Mon – Fri, 9AM-6PM
Follow Us

The Future of Work in the Age of Quantum Computing and AI

The arrival of any new technology is often met with apprehension and many of today’s conversations around new and innovative tech circle around the fear of technology being used to replace humans in the workplace.

But for better or for worse, emerging technologies such as machine learning, quantum computing, and AI are bound to change our world. It becomes our responsibility then, to make sure that AI systems are designed and deployed to improve and augment everyone’s lives.

Editor’s Note: Quotes from the AyAyAy AI Podcast have been edited for clarity.

A quick primer on artificial intelligence

Artificial intelligence (AI) is a field that combines computer science and various datasets to enable a system to solve problems. This field is deeply tied to machine learning, whose focus is on the use and development of computer systems that leverage data and algorithms to imitate the way that humans learn.

The most recent example of AI is ChatGPT—a conversational AI that’s making waves across industries. What makes this AI model stand out from previous models is the advanced technology that allows it to ​​answer follow-up questions, admit its mistakes, challenge incorrect premises, and reject inappropriate requests.

How quantum computing powers AI and machine learning

While AI and machine learning are impressive, they are only parts of a larger field called quantum computing. Traditional computing relies on bits or the 1s and 0s to encode information. Similarly, quantum computing relies on quantum bits or qubits to process huge amounts of complex datasets. Because of quantum computing, the algorithms for AI and machine learning make room for the possibility of better learning, reasoning, and understanding.

Quantum computing will become mainstream in about 10 years

In the December episode of the AyAyAyAI Podcast, Divergence Academy President and 9Brains CEO Sravan Ankaraju sat down with hosts Asif Haider and Lucky Rabago to discuss when we may expect quantum computing to hit the mainstream. Sravan’s answer: we might see this happen in about a decade.

“There will be new programming languages built on quantum computing. There’s already Q# and other experimental languages from Microsoft.” Sravan explained that with all these new languages created for quantum computing, there are those who can already run experiments and simulate scenarios.

While AI, machine learning, and quantum computing show a lot of potential to change the world for the better, many people still fear these emerging technologies.

Why do people fear emerging technologies?

With the recent surge in the popularity of artificial intelligence, many have raised concerns about disruptions directed toward the labor market. When asked to share his thoughts on how AI will affect the future of work, we sum up what Sravan had to say:

People’s fear of emerging technology is not new

In fact, Sravan cited a 1960s article about industrialization in steel and steel manufacturing in the United States that said that people were going to be replaced by machines leading to widespread unemployment. However, several years after that, the United States ended up producing so much steel because of automation that many new jobs were created. This was possible because of all the opportunities brought by the newly founded steel industry.

“Yes, there is a concern about the future of work,” Sravan continues. “There will be a need for people to reskill and find new kinds of jobs.” In other words, the introduction of technology heralds changes in the industry, which sets the foundation for the creation of new jobs.

The disruption of the job market is inevitable—but it’s not necessarily a bad thing

As an example, Sravan cited the advent of self-driving cars and how quickly an industry has been built around them. Self-driving cars became widespread in the market only recently, yet there are companies established to monitor and maintain fleets of these cars such as EasyMile.

This, according to Sravan, is a prime example of how people can adapt to emerging technologies and the impact they leave on our job markets.

The advent of artificial intelligence in the workplace is going to replace some jobs—there’s no doubt about it. And if we take a look at the last 30-40 years, technology has actually empowered us to be more productive. Thanks to technological advancements such as automation and AI, we now do less physical labor. Innovation in tech has allowed us to work fewer hours while staying productive—offering people a better work-life balance.

Why should we learn to conquer our fear of change?

Going back to the AyAyAy AI podcast, host Asif Haider talks about why people fear change and how it affects their comfort.

Asif noted that any possibilities brought about by new technology generally bring people a sense of fear. However, if people are able to tamp down on and control that fear, there is a great chance that that same fear will lead to discoveries that change life for the better.

To illustrate his point, Asif likes to think of that fear as a fire that lifts up a hot air balloon. If you learn to control that fire, it will take you to places you want it to go. But if that fear goes out of control, that balloon can fall from midair and cause all sorts of disasters—and we’ve seen that happen.

“It’s important to talk about this fear because of what has driven us as human society and as far as evolution goes. We have evolved from our fear,” Asif added. We can never be certain what possibility or outcome lies in wait unless we conquer that fear and learn to embrace change.

Artificial intelligence is a reflection of who we are

AI and other machine learning systems are a reflection of how we think, our biases, and how we manage them. As human beings, it’s important to remember that we are the ones training these systems. As such, it’s important to avoid introducing biases of geographic boundaries, notions of freedom, and political views so that the AI system learns to treat everyone fairly.

The question then becomes: how do we fix this problem?

Sravan reflects that the responsibility falls to us. “We have got to fix the way we do work. We also need to fix the way we are going to understand what a bias says and how we’re going to manage these systems.” He continued to say that: “My fear is not AI—it is us human beings. We are the ones guiding these systems on how to think.”

Adapting the principles of Responsible AI

Artificial intelligence has the potential to improve our lives in many different ways. Because of that, it becomes the responsibility of people to ensure that the changes AI has the potential to bring are for the benefit of all.

As AI becomes more and more business-critical, achieving Responsible AI should be a top priority for any organization. Companies such as Microsoft and Google have already put together mission statements on how they approach AI. But the overall sentiment is that people need to proactively drive fair, responsible, ethical decisions regarding AI and ensure that the systems they design and deploy comply with current laws and regulations. This is critical to ensuring that AI systems are developed responsibly and in ways that warrant people’s trust.

Defining the core principles of Responsible AI

In order to design, develop, and deploy AI systems that empower employees and businesses while fairly impacting customers and society, we need to ensure that these systems follow the core principles of Responsible AI including the following:

  • Fairness. We need to create AI systems with no biases and make sure that they treat everyone fairly.
  • Reliability and safety. Every AI system should be able to reliably work as intended while staying consistent with our values and principles. 
  • Privacy and security. Developing and training AI systems require us to work with data at a larger scale. This also means that we need to establish and follow rules for info security and privacy.
  • Inclusiveness. AI should empower and engage communities around the world. As such, we need to create trained systems that are intentionally inclusive.
  • Transparency. We should be open about how and why we use AI systems and transparent about their limitations.
  • Accountability. We, as people, are accountable for how our AI systems impact the world.

Final Thoughts

As AI continues to reshape the future of work, we need to develop a deeper understanding of its potential and embrace the principles of Responsible AI. While many feel uncertain or even fearful about the impact of AI on our society, it is critical that leaders in the industry step up and usher them into a job market where humans and AI work in harmony.

Unlock the Potential of Responsible AI

We are hosting a series of enlightening and empowering training sessions focused on Responsible AI and emerging technologies. Discover how you can leverage these valuable tools for our future.

New call-to-action