Power in AI by VB

“In this issue

AI ethics is all about power

Facial recognition regulation is surprisingly bipartisan

When AI is a tool, and when it’s a weapon

As AI grows, users deserve tools to limit its access to personal data

AI-generated fake content could unleash a virtual arms race

AI in patent law: Enabler or hindrance?

Richard Bartle interview: How game developers should think about sapient AI characters

From black box to white box: Reclaiming human power in AI (Sponsored)

The pitfalls of a ‘retrofit human’ in AI systems”


Apple Card: Did AI Run Amok?

  • “Yes, when it comes to sophisticated algorithms and AI (Artificial Intelligence), even some of the world’s most valuable companies can get things wrong. What’s interesting is that one of the selling points of the Apple Card was that it would provide credit to those with little or no credit histories
  • ‘Here’s the thing most people don’t understand: Certain kinds of advanced algorithms, machine-learning algorithms, need a lot of data to train on in order to make predictions. We turn to the past to find that data. But if you’re not careful, the algorithms learn the mistakes of the past. In this case, that would be gender bias. Algorithms that learn from history are doomed to repeat it. That’s the great irony. You have to really work to correct for the mistakes of the past. In life and in algorithms.'”


Using an AI Trust Index Stalled Machine Learning & AI Projects

  • “According to a recent survey by Dimensional Research, nearly eight out of 10 enterprise organizations currently engaged in AI and ML report that projects have stalled due to issues of data quality and model confidence. 
  • An AI Trust Index is a FICO-like score for algorithmic vulnerability and risk based on five major AI business risks — bias, explainability, robustness, compliance and data privacy.
  • Much as FICO accelerated risk rating has transformed the financial services industry, AI Trust Index will help accelerate development of Trusted AI systems that are free from bias, transparent in their operations, and are able to reflect the core values and policies of the business.”


Cognitive Scale