In my previous article, I explored the moral implications of superintelligent AI.
I’ll be the first to admit that the outlook was a little bleak.
When you consider the fact that these machines may be allowed to make decisions that affect mankind, without having or after evolving past the innate ethics that (most) people operate by, the future can look scary.
It’s time to scope out the positives now, because when it comes to AI in the workplace, there are HUGE benefits in store.
Tech giants are racing to get their slice of the AI pie, and are adding more fuel to the fire – Google bought DeepMind in 2014. Facebook’s planning to use neural networks to ‘narrate’ photos to blind users, and using deep learning to find out what their users actually want.
There’s even a Partnership on AI, which includes Google, Facebook, IBM, Amazon, and Microsoft, to create an open forum for the discussion of AI and AI ethics.
These are exciting times!
So what could happen when we put AI to work?
Getting The Grunt Work Done
When you’re at work, what do you do all day? Apart from your main objective, which could be to write as many lines of code as possible, achieve certain goals to get that promotion, or hit performance targets, what is your time filled with?
The grunt work: Answering emails. Scheduling meetings. Sifting through humungous piles of data or research material.
And this is where machine learning can help you out.
AI will be capable of leveraging data to make predictions, faster and more accurately than it can ever be done manually. It will also be able to analyse emails for content and context, and create appropriate replies. And even manage scheduling conflicts on its own – x.ai’s personal assistant, Amy can already do this.
Mining Data To Give You Answers
The difference between Cortana and Siri, and a workplace question-answer AI, is intuition and specific learning.
Cortana and Siri are broad spectrum, but an AI assistant that answers your professional questions for you must specifically understand the objectives of the company, how it operates, and the style of working at your firm.
Let’s take ROSS, an AI-powered lawyer, as an example. Employees in a law firm can ask ROSS any question, whether for case details or citations, and he’ll sift through tons of data in publicly available law documents to return an answer.
But will ROSS be able to intuitively figure what kind of citations this particular firm values more? Some firms may value the most current rulings, while others may value the rulings of more prominent cases.
Hitachi announced in 2015 that they were using an AI system to manage a warehouse. Just take a moment to imagine that – an AI manager. And it almost immediately improved efficiency by 8%, by issuing orders upon continuously analysing workflow and efficient work practices.
But how would the AI manager respond to an emergency situation, a one-in-a-million incident that it has no data on?
This is where we can all breathe a sigh of relief about AI stealing our jobs.
Machine learning may be able to do a lot of things better than we can, but it won’t be able to grasp nuance.
But We’re Not There Yet!
Plug-and-play AIs like Siri and Amazon’s Echo are too simple to bring into the workplace.
AI that can process data to give solutions and suggestions, AI that can make diagnoses, AI that can analyse human behavior, all takes a level of configurations way beyond the basic personal assistant we all have on our smartphones.
And that’s okay.
AI startups all over the world are designing and redesigning technologies that can do all these things. And what we can predict is that they will lead to insane savings in time and money for companies in almost every industry when they’re completed.
A chunk of the work in AI is going into making the human-machine interactions feel natural, delightful even, like when Siri gives you a sassy response to a question.
The focus seems to be on blurring the line, so that man and machine are working together to achieve a common business goal.
Think of it this way: there will soon be a Siri for work, but it will be laser-focussed on each particular vertical, configured to produce amazing results in the completion of a few specific tasks, and it will even talk to you like any other colleague does.
What roles do you see AI taking over, in a professional environment? How do you see that affecting the current working system? Let me know your thoughts in the comments, or on Twitter!
The opinions expressed in this article are my own, based on my years of experience in the field of People Management, and not on behalf of Intuit.
About Srini Ramaswamy
Srini Ramaswamy has over 15 years of experience and has worked with organizations like Intuit, Amdocs, Sonata Software Ltd, Aditya Birla Minacs & Naukri.com. Srini holds a Management, specializing in Human Resources from Bangalore University.