What Happens When We Compare Ourselves to Generative AI?

Source: https://itsoli.ai/

What happens when we compare ourselves to generative AI?  What conclusions do we reach about our own capabilities? Taly Reich and Jacob Teeny have examined these questions in a new paper titled, "Does Artificial Intelligence Cause Artificial Confidence? Generative AI as an Emerging Social Referent."  The scholars conducted several experiments in which they exposed people to precisely the same work, but told some that it was performed by AI and others that it was completed by human beings.  Interestingly, the  researchers found that people exhibit greater self-confidence (with regard to completing a creative task) when they believe that the work they observed was completed by a generative AI model rather than fellow humans. Teeny offered some explanation in this feature from Kellogg Insight:

"From a practical standpoint, self-confidence is such an important driver of innovation, and past research shows so much of our behavior is driven by the simple perception that we are capable of doing that behavior, whether it’s to undertake a piece of creative work or apply for a dream job... Much of our self-perceptions are based on how we compare ourselves to others. If we’re exposed to people we believe are really good at something, we may think, ‘Oh, I’m not as good at that [task] as I thought I was.’ But if we’re exposed to people who do something poorly or who we believe are less skilled, we think, ‘I’m actually pretty good at that.’”

Of course, simply having more self-confidence does not mean people actually will perform well on a subsequent task.   In one of their studies, Reich and Teeny show that those who had compared themselves to an AI model did no better at a creative task than the individuals who compared themselves to other humans.  

Scarcity, Pricing, and Luxury Goods: The Case of the Birkin Bag

Source: Teen Vogue

Why do we exhibit a strong desire to buy something that is not readily available?  Many people would say that we all fall victim to FOMO at times (Fear of Missing Out).  Psychologists have posited that "reactance theory" helps explain our behavior.  In short, this theory argues that we become very uncomfortable, and perhaps even anxious, when our freedom is constricted.  As a result of that discomfort, people have an even stronger desire to purchase a product.  Of course, consumers also care about status.  Thus, they value products more if many others cannot purchase it.  Having a product that others can't get their hands on turns out to be very enticing.  Thus, luxury goods manufacturers tend to use limited time offerings, special exclusive collections, and other related strategies to entice consumers.  They intentionally create scarcity so as to stimulate demand and enhance willingness to pay on the part of potential customers.  

No company has mastered scarcity better than Hermès.  The company markets the famous Birkin bag, named after British actress Jane Birkin, who inspired Hermès Executive Chairman Jean-Louis Dumas to create the leather bag during a conversation aboard a flight in 1984.  A classic Birkin 25 bag sells for more than $12,000 today.  Could the company raise prices even further?  Given the even higher prices on the resale market, it seems the firm could raise prices. However, as Carol Ryan wrote this week in the Wall Street Journal, Hermès chooses to drive profitability through a different strategy. She writes:

The brand limits how many it produces, so demand far outstrips supply. Hermès could easily jack up the price but has found a smarter way to profit from the Birkin’s popularity that is less likely to alienate loyal clients.  To get a Birkin, shoppers must build a relationship with one of the brand’s sales assistants and wait to be offered a purse. This creates a perception that the biggest spenders get access to Birkins and encourages customers to splurge on other goods to build the equivalent of an “Uber rating” at the Hermès store.

If you would like to learn more about the incredibly successful luxury goods firm Hermès, I highly recommend the episode of the Acquired podcast that tells the company's long and storied history and breaks down its competitive strategy. 

Scarcity does not only apply in the luxury goods market though.  Special limited offerings prove to be an essential part of the "treasure hunt" experience at value-based retailers such as Zara, Costco and Trader Joe's as well.  For these firms, the business model calls for drawing customers in to find those special offerings, but then hoping to sell them many other items while they are in the store.  At a company such as Zara, customers visit more often than the usual apparel retailer, because they know that products won't stay in the stores for a long time.  At Trader Joe's, special seasonal offerings will come and go, causing people to act quickly to grab popular items. 

Rethinking the Exit Interview

We all know that employee turnover can be extremely costly for organizations.  Yet, we also recognize that many firms struggle with employee retention.  Managers sometimes cannot determine why people are leaving. They try to use exit interviews to learn about the conditions creating turnover, but they fail to arrive at concrete conclusions.  Often, departing employees hold back in those exit interviews, rather than disclosing completely the reasons for their move to a different company. 

Writing in Harvard Business Review, Ethan Bernstein, Michael B. Horn, and Bob Moesta explain a different approach to learning about what drives people to switch jobs.  They write,

As we noted earlier, exit interviews can be a bit of a joke. People usually assume it’s too late to address why they are leaving—so they say safe things and move on.  We’ve found that it’s more productive to interview employees about their previous roles soon after they’ve started something new. That’s essentially what we did in our research. By closely examining the pushes and pulls that compelled each person’s most recent job move, you can better understand what might motivate your employees to make another change soon—and, conversely, what might make them choose to stick around. You can frame these talks with employees as your way of identifying important features of their experience so that with their input you can create a workplace that they’ll want to “rehire” each day.

This strategy makes a good deal of sense to me.  These conversations can be useful in two key ways.  First, managers can get to know their new employees - what motivates and drives them, what they care deeply about, and what they love (and don't love) about their work.  Second, managers can begin to detect themes across their employee population.  What type of people are attracted to the organization?  Why are people self-selecting this company?  What, if anything, made them hesitant about taking a new job here?  The answers to these questions can shape a company's recruitment and retention strategies.  Finally, I would argue that the answers to some of these questions may emerge during the interview process.  Yet, managers are often focused on selecting the best candidate, rather than thinking about the interview process as an opportunity to learn about what motivates people to switch jobs.  Mining the interviews for this additional information could be very useful. 

Will Using AI at Work Damage Your Reputation?

How does using AI at work shape others' perceptions of you?  Could you enhance or damage your reputation by leveraging AI extensively?  Jessica Reif , Richard Larrick, and Jack Soll have published a fascinating new paper on this topic titled "Evidence of a social evaluation penalty for using AI."   The scholars conducted a series of experiments to examine how people perceive those that use AI extensively at work.   The authors concluded, "This work provides experimental evidence that people incur a social evaluation penalty for using AI tools at work. This generates a dilemma for employees: The productivity gains they can achieve with AI tools carry a social cost." 

Duke Fuqua Insights reported on this study's findings: "The study found that employees judge colleagues who use AI as less competent and lazier, and recruiting managers may act based on this perception by penalizing job candidates who rely on AI to complete tasks." On the other hand, if the manager also uses AI to enhance efficiency and productivity, this social penalty goes away.

Will these attitudes about AI shift over time? The authors think so. They write, "Perceptions of technology tend to be influenced by its age, and thus the social evaluation penalties we documented are likely to shift as AI tools become more commonplace and organizational norms around their use continue to develop."

What do I take away from this research?  What is the practical implication?   For me, I recommend that employees explain their rationale for using AI to enhance productivity and efficiency.  You have to make your case to the skeptics in your organization and provide evidence of the how it improves workplace performance.  Don't just assume others recognize its merits.  However, you also don't want to disparage colleagues and managers who might be resistant, or who might perceive AI users as lazy or incompetent.  Give them concrete evidence of its benefits, rather than making conceptual arguments.  Invite them to collaborate with you on projects that involve the use of AI.  Help them see firsthand how it can help them.  Finally, don't downplay the risks and problems associated with AI use.  Acknowledge the challenges associated with hallucinations and biases.  Explain how you try to address those risks in your work.  

Deep Curiosity to Solve Hard Problems

Recently, AMD CEO Lisa Su spoke at Stanford's Graduate School of Business. She described how leaders should be aiming to provide opportunities for their people to tackle hard problems. She argued that you won't be sure they can achieve those ambitious goals, but your job is to create those opportunities and provide them support. For employees, their goal should be to have an intense curiosity about solving tricky problems and an interest in exploring new challenges. Together, a leader looking to provide challenges and an employee with curiosity can be a perfect match. Here's an excerpt from Lisa Su's interview:

Well, I think the most important thing for all of us is to have a deep curiosity of just solving problems. That’s my view of the world. When I think about… In the early part of my career, some of the most difficult things, like the first product I ever worked on was a product that was a microprocessor, and we were just about to announce the processor and nothing worked. I mean, the chip did not work. We didn’t know why it didn’t work, but the company was about to announce it. And you think, “Oh, that’s terrible.” That’s very stressful. But actually, what it is it allows you to really galvanize teams on really taking, opening up every ounce of creativity you have to figure out, okay, how are we going to figure out why is this not working and how do we bring it, move the projects forward?

And so that’s what I view as the beauty of hard problems. You can work on anything in life, but when you work on a really hard problem, or in a company context, when you work on, let’s call it the most important projects, you can garner an incredible amount of just resources, creativity, focus that will allow you to do something that you wouldn’t imagine possible. That’s what I believe is the most important thing managers do or leaders do. What leaders do is they actually bring teams together to do something that nobody thought was possible. And that’s what I enjoy about the world that we’re in, is that you’re working on problems that are super interesting and quite impactful to the industry, and you’re also working on something that someone hasn’t done before.

Are You Leaning on AI Because You Are Afraid To Speak With Your Manager?

Are You Leaning on AI for Advice and Feedback Because You Are Afraid To Speak With Your Manager?  Perhaps many employees are doing so these days.  Fortune's Brit Morse writes:

Given an increasingly personal reliance on AI, HR professionals should also take note of where employees—and especially the youngest office workers—are getting career advice. Around 40% of employees overall say they rely more on ChatGPT than their manager to answer questions about work, with nearly half (49%) of Gen Zs agreeing. Pichura career coach for Resume.org.) notes that this generation is accustomed to receiving instant feedback, and when they’re not getting that from their manager, they may look to other sources instead.

What do we make of these findings?  I see two forces at play here. First, managers may not be providing the type of constructive, real-time advice and feedback that employees desire.  Second, many employees may be leaning on AI models because they are not comfortable speaking with their manager about their performance and opportunities for improvement.  I'm certainly not against using AI to enhance your productivity and performance on the job.  However, something very important is missing if we are avoiding conversations with our managers out of discomfort or conflict avoidance tendencies.  Managers need to make themselves more accessible and need to help their employees become more comfortable asking for help.  Employees need to tackle their discomfort head-on, and they must be willing to hear the hard truths needed to enhance performance. 

The Pressure To Appear Confident

Do you feel pressure at times to appear confident in your decisions and plans? Are you actually certain, or are you trying to put on a brave face for your team members and/or external constituents? Are you afraid of appearing as though you are not sure how to proceed, or how the future will unfold for your organization? Fast Company's Kate O'Neill addresses the topic of confidence in a great new article titled Why the best leaders embrace ‘strategic disappointment’ (and how you can, too)  

O'Neill argues that the more success you have, the more likely you will disappointment your followers at some point. After all, expectations grow quickly if you deliver good results.  Moreover, she argues that you are probably not pushing the boundaries of innovation if you never disappoint.  O'Neill argues that we have to work through lofty expectations and potential disappointment, rather than trying to avoid ever disappointing others.  Managing expectations (our own and others' expectations) means understanding feelings of confidence very clearly. She writes: 

Part of the challenge is that we fundamentally misunderstand confidence. As Nobel laureate Daniel Kahneman explains, “Subjective confidence in a judgment is not a reasoned evaluation of the probability that this judgment is correct. Confidence is a feeling, which reflects the coherence of the information and the cognitive ease of processing it.”  In other words, our feeling of confidence often has more to do with how neatly our story fits together than with its actual likelihood of being correct. This creates a dangerous dynamic in leadership, where seemingly “confident” decisions may simply reflect coherent but flawed narratives, especially when those narratives align with what stakeholders want to hear... True confidence comes not from eliminating uncertainty, but from understanding precisely what we know and what we don’t, and responding appropriately.

In my view, this last sentence makes a crucial point. The best leaders acknowledge the gaps in their own knowledge and expertise.  As Microsoft CEO Satya Nadella says, they are "learn-it-all" leaders, not "know-it-all" leaders.  You can be confident without fooling yourself into thinking you have made all the correct assumptions and have made clear and accurate predictions of how the future will unfold.  Christa Quarles, CEO of Alludo, put it well when she says that effective and authentic leaders explain, "Here's what I know.  Here's what I don't know.  Now let's assemble the team and the people to go solve those problems in a holistic way."