AI Can Help You—And Your Boss—Maximize Your Potential. Will You Trust It?
Would you trust an Artificial Intelligence (AI) to tell you how to become more effective and successful at your job? How would you feel if you knew your HR department uses AI to determine whether you are leadership material? Or that an AI just suggested to your boss that she should treat you better or else you might soon quit and join a competitor—well before the thought of jumping ship entered your mind?
Meet Yva, introduced by her creator David Yang in this fascinating podcast discussion.
David Yang is an impressive serial entrepreneur: he has launched twelve companies, beginning when he was in fourth grade. David started training as a physicist, to follow in his parents’ footsteps. He won math and physics Olympiads; then his first entrepreneurial detour “distracted” him from his studies for a while and sparked his passion for computer science and AI—it’s really worth hearing the story from David’s own voice, especially his concern of possibly disappointing his parents even as he was launching a hugely successful entrepreneurial and scientific career.
Yva, David’s latest creation, is an AI-powered people analytics platform—a remarkable example of the powerful role that AI is starting to play in the workplace, with the ethical implications that quickly come to the fore.
Yva’s neural network can mine and analyze workers’ activities across a range of work applications: email, Slack, G-Suite, GitHub. With these data, the AI can pick up a treasure trove of nuanced insights about employee behaviors: how quickly an employee responds to certain types of emails; or the tree structure of her communications: how many to subordinates, how many to peers or superiors, how many outside the company; and much more.
These insights can provide value to an organization in two main ways:
First, in identifying which employees have high potential to be great performers or strong leaders. The company tells Yva which individuals it currently considers as best performers; Yva’s neural network identifies which behaviors are characteristic of these top performers, and then finds other employees who exhibit some if not all of the same traits. It can tell you who has the potential to become a top salesperson, or an extremely effective leader; and it can tell you which characteristics they already possess and which ones they need to develop.
Second, Yva helps minimize “regrettable attrition” by identifying employees who are a high resignation risk. A decision to resign never comes out of the blue. First the employee will feel increasingly frustrated or burnt out; then she will become more open to consider other opportunities; then she will actively seek another job. Each stage carries subtle changes in our behavior: maybe how early we send out our first email in the morning, or how quickly we respond, or something in the tone of our messages. We can’t detect these changes, but Yva can.
For large companies, reducing regrettable attrition is Yva’s top contribution: losing and having to replace valuable employees represents a substantial cost. This, notes David Yang, makes the Return On Investment from deploying Yva very easy to identify. For smaller companies, especially in their growth stage, attrition is less of a concern and the greater value comes from the way Yva helps them build talent and leadership from within their ranks.
Given the ubiquitous concerns that technology will eliminate jobs, it’s refreshing and reassuring to hear that Yva instead proves its value by boosting employee retention.
Yva can also help the individual worker; it can create your personal dashboard with insights and suggestions on how you can change your behavior to become more effective and successful.
There is a trade-off. By default, Yva will respect your privacy, working on anonymized data. But the more individual data you are willing to share, the more Yva can help. The choice is yours.
David Yang notes some interesting geographic differences in the share of employees who opt in; he also notes that across the board, close to one employee in five remains adamantly opposed to disclosing her individual data.
Privacy concerns are fully understandable when faced with an AI that can drive important HR decisions. But is it smart to trust humans more than AI? David Yang notes that AI can help eliminate the human biases that often influence hiring and promotion decisions. Provided—he stresses—that the AI gets trained in the right way, only on final outcomes, on objective performance criteria, without feeding into it intermediate variables such as race, gender or age, which could create a built-in bias in the AI itself.
David Yang, unsurprisingly, is very bullish on the role that AI can play in people analytics and in our lives. Bullish, but very realistic and thoughtful, and willing to put himself on the line—at the end of the podcast discussion he talks of the role that Morpheus, another AI, plays in his personal life.
David thinks that in the future smaller companies (500 employees or less) will rely completely on AI-powered people analytics platform; he believes that AI will play a major role in leveraging the creativity and efficiency of individuals, while HR (human) professionals will focus on business-specific HR-partner roles. He has a horse in the race—Yva. But there seems to be little doubt that whatever role AI takes in HR and people analytics, it will be one of its most powerful influences in our professional—and personal—lives.