Could the way we speak reveal what’s happening in our brains? In article, science writer Carly Cassella dives into new research showing that slower speech might be an early sign of cognitive decline — even before memory issues show up. Using AI to analyze speech from people across a wide age range, researchers found a strong link between speaking speed and brain health. It’s a thought-provoking read, especially for anyone interested in aging, neuroscience, or just how much our words might say about us.

Early signs of Alzheimer’s disease may be hidden in the way a person speaks, but it’s not yet clear which details of our diction are most critical for diagnosis.

A study from 2023 suggests that as we age, how we say something may matter more than what we say. Researchers at the University of Toronto think the pace of everyday speech may be a better indicator of cognitive decline than difficulty finding a word.

Lethologica, also known as ‘tip of the tongue‘ phenomenon, is experienced by young and old alike. But as we grow older, finding the name for things can become more challenging, especially over the age of 60.

To explore why that is, researchers at the University of Toronto asked 125 healthy adults, between the ages of 18 and 90, to describe a scene in detail.

Next, the participants were shown pictures of everyday objects while listening to audio that was designed to confirm or confuse them.

For instance, if participants were shown a picture of a broom, the audio might say ‘groom’, which helps them recall the word through rhyme. But on the flip side, the audio might also offer a related word like ‘mop’, which can lead the brain astray, momentarily.

The faster a person’s natural speech in the first task, the more quickly they came up with answers in the second task.

The findings align with the ‘processing speed theory’, which argues that a general slowdown in cognitive processing lies at the very center of cognitive decline, not a slowdown in memory centers specifically.

“It is clear that older adults are significantly slower than younger adults in completing various cognitive tasks, including word-production tasks such as picture naming, answering questions, or reading written words,” explained a team led by University of Toronto psychologist Hsi T. Wei.

“In natural speech, older adults also tend to produce more dysfluencies such as unfilled and filled pauses (e.g., “uh” and “um”) in between speech and have a generally slower speech rate.”

In a 2024 piece for The Conversation, dementia researcher Claire Lancaster said that the study from Toronto “has opened exciting doors… showing that it’s not just what we say but how fast we say it that can reveal cognitive changes.”

Recently, some AI algorithms have even been able to predict an Alzheimer’s diagnosis with an accuracy of 78.5 percent using speech patterns alone.

Other studies have found that patients with more signs of amyloid plaque in their brain are 1.2 times more likely to show speech-related problems.

Amyloid plaques are a hallmark of Alzheimer’s disease.

In 2024, researchers at Stanford University led a study that found longer pauses and slower speech rates were also associated with higher levels of tangled tau proteins, another hallmark of Alzheimer’s.

“This suggests that speech changes reflect development of Alzheimer’s disease pathology even in the absence of overt cognitive impairment,” the authors of the study concluded.

The groundwork is still being laid, but scientists are getting closer to decoding the nuances of human speech to figure out what our words are saying about our brains.

The 2023 study was published in Aging, Neuropsychology, and Cognition.

As part of his Metatheory of Change, Dr. Stern talks about self-interruption. It’s very difficult to find information about self-interruption, but in transcribing speech, it’s something we encounter every day. In research interviews, in oral histories, in patient narratives.

When a parent is asked about receiving the initial diagnosis of their child’s cancer, they stutter and stumble, no matter how long they’ve been dealing with the news. Those stutters and stumbles speak volumes.

Here’s what he has to say:

When people interrupt their inner processes (self-interruption), a motive is required for this.

Why does someone push back their tears? Why does someone hide a tenderly emerging insecurity? Why does someone pretend they are not angry?

These are everyday situations which we are used to. Because of the interruption, the experience remains more diffuse, and the inner process terminates more quickly. Why do people use such self-interruptions?

When internal reasons are at play, then, as a rule, it is the expectation that the consequences of the interruptions will be less grave than the consequences of permitting them. Thus, fears are involved which often play in the background and are not questioned. The simple question “Why do you not allow yourself to cry?” will often cause a degree of alienation. However, if something new is really supposed to happen, then it needs an interruption of the self-interruption of the self-perception. From a metatheory viewpoint this is a core function of counselling. Only then can either the need, and the associated fear, become concise, or the ways and means by which the client works himself up into an unfruitful inner dialogue.

One of the most favoured ways in which people interrupt their self-perception is through speaking. However, when speaking serves to reduce experiencing (‘talking something away’), then it is important that the counsellor prevents the speaking. Otherwise highly fruitful chances in the present moment are lost and the possible intensity in the counselling sequence is destroyed (<a href=”https://metatheorie-der-veraenderung.info/wpmtags/daniel-stern/”>Daniel Stern</a>).

I’m going to continue to explore self-interruption because I think it is a critical part of self-expression.

Q. “. . . go to high school in Washington[, D.C.].” Is the final period necessary? Delete it? (Yes, it’s the last of a longer quotation.)

A. In your version, where you’re using brackets to supply not just the abbreviation but the comma that would normally go with it, you don’t need that final period; we can assume that your bracketed interpolation includes all sentence punctuation, including any final period. And that’s what we might expect if you were supplying the end of a sentence that’s missing or illegible in the source. In other words, your brackets restore the end of a sentence that would normally be punctuated like this:

“. . . go to high school in Washington, D.C.”

But if you’re simply clarifying for readers that the text is referring to the district rather than the state, don’t add that comma. Instead, put “D.C.” in brackets and add the sentence-ending period:

“. . . go to high school in Washington [D.C.].”

That extra period is needed for the same reason you’d add a period to the end of a sentence like this one (from CMOS 6.13):

His chilly demeanor gave him an affinity for the noble gases (helium, neon, etc.).

But there would be no periods in an initialism like DC in current Chicago style, so you’d normally write this:

“. . . go to high school in Washington [DC].”

See also CMOS 6.110 (which has a similar set of examples but without periods) and 12.70–74 (on editorial interpolations and clarifications).

This one has been driving me crazy!

Abbreviations

Q. Is there any chance that “am” and “pm” will become acceptable as correct forms of “a.m.” and “p.m.”?

A. There are six ways to write the abbreviations for ante meridiem (before noon) and post meridiem (after noon):

All caps with periods: 10 A.M., 10 P.M.
All caps without periods: 10 AM, 10 PM
Small caps with periods: 10 A.M., 10 P.M.
Small caps without periods: 10 AM, 10 PM
Lowercase with periods: 10 a.m., 10 p.m.
Lowercase without periods: 10 am, 10 pm

Each of these—including “am” and “pm”—is a legitimate choice. For nearly a century, Chicago’s preferred form was the third: small capital letters with periods. This preference, however, applied only to published documents (among other factors, small capitals weren’t an option on typewriters).

When we changed our preference to “a.m.” and “p.m.” (in 2003, with the publication of CMOS 15), the growth of computers in writing and publishing played a role: small caps require extra steps to apply, and they don’t always translate well across applications (when they’re even available). We could have flipped a coin and settled on all-caps “AM” and “PM” (but not “A.M.” and “P.M.”; Chicago style now omits periods in abbreviations that include two or more capital letters). When we instead chose lowercase “a.m.” and “p.m.,” we liked the fact that they’re unambiguous (“AM” and “PM” both have a number of other meanings), and we hoped the periods would help readers recognize in any context that these are abbreviations, not words.

But if you don’t like the periods, don’t fret: Merriam-Webster labels “am” and “pm” as British variants, so you’re hardly alone in your preference. If you’re being published, however, be prepared to defer to your publisher’s house style, whatever that may be.

Trump-aligned lawmakers are pushing AI companies to abandon “woke AI” efforts like fairness, safety, and bias mitigation—branding them as ideological overreach. But here’s the danger: that erases vital protections for racial, gender, and LGBTQ+ communities.

When fairness becomes “woke”—what happens to marginalized voices? Human-led, bias-aware language services are crucial when tech is being politically optimized.

By MATT O’BRIEN

Updated 7:00 AM GMT-3, April 27, 2025

CAMBRIDGE, Mass. (AP) — After retreating from their workplace diversity, equity and inclusion programs, tech companies could now face a second reckoning over their DEI work in AI products.

In the White House and the Republican-led Congress, “woke AI” has replaced harmful algorithmic discrimination as a problem that needs fixing. Past efforts to “advance equity” in AI development and curb the production of “harmful and biased outputs” are a target of investigation, according to subpoenas sent to Amazon, Google, Meta, Microsoft, OpenAI and 10 other tech companies last month by the House Judiciary Committee.

And the standard-setting branch of the U.S. Commerce Department has deleted mentions of AI fairness, safety and “responsible AI” in its appeal for collaboration with outside researchers. It is instead instructing scientists to focus on “reducing ideological bias” in a way that will “enable human flourishing and economic competitiveness,” according to a copy of the document obtained by The Associated Press.

In some ways, tech workers are used to a whiplash of Washington-driven priorities affecting their work.

But the latest shift has raised concerns among experts in the field, including Harvard University sociologist Ellis Monk, who several years ago was approached by Google to help make its AI products more inclusive.

Back then, the tech industry already knew it had a problem with the branch of AI that trains machines to “see” and understand images. Computer vision held great commercial promise but echoed the historical biases found in earlier camera technologies that portrayed Black and brown people in an unflattering light.

“Black people or darker skinned people would come in the picture and we’d look ridiculous sometimes,” said Monk, a scholar of colorism, a form of discrimination based on people’s skin tones and other features.

Google adopted a color scale invented by Monk that improved how its AI image tools portray the diversity of human skin tones, replacing a decades-old standard originally designed for doctors treating white dermatology patients.

“Consumers definitely had a huge positive response to the changes,” he said.

Now Monk wonders whether such efforts will continue in the future. While he doesn’t believe that his Monk Skin Tone Scale is threatened because it’s already baked into dozens of products at Google and elsewhere — including camera phones, video games, AI image generators — he and other researchers worry that the new mood is chilling future initiatives and funding to make technology work better for everyone.

“Google wants their products to work for everybody, in India, China, Africa, et cetera. That part is kind of DEI-immune,” Monk said. “But could future funding for those kinds of projects be lowered? Absolutely, when the political mood shifts and when there’s a lot of pressure to get to market very quickly.”

Trump has cut hundreds of science, technology and health funding grants touching on DEI themes, but its influence on commercial development of chatbots and other AI products is more indirect. In investigating AI companies, Republican Rep. Jim Jordan, chair of the judiciary committee, said he wants to find out whether former President Joe Biden’s administration “coerced or colluded with” them to censor lawful speech.

Michael Kratsios, director of the White House’s Office of Science and Technology Policy, said at a Texas event this month that Biden’s AI policies were “promoting social divisions and redistribution in the name of equity.”

The Trump administration declined to make Kratsios available for an interview but quoted several examples of what he meant. One was a line from a Biden-era AI research strategy that said: “Without proper controls, AI systems can amplify, perpetuate, or exacerbate inequitable or undesirable outcomes for individuals and communities.”

Even before Biden took office, a growing body of research and personal anecdotes was attracting attention to the harms of AI bias.

One study showed self-driving car technology has a hard time detecting darker-skinned pedestrians, putting them in greater danger of getting run over. Another study asking popular AI text-to-image generators to make a picture of a surgeon found they produced a white man about 98% percent of the time, far higher than the real proportions even in a heavily male-dominated field.

Face-matching software for unlocking phones misidentified Asian faces. Police in U.S. cities wrongfully arrested Black men based on false face recognition matches. And a decade ago, Google’s own photos app sorted a picture of two Black people into a category labeled as “gorillas.”

Even government scientists in the first Trump administration concluded in 2019 that facial recognition technology was performing unevenly based on race, gender or age.

Biden’s election propelled some tech companies to accelerate their focus on AI fairness. The 2022 arrival of OpenAI’s ChatGPT added new priorities, sparking a commercial boom in new AI applications for composing documents and generating images, pressuring companies like Google to ease its caution and catch up.

Then came Google’s Gemini AI chatbot — and a flawed product rollout last year that would make it the symbol of “woke AI” that conservatives hoped to unravel. Left to their own devices, AI tools that generate images from a written prompt are prone to perpetuating the stereotypes accumulated from all the visual data they were trained on.

Google’s was no different, and when asked to depict people in various professions, it was more likely to favor lighter-skinned faces and men, and, when women were chosen, younger women, according to the company’s own public research.

Google tried to place technical guardrails to reduce those disparities before rolling out Gemini’s AI image generator just over a year ago. It ended up overcompensating for the bias, placing people of color and women in inaccurate historical settings, such as answering a request for American founding fathers with images of men in 18th century attire who appeared to be Black, Asian and Native American. Google quickly apologized and temporarily pulled the plug on the feature, but the outrage became a rallying cry taken up by the political right.

With Google CEO Sundar Pichai sitting nearby, Vice President JD Vance used an AI summit in Paris in February to decry the advancement of “downright ahistorical social agendas through AI,” naming the moment when Google’s AI image generator was “trying to tell us that George Washington was Black, or that America’s doughboys in World War I were, in fact, women.”

“We have to remember the lessons from that ridiculous moment,” Vance declared at the gathering. “And what we take from it is that the Trump administration will ensure that AI systems developed in America are free from ideological bias and never restrict our citizens’ right to free speech.”

A former Biden science adviser who attended that speech, Alondra Nelson, said the Trump administration’s new focus on AI’s “ideological bias” is in some ways a recognition of years of work to address algorithmic bias that can affect housing, mortgages, health care and other aspects of people’s lives.

“Fundamentally, to say that AI systems are ideologically biased is to say that you identify, recognize and are concerned about the problem of algorithmic bias, which is the problem that many of us have been worried about for a long time,” said Nelson, the former acting director of the White House’s Office of Science and Technology Policy who co-authored a set of principles to protect civil rights and civil liberties in AI applications.

But Nelson doesn’t see much room for collaboration amid the denigration of equitable AI initiatives.

“I think in this political space, unfortunately, that is quite unlikely,” she said. “Problems that have been differently named — algorithmic discrimination or algorithmic bias on the one hand, and ideological bias on the other —- will be regrettably seen us as two different problems.”