Ethics In AI: Why Values For Data Matter; Forbes, December 18, 2020

Marc Teerlink, SAP, Global Vice President of Intelligent Enterprise Solutions & Artificial Intelligence, Forbes; Ethics In AI: Why Values For Data Matter

"The Double-Edged Sword of AI and Predictive Analytics

This rising impact can be both a blessing and a concern. It is a blessing — for example when AI and Predictive analytics are using big data to monitor growing conditions, to help an individual farmer make everyday decisions that can determine if they will be able to feed their family (or not).
Yet it can also be real concern when biased information is applied at the outset, leading machines to make biased decisions, amplifying our human prejudices in a manner that is inherently unfair.

As Joaquim Bretcha, president of ESOMAR says, “technology is the reflection of the values, principles, interests and biases of its creators”...

What’s the takeaway from this? We need to apply and own governance principles that focus on providing transparency on how Artificial Intelligence and Predictive Analytics achieve its answer.

I will close by asking one question to ponder when thinking about how to treat data as an asset in your organization:

“How will machines know what we value if we don’t articulate (and own) what we value ourselves?” *

Dig deeper: Want to hear more on ethics in AI, transparency, and treating data as an asset? Watch Marc’s recent masterclass at Web Summit 2019 here. 

*Liberally borrowed from John C Havens “Heartificial Intelligence”"

In Silicon Valley, Searching for Diversity in an Algorithm; Fox Business, 6/9/14

Jennifer Booton, Fox Business; In Silicon Valley, Searching for Diversity in an Algorithm:

"Mountain View, Calif.-based Google said its 46,000-person workforce is “miles” away from where Google would like to be. It blamed education, and touted its efforts to try and fix the problem such as sending engineers to historically black colleges to reinvent IT curriculums and investing in education for girls...

“My concern is the 99% of other companies who want and need diverse teams but don’t have the team to recruit them,” Bischke said. “This could help level the playing field.”

What Entelo provides is more than 20 million profiles of potential employees filled with publicly-available data pulled from sites like Twitter (TWTR) and LinkedIn (LNKD).

Its proprietary algorithms then sort through this information using big data, predictive analytics and social cues, to determine the likelihood that people fall into a number of demographic subsets: female vs. male, white vs. black, etc.. It also identifies U.S. military veterans.

"We realized we could do this with a high degree of accuracy,” Bischke said.

The idea is that it would help companies to more cost-effectively and efficiently scour a wider group of potentially ethnically-diverse and qualified candidates, freeing up resources to focus on innovation, training, and ideally develop these people into future industry leaders."