The U.K. government announced today a data protection bill as well as a proposal for AI regulations. Included in the announcement was a new policy paper from the U.K. Secretary of State for Digital, Culture, Media and Sport. The policy states “Our ambition is to support responsible innovation in AI - unleashing the full potential of new technologies, while keeping people safe and secure.”
The news out of the U.K. this week is aligned with the National AI Strategy that was published in fall 2021. The AI regulation policy paper is intended to be “pro-innovation” and “risk-based.” Learn more about today’s announcements, and read the full AI policy paper.
In her recent Forbes article, Cindy Gordon catches us with quite a lede including an introduction to corporate purpose and AI ethics amid the current "challenges given the decline of human happiness.”
Gordon goes on to cover:
“I truly believe that more humanity in business practices is critical and the decline of human happiness is one of the reasons, I am so passionate about more humanity in all business interactions and decisions impacting AI to ensure its AI for good,” writes Gordon.
Kashyap Kompella shares important insights in this recent TechTarget series. Kompella discusses what recent data privacy regulations have to do with AI governance (regulations including the Health Insurance Portability and Accountability Act, the California Consumer Privacy Act, the General Data Protection Regulation, and the Biometric Information Privacy Act).
He points out that “data governance is at the core of AI governance” but that it’s “possible to strike a balance between utility and privacy.” Kompella also shares four ideas on how AI and data privacy can coexist.
In Sharon Goldman’s latest for VentureBeat, she examines the work and philosophy of JoAnn Stonier. As Chief Data Officer at MasterCard, Stonier and her team “develop data strategy and work on data governance, data quality and data compliance” while also enabling “artificial intelligence and machine learning and helps design and operate some of the company’s enterprise data platforms.”
“You need to have a strong, ethical approach to your use of data, a strong commitment to really truthful and accurate and good quality of information, so you don’t have the wrong information in your products and solutions,” says Stonier.
Read the full article for more on data principles, AI innovation, and women in AI.
It’s official: beginning in early 2023 New York City will require that organizations complete “annual bias audits of any AI-based employment decision tools, including those supported by machine learning, statistical modeling and data analytics solutions.”
In this article from Corporate Compliance Insights, Lofred Madzou covers four ways companies can prepare now as well as outstanding questions that remain unanswered when it comes to this new law.
