If you’re still wondering about the role that AI will play as recruiting technology evolves, there are about 40 million new reasons to believe it will continue to heavily influence the future. Paradox, a conversational AI platform, announced yesterday that it received $40 million in new funding. The company, whose clients include McDonald’s, CVS, Unilever, and other large organizations, plans to “leverage the funding to expedite its vision of a future where AI is a liberating force to help people do their best work,” according to the company’s press release.
As Paradox’s founder and CEO Aaron Matos explains, “No one goes into recruiting or HR because they like screening resumes, scheduling interviews, or managing paperwork.” Hence, the company is looking to advance efforts around using its AI assistant, Olivia, to relieve common administrative burdens.
Indeed, Olivia automates a host of tasks by creating conversational experiences online, as well as via texting and other messaging apps (WhatsApp, Facebook Messenger, etc.). “I love the idea of using Olivia for answering general questions from candidates and scheduling interviews, both of which could be helpful to both the candidate and the recruiter,” remarks Mary Faulkner, ERE’s strategy and leadership columnist and senior advisor with IA, a boutique consulting firm focused on HR transformation.
“Paradox manages to avoid the trap that most AI startups find themselves in,” adds Steve Smith, a partner and chief marketing officer at The Starr Conspiracy, a marketing agency whose clients are primarily workplace tech companies. “Too often, conversational AI and bots make brands feel more impersonal and mechanical. Paradox has succeeded because they use AI to bring more humanity into recruiting and common HR tasks and communication.”
Perhaps the real story here is not that Paradox received a huge amount of funding from investment firm Brighton Park Capital. It’s that it received the cash right now as the economy plunges downward to an evermore ominous nadir.
“Paradox is fundamentally aligned with where the world is going,” says Mike Gregoire in the press statement. A partner at Brighton, Gregoire, who will also serve as chairman at Paradox (and who is also former Taleo and CA Technologies CEO), says that “the company is seeing increased adoption as digital transformation becomes more critical to organizational resiliency and long-term success.”
That a vendor like Paradox would get tens of millions of dollars during the current pandemic suggests a heavy vote of confidence in the vendor. But no one should construe this as confidence in AI technology as a whole.
“There are a lot of tech companies out there trying to capture lightning in a bottle, and Brighton clearly thinks Paradox is going about it in the appropriate way,” Faulkner says. “However, there is still a lot of misunderstanding around AI, so investors may be throwing money at anything that looks like it might be desirable, regardless of whether a particular technology is good.”
Faulkner is quick to add that she’s not casting aspersions on Brighton’s funding of Paradox — indeed, she sees great potential benefits to it, particularly around generating jobs in AI.
Nor is Faulkner denigrating Paradox’s solutions. Her concern is less about Paradox specifically and more about the broader role of AI. She cautions that “elements of AI technology, especially when it comes to screening, continue to be worrisome.” That is, automation AI is one thing. Machine learning AI is another. And it is the latter that should continue to give pause for employers.
“We know keywords and SEO are biased as it is,” Faulkner says, “so now we’re embracing AI to make those determinations even further? AI is still programmed by people. I’ll be curious to see how Paradox mitigates issues with the screening algorithm.”
When contacted about such concerns, Paradox’s chief product officer Adam Godson noted that Paradox focuses its machine learning on natural language processing in conversations. “The goal is to ensure a high-quality understanding of the intent behind each conversation, like whether someone wants to apply for a job or just learn more about the company, as well as each person’s objective qualifications for a specific position,” Godson explains.
“When it comes to qualifying and screening candidates, Olivia focuses on facts rather than trying to infer them from language, patterns, or past actions of recruiters,” Godson says, adding that such a model helps to reduce bias.
In other words, there’s AI. And then there’s AI.
