Interesting article here in Information Week by Lisa Morgan, regarding 7 sources of bias in data, including:
1 Confirmation bias
2 Selection bias
3 Outliers
4 Simpson Paradox
5 Overfitting and underfitting
6 Missing variables
7 Non-normal data distribution
Good article from McKinsey about living and surviving in a digitally disrupted world – thanks to sensors, big data, AI and cloud computing.
Every C-level executive needs to understand these issues in a significant way – it’s too important, too consequential, to be left to other people.
Of course, as with previous technology adoptions, people who can bridge the technology world and business world will be of paramount value.
Interesting article from Bloomberg about 16,000 financial advisors at Morgan Stanley getting machine learning assistants. Also, includes research from Morgan Stanley about the exponential growth in such robo-advisors over the next decade or so.
It’s expected that around $6,500B of global wealth will be managed by such robo-advisors by 2025.
Always something interesting posted by Daniel Faggella at TechEmergence.
Tends to cover a wide range of new technologies, including:
✽ Machine learning
✽ Image recognition
✽ Robotics and
✽ Artificial intelligence
across industries, including:
✽ Aerospace
✽ Agriculture
✽ Automotive
✽ Financial services
✽ Government
✽ Healthcare
✽ Mining
✽ Pharmaceuticals
✽ Retail and
✽ Security
When one of world’s most insightful firms starts talking about re-inventing itself, for the benefit of its clients, may be we should all take some notice …
… before it’s too late ?
Click here for the McKinsey message (be sure to click the audio on their video command line)
This timely and insightful book by Andrew McAfee and Erik Brynjolfsson, both of MIT – Sloan School of Management, is a brilliant description of the seismic changes that have already started to be felt across the world and across many sectors of business and government.
As the title suggests, in addition to machine learning, the book also covers the online platform that enables it, and the crowd that is enabled by it.
In addition to machine learning, they focus on the “free”, “perfect” and “instant” nature of the platform, and the consequences of it, with regard to radical new approaches that are made possible.
Whole industries are at risk of being replaced by new entrants, unless the existing suppliers face up to the consequences of machine learning and the platform that enables it – Uber and airbnb is just the start of it.
The fact that the book’s jacket includes glowing testimonials from Eric Schmidt, Arianna Huffington, Reid Hoffman and Christine Lagarde is praise indeed – and this insightful book is well worthy of their illustrious comments.
