AI MUST READS — W10 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. Why ChatBots will change marketing as we know it
I believe in chatbots, they have their place and they serve their purpose. However, I also don’t believe, as some do, that they are the answer to all our problems. Through my work I’ve had the opportunity to work with cutting edge technology and some of the top trailblazers within their field and throughout it all there has been a constant chatbot hype. It’s something I think we need to finally lay to rest.
When speaking about marketing, chatbots changing the industry entirely is something I find difficult to envisage. Yes, they will serve a purpose. Yes, they’ll definitely become a profitable point of contact for consumers and customers. But is their potential really unlimited?
What do you think?
2. Racist, Sexist AI Could Be a Bigger Problem Than Lost Jobs
Stephen Buryani put it well in his article — “Rise of the racist robots — how AI is learning all our worst impulses“ — ‘There is a saying in computer science: garbage in, garbage out. When we feed machines data that reflects our prejudices, they mimic them — from antisemitic chatbots to racially biased software”. How do we guarantee that we don’t feed our machines with racist or sexist data?
This article brings me a mixture of joy and apprehension about the future of AI, a combination of feelings that is becoming more and more common. I worry that at such an early stage in the technologies adoption it is already beginning to become influenced by our negative human bias to one another based on the colour of our skin or what resides between our legs. However watching women like Joy Buolamwini actively call out and try to cut the strings that tie this technology to the problems of the past gives me a joyful hope that this technology can help towards our betterment.
3. Real-world AI: lessons from the field
It’s not that often that we get an article centered around actual ‘in-the-field’ applications of artificial intelligence that offer lessons to be learnt from — ‘Adopting emerging technologies always presents some risk — but don’t wait for AI to fully mature before you start thinking about an implementation strategy’. I personally find it refreshing to read about fields that have found a place for functional AI that isn’t self driving cars or the threat it represents to your jobs.
The ‘mysticism and magic’ behind artificial intelligence is something that isn’t often addressed within articles. It doesn’t exist. It takes data, lessons learnt and hard work from skilled workers. Something that is addressed upon within this article, ‘Again, it takes smart people out in the field, not just machines, to make this all work.’
As a community we need to make sure that Arthur C Clarke’s third law, ‘Any sufficiently advanced technology is indistinguishable from magic’ doesn’t end up being the general consideration of AI.
