The Future of Jobs in Artificial Intelligence Era

Khaled Adel
Aug 30, 2019 · 13 min read

Idea:

Artificial intelligence has no particular definition however you can describe it as the act of simulating the human brain in a machine to make this machine do “reasoning, knowledge representation, planning, learning, natural language processing, perception and the ability to move and manipulate objects, as you can say it’s all about creating artificial human mind, but it’s far powerful than humans.

Artificial intelligence researches can be divided into two main sub-fields, Robotics and Machine learning.

Robotics is an interdisciplinary branch of engineering and science that includes mechanical engineering, electronics engineering, and computer science; Robotics deals with the design, construction, operation, and use of robots.

Machine learning which we will focus on is a field of computer science that uses statistical techniques to give computer systems the ability to “reasoning, knowledge representation, planning, learning, natural language processing, perception” (e.g., progressively improve performance on a specific task) with data, without being explicitly programmed.

Artificial Neural Networks or connectionist systems are computing systems vaguely inspired by the biological neural networks that constitute animal brains. Such systems “learn” to perform tasks by considering examples or we simply call it a computer system modeled on the human brain and nervous system.

An Artificial Neural Networks is based on a collection of connected units or nodes called artificial neurons which loosely model the neurons in a biological brain. Each connection, like the synapses in a biological brain, can transmit a signal from one artificial neuron to another. An artificial neuron that receives a signal can process it and then signal additional artificial neurons connected to it.

Artificial Intelligence History:

The term artificial intelligence was coined in 1956, but AI has become more popular today thanks to increased data volumes, advanced algorithms, and improvements in computing power and storage.

Early AI research in the 1950s explored topics like problem solving and symbolic methods. In the 1960s, the US Department of Defense took interest in this type of work and began training computers to mimic basic human reasoning. For example, the Defense Advanced Research Projects Agency (DARPA) completed street mapping projects in the 1970s. And DARPA produced intelligent personal assistants in 2003, long before Siri, Alexa or Cortana were household names.

This early work paved the way for the automation and formal reasoning that we see in computers today, including decision support systems and smart search systems that can be designed to complement and augment human abilities.

While Hollywood movies and science fiction novels depict AI as human-like robots that take over the world, the current evolution of AI technologies isn’t that scary — or quite that smart. Instead, AI has evolved to provide many specific benefits in every industry.

Artificial Intelligence Innovations:

The Google Assistant, is a virtual personal assistant powered by artificial intelligence and developed by Google that is primarily available on mobile and smart home devices, it’s capable of search the Internet, schedule events and alarms, adjust hardware settings on the user’s device, and show information from the user’s Google account. Unlike Google Now, however, the Assistant can engage in a two-way conversation, using Google’s natural language processing algorithm.

Google Duplex, extension of the Google Assistant that allows it to carry out natural conversations by mimicking human voice. The assistant can autonomously complete tasks such as calling a hair salon to book an appointment, scheduling a restaurant reservation, or calling businesses to verify holiday store hours. While Duplex can complete most of its tasks fully autonomously, it is able to recognize situations that it is unable to complete and can signal a human operator to finish the task. Duplex was created to speak in a more natural voice and language by incorporating speech disfluencies such as filler words like “hmm” and “uh” and using common phrases such as “mhm” and “gotcha”, along with more human-like intonation and response latency.

Tesla Autopilot, is an advanced driver-assistance system feature offered by Tesla that has lane centering, adaptive cruise control, self-parking, ability to automatically change lanes without requiring driver steering, and enables the car to be summoned to and from a garage or parking spot. Planned improvements to Enhanced Autopilot include transitioning from one freeway to another and exiting the freeway when the user’s destination is near, as an upgrade above and beyond Enhanced Autopilot’s capabilities, the company’s stated intent is to offer full self-driving at a future time, acknowledging that legal, regulatory, and technical hurdles must be overcome to achieve this goal.

Facebook DeepFace, is a biometric Artificial Intelligence based application technology capable of identifying or verifying a person from a digital image or a video frame from a video source. There are multiple methods in which facial recognition systems work, but in general, they work by comparing selected facial features from given image with faces within a database.

Humox Hex, a watch wearable developed by a team at MIT, goes deeper than any wearable device till date. Rather than monitoring just the heart rate, it calculates oxygen consumption in the muscles to make real-time recommendations to the user. This reduces injury, optimizes exercises and monitors the recovery process.

Sophia, is a social humanoid robot developed by Hong Kong-based Company Hanson Robotics, cameras within Sophia’s eyes combined with computer algorithms allow her to see. She can follow faces, sustain eye contact, and recognize individuals. She is able to process speech and have conversations using a natural language subsystem, around January 2018 Sophia was upgraded with functional legs and the ability to walk.

Near Future of Artificial Intelligence:

Entertainment: Move over, Netflix. In the future, you could sit on the couch and order up a custom movie featuring virtual actors of your choice. Meanwhile, film studios may have a future without flops: Sophisticated predictive programs will analyze a film script’s storyline and forecast its box office potential.

Medicine: Why have medicine that’s good for the average person, when it could be tailored to your exact genome? AI algorithms will enable doctors and hospitals to better analyze data and customize their health care to the genes, environment and lifestyle of each patient. From diagnosing brain tumors to deciding which cancer treatment will work best for an individual, AI will drive the personalized medicine revolution.

CyberSecurity: There were about 707 million cybersecurity breaches in 2015, and 554 million in the first half of 2016 alone. Companies are struggling to stay one step ahead of hackers. USC experts say the self-learning and automation capabilities enabled by AI can protect data more systematically and affordably, keeping people safer from terrorism or even smaller-scale identity theft. AI-based tools look for patterns associated with malicious computer viruses and programs before they can steal massive amounts of information or cause havoc.

Vital Tasks: AI assistants will help older people stay independent and live in their own homes longer. AI tools will keep nutritious food available, safely reach objects on high shelves, and monitor

movement in a senior’s home. The tools could mow lawns, keep windows washed and even help with bathing and hygiene. Many other jobs that are repetitive and physical are perfect for AI- based tools. But the AI-assisted work may be even more critical in dangerous fields like mining, firefighting, clearing mines and handling radioactive materials.

Transportation: The place where AI may have the biggest impact in the near future is self-driving cars. Unlike humans, AI drivers never look down at the radio, put on mascara or argue with their kids in the backseat. Thanks to Google, autonomous cars are already here, but watch for them to be ubiquitous by 2030. Driverless trains already rule the rails in European cities, and Boeing is building an autonomous jetliner (pilots are still required to put info into the system).

Commercial Usage of Artificial Intelligence:

  • Language translation systems
  • Speech to text system
  • Air traffic control systems
  • Automates personal systems
  • Supervisory systems
  • Intelligent highways — traffic monitoring
  • Robots for hazardous conditions
  • Expert system for law, medicine
  • Neural network based forecasting — finance, stocks, medicine
  • Executive summary producing systems
  • Automatic programming
  • Summarizing news from papers
  • Intelligent design — architecture, mechanical and electrical systems
  • Game playing systems “deep blue”
  • Medical diagnostic systems

Future of Artificial Intelligence:

  • 72% of business leaders say AI will bring a business advantage.
  • 1 billion video cameras will be connected to AI by 2020.
  • 85% of customer interactions will be managed without a human by 2020.
  • 4 billion devices currently in use include AI voice capabilities.
  • 2.3 million jobs created from AI while 1.8 million are eliminated by 2020.
  • By 2020, smart agents will manage 40% of mobile interactions.
  • $15.7 trillion will be added to economy by 2030 from AI productivity and personalization.
  • In 2021, AI augmentation will generate $2.9 trillion in business value and recover 6.2 billion hours of worker productivity.
  • $300 million in venture capital invested in AI startups in 2014, a 300% increase over the year before.

WHILE NO ONE knows what artificial intelligence’s effect on work will be, we can all agree on one thing: it’s disruptive. So far, many have cast that disruption in a negative light and projected a future in which robots take jobs from human workers.

That’s one way to look at it. Another is that automation may create more jobs than it displaces. By offering new tools for entrepreneurs, it may also create new lines of business that we can’t imagine now.

A recent study from Redwood Software and Sapio Research underscores this view. Participants in the 2017 study said they believe that 60 percent of businesses can be automated in the next five years.

On the other hand, Gartner predicts that by 2020 AI will produce more jobs than it displaces. Dennis Mortensen, CEO and founder of x.ai, maker of AI-based virtual assistant Amy, agreed. “I look at our firm and two-thirds of the jobs here didn’t exist a few years ago,” said Mortensen.

In addition to creating new jobs, AI will also help people do their jobs better — a lot better. At the World Economic Forum in Davos, Paul Daugherty, Accenture’s Chief Technology and Innovation Officer summed this idea up as, “Human plus machine equals superpowers.”

For many reasons, the optimistic view is likely the more realistic one. But AI’s ability to transform work is far from preordained. In 2018, workers are not being adequately prepared for their futures. The algorithms and data that underlie AI are also flawed and don’t reflect the diverse society it’s meant to serve.

How AI Could Grow Jobs: Inventing New Ones, Empowering Existing Ones:

While AI will certainly displace some jobs, such displacement has occurred long before AI was on the scene. In the past century, we’ve seen the demise or diminishment of titles like travel agent, switchboard operator, milkman, elevator operator and bowling alley pinsetter. Meanwhile, new titles like app developer, social media director, and data scientist have emerged.

Daugherty and Jim Wilson, managing director of Information Technology and Business Research at Accenture Research have co-authored a book titled Human+Machine: Reimagining Work in the Age of AI. In their view, future (and current) jobs include trainers and explainers. Trainers will teach AI systems how to perform and mimic human behaviors. Explainers will liaise between machines and human supervisors.

Trainers Chatbots have recently emerged as a new communications conduit for brands and consumers. It’s no secret though that they have often been stiff and offered inappropriate responses. For instance, we might say “It’s raining again. Great,” and humans would recognize the sarcasm. A machine wouldn’t.

Understanding language is one component of perfecting chatbots. Another is empathy. A new wave of startups is injecting the emotional intelligence into chatbot-based communication.

Eugenia Kuyda, cofounder of Replika, said empathetic chatbots like hers rely on human trainers. “In the future I think one of the most interesting areas of knowledge will be knowing human behavior and psychology,” she said. “You have to build chatbots in a way that makes people happy and want to achieve their goals. Without a certain amount of empathy, it’s not going to happen.”

In addition, companies like Facebook and Google use humans to moderate content. Facebook currently employs around 7,500 people for this purpose. Google parent company Alphabet also recently said it planned to have 10,000 people moderating YouTube content.

Explainers Trainers bring a human element to AI systems, but “explainers” will bridge the gap between the new systems and their human managers.

C-suite executives, for instance, will be uneasy about basing decisions on “black box” algorithms. They will need explanations in plain English — delivered by a human — to ease their concerns.

Legislation is another impetus. The European Union’s General Data Protection Regulation, which goes into effect this year, includes the “right to explanation.” That means consumers can question and fight any decision made on an algorithmic base that affects them

Such explainers will perform “autopsies” when the machines make mistakes. They will also diagnose the error and help to take steps to avoid similar mistakes in the future.

Empowering Workers, Businesses and Industries Rather than replacing workers, AI can be a tool to help employees work better. A call center employee, for instance, can get instant intelligence about what the caller needs and do their work faster and better. That goes for businesses and industry too. In another example, in life sciences, Accenture is using deep learning and neural networks to help companies to bring treatments to market faster.

In addition to helping existing businesses, AI can create new ones. Such new business include digital-based elder care, AI-based agriculture and AI-based monitoring of sales calls.

Finally, automation can be used to fill currently unfilled jobs. As Daugherty noted recently, there is a shortage of 150,000 truck drivers in the U.S. right now. “We need automation to improve the productivity of the drivers, the lifestyle of the drivers to attract more people to the industry,” he said.

Changes We Need To Make Today:

It will likely take a decade or so until some AI technologies become the norm. While that provides plenty of lead time for the transition, few companies are taking action now to train their workers. Another little-noticed problem is that the AI systems themselves are being created with data and algorithms that don’t reflect the diverse American society.

Regarding the former, Accenture research shows business leaders don’t think that their workers are ready for AI. But only 3% of those leaders were reinvesting in training. At a Davos meeting held by Accenture, Fei-Fei Li, an associate professor at Stanford University and director of the school’s AI lab, suggested using AI to retrain workers. “I think there’s a really exciting possibility that machine learning itself would help us to learn in more effective ways and to re- skill workers in more effective ways,” she said. “And I personally would like to see more investment and thought going into that aspect.”

Another issue to address in 2018 is the lack of diversity among the companies creating AI. As Li noted, this lack of diversity “is a bias itself.” Recent research from MIT has underscored this point. MIT Media Lab researcher Joy Buolamwini said she found evidence that facial recognition systems recognizing white faces better than black faces. In particular, the study found that if the photo was of a white man, the systems guessed correctly more than 99 percent of the time. But for black women, the percentage as between 20 percent and 34 percent. Such biases have implications for the use of facial recognition for law enforcement, advertising and hiring.

As such research illustrates, AI may present itself as an alien force of disruption, but it’s actually a human invention that reflects its creator’s flaws and humanity. “The effect of AI on jobs is totally, absolutely within our control,” Cathy Bessant, chief operations and chief technology officer, Bank of America, said in her Davos chat.

“This isn’t what we let AI do to the workforce, it’s how we control its use to the good of the workforce.”

Goal:

Humans we have a little capabilities, limited storage brains, slowly learning and a limited life-time, imagine overcoming all of those barriers, although scientists is still researching and developing more in that field which didn’t come far to the term Artificial Intelligence but imagine a mind that can read that can read thousands of books a second, not only reading but also understanding, perception and analyzing it making a new connection and reasoning between different fields of science (e.g., biology and astronomy, geology and astronomy) imagine what would happen if super-minded machine read and analyzed all of those medical books and researches we have today, what would be the result; Medical industry leap, cures for all chronic diseases (cure for Cancer and HIV), helping disabled persons to replace what they lost, extending the human life span; Exploration of other universes; Technical advancement in all industries; Helping companies better plan business operations and better insight into their organizations as they function, allowing them to increase revenue, reduce costs and improve overall customer satisfaction; Different but Better world than we have today.


Khaled Adel

Written by

Researcher at Nile University Teaching Assistant at Misr University for Science and Technology

Analytics Vidhya

Analytics Vidhya is a community of Analytics and Data Science professionals. We are building the next-gen data science ecosystem https://www.analyticsvidhya.com

Welcome to a place where words matter. On Medium, smart voices and original ideas take center stage - with no ads in sight. Watch
Follow all the topics you care about, and we’ll deliver the best stories for you to your homepage and inbox. Explore
Get unlimited access to the best stories on Medium — and support writers while you’re at it. Just $5/month. Upgrade