Artificial intelligence intersects with many aspects of our daily lives, from navigation apps to search algorithms, email filtering to online shopping, and more — but the technology is also beginning to shape the workplace of today and tomorrow. Its tremendous potential and its power to disrupt entire industries is becoming a critical issue in the modern office.
As AI’s capabilities continue to accelerate, the technology is increasingly being used to create new ways of working and altering the skill sets that tomorrow’s workers will need in order to thrive.
In a meeting with leaders in technology, business, academia and the nonprofit sector on this topic, Samsung NEXT and NationSwell explored how AI is impacting the workplace, which uncovered a number of key benefits ahead, as well as risks that may need mitigating.
Here are five key takeaways.
AI Is Restructuring Jobs and Roles
AI is transforming today’s workplace, serving to restructure some jobs while introducing others more highly in demand (e.g., data scientists). As AI is increasingly leveraged to perform work tasks that can be repetitive and monotonous, humans are freed up to perform an array of value-adding functions.
One key issue is how to blend the roles played by both humans and technology, enabling each to do what they do best. Human workers may need to develop new skills in order to take advantage of AI and accommodate its growing use in the workplace.
AI Solves Some Challenges Better Than Others
AI is better suited to solving some challenges than others — for instance, where large and complete data sets are available, where issues are well-defined or where ethical concerns are less critical.
However, as Jean Horstman, founder and former CEO of Interise, notes, “The evolution of AI is what Russ Ackoff called a ‘wicked mess’ — high human behavior and high dynamic system complexity. How is AI going to evolve to actually improve outcomes for all people, mitigating the unintended negative consequences that will arrive if both types of complexities aren’t addressed together?”
Robert Nagle, chief product officer and CTO of Interactions, believes that the future of work involves a careful blending of technology (like AI) and humans, allowing each to do what they do best. “The future isn’t so binary,” Nagle says. “We’re showing how to supplement AI with human intelligence. Each can complement the other, with both improving in our closed loop.”
Hiring Is Hard, But AI Can Help
Some companies, such as Unilever, leverage AI to screen candidates early on in the hiring process, then arrange human interviews with the few remaining candidates. Using AI in these ways can help reduce the cost and time of hiring, a massive benefit for companies and workers alike.
Some participants expressed concerns around how using AI in hiring might hinder the promotion of fairness and inclusion. Much of that hinges on whether there’s enough of the “right” data available to “solve” the challenge of hiring the right person for the right job, especially when there may be potential bias hidden in the data sets.
Better Data Means Better AI
More and better data can support the effective development and use of AI. But it’s important to examine what data goes into building algorithms. More and better data can support the effective development and use of AI. But it’s important to examine what and whose data goes into building algorithms. “Our unconscious biases can be built into the data [underlying AI systems],” Horstman says.
Rudina Seseri, founder and managing partner of Glasswing Ventures, expresses special concern about one element of risk: “Our inherent gender biases are getting captured in these algorithms, while we should be promoting more diversity and inclusion.”
Shawn Bohen, chief transformative impact officer at Year Up, points to the use of college degrees as a screening criteria in hiring. Requiring a college degree may exclude highly capable talent who may actually have the requisite skills to succeed in today’s landscape of accelerating change, where the ongoing ability to learn is as important as what is learned.
We Need to View AI in a Multidisciplinary Way
Discussions involving actors from a variety of disciplines are key to optimizing the opportunities and mitigating some of the risks of artificial intelligence. And those who work on the technology can help with this process by more clearly communicating to a lay audience its potential impacts.
Ali Amarsy, co-founder and CSO of Gram Labs, says, “There’s a responsibility to have more transparency with data sets. Especially if the data sets are public, the algorithms [built using them] should also serve the public.”
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