What I've been reading w/c 27/03/2017: Chatbots and AI
Chatbots are an interesting example of how supporting technology can be the catalyst for innovation. In this case smartphones with messaging apps, constant fast network connections, and an API economy. All these enable comparatively low-tech chatbots to be viable (even I wrote a production text interface to an asset DB in 2000!). So, it's not new technology that's the innovation, it's combining existing technology in ways that change behaviour.
This article in the Harvard Business Review is spot on. AI systems much more like employees than traditional IT. Because it "learns" you often can't just lift the data/business rules into a new system. So you need to start thinking about "handover periods" and "training" a lot more. (Also make the jobs-to-be-done framework about hiring tools to do a job much more apt!)
There is much promise in Artificial Intelligence, this article on what to think about machines that think contains some views around that which don't seem to be common outside academia or TED talks. (So possibly useful for those looking at AI without that academic connection, definitely much more informative than a lot of mainstream press coverage)
Time to go beyond mobile first to AI first products, different personalities needed for different user experience (UX) that the AI driven product will provide. This needs to be considered up front, in the same way that moving from desktop to mobile needed a mobile first approach.
Interesting that from a marketing POV there is a lot of AI technology around but not many integrations in use. Maybe they need some tools like Wrappup?
Over on Medium a brilliant example of going from technological differentiator to commodity item. Reminds me of a friend's complaint years ago that his hard-won Flash skills were now standard tools. Same thing now with AI, what I learned to hand code is now a cloud-based resource. At least I will have appreciation of how it works (and pitfalls in training ;)
Finally, Fred Hsu CEO of Agent.ai explains how for SaaS and other tools AI is not only going to change the way we work but also the way our tools and services are priced ... there could be opportunities with both.
This article in the Harvard Business Review is spot on. AI systems much more like employees than traditional IT. Because it "learns" you often can't just lift the data/business rules into a new system. So you need to start thinking about "handover periods" and "training" a lot more. (Also make the jobs-to-be-done framework about hiring tools to do a job much more apt!)
There is much promise in Artificial Intelligence, this article on what to think about machines that think contains some views around that which don't seem to be common outside academia or TED talks. (So possibly useful for those looking at AI without that academic connection, definitely much more informative than a lot of mainstream press coverage)
Time to go beyond mobile first to AI first products, different personalities needed for different user experience (UX) that the AI driven product will provide. This needs to be considered up front, in the same way that moving from desktop to mobile needed a mobile first approach.
Interesting that from a marketing POV there is a lot of AI technology around but not many integrations in use. Maybe they need some tools like Wrappup?
Over on Medium a brilliant example of going from technological differentiator to commodity item. Reminds me of a friend's complaint years ago that his hard-won Flash skills were now standard tools. Same thing now with AI, what I learned to hand code is now a cloud-based resource. At least I will have appreciation of how it works (and pitfalls in training ;)
Finally, Fred Hsu CEO of Agent.ai explains how for SaaS and other tools AI is not only going to change the way we work but also the way our tools and services are priced ... there could be opportunities with both.
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