Ethics In AI: Why Values For Data Matter

Marc Teerlink
forbes.com
Originally posted 18 Dec 19

Here is an excerpt:

Data Is an Asset, and It Must Have Values

Already, 22% of U.S. companies have attributed part of their profits to AI and advanced cases of (AI infused) predictive analytics.

According to a recent study SAP conducted in conjunction with the Economist’s Intelligent Unit, organizations doing the most with machine learning have experienced 43% more growth on average versus those who aren’t using AI and ML at all — or not using AI well.

One of their secrets: They treat data as an asset. The same way organizations treat inventory, fleet, and manufacturing assets.

They start with clear data governance with executive ownership and accountability (for a concrete example of how this looks, here are some principles and governance models that we at SAP apply in our daily work).

So, do treat data as an asset, because, no matter how powerful the algorithm, poor training data will limit the effectiveness of Artificial Intelligence and Predictive Analytics.

The info is here.

Consider ethics when designing new technologies

by Gillian Christie and Derek Yach
Tech Crunch
Originally posted December 31, 2016

Here is an excerpt:

A Fourth Industrial Revolution is arising that will pose tough ethical questions with few simple, black-and-white answers. Smaller, more powerful and cheaper sensors; cognitive computing advancements in artificial intelligence, robotics, predictive analytics and machine learning; nano, neuro and biotechnology; the Internet of Things; 3D printing; and much more, are already demanding real answers really fast. And this will only get harder and more complex when we embed these new technologies into our bodies and brains to enhance our physical and cognitive functioning.

Take the choice society will soon have to make about autonomous cars as an example. If a crash cannot be avoided, should a car be programmed to minimize bystander casualties even if it harms the car’s occupants, or should the car protect its occupants under any circumstances?

Research demonstrates the public is conflicted. Consumers would prefer to minimize the number of overall casualties in a car accident, yet are unwilling to purchase a self-driving car if it is not self-protective. Of course, the ideal option is for companies to develop algorithms that bypass this possibility entirely, but this may not always be an option. What is clear, however, is that such ethical quandaries must be reconciled before any consumer hands over their keys to dark-holed algorithms.

The article is here.