On hearing the term “Artificial Intelligence”, the majority of us think about robotic post-apocalypse movies. And even though we enjoyed watching Will Smith’s performance in “I, Robot”, the fear of robots taking over the world is often blind and based on false facts. And if the robotic end of the world is still far, a threat of AI taking over our jobs seems to be right around the corner!
But what everybody is scared of? The answer is simple – people are scared of the unknown.
It is easy to get scared when the media depicts our future so bleakly. It gets scarier when we see self-serve touchscreens at McDonald’s to realize that cashiers must have had to change their qualifications when touchscreens and mobile apps started assisting customers.
The keyword here is ‘change’. See, the human is quite a flexible creature. It can learn and change. I bet lamplighters were also frightened when they heard that certain Mr. Edison and Mr. Tesla were serious about something called electric power. They had the option to be frightened – or learn to install light-bulbs.
What if technology would stop being seen as the opposite of humanity, and would actually be considered as an advantage to the people?
In the last article, we wrote about how Uber improved the taxi business. Taxi drivers worldwide were scared of losing their jobs when Uber appeared. The reality is that more drivers were created and they have received even more business from customers.
In this article, let’s see the example of edX which started out as the ultimate opportunity for professors to develop online courses for students worldwide to get valuable knowledge. The secret sauce contained the course-design tools and recommendations that were provided to professors and were based on the algorithmic analysis of students’ behaviour on the platform (clicks, posts, pauses in video replay, etc). First seen as a boutique learning platform, edX has given major opportunities for professors and students worldwide.
But the change was not easy. Based on the research of Shreeharsh Kelkar at UC Berkeley, professors faced difficulties when starting to use edX. Signing up meant learning many new skills: navigate the user interface, interpret analytics on learner interaction, create and manage the course’s project team. New tools, metrics, and expectations arrived daily, and instructors had to adjust and master them. It was quite a challenge for those who were not prepared. Besides learning all these new skills, they still had to keep existing old school skills sharp for teaching their classes!
We are sure that edX seemed frustrating in the beginning, and at the same time disruptive. Few tech-savvy professors were able to run massive classes for their online audience. Those who couldn’t conquer the platform felt like their teaching career would be over. It seemed like the online world would make their academic experience worthless.
But what did learning to use it actually mean in the long run? Instead of losing an academic career, it meant developing it on a bigger scale. Professors had a severe limitation – they were only known by people who they meet or who were interested in their subject. Now, using digital tools such as edX, they were making education more popular to a worldwide audience. They learned new digital skills, automated parts of their work, and were able to grow the pool of potential students exponentially. It wasn’t old-fashioned academic knowledge vs. digital tools – professors need both to succeed.
Technical skills improve old-school jobs. Construction workers use calculation tools to get accurate results in less time, teachers use software to keep students score on track, restaurants increase their sales by adopting food delivery apps. The list is endless. Adoption takes time, but knowledge speeds it up.
So is the case for Artificial Intelligence. It augments intelligence. Elite companies such as Amazon, Google, or Tesla seem to be making the most of it. But small businesses are frightened as they cannot afford it. This prompted innovative technology companies to come up with solutions. Our company is an example of this effort. We worked in such large companies and questioned why such progress should be elite. The opportunity was to make AI easy for all.