One day we will all become “citizen AI users”

I recently took the time to listen to a very cool podcast on HBR about the ways humans and machines are likely to work together in the future (and it was a lot less science-fiction than watching any of the Terminator movies). The podcast was so fascinating, so I started thinking of my own examples of quite a few collaborations that are already happening in different fields. In addition, it also led me to the conclusion that since we’re seeing this trend happening in so many industries, we are more likely to see a lot more “citizen AI users” (workers who are trained on the job to collaborate with AI, unlike the experts who specialized in it) than citizen data scientists (people trained on the job to perform all sorts of statistical predictions based on the data they usually see), since learning how to collaborate with AI doesn’t necessarily require any knowledge of statistics or computer programming, unlike data science.

So, let’s jump into some areas where users already use AI to some extent to make decisions:

1. Music – I came across this great course on Kadenze that teaches musicians and artists how AI can help with their artistic creation, and only a minimal understanding of the mechanism behind the scene is needed in order to actually create something with the tools taught in this course. I’ve yet to try.
   In addition, Cubase, one of the leading tools for music production in the market is offering this feature called the "Circle of fifths" that helps musicians that do not have a lot of music theory knowledge to start composing music by suggesting chord patterns based on other chords they chose. Being an amateur musician, I really enjoyed learning about these two examples.
2. E-commerce, retail, and fashion – Edited developed a tool that uses an algorithm that can crawl the web and provide companies with lots of valuable information about their competitors. It is not easy to fine-tune an algorithm like this to know how to recognize an item properly using advanced machine learning techniques such as image recognition, but their product can definitely help users in augmenting their market analysis capabilities.
3. IT – New Relic is one of the leading tools that helps engineering and IT departments monitor metrics such as webpage loading time, and app specific metrics. One of their more advanced features is called Synthetics and it helps DevOps teams simulating loading problems in different locations around the world based on historic trends. Users have to learn how to put together the right test, and then it’s pretty much an auto-pilot that will let you know if it seems like a technical issue is on the horizon.
4. HR and recruiting – Intervyo is a company that already offers an interesting solution to help automating part of the hiring process by offering video interviews and AI capabilities that can help predict the candidate’s suitability to specific roles based on factors such as facial expressions, intonation, and semantic analysis. With proper integration into a holistic recruiting process that includes humans and AI, we can see a very interesting shift happening in the way recruitment processes are designed.
5. Higher Education – Saint Louis University (SLU) partnered with Amazon to develop a voice-user interface for every dorm room in the university to help students with the orientation (and possibly, listen to what’s happening in their dorms…). It will require students to learn how to interact with such interface and even “train” it to give them better results overtime.

AI is a technology that still needs quite a lot of time to fully mature, but we are likely to see a lot more business and industrial processes designed around it with humans and machines complementing each other and augmenting the human capabilities, irrespective of one’s levels of education or understanding of the technology. One thing for sure, we will all need better critical thinking in order to assess the judgement of these machines, and those who can master the skill will be in great demand once AI is more mature and integrated into most sectors of the economy.