AI MUST READS — W31 2018, by City AI
Artificial Intelligence, Machine Learning and related fields are in a constant state of change. We want to inform but also encourage discussions on well presented topics we think are necessary in the context of putting AI into production. Every week we’re picking applied AI’s best articles plus adding a discussion starter
1. Robots Could Emotionally Manipulate Humans, Study Shows
Author — Abbey Interrante (Follow on Twitter)
Whilst this experiment provides an insight into whether or not people can find themselves being emotionally effected by the imitation of human emotions, this also isn’t a new revelation. Companies have known that the imiation of natural “emotions” whether it be that of a humans or an animals can be used to manipulate their audience. Lets be honest sometimes little, to no effort can be made to convince people to buy something, simply putting the word ‘Pet’ allowed Gary Dahl to sell 100,000 “Pet Rocks” a day at its height of popularity.
Whilst intersting, it’s key to point out that these robots were built and programmed by humans and so are not ‘thinking’ for themselves but instead following programming that imitates human emotions that have been input by a human. When we reach the stage where Machine Learning AI can replicate these same results, then it would be fair to begin to draw the inferences that this article is implying. It seems as of late there has been a rise in ‘studies’ that have found a new ‘revelation’ whilst missing a crucial factor in the testing.
2. Machine Learning: Where to begin…
Author — srnghn
Machine Learning can be a complicated enough field for the experts within the field, let alone those trying to get into and understand the technology. This is apparent especially at the moment with the “AI talent shortage”, srnghn has built a tool to allow someone to begin to learn and work with Machine Learning without having to throw themselves into the deep end.
By first identifying what you are trying to achieve, you can then narrow the scope of searching for solutions.
Reducing the entry cost to learning and working with these technologies will become a necessity as the impacts and use cases become more wide spread and as such tools such as these will prove vital.
3. In breakthrough, Japanese researchers use AI to identify early stage stomach cancer with high accuracy
By Japan Times
The medical applications of Artificial Intelligence and Machine Learning continue to amaze me. Whilst arguably we are still in the early stages, we are making staggering leaps in combining it with Medical applications.
It took AI only 0.004 seconds to judge whether an endoscopic image showed early stage cancer or normal stomach tissue. AI correctly detected cancer in 80 percent of cancer images, while the accuracy rate was 95 percent for normal tissue.
Whilst I’m not entirely convinced this could be considered a ‘breakthrough’, instead its applying already new techniques in a new capacity, that has produced encouraging results. Arguably its more encouraging that we can already use techniques to produce these results, whats possible when we develop new techniques?
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