Prejudice in A.I.

Posted by Rennan Tilbury on Aug 29, 2019 8:30:00 AM

Over the past 25 years, computers have slowly encroached into the domain of human intellect, the machines first victory was in 1997 when Kasparov lost to Deep Blue at Chess1. Since then A.I. have continued to expand the games they can beat us at, from Go to Poker, and Shogi to Starcraft2. These achievements of machine learning, whilst shockingly impressive, are in stark contrast to the failures of A.I. in the real world.

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Topics: AI, Artificial Intelligence, Technology, AI Platforms, Data, Machine Learning

Five practical steps to make Artificial Intelligence interpretable

Posted by PwC on Aug 28, 2019 2:54:02 PM

If AI is to gain people’s trust, organisations should ensure they are able to account for the decisions that AI makes, and explain them to the people affected. Making AI interpretable can foster trust, enable control and make the results produced by machine learning more actionable. How can AI-based decisions therefore be explained?

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Topics: AI, Artificial Intelligence, Technology, Data, Machine Learning, Responsible AI

The curse of the data lake monster

Posted by ThoughtWorks on Aug 7, 2019 10:46:42 AM

Artificial intelligence and machine learning are currently all the rage. Every organization is trying to jump on this bandwagon and cash in on their data reserves. At ThoughtWorks, we’d agree that this tech has huge potential — but as with all things, realizing value depends on understanding how best to use it. 

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Topics: Artificial Intelligence, Technology, Data, Data Science, Machine Learning

Fusing data and design to supercharge innovation—in products and processes

Posted by McKinsey on May 20, 2019 3:23:49 PM

While many organizations are investing in data and design capabilities, only those that tightly weave these disciplines together will unlock their full benefits.

Often in business, the biggest breakthroughs come when organizations connect different, and seemingly disparate, ideas and approaches. Diversity of perspective has been shown time and again to foster fresh thinking to solve tough problems. Such is the promise for organizations that can effectively bring together data and design.

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Topics: Artificial Intelligence, Data