The Human-Centric Future of AI and Automatiom

This isn’t a new topic. For the past couple of years automation has been at the center of heated discussion involving Artificial Intelligence (AI), skilled labor and, from time to time, even evil robots reminiscent of Skynet. The usual suspects come to mind: Amazon with their machine arms and drone deliveries; Google with their robots that can run and climb stairs; Uber and Tesla getting closer and closer to putting driverless cars on the roads.
Such technological advancements tend to go hand-in-hand with talk about people losing their jobs to machines and advanced algorithms. Yet in a future where repeatable tasks are performed by automated technology, people skills like empathy, analysis, and human-centric design will be more important than ever. In this near future, instead of a shortage of jobs, we will see a shift towards more meaningful careers for people: number crunchers in finance will have more time to analyze and act on data, and instead of factory workers mindlessly taking a box from point A to point B, they will be in charge of ensuring that systems run smoothly while adding human common sense to the process.
More Meaningful Jobs
In a recent New York Times article, we got a glimpse into what this future cohabited by humans and machines looks like. Nissa Scott works at this warehouse and her job is to monitor several robots at a time, making sure they have bins to load and that they are placing the bins in the right place.

“For me, it’s the most mentally challenging thing we have here,” she told the New York Times. “It’s not repetitive.”

Often accused of destroying retail jobs, Amazon has in fact become a hiring machine, constantly hiring thousands of workers and with a workforce three times the size of Microsoft and 18 times the size of Facebook. The company recently announced it was opening a second headquarters in North America, a location that would create at least 50,000 new jobs.
Yet not all automation advancements come in the way of futuristic looking factory robots. In fact, some of the coolest developments in fields like banking, manufacturing and media are happening in software and application development. An article in American Banker took a look at how multiple financial institutions in North America are experimenting with tools and software that would do away with repeatable tasks.
One specific example stood out: Doug Shulman, senior executive vice president of client delivery at BNY Mellon, views process automation as smart way to use tech to provide a better client experience while making their offices a space where “our talent is working on the higher-value-added work, reducing risks and reducing costs.”
He’s only one of many who are leveraging automation and cloud technology to provide rapid value, while creating more meaningful careers for his employees. It comes down to leaving the tasks that make you feel like a robot, well, to robots.
Human-Centric Design
Earlier this year design consultancy IDEO acquired Datascope, a Chicago-based data science company. The acquisition hints at the future of the design industry as it tackles demands from AI-powered clients and looks ahead to a future that puts humans at the center of innovation.
IDEO CEO Tim Brown explained to FastCompany that for the past thousand years the artifacts designers worked on were somewhat unintelligent, inanimate objects that were finished and final with all the intelligence coming from the end-user. Now machines can learn on their own, adapting to the end-user so instead of just building artifacts, designers have to think about building relationships that improve with time as more data comes in.
“Ultimately, we’re using the term ‘augmented intelligence’ to really focus on the fact that we’re extending and enhancing people’s capabilities through technology, as opposed to thinking of technology as a separate thing, or replacing capabilities with technology,” said Datascope founder Mike Stringer.
Here at Rangle, we also see technology as an extension of human capabilities, and the human end-user is always at the center of the powerful apps we build. In development for example, as automation becomes more commonplace in testing and in self-learning machines, our BQAs are in charge of making sure that the AI implemented takes into account accessibility issues and human behavior that can sometimes be unpredictable.
Instead of thinking technology will replace our jobs, BQAs play a crucial role in guiding said technology to account for people and thinking outside the box. For example, when we incorporate machine learning into the applications we build for our clients, it’s a human who benefits: both the client who gets to better understand their customers and the customer, who is presented with a version of an app designed just for him.
At the end of the day everything we make is for the benefit of humans. More and more the spaces we share and the interactions we have online are facilitated by advanced tech. However, empathy is what decides whether a product succeeds or not and for that you need people who understand the human condition.