Mahi Sall, Advisor, Fintech-Bank Partnerships, Payments and Financial Inclusivity
January 25th, 2023
Forbes |
It's obvious that artificial intelligence is already impacting the way we live. Every time we ask Siri to do basic math or Alexa to turn up the heat, we're using AI.
But it's unclear how AI is going to disrupt the way we work.
One thing we do know: it will cost jobs. Estimates range from 40 percent of all jobs that exist today to a perhaps less credible 99 percent of all jobs as we currently know them.
But even as AI, with automation and robotics, destroys jobs, it should create new ones as well. That might be scant comfort for the tens of millions of workers whose jobs are likely to be eliminated, but it does give us hope that as a society, we'll survive the massive change that is coming.
Some white collar workers feel safe.
After all, they don't drive a truck that could go self-driving. They don't operate a machine that could be a smart robot in five to ten years.
But white collar workers are no less at risk of disruption than blue-collar. And perhaps more so. After all, they can largely be replaced by software, which is cheap to replicate, while robots and automation are still expensive to purchase and maintain.
I recently had the opportunity to interview the chief product officer of a company that should know something about white collar work and process. 92,000 businesses use Box to automate processes and manage workflows, and the company has been building intelligence into its product for years.
Ultimately, according to Box's Jeetu Patel, half a billion white collar jobs will be impacted.
And Silicon Valley has to do more to help those affected ... rather than just continue the disruption that is changing and even eliminating jobs.
Patel: There are an estimated 500 million knowledge workers across the globe who work eight to twelve hours a day. Their work with content has not changed dramatically in the past twenty-five years. However, in the next five years, we expect to see more transformation in how people work than the last two decades. This completely new way of working with content has largely been driven by three converging trends - information moving the cloud, access to modalities and now artificial intelligence and machine learning technologies.
Content is integral to business processes and companies have terabytes of data sitting in their content management systems. There is so much potential value in this content that has yet to be realized. AI and ML will help enterprises extract intelligence from this data to empower employees with the information they need to be more agile and make faster, smarter decisions. From our customers spanning the Fortune 500, use cases for AI are applicable across industries. For example, a large retail company is using Box’s image intelligence skill to tag and organize large volumes of images to drive marketing campaigns and a large city council is using our video intelligence skill to transcribe council meetings and highlight speakers and key topics of discussion to share with constituents.
As algorithms become more intelligent, we’re seeing them complement highly skilled work. The impact of AI and ML on work will allow employers and employees to scale solutions in ways that was not possible before. These emerging technologies enable workforces to spend more energy on deep thinking versus completing low value tasks like data entry. With work that can be automated, enterprises can redistribute talent resources and gain cost savings.
Patel: Both. AI will replace some jobs, potentially those that are centered around process-oriented repeatable tasks. It will also create new opportunities for people to apply their skills to more value-adding jobs and will ultimately lead to untapped industries. The challenge will be figuring out how to reach an equal level where jobs lost are balanced with jobs created. This is not an easy task. It will take time and we must have retraining programs to help account for the jobs we will lose. With AI, there are potential new categories of jobs that haven’t existed before. If we look back just 10 to 15 years, we did not have as many industries or occupations that have evolved for our needs today, especially in the areas of security, privacy and compliance.
Patel: We should approach this shift in work and jobs by consciously thinking about where workers will be able to re-apply their skills. If routine jobs that involve data entry and processing, or workflow patterns are fully automated, this frees up employees to focus on higher value, more impactful work. We can redistribute resources for people to do the things we do best and what technology can do best. This is leads to more motivated teams working on the highest value problems that only humans can solve.
Patel: It is true that some jobs will be replaced by technology. When there is a major technology disruption that occurs, we have to think about a path forward and how-to re-train workforces. This is a mental shift in Silicon Valley, where there is a longstanding belief that disruption is always good and has a net positive effect. We do not think enough about the impact these emerging technologies leave behind. We have an ethical and social responsibility to develop a solution for mobilizing and re-educating our workforce. These are real lives and people. As a community, we do not currently have the infrastructure or programs in place for retraining displaced jobs. This re-skilling and forethought need to start happening now.
Patel: No matter how much technology or robotics a company has, we will always need humans for deep thinking and creative problem solving. Increased automation will give way to a wave of new interesting projects. Because the broad implementation of AI, the technologies will have an immense impact on compliance, privacy and security. We will need roles that provide oversight and address the potential biases of algorithms. We envision new categories of jobs such as a Chief Ethics Officer who can address new challenges as a result of automation, ensure moral use of the technology and help reduce the potential of bias.
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