
The principal of robustness means that AI applications should operate safely and reliably. It also enables mechanism to assess and manager risks throughout a system’s life cycle. SAS Viya includes a number of ways to manage algorithms and models and to monitor their depreciation over time.
Privacy & Security
Privacy and security means that SAS software must protect any data it accesses as well as any IP of its users. SAS has close to 50 years of experience in software privacy and security and continues to follow the latest in this realm.
For More Information:
See the excellent webinar on Trustworthy AI and using SAS tools to mitigate bias by Tamara Fischer and Veron....
Ponder This: Grannies and Grammys vs AI Is all the AI in the world equal to the wisdom of one granny? AI might have pointed to Beyonce to win album of the year (she didn't). AI might have pointed to Taylor Swift for getting called up on stage at least one time (she didn't). But it took a wise Granny to predict that Harry Styles would win album of the year. Harry was not the greatest singer nor did he have the greatest songs. But Harry has that certain je ne sais quoi that eludes quantification and thus AI. But any Granny sees it immediately and tells her young granddaughter, “Stay away from that guy; but if you must invite him for dinner, seat him next to me.”
Harry Styles hugs a granny who predicted his Grammy win in February 2023
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