The Insightful Leader
Sent to subscribers on February 7, 2024
Good morning,
What’s the best presentation you’ve ever seen at work? Chances are, you remember it less because of the information it contained and more because of how that information was conveyed.
“To be successful, it’s simply not enough to have brilliant ideas. You must also be able to communicate your ideas clearly and concisely in order to persuade investors, stakeholders, and clients,” says Michael Foley, a clinical assistant professor of leadership and communication at the Kellogg School.
This week, we’ll offer some of Foley’s tips for honing your message and connecting with your audience. We’ll also share some research from Matt Groh, an assistant professor of management and organizations, on the use of AI in medicine.
A balancing act
Most speakers are either scripters or wingers, says Foley. Scripters stick closely to their talking points; wingers just, well, tend to wing it. Which method is more effective? According to Foley, neither. The sweet spot is in the middle.
Leaders should aim for what Foley calls “structured improvisation,” where you prepare your key talking points while giving yourself the freedom to express yourself in a natural and conversational manner.
“The structure shows the audience that you’ve done your due diligence and that you’re going to be crisp, clear, and on point,” Foley says. “It also shows you know where they’re coming from, you’ve anticipated some of their questions already, and you’ve woven them into your content.”
When you master this technique, you can jot down notes on a napkin and talk effortlessly for twenty minutes or more, he says.
Speakers should also aim to strike a balance between objective and subjective evidence. Objective evidence—data, statistics, charts—helps you establish context and build a case, especially with technical audiences. Subjective evidence is best used to illustrate a point, such as relating a testimonial to demonstrate client impact.
Knowing your audience can help you determine how much of each type of evidence you cite. For example, stories work well in business presentations or investment pitches, but might not resonate with analytical audiences such as engineers, PhD researchers, and accountants.
You can read the rest of Foley’s recommendations in Kellogg Insight.
What AI can—and can’t—do for medical diagnosis
Like many fields, medicine is still figuring out how it will make the most effective use of artificial intelligence. While robots are unlikely to replace doctors anytime soon, it’s easy to imagine a future in which the two work together. These physician–machine partnerships hold particular promise for dermatology, a specialty in which diagnosis often comes down to recognizing the visual characteristics of a disease—something that deep-learning systems (DLSs) can be trained to do with great precision.
There’s even hope that machine learning could help address a known problem in the field: only 10 percent of images in dermatology textbooks depict patients with darker skin, meaning that physicians may be unfamiliar with the different ways diseases can present across skin tones.
In new research, Groh put the issue of machine-aided dermatology to the test by seeing how suggestions from deep-learning systems affected physicians’ photo-based diagnoses.
The results were mixed. Assistance from even an imperfect deep-learning system increased dermatologists’ and general practitioners’ diagnostic accuracy—but among general practitioners, the DLS exacerbated disparities in accuracy across light and dark skin. In other words, generalists supported by AI got much better at making correct diagnoses in light skin but only slightly better in darker skin.
The findings suggest that the best AI-supported dermatology might look different from how we currently imagine it—and that DLSs and doctors are more powerful together than they are alone. “It’s all about augmenting humans,” Groh says. “We’re not trying to automate anyone away. We’re actually trying to understand how augmentation might work, when and where it will be useful, and how we should appropriately design augmentation.”
You can read more about the research in Kellogg Insight.
“What my research tries to highlight is that there are certain ESG factors and signals that can be taken advantage of from an investor’s perspective.”
— Assistant professor of accounting Aaron Yoon, in Kellogg Insight, on the link between supply-chain ESG risks and stock prices.
See you next week!
Susie Allen, senior research editor
Kellogg Insight