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#WorkTrends: The Future of HR Tech

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Technology is disrupting everything, and HR is no exception. The tools and platforms available for today’s HR teams are light-years ahead of what we worked with 10 years ago. What does this new tech mean for recruitment, talent management and other HR functions? I talked to one of the smartest people in the HR tech world to get her take.

This week on #WorkTrends, we’re talking to Anna Ott about what’s next in HR tech. Anna is head of HR tech startups for UNLEASH. Last week at UNLEASH America in Las Vegas, I joined hundreds of other HR tech analysts, practitioners and vendors to think about how work and HR are changing.

You can listen to the full episode below, or keep reading for this week’s topic. Share your thoughts with us using the hashtag #WorkTrends.

HR Problems Technology Can Solve

Anna has spent the past 18 years working at digital companies — especially startups — and has held various HR-related roles. “I believe we are in a renaissance of HR as it has regained its strategic value of shaping organizations in the Fourth Revolution,” she says. “I am driven by enabling HR practitioners to be a stronger partner, feel more tech-savvy and enabled to shape the future of work.”

No one goes into HR because they love the repetition of filling out forms and going through the same processes over and over again. Most people sign up to work in HR because they want to work with people. “I think anything that automates processes and reduces the administrative work of HR is definitely something that we all appreciate,” she says.

Anna also acknowledges that, as humans, we struggle with unconscious bias during the recruitment process, and she believes that technology can remove human factors that tend toward partiality — and even create new ways to approach problems.

In March of this year at UNLEASH London, she met the team at Vault Platform that is working on a project that never would have been on the radar even a year ago. “They are trying to face the #MeToo debate by building a counter-harassment platform on blockchain,“ Anna says.

HR Issues Technology May Create

While she’s passionate about the possibilities that new technology brings, Anna is keenly aware of the risks and uncertainties involved.

Some solutions are helpful, but she says they could also be hurtful at a certain point. “It’s always two-sided. For example, when you look at security detection and skill-matching, at which point do we become too transparent?”

There’s a chance that people will reveal too much of themselves for the sake of developing in their careers and learning new things and trying to be a match to great jobs, she cautions. At the same time, she says, “At what point does it feel scary if a company monitors everything I do and everything I write, or the chats that I do within my company, or all the documents I create on Google?”

Another issue is just trying to manage all of the point solutions in the HR tech market. “HR people and practitioners can’t orchestrate a solution landscape of 100 different small things,” she says. There needs to be a more holistic approach.

Taking the HR Technology Plunge

For HR people who want to understand what HR tech can do for them and their organization, Anna recommends starting with one particular problem in need of a solution. “Try to find people who either have tackled this before,” she says. “Find peers, or look at those people who actually observe the market as I do, or analysts or thought leaders.”

She also recommends going to HR tech startups, talking to them, looking at their solutions, watching demos and meeting with them at conferences or HR tech competitions.

“When I was in my corporate payroll employment job, previous to UNLEASH, I wanted to eliminate the CV in the hiring process, but I didn’t know where to start,” she says. She spoke with a lot of startups that she thought might have a solution, and found one company that used video interviews instead of CVs.

“We actually sat down, created a new candidate experience and process, and then we eliminated the CV in my hiring process with their tool.” But she says it was a trial-and-error process — an experiment.

A year later, she switched from video interviews to chatbots, so she needed to speak with a chatbot startup about recruitment. Again, she labelled it as an experiment so it would be OK to fail, learn from that mistake, then pivot.

Anna is now a big advocate of chatbots. “Most of people looking actively for jobs want instant information,” she says. They want to have an instant response on the salary, location and other core details of a job. “In fact, in our chatbot at my previous company, people wouldn’t even write whole sentences,” she says. They would write “dog to work” to find out if they could bring their dog to work. She says candidates were comfortable doing that because they knew they were talking to a machine. Another benefit of that automation? “Chatbots also help us to get back to candidates and re-engage with those people that probably haven’t applied yet, allowing us to tap into a new pool of potential candidates.”

Continue the conversation. Join us on Twitter (#WorkTrends) for our weekly chat on Wednesdays at 1:30 p.m. Eastern, 10:30 a.m. Pacific, or anywhere in the world you are joining from to discuss this topic and more.

AI and Chatbots: Getting Their Sensitivity Training

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Earlier this year, Microsoft dipped a toe into the Artificial Intelligence space with an AI-powered chatbot that it set loose on Twitter. Designed to pass for a conversational teenager, responding to queries and mimicking casual, playful speech patterns familiar to Millennial and Gen Z users, it was supposed to be cool. Unfortunately, it wasn’t long before Tay, the Microsoft-labeled “AI fam from the internet that’s got zero chill” devolved into a racial slur spewing monster.

Of course, the curious case of Tay was somewhat of a fluke, a science experiment gone rogue, hijacked by internet trolls bent on exploiting the software that ran her. Nevertheless, Microsoft’s negative run with Tay highlights an interesting problem facing chatbot developers as well as those who will adopt artificial intelligence technologies for customer service and marketing purposes: How do you make sure your AI chatbot not only stays on the rails, but also operates in a manner that’s sensitive to your customers’ needs?

That’s what Fraser Kelton hopes his co-founded, MIT-born, machine-learning startup called Koko will solve. “We’re working toward providing empathy as a service to any voice or messaging platform,” says Kelton in an article with FastCode. “We think that’s a critical user experience for a world in which you’re conversing with computers.”

Kelton’s not wrong. In fact, it wouldn’t be too far off to say that an empathy injection from Koko is something even the most recognizable AI smartbots are sorely in need of. A study published in JAMA found that smartphone AIs like Siri, Cortana, and Google Now severely underperform in responding to queries involving physical ailments, depression, and even sexual assault. Writer Sara Wachter-Boettcher relates her own experience on her Medium blog, reporting that when she asked for help with rape, sexual assault, and sexual abuse, all she received from Siri was one of her pre-programmed snarky remarks telling her that sexual abuse “is not a problem.” Apple responded almost immediately by reprogramming Siri to send users mentioning sexual assault and rape to RAINN’s National Sexual Assault Hotline.

Koko’s three-person team just received their first major round of funding, and are hoping that they can circumnavigate these situations before they ever happen in the first place. The concept is that Koko’s empathy API would be able to connect to any third-party chatbot and imbue it with the ability to recognize speech patterns or vocal cues indicative of mood, as well as to adjust responses appropriately. Sharp responses when somebody is frustrated or angry could trigger the chatbot’s doling out of calm, patient responses, so as not to incite further emotion, while languid or playful language might be met with more creative or humorous responses.

Many see this as a critical endeavor—a stepping stone or a building block for customer service—AI that may someday be indistinguishable from a living, breathing, human being. I’m definitely in this camp, as AI and machine learning are getting more sophisticated at a rapid clip and there is so much possibility there, and the implications it has on business, on customer service, on processes and simplification, and on our personal lives—is exciting as hell.

Not everyone is crazy about chatbots, and Teckst’s Matt Tumbleson expressed his opinions in an article on VentureBeat, saying that though the buzz around chatbots is growing, his team speaks “on a daily basis with customer service leaders from Fortune 500s who believe chatbots add more problems than they solve.”

Tumbleson argues that conversation trees and nuances in vocal communication are simply too complex for bots to replace customer service agents completely, though he does believe that they can act as great supplements. Automated, rote tasks, such as sending a blanket update to users and responding to the same generic question is a perfect task for bots, in his opinion, while the truly human matters of connecting with another individual on an emotional level is best left to… well, humans.

While Tumbleson is right about the current state of chatbot technology—it’s not yet where it needs to be—it’s hard to say whether he’s right about bots being able to replace humans in conversation. Koko aims to remedy what Tumbleson claims is holding back customer service bots from full serviceability, and, if successful, will bring us one step closer to a world where software is indistinguishable from personality.

One thing is for sure: as A.I. software becomes more affordable to produce, we’ll see more and more Siris, Cortanas, and Alexas. Whether replacements for customer service or supplements to them, we certainly won’t be interacting with chatbots any less in the future–the least we can do is teach them to respond with empathy and manners.

A version of this was first posted on Futurum.xyz

How Chatbots And Deep Learning Will Change The Future Of Organizations

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Don’t let the fun, casual name mislead you. Chatbots—software that you can “chat with”—have serious implications for the business world. Though many businesses have already considered their use for customer service purposes, a chatbot’s internal applications could be invaluable on a larger scale. For instance, chatbots could help employees break down siloes and provide targeted data to fuel every department. This digital transformation is happening, even in organizational structures that face challenges with other formats of real-time communication.

Still unclear on what chatbots are and what they do? Think of a digital assistant—such as iPhone’s Siri or Alexa, the Artificial Intelligence within the Amazon Echo. A chatbot reduces or eliminates the need for many mobile apps, as the answers are stored inside the chatbot. Need to know what the weather’s like in LA? Ask your chatbot. Is your flight running on time? Ask your chatbot. Is the package you ordered going to be delivered while you’re away? You get the gist.

Chatbots have been around for a while, but the technology is developing in a way that has technology firms excited about the new capabilities. The next generation of chatbots store, synthesize, and recall important data. They can make purchases for you using stored credit cards, or sync your calendar with weather info to warn you about impeding rain at your kid’s afternoon soccer game across town.

Embrace Chatbots In Business

Chatbots use a process called deep learning, a type of machine learning in which a neural network can recognize speech, data, and specific patterns and transmit that data through the layers of the network. The second layer builds upon the first, and so on, for more accurate results each time the Artificial Intelligence faces a similar query or problem.

The novelty of chatbots appeals to many people balancing busy work and life schedules. But they also have significant implications in business, where they could streamline processes and maximize efficiency. Imagine a machine that could access your company wikis or knowledge bases and serve up information in real time, in a context that’s helpful to the employee who needs it—much like the computer on Star Trek’s “Enterprise.”

Businesses such as call centers have much to gain from this technology. Today’s consumers face a lot of steps to reach a company if they have a customer service issue., Google to find the 1-800 number, navigate a series of numerical prompts—or worse, voice prompts (“No, speak to a customer representative!) until you’re connected with a person 10 minutes later who still has to confirm information before helping you solve your problem.

Now consider how a chatbot could streamline the process: A customer tells a chatbot to get in touch with a company’s customer service department. The company chatbot ascertains the reason for the call and automatically decides whether it’s a case that can be automated or an edge case that requires human interaction. In the latter situation, the chatbot can bring up all relevant information that a customer service representative needs to assist.

A chatbot delivers data-driven results, helping the customer service representative solve problems quicker, saving time and increasing customer satisfaction. Best of all, because the chatbot learns over time, the process will get faster as the chatbot faces the same type of calls time after time.

Individual Chatbots For Efficiency

Because of their deep learning ability, chatbots can be individualized to specific employees and eliminate any data that’s not relevant to them. Rather than sifting through work data in an effort to complete daily tasks, workers can simply ask individual chatbots for the information they require. In essence, chatbots will make the acts of Googling and searching through webmail obsolete. Anything you use the internet for you can use a chatbot for—without the hassle of sifting through unnecessary information.

Enterprises are increasingly turning to web applications to streamline their processes and make collaboration easier. Still, applications are siloed and unable to communicate with one another. A chatbot could one day render apps obsolete. Chatbots can conduct the same tasks as most applications in one integrated system and tailor the results to the user as the chatbot employs its deep learning algorithms to “understand” that employee’s typical needs.

I think we’re quickly moving toward a future where we’ll see workers at every level of the enterprise—from the C-suite down—using their own chatbots to streamline work processes and improve customer service. Chatbots can provide scalable access to organizational information in real time, and that’s just what businesses need to stay competitive in a constantly changing market landscape.

A version of this was first posted on Forbes.