By Steve Bien-Aimé • March 20, 2019

When we die, we lose much of our say in how we want our lives, achievements, and identities framed in obituaries—that power is given to editors and journalists, who often follow industry norms.

Even though most U.S. publications have stopped using courtesy titles, exceptions are sometimes made for obituaries, where Mr., Ms., and so on are used to show respect. For example, Philly.com, the website for The Philadelphia Inquirer and Philadelphia Daily News, generally does not use honorifics; however, in a 2018 obit for legendary Philadelphia Eagles player Tommy McDonald, an honorific was used—for him and no one else. Honorifics also hold a precious place in certain cultural contexts, such as racial or regional. Using titles in the South, for example, can be a matter of respect and even racial equality.

Even though most U.S. publications have stopped using courtesy titles, exceptions are sometimes made for obituaries.

Gendered honorifics, however, can have unintended harms. For some, the discomfort arises from the inherent emphasis on one part of a person—gender—when we go through life with many identities. Language shapes how we interpret reality, so placing a gender modifier before a person’s name gives the impression that we should be viewed through gender first and that all other characteristics fall in descending importance. The resulting issue is that some people don’t want to be viewed primarily through their gender. Also, courtesy titles for men and women are unequal: Before the use of Ms., the courtesy titles Miss and Mrs. revealed a woman’s marital status when married and unmarried men shared the status-free Mr.

The courtesy titles with longevity are ones without a gender bias. Because of systemic erasure of women’s achievements, some women with a PhD have added Dr. to their Twitter handles. My Northern Kentucky University colleague Alina Campan, an associate professor in computer science, says that while Mrs. is too general for her, she would want to be called Professor in an obituary because “My career defines a lot of who I am. I act in this role, and it has become an inherent part of my personality.”

Placing a gender modifier before a person’s name gives the impression that we should be viewed through gender first.

Associated Press Stylebook editor Paula Froke noted that AP style generally recommends not to use courtesy titles. However, she said by email that “If the person was a medical doctor, we would use Dr. as the title on first reference in an obituary just as we would in any other kind of story. Same with the Rev., when relevant.” Journalism bellwether The New York Times, which still uses courtesy titles except in certain sections, permits alternate courtesy titles, said the Times’ associate managing editor for standards, Philip B. Corbett, in an email. Mx., for example, has seen increasing acceptance for those failed by gender binaries or don’t believe in gendered honorifics.

Though journalists have begun using Mx., its usage is drawing attention in different ways. After The New York Times used Mx. in 2015, it explained its decision in a column: “People inside and outside the newsroom wondered if ‘Mx.’—an unfamiliar term to many—had suddenly taken its place alongside ‘Mr.’ and ‘Ms.’ in our stylebook’s entry on courtesy titles. The short answer is no. Or not yet. Or perhaps, ask me again in a while. Things are changing fast in this area.”

The courtesy titles with longevity are ones without a gender bias.

Recognizing societal changes, the 2017 Associated Press Stylebook called for editors and journalists to modify their language: “In stories about people who identify as neither male nor female or ask not to be referred to as he/she/him/her: Use the person’s name in place of a pronoun, or otherwise reword the sentence, whenever possible. If they/them/their use is essential, explain in the text that the person prefers a gender-neutral pronoun. Be sure that the phrasing does not imply more than one person.”

Introducing new terms and meanings can be a balancing act. While the visibility of Mx. indicates progress, explaining why Mx. was used for specific people might inadvertently overemphasize an aspect that is not germane to the story, such as the person’s gender. However, providing detailed explanations might be part of necessary growing pains as it takes a conscious effort to normalize new practices. As such, some educators are bringing the knowledge into the classroom: One substitute teacher engages with students about gender diversity by introducing themself with Mx.

Mx., for example, has seen increasing acceptance for those failed by gender binaries or don’t believe in gendered honorifics.

It’s important to differentiate between someone highlighting one of their identities (such as gender) versus an outsider’s description presenting their own bias (such as that gender is the primary identity). Habitual use of gendered honorifics reinforce one identity over and over, which causes other elements of one’s life to be overlooked. Determining the salience of something so personal as identity is hard—for some it’s their job, for others it’s their family roles—especially when the subject isn’t here to clarify. Thus, it’s time to end gendered courtesy titles in obits. As linguistic conventions evolve (as they always do), we must remember our complexity as individuals and to respect one another by not overemphasizing one identity in lieu of others.

Steve Bien-Aimé is an assistant professor of journalism at Northern Kentucky University. Before receiving his doctorate from Penn State’s College of Communications, Steve worked as a copy editor at The News Journal in Delaware and The Baltimore Sun and served in a variety of functions at FOXSports.com, departing as deputy NFL editor. His research interests include race and gender portrayals in news and sports media.

Listening, in particular, was more demanding. As stories unfolded into complex ideas, listeners recruited a broader set of brain regions involved in memory retrieval, sustained attention, and social cognition. These included areas like the angular gyrus and posterior cingulate cortex, which help link incoming language to stored knowledge, and the medial prefrontal cortex, which supports imagining other people’s thoughts and intentions.

These networks allowed the listener not only to absorb the speaker’s words but to track their meaning over time, integrate it with prior knowledge, and infer intention. Speaking did not require the same level of integration. It remained more localized, focused on generating language and responding to immediate context. This involved regions like Broca’s area in the left frontal lobe, which helps plan speech, and nearby motor areas responsible for controlling the muscles used in speaking.

Cognition

How the Brain Builds Conversations Across Time

Related brain processes—speaking and listening—use distinct systems.

Posted July 14, 2025 | Reviewed by Devon Frye

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Key points

• The brain builds conversational meaning across multiple timescales, from short phrases to full narratives.

• While brief segments rely on shared brain regions, others engage different systems for speaking and listening.

• These findings explain how people keep track of conversations and shift fluidly between roles.

“Happy talk,

Keep talkin’ happy talk,

Talk about things you’d like to do.”

These lyrics from South Pacific hint at something deeply human: Our lives unfold through talk.

Our conversations give form to our thoughts and tie us to one another. But beneath the surface of every spoken exchange lies a complex neural process, one that shapes how we create and interpret meaning together.

A new study published in Nature Human Behaviour reveals that the brain organizes this exchange by adapting to the timescale of the conversation. At shorter intervals, the brain uses overlapping systems for both speaking and listening. But as the dialogue stretches into full thoughts or stories, speaking and listening begin to rely on distinct processes. This layered structure helps explain how people carry out fluid, responsive conversations.

How the Brain Follows Conversations

To explore the inner mechanics of dialogue, researchers in Japan invited pairs of individuals to engage in unscripted conversation while lying in separate scanners, speaking through headphones and microphones. Their goal was not to study isolated words or scripted exchanges, but the fluid, spontaneous rhythms of how human communication unfolds in daily life.

The researchers segmented each conversation into varying lengths, from fleeting phrases to full narrative arcs. They then examined how the brain responded to these different timescales. During short exchanges, the same neural systems were active whether a person was speaking or listening. It seemed that, in the early moments of a conversation, both parties relied on a shared set of circuits to manage the rapid flow of words. However, as the conversation deepened and the timescale lengthened, the brain began to diverge in its treatment of each role.

Listening, in particular, was more demanding. As stories unfolded into complex ideas, listeners recruited a broader set of brain regions involved in memory retrieval, sustained attention, and social cognition. These included areas like the angular gyrus and posterior cingulate cortex, which help link incoming language to stored knowledge, and the medial prefrontal cortex, which supports imagining other people’s thoughts and intentions.

These networks allowed the listener not only to absorb the speaker’s words but to track their meaning over time, integrate it with prior knowledge, and infer intention. Speaking did not require the same level of integration. It remained more localized, focused on generating language and responding to immediate context. This involved regions like Broca’s area in the left frontal lobe, which helps plan speech, and nearby motor areas responsible for controlling the muscles used in speaking.

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In this asymmetry lies a profound insight. To speak is to project thought outward, but to listen is to reconstruct another person’s inner world. It is no surprise, then, that the brain allocates its deepest resources to the act of listening.

Why Speaking and Listening Feel So Different

To uncover how this works, the researchers constructed computational models capable of predicting whether a person was speaking or listening based solely on their brain activity.

Even the smallest acknowledgments, like “right,” “uh-huh,” and “you know,” elicit stable patterns in the brain. These fragments serve a subtle but vital purpose. They signal presence, mark engagement, and keep the rhythm of dialogue intact. In doing so, they reflect the fundamentally social nature of language: We do not speak into a void, but to be heard, understood, and affirmed.

As conversations become emotionally charged or intellectually complex, the gap between speaker and listener widens. The listener, more than the speaker, must navigate shifting layers of meaning. This involves not only cognitive effort, but emotional attunement.

Brain areas like the anterior insula and amygdala become more active during emotionally rich moments, helping the listener register tone and affect. Other regions, such as the temporoparietal junction, help track the speaker’s perspective, allowing the listener to imagine what the speaker might be feeling or intending. To listen well is to hold another person’s experience in mind, to mirror their emotions without losing oneself.

A Brain Designed for Dialogue

Conversation is more than the exchange of words. It is a layered, time-dependent process involving memory, emotion, attention, and the ability to switch between speaker and listener. The brain makes this possible by drawing on flexible systems: some geared for rapid responses, others tuned for extended stretches of meaning.

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What emerges is a brain finely shaped for connection. As South Pacific reminds us, “Happy talk, keep talkin’ happy talk.” The complex choreography within the brain allows us not only to speak, but to understand and be understood.

References

Yamashita, M., Kubo, R., & Nishimoto, S. (2025). Conversational content is organized across multiple timescales in the brain. Nature Human Behaviour, 1-13.

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About the Author

William A. Haseltine, Ph.D., is known for his pioneering work on cancer, HIV/AIDS, and genomics. He is Chair and President of the global health think tank Access Health International. His recent books include My Lifelong Fight Against Disease.

Online:

Access Health, Facebook, X, LinkedIn

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Our 30th year of watching Word, Excel, Outlook and PowerPoint.

20 August 2025 – Vol. 30 No.32

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Just like Copilot or its parent ChatGPT, the Copilot function in Excel use for analysis but not so much for getting hard facts. Our testing of the new Copilot() feature shows that no-one should trust what AI says is true.

We’ve taken Microsoft’s example and extended them a little to show the real-world pitfalls and tricks for using Copilot() in Excel. It wasn’t hard to find factual errors in Copilot() responses, some big, small or not understandable!

Some lessons we learned from Copilot()

• Copilot has a slippery and changing concept of ‘truth’.

• Carefully word the prompt and context.

• Carefully check results.

• Sorting has to be done as part of the Copilot prompt, but isn’t always correct.

• Filtering to exclude some results, individual or as a group, can be done in the prompts

• Copilot has trouble parsing first and last names with a middle initial.

• Headings for Copilot() lists may or may not appear. Better to be specific.

Airports

Microsoft’s Copilot() example shows how to get a list of airports.

Source: Microsoft

Like most Microsoft carefully chosen examples, if you do a little digging the problems arise.

We add a filter by population and asked for more details “Airports in cities over half million people, show airport name and code”

As you can see, Copilot() returns a dynamic (spill) array which can include multiple columns.

However, there are problems:

• Gold Coast/Tweed Heads has a population of over 700k and it’s airport should be on the list.

• Canberra and Newcastle have populations just over 500k and should have been included.

• The proper name is “Sydney Kingsford Smith Airport”. Changing the prompt to ask for “full airport name” gives a more accurate result.

  • Just one example of how careful wording of AI prompts is important.

Which only confirms what we’ve said about AI for some time:

Always check the facts and be careful about the wording of prompts.

Another factual error

Just another factual error we found in our testing. Asking for ” Airports in cities over half million people, show airport name and code” for the UK might seem correct but it’s not.

London has 5 or 6 airports (it depends). However, you define “London airports”, it should at least include Gatwick (LGW) and London City (LCY). Luton, Stansted and especially Southend are also called “London airports” with a certain generosity of spirit .

Copilot makes the same mistake with New York, only listing JFK and not La Guardia (LGA).

But change the prompt to ask for distance from a location and suddenly Gatwick airport appears! LCY, which is even closer to Greenwich, is still missing.

This isn’t pedantic nit-picking, it’s examples of a common problem with the current AI systems. We rarely get a ‘factual’ result from Copilot or ChatGPT that doesn’t need some changes.