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.  

What Driving a New Car Teaches Us About Managing Enterprise Risk

If you have purchased a new car in the past few years, you probably have many new technological features to "assist" your driving:  forward collision warning, lane departure warnings, lane keeping assist, back-up camera, adaptive cruise control, blind spot monitoring, etc.   Hopefully, these features make us safer.  Theoretically, they should help reduce human error.  However, four countervailing forces emerge when you install such an array of safety features in a vehicle.  

1.  Drivers develop a false sense of security, and therefore, they take more risk.  Perhaps they drive faster, or they are more apt to text behind the wheel.  

2.  Drivers become overly dependent on the technology.  Over time, their skills erode as the car makes more and more decisions for them.   Consider a scenario where suddenly your back-up camera and parking assist features go away.  Can you parallel park as effectively as you did ten years ago?  

3.  Drivers develop alarm fatigue.  All the warnings and signals become annoying, and drivers simply start ignoring some of them (or turning them off).   

4.  The additional complexity of the vehicle becomes problematic and adds to the risk of a major failure.  For instance, consider renting a vehicle from a different manufacturer than the car you own.  Will the different systems befuddle you a bit? Could the confusion lead to errors?  Similarly, could the added complexity mean that the car is more prone to break down and be costly to repair, given all the technology embedded in the vehicle?

These four concerns all apply to your enterprise as well.  As you add systems to "assist" decision makers, you face these countervailing forces.  Redundant systems may provide crucial back-up to protect against human error, but they add complexity and they create these offsetting risks because of human nature.  We should all be aware of these other risks as we embrace the use of fail-safe, back-up, and decision support systems in our organizations.  

Don't Brag About Being a Dinosaur

The Boston Globe published an interview with Jack and Suzy Welch today (the two will be speaking here at Bryant University on Monday, April 13th).   I thought the excerpt below about the adoption of technology in the workplace was important to highlight. 

 Jack: Nothing is worse than the person in their 40s who says, ‘I’m not going to learn this.’ ‘I don’t carry an iPad.’ That will label you and put you right in the corner. Some people do it as a badge of honor. I’ve seen them myself, they walk around bragging [about not knowing much about technology].

Suzy: Why don’t you carry a placard saying ‘I am a dinosaur.’ You’ve got to dig in [and learn about things you don’t know] if you want to stay in the conversation.

I agree wholeheartedly.   I can never understand the rationale of those who brag about being dinosaurs. "Oh, I don't get the whole Twitter thing."  "I can't figure out how to sync my calendar across all my devices."  "I don't really need most of the functionality of my smartphone; that's why I haven't bothered to learn about those apps."  I think people put a target on their back when they make such statements.  I understand that one does not have to embrace every new social media platform, and some will rely on certain devices more than others.  However, bragging about being a dinosaur signals to others a reluctance to learn new things, make mistakes, and take risks.   The last thing that many leaders want in their organizations want is someone who is not a voracious lifelong learner. 

IBM: What explains the sustained success?

IBM serves as a rare example of a very large organization that went through a near-death experience and came back to become one of the most successful and admired companies in the world.  If you look at the top 10 most admired companies on Fortune's original list in 1983 and compare it to today's list 30 years later, only 1 company is in the top 10 in both years - IBM.   In the middle years, of course, the company nearly did not survive.  Lou Gerstner led a remarkable transformation during the 1990s.

What accounts for IBM's remarkable sustained success over many decades?  One answer may be found in a quote from CEO Ginny Rometty in the current issue of Fortune magazine.  She says, "To be 100 years old, you can never define yourself by a product."  What an astute observation.  Too many firms become defined by a particular product that becomes very popular and profitable.  Then, as  the world changes, they can't adapt and newer, better products pass them by.   In IBM's case, they have not let a particular product become paramount.  They have been able to move beyond one generation of technology and embrace a new wave, and they have done that multiple times.  It's rare.  One wonders whether that "defined by a particular product" phenomenon serves as an explanation for the struggles of firms such as Blackberry.  

The Launch of the New Wii U Gaming Console

In November, Nintendo will launch its new Wii U gaming console.  The company hopes to revive lackluster gaming revenues that have resulted from the maturation of the original Wii product line, as well  as the shift to mobile gaming that has hurt the console business overall.  Kyle Orland writes in this article about Nintendo's pricing strategy.  The firm will be pricing at below cost at launch.   In some ways, we should not find that fact surprising; after all, most gaming companies price below cost at launch. However, Orland notes that Nintendo did not have to do that when it launched the original Wii.  It actually turned a profit at the start.  That proved rather unusual though, running contrary to most product launches in the gaming industry's history.

Source: Nintendo

Why do most gaming consoles sell below cost at launch?  Three major reasons exist. First, companies hope to capitalize on network effects.  They want to build the installed base quickly.  As they do so, the value to each customer grows, and the attractiveness of the console to software developers increases as well. Second, the companies hope to use a "razor and blades" model to make money.   A higher installed base of consoles brings with it higher software sales, which can be very profitable.   Third, the cost of producing a console decreases significantly over time.  Those cost decreases occur for two reasons:  economies of scale and learning curve effects.  

For these reasons, Nintendo rightfully can expect to improve console profitability over time.   Still, they will need strong launch sales to kick off this virtuous cycle.  With the explosing of mobile gaming, the question remains:  Can consoles bounce back?  Have their struggles in recent years simply been due to the usual cyclical downturn in the later years of a technological generation, or are they experiencing a permanent disruption to their business due to the emergence of attractive substitutes?

Will Non-Experts Fuel Future Disruptive Innovation?

Highly successful entrepreneur and philanthropist Naveen Jain has published an interesting essay on the Forbes website.  Jain argues that non-experts will fuel much of the future disruptive innovations.  He challenges Gladwell's emphasis on experts in his book, Outliers.  Jain explains that the experts won't necessarily be the ones to solve some of the world's most challenging problems. 

Jain offers two main reasons.  First, he explains that experts can often be quite myopic.   Second, Jain argues that information is widely available these days, not restricted to a few experts.   Moreover, technology is moving so quickly that expertise seems to become outdated much sooner than in the past.  Here is an excerpt that describes his thinking:

The human brain, or more specifically the neo-cortex, is designed to recognize patterns and draw conclusions from them. Experts are able to identify such patterns related to a specific problem relevant to their area of knowledge. But because non-experts lack that base of knowledge, they are forced to rely more on their brain’s ability for abstraction, rather than specificity. This abstraction—the ability to take away or remove characteristics from something in order to reduce it to a set of essential characteristics—is what presents an opportunity for creative solutions.

Do you agree with his arguments? 

Four Questions About IT For All Leaders

From today's WSJ (article by Jeanne Ross and Peter Weill of MIT) - Four Questions Every CEO Should Ask About IT:

1. Are we using technology to transform our business, or are we just adding bells and whistles to existing processes?

2. Are you ignoring important business differences as you standardize processes across the company?

3. Who is making sure the company's digital strategy is being implemented?

4. Is electronic data empowering your people or controlling them?