Yes, health care needs AI - but maybe not in the ways we think. A new book on AI's medical potential needs a critical eye. With AI, there is always a human consequence beyond the tech storyline.
The issue of AI ethics has sharpened - ideas for governing AI and ethical oversight are gaining a foothold. But will they have any teeth? And what about the possibility that AI can oversee itself?
A new research paper from Georgia Tech takes a surprising position on algorithmic bias in hiring. Their view: we can reduce screening bias if algorithms take the impacted demographic groups into account. Here's my critique.
New York state regulators pushed back on data brokers for insurance - will other states and industries follow?
A warning letter from New York State's Department of Financial Services (DFS) raised far-reaching data privacy questions for the insurance industry. With the increasing role of algorithmic claims processing, this is an ethics debate we can't ignore.
The fall of MapR caused a rush to judgement about the future of Hadoop. To understand what this means for data initiatives, the viability of Hadoop and data lakes must be separately examined.
AI marketing literature extols the benefits of algorithmic hiring. But the problem of algorithmic bias and hiring fairness raises serious questions.
The term "data sharing" is expanding, but in a problematic way that raises flags for companies and consumers alike. Neil Raden provides a deeper context for data sharing trends, dividing them into the good, bad and ugly.
Surfacing the issues around securing the IoT.
Advances in genomic research have changed our view of the human genome. Promising health care advances are in the works, but we'll need massive computing power to see this through. Will enterprise software as we know it change as a result?
Casting a net over Bayesian Inference.
In pursuit of happiness with the promise of harmonized data.