Call us toll free: +1 4062079616
How To Be Spiritual In A Material World
Call us toll free: +1 4062079616
26 Sep 2023
Comments: 0

Humans Could Live up to 150 Years, New Research Suggests

The chorus of the theme song for the movie Fame, performed by actress Irene Cara, includes the line “I’m gonna live forever.” Cara was, of course, singing about the posthumous longevity that fame can confer. But a literal expression of this hubris resonates in some corners of the world—especially in the technology industry. In Silicon Valley, immortality is sometimes elevated to the status of a corporeal goal. Plenty of big names in big tech have sunk funding into ventures to solve the problem of death as if it were just an upgrade to your smartphone’s operating system.

Yet what if death simply cannot be hacked and longevity will always have a ceiling, no matter what we do? Researchers have now taken on the question of how long we can live if, by some combination of serendipity and genetics, we do not die from cancer, heart disease or getting hit by a bus. They report that when omitting things that usually kill us, our body’s capacity to restore equilibrium to its myriad structural and metabolic systems after disruptions still fades with time. And even if we make it through life with few stressors, this incremental decline sets the maximum life span for humans at somewhere between 120 and 150 years. In the end, if the obvious hazards do not take our lives, this fundamental loss of resilience will do so, the researchers conclude in findings published in May 2021 in Nature Communications.

“They are asking the question of ‘What’s the longest life that could be lived by a human complex system if everything else went really well, and it’s in a stressor-free environment?’” says Heather Whitson, director of the Duke University Center for the Study of Aging and Human Development, who was not involved in the paper. The team’s results point to an underlying “pace of aging” that sets the limits on life span, she says.

For the study, Timothy Pyrkov, a researcher at a Singapore-based company called Gero, and his colleagues looked at this “pace of aging” in three large cohorts in the U.S., the U.K. and Russia. To evaluate deviations from stable health, they assessed changes in blood cell counts and the daily number of steps taken and analyzed them by age groups.

For both blood cell and step counts, the pattern was the same: as age increased, some factor beyond disease drove a predictable and incremental decline in the body’s ability to return blood cells or gait to a stable level after a disruption. When Pyrkov and his colleagues in Moscow and Buffalo, N.Y., used this predictable pace of decline to determine when resilience would disappear entirely, leading to death, they found a range of 120 to 150 years. (In 1997 Jeanne Calment, the oldest person on record to have ever lived, died in France at the age of 122.)

The researchers also found that with age, the body’s response to insults could increasingly range far from a stable normal, requiring more time for recovery. Whitson says that this result makes sense: A healthy young person can produce a rapid physiological response to adjust to fluctuations and restore a personal norm. But in an older person, she says, “everything is just a little bit dampened, a little slower to respond, and you can get overshoots,” such as when an illness brings on big swings in blood pressure.

Measurements such as blood pressure and blood cell counts have a known healthy range, however, Whitson points out, whereas step counts are highly personal. The fact that Pyrkov and his colleagues chose a variable that is so different from blood counts and still discovered the same decline over time may suggest a real pace-of-aging factor in play across different domains.

Study co-author Peter Fedichev, who trained as a physicist and co-founded Gero, says that although most biologists would view blood cell counts and step counts as “pretty different,” the fact that both sources “paint exactly the same future” suggests that this pace-of-aging component is real.

The authors pointed to social factors that reflect the findings. “We observed a steep turn at about the age of 35 to 40 years that was quite surprising,” Pyrkov says. For example, he notes, this period is often a time when an athlete’s sports career ends, “an indication that something in physiology may really be changing at this age.”

The desire to unlock the secrets of immortality has likely been around as long as humans’ awareness of death. But a long life span is not the same as a long health span, says S. Jay Olshansky, a professor of epidemiology and biostatistics at the University of Illinois at Chicago, who was not involved in the work. “The focus shouldn’t be on living longer but on living healthier longer,” he says.

“Death is not the only thing that matters,” Whitson says. “Other things, like quality of life, start mattering more and more as people experience the loss of them.” The death modeled in this study, she says, “is the ultimate lingering death. And the question is: Can we extend life without also extending the proportion of time that people go through a frail state?”

The researchers’ “final conclusion is interesting to see,” Olshansky says. He characterizes it as “Hey, guess what? Treating diseases in the long run is not going to have the effect that you might want it to have. These fundamental biological processes of aging are going to continue.”

The idea of slowing down the aging process has drawn attention, not just from Silicon Valley types who dream about uploading their memories to computers but also from a cadre of researchers who view such interventions as a means to “compress morbidity”—to diminish illness and infirmity at the end of life to extend health span. The question of whether this will have any impact on the fundamental upper limits identified in the Nature Communications paper remains highly speculative. But some studies are being launched—testing the diabetes drug metformin, for example—with the goal of attenuating hallmark indicators of aging.

In this same vein, Fedichev and his team are not discouraged by their estimates of maximum human life span. His view is that their research marks the beginning of a longer journey. “Measuring something is the first step before producing an intervention,” Fedichev says. As he puts it, the next steps, now that the team has measured this independent pace of aging, will be to find ways to “intercept the loss of resilience.”

 

 

 

Original article here

 

22 Sep 2023
Comments: 0

Selfishness Is Learned

Many people cheat on taxes — no mystery there. But many people don’t, even if they wouldn’t be caught — now, that’s weird. Or is it? Psychologists are deeply perplexed by human moral behavior, because it often doesn’t seem to make any logical sense. You might think that we should just be grateful for it. But if we could understand these seemingly irrational acts, perhaps we could encourage more of them.

It’s not as though people haven’t been trying to fathom our moral instincts; it is one of the oldest concerns of philosophy and theology. But what distinguishes the project today is the sheer variety of academic disciplines it brings together: not just moral philosophy and psychology, but also biology, economics, mathematics, and computer science. They do not merely contemplate the rationale for moral beliefs, but study how morality operates in the real world, or fails to. David Rand of Yale University epitomizes the breadth of this science, ranging from abstract equations to large-scale societal interventions. “I’m a weird person,” he says, “who has a foot in each world, of model-making and of actual experiments and psychological theory building.”

In 2012 he and two similarly broad-minded Harvard professors, Martin Nowak and Joshua Greene, tackled a question that exercised the likes of Thomas Hobbes and Jean-Jacques Rousseau: Which is our default mode, selfishness or selflessness? Do we all have craven instincts we must restrain by force of will? Or are we basically good, even if we slip up sometimes?

They collected data from 10 experiments, most of them using a standard economics scenario called a public-goods game. Groups of four people, either American college students or American adults participating online, were given some money. They were allowed to place some of it into a pool, which was then multiplied and distributed evenly. A participant could maximize his or her income by contributing nothing and just sharing in the gains, but people usually gave something. Despite the temptation to be selfish, most people showed selflessness.

 

The fuzziness of psychological ideas makes them hard to test. If an experimental result doesn’t fit your theory of human behavior, you can fiddle with the definitions.

 

This finding was old news, but Rand and his colleagues wanted to know how much deliberation went into such acts of generosity. So in two of the experiments, subjects were prodded to think intuitively or deliberately; in two others, half of the subjects were forced to make their decision under time pressure and half were not; and in the rest, subjects could go at their own pace and some naturally made their decisions faster than others. If your morning commute is any evidence, people in a hurry would be extra selfish. But the opposite was true: Those who responded quickly gave more. Conversely, when people took their time to deliberate or were encouraged to contemplate their choice, they gave less.

The researchers worked under the assumption that snap judgments reveal our intuitive impulses. Our intuition, apparently, is to cooperate with others. Selfish behavior comes from thinking too much, not too little. Rand recently verified this finding in a meta-analysis of 51 similar studies from different research groups. “Most people think we are intuitively selfish,” Rand says — based on a survey he conducted—but “our lab experiments show that making people rely more on intuition increases cooperation.”

The cooperative impulse isn’t confined to an artificial experimental setting. In another paper, Rand and Ziv Epstein of Pomona College studied interviews with 51 recipients of the Carnegie Hero Medal, who had demonstrated extreme altruism by risking their lives to save others. Study participants read the interviews and rated the medalists on how much their thinking seemed intuitive versus deliberative. And intuition dominated. “I’m thankful I was able to act and not think about it,” a college student who rescued a 69-year-old woman from a car during a flash flood explained.

So Rand made a strong case that people are intuitive cooperators, but he considered these findings just the start. It’s one thing to put forward an idea and some evidence for it — lots of past researchers have done that. It’s quite another to describe and explain that idea in a rigorous, mathematical fashion. Ironically, Rand figured he could make better sense of humans by stepping away from studying real ones.

The overwhelming majority of psychological theories are verbal: explanations of the ways people act using everyday language, with maybe a few terms of art thrown in. But words can be imprecise. It may be true that “cooperation is intuitive,” but when is it intuitive? And what exactly does “intuitive” mean? The fuzziness of psychological ideas makes them hard to test. If an experimental result doesn’t fit your theory of human behavior, you can fiddle with the definitions and claim you were right all along.

Rand has sought to create quantitative models. “Science is about developing theories,” he says, “not about developing a list of observations. And the reason formal models are so important is that if your goal is theory-building, then it’s essential that you have theories that are really clearly articulated and are falsifiable.”

To do that, he has developed computer simulations of society — The Sims, basically. These models represent collections of individual people described by computer “agents,” algorithms that capture a specific package of traits, such as a tendency to cooperate or not. You can do controlled experiments on these computerized citizens that would be impossible or unethical to do with real people. You can endow them with new personalities to see how they’d fare. You can observe social processes in action, on time scales ranging from seconds to generations, instead of just taking a snapshot of a person or group. You can watch the spread of certain behaviors throughout a population and how they influence other behaviors. Over time, the patterns that emerge can tell you things about large-scale social interaction that a lab experiment with a few real people never could.

 

 

One of the first such models, in the early 1970s, studied housing segregation. It represented a city as a 16-by-13 grid of squares, populated by two types of people: stars and circles. Each star would move to the nearest location in which at least half its neighbors were also stars — it had a slight bias to be among similar others. Circles did the same. Even these mild biases led quickly to stark segregation, with all-star and all-circle regions of the board — a much more extreme partitioning than any one agent sought. The researcher, the economist Thomas Schelling, used his model to help explain racial segregation in American cities. A neighborhood can splinter into homogeneous patches even when individual residents are hardly prejudiced at all. (Of course, in reality, segregation also reflects outright racism and explicit policies of exclusion.) Schelling’s work became a case study of how a group’s collective behavior can diverge from the desires of any one agent.

Such models have also been used to explore cooperation. In an influential paper in 1981, the political scientist Robert Axelrod programmed agents to play a simple game called the Prisoner’s Dilemma. Two players have to decide whether to cooperate with or betray the other, and they receive points based on their choices. The scoring system is set up to mimic an essential dilemma of social life. Together the players perform best if they both cooperate, yet each can maximize his or her own individual outcome, at the expense of the other, by acting selfishly. The game takes its name from a scenario in which the police interrogate two thieves, offering each a reward for ratting out his or her accomplice. The thieves aren’t able to communicate to reach a joint decision; they have to make their decisions independently. Acting rationally, each should rat out the other. But when they both act “rationally,” they actually end up with the most combined jail time.

 

It’s possible we’re born with a tendency to cooperate, but frequent cooperation (with beneficial results) is required to sustain our benevolence.

 

The game gets more interesting — and more analogous to real life — when you play multiple rounds with the same partner. Here, repeated cooperation is best not just for both partners as a unit but also for each individually. You can still occasionally double-cross your partner for extra points, however, as long as it doesn’t trigger later betrayal.

What is the best strategy, then? To find out, Axelrod solicited Prisoner’s Dilemma strategies from mathematicians, biologists, economists, political scientists, computer scientists, and physicists from around the world. Axelrod programmed his computerized agents with these strategies and made them play a round-robin tournament. Some strategies were quite sophisticated, but the winner was a simple one called tit-for-tat.

Tit-for-tat resembles human reciprocity. It starts with cooperation and, after that, does whatever the other player did on the previous round. An agent using the strategy extends an olive branch at first. If its opponent reciprocates, it keeps cooperating. But if its opponent double-crosses it, the tit-for-tat agent rescinds its peace offering until its opponent makes amends.

 

 

By combining the short-term temptation to be selfish with the long-term benefits of collaboration, the Prisoner’s Dilemma is an ideal model for human cooperation, and Rand has built on Axelrod’s work to understand why evolution might have favored intuitive selflessness. 

Rand and his grad student Adam Bear considered a variant of the Prisoner’s Dilemma in which matchups were either one-shot or multiple-round, chosen at random.8 The computerized agents faced a tough choice. In a one-off, they would score more points by betraying their opponent, whereas in repeated play cooperation made more sense. But the uncertainty made it unclear which strategy was best. Rand and Bear then added a twist. An agent could elect to pay some points at the start of an encounter—representing the efforts of deliberation—to suss out what kind of matchup it would face, so that it could tailor its strategy.

The agent had to decide whether the advantage of foreknowledge outweighed its cost. The price of the tip-off varied randomly, and each agent was programmed with a maximum price it would agree to pay; if the price exceeded that amount, the agent did not receive any advance information and instead chose some default behavior, following its “intuition.” In this way, the simulation allowed for different personality types. Some agents intuitively cooperated, others intuitively betrayed. Some occasionally deliberated, others didn’t.

Is deliberation helpful? That’s not immediately obvious. Intuitive thinking is fast but inflexible. Deliberative thinking can achieve better outcomes but takes time and energy. To see which strategy excelled in the long run, Rand and Bear’s model simulated a process of evolution. A large population of agents played the game with one another and either proliferated or died depending on how well they did. This process can model either genetic evolution or cultural evolution, in which the weak players don’t actually die, but merely adopt stronger strategies through imitation.

 

Most of us are genuinely good. And if we’re not, we can be encouraged to be. The math is there.

 

Typically, one strategy swept through the population and replaced the alternatives. This victorious strategy depended on the precise parameters of the game. For example, Rand and Bear varied the probability that matchups would be single- or multiple-round. When most were multi-round, the winning agents defaulted to cooperating but deliberated if the price was right and switched to betrayal if they found they were in a one-shot game. But when most were one-shots, the agents that prevailed were no longer willing to pay to deliberate at all. They simply double-crossed their opponents. In other words, the model produced either wary cooperation or uncompromising betrayal.

This outcome was notable for what was missing. Agents that always cooperated usually died off completely. Likewise, almost no set of game parameters favored agents that defaulted to the double-cross but were sometimes willing to deliberate. Bear and Rand stared at this asymmetry for several weeks, baffled.

Finally, they had a breakthrough. They realized that when your default is to betray, the benefits of deliberating — seeing a chance to cooperate — are uncertain, depending on what your partner does. With each partner questioning the other, and each partner factoring in the partner’s questioning of oneself, the suspicion compounds until there’s zero perceived benefit to deliberating. If your default is to cooperate, however, the benefits of deliberating — occasionally acting selfishly — accrue no matter what your partner does, and therefore deliberation makes more sense.

So, it seems there is a firm evolutionary logic to the human instinct to cooperate but adjust if necessary — to trust but verify. We ordinarily cooperate with other people, because cooperation brings us benefits, and our rational minds let us decipher when we might occasionally gain by acting selfishly instead.

The model also ties up a loose end from Rand’s earlier studies of public-goods games. In that research, time pressure caused some people to cooperate more, but never caused anyone to cooperate less. This asymmetry now makes sense. The only people who would have shown that behavior were those who were willing to deliberate, but defaulted to betrayal; the time pressure would bring out their Machiavellian inclinations. Evidently such people are rare. If someone is deep-down selfish, rational deliberation will only make them more so. And the evolutionary model shows why. Defectors who have qualms are quickly winnowed out by genetic or cultural evolution.

When it comes to getting people to cooperate more, Rand’s work brings good news. Our intuitions are not fixed at birth. We develop social heuristics, or rules of thumb for interpersonal behavior, based on the interactions we have. Change those interactions and you change behavior.

Rand, Nowak, and Greene tested that idea in their 2012 paper. They asked some subjects whether they’d ever played such economics games before. Those with previous experience didn’t become more generous when asked to think intuitively; they’d apparently become accustomed to the anonymous nature of such games and learned a new intuition. Unfortunately, it was a cynical one: They could get away with mooching off others. Similarly, subjects who reported that they couldn’t trust most of the people in their lives also didn’t become more generous when acting on intuition. It’s possible we’re born with a tendency to cooperate, but frequent cooperation (with beneficial results) is required to sustain our benevolence.

Happily, even the Grinch can expand his heart by three sizes, as Rand demonstrates in a recent study. First, he had test subjects play the Prisoner’s Dilemma for about 20 minutes with a variety of opponents. For half of the subjects, the average game lasted eight rounds, meaning cooperation was the best strategy; for half, the average game lasted a single round, which discouraged cooperation. Afterward, everyone played a public-goods game. Those stewed in cooperation gave significantly more money in the second phase of the experiment than did those without it. In less than half an hour, their intuitions had shifted.

How do you encourage cooperation in places where cooperation isn’t the norm? Corporate America comes to mind. “In a lot of situations people are basically rewarded for backstabbing and ladder-climbing,” Rand says. Rand and Bear’s modeling paper, in which intuitive defectors don’t trust each other enough even to consider whether cooperation would pay off, points to an answer. Rand suggests that, at least at first, incentives could come from above, so that the benefits of cooperating don’t depend solely on whether one’s partner cooperates. Companies might offer bonuses and recognition for helpful behavior. Once cooperation becomes a social heuristic, people will begin to cooperate when it benefits them, but also even when it doesn’t. Selflessness will be the new norm.

When selflessness is the norm, encouraging people to make decisions quickly can bring out their better angels. Extensions of this research reveal that we see quick or unthinking acts of generosity as particularly revealing of kindness, and that people may even use this signal strategically. In recent work, Rand and his collaborators have shown that people are faster to make decisions to cooperate when they know someone is watching, as if aware that others will judge them by their alacrity. Among other puzzles, Rand is currently trying to untangle this apparent paradox—the strategic use of intuition.

Rand’s work offers a correction to those misanthropes who peer into the hearts of men and women and see shadows. Most of us are genuinely good. And if we’re not, we can be encouraged to be. The math is there.

If you think seeing life as a set of economics games and cooperation as self-interest in disguise sounds dismal, it is actually not so distanced from what you might call virtue. “When I’m nice to other people, I’m not doing it because of some kind of calculation. I’m doing it because it feels good,” Rand says. “And the reason it feels good, I argue, is that it is actually payoff maximizing in the long run.”

Rand then adds a crucial clarification. “It feels good to be nice — unless the other person is a jerk,” he says. “And then it feels good to be mean.”

Tit for tat indeed.

 

 

 

Original article here

18 Sep 2023
Comments: 0

Voice Is the Next Big Platform, Unless You Have an Accent

 My mother waited two months for her Amazon Echo to arrive. Then, she waited again — leaving it in the box until I came to help her install it. Her forehead crinkled as I download the Alexa app on her phone. Any device that requires vocal instructions makes my mother skeptical. She has bad memories of Siri. “She could not understand me,” my mom told me.

My mother was born in the Philippines, my father in India. Both of them speak English as a third language. In the nearly 50 years they’ve lived in the United States, they’ve spoken English daily — fluently, but with distinct accents and sometimes different phrasings than a native speaker. In their experience, that means Siri, Alexa, or basically any device that uses speech technology will struggle to recognize their commands.

My parents’ experience is hardly exclusive or unknown. (It’s even been chronicled in comedy, with this infamous trapped-in-a-voice-activated elevator sketch.) My sister-in-law told me she gave up on using Siri after it failed to recognize the “ethnic names” of her friends and family. I can vouch for the frustration: The other day, my command of “Text Zahir” morphed into “Text Zara here.”

Right now, it’s not much of a problem — but it’s slated to become more serious, given that we are in the middle of a voice revolution. Voice-based wearables, audio, and video entertainment systems are already here. Due in part to distracted drivers, voice control systems will soon be the norm in vehicles. Google Home and Amazon’s Alexa are radicalizing the idea of a “smart home” across millions of households in the US. That’s why it took so long for my mother’s Echo to arrive — the Echo was among Amazon’s bestsellers this holiday season, with a 900 percent increase from 2016 sales. It was backordered for weeks.

Overall, researchers estimate 24.5 million voice-driven devices will be delivered to Americans’ daily routines this year — evidence that underscores ComScore’s prediction that by 2020, half of all our searches will be performed by voice.

But as technology shifts to respond to our vocal chords, what happens to the huge swath of people who can’t be understood?

To train a machine to recognize speech, you need a lot of audio samples. First, researchers have to collect thousands of voices, speaking on a range of topics. They then manually transcribe the audio clips. This combination of data — audio clips and written transcriptions — allows machines to make associations between sound and words. The phrases that occur most frequently become a pattern for an algorithm to learn how a human speaks.

But an AI can only recognize what it’s been trained to hear. Its flexibility depends on the diversity of the accents to which it’s been introduced. Governments, academics, and smaller startups rely on collections of audio and transcriptions, called speech corpora, to bypass doing labor-intensive transcriptions themselves. The University of Pennsylvania’s Linguistic Data Consortium (LDC) is a powerhouse of these data sets, making them available under licensed agreements for companies and researchers. One of its most famous corpora is Switchboard.

Texas Instruments launched Switchboard in the early 1990s to build up a repository of voice data, which was then distributed by the LDC for machine learning programs. It’s a collection of roughly 2,400 telephone conversations, amassed from 543 people from around the US — a total of about 250 hours. Researchers lured the callers by offering them long-distance calling cards. A participant would dial in and be connected with another study participant. The two strangers would then chat spontaneously about a given topic — say, childcare or sports.

For years linguists have assumed that because the LDC is located in Philadelphia, the conversations skewed towards a Northeastern accent. But when Marsal Gavaldà, the director of machine intelligence at the messaging app Yik Yak, crunched the numbers in Switchboard’s demographic history, he found that the accent pool skewed more midwestern. South and North Midland accents comprised more than 40 percent of the voice data.

Other corpora exist, but Switchboard remains a benchmark for the models used in voice recognition systems. Case in point: Both IBM and Microsoft use Switchboard to test the word error rates for their voice-based systems. “From this set of just over 500 speakers, pretty much all engines have been trained,” says Gavaldà.

But building voice technology on a 26-year-old corpus inevitably lays a foundation for misunderstanding. English is professional currency in the linguistic marketplace, but numerous speakers learn it as a second, third, or fourth language. Gavaldà likens the process to drug trials. “It may have been tried in a hundred patients, [but] for a narrow demographic,” he tells me. “You try to extrapolate that to the general population, the dosage may be incorrect.”

Larger companies, of course, have to think globally to stay competitive — especially because most sales of smartphones happen outside the US Technology companies like Apple, Google, and Amazon have private, in-house methods of collecting this data for the languages and accents they’d like to accommodate. And the more consumers use their products the more their feedback will improve the products, through programs like Voice Traininglanguage on the Alexa app.

But even if larger tech companies are making headway in collecting more specific data, they’re motivated by the market to not share it with anyone — which is why it takes so long for the technology to trickle down. This secrecy also applied to my reporting of this piece. Amazon never replied to my request for comment, a spokesperson for Google directed me to a blog post outlining its deep learning techniques, and an Apple PR representative noted that Siri is now customized for 36 countries and supports 21 languages, language variants, and accents.

Outside the US, companies are aware of the importance of catering to accents. The Chinese search engine company Baidu, for one, says its deep learning approach to speech recognition achieves accuracy in English and Mandarin better than humans, and it’s developing a “deep speech” algorithm that will recognize a range of dialects and accents. “China has a fairly deep awareness of what’s happening in the English-speaking world, but the opposite is not true,” Baidu chief scientist Andrew Ng told The Atlantic.

Yet smaller companies and individuals who can’t invest in collecting data on their own are beholden to cheaper, more readily available databases that may not be as diverse as their target demographics. “[The data’s] not really becoming more diverse, at least from my perspective,” Arlo Faria, a speech researcher at the conference transcription startup Remeeting, tells me. Remeeting, for example, has used a corpus called Fisher that includes a group of non-native English speakers — but Fisher’s accents are largely left up to chance, depending on who happened to participate in the data collection. There are some Spanish and Indian accents, for instance, but very few British accents, Faria recalls.

That’s why, very often, voice recognition technology reacts to accents differently than humans, says Anne Wootton, co-founder and CEO of the Oakland-based audio search platform Pop Up Archive, “Oftentimes the software does a better job with like, Indian accents than deep Southern, like Shenandoah Valley accents,” she says. “I think that’s a reflection of what the training data includes or does not include.”

Rachael Tatman, a PhD candidate at the University of Washington’s Department of Linguistics who focuses on sociolinguistics, noted that the underrepresented groups in these data sets tend to be groups that are marginalized in general. A typical database of American voices, for example, would lack poor, uneducated, rural, non-white, non-native English voices. “The more of those categories you fall into, the worse speech recognition is for you,” she says.

Still, Jeffrey Kofman, the CEO and co-founder of Trint, another automated speech-to-text software based in the UK, is confident accent recognition is something speech science will be able to eventually solve. We video chatted on the Trint platform itself, where Australian English is now available alongside British and North American English as transcription accents. Trint also offers speech-to-text in a dozen European languages, and plans to add South Asian English sometime this year, he said.

Collecting data is expensive and cumbersome, which is why certain key demographics take priority. For Kofman, that’s South Asian accents, “because there are so many people from India, Pakistan, and those countries here in England, in the US and Canada, who speak very clearly but with a distinct accent,” he says. Next, he suspects, he’ll prioritize South African accents.

Obviously, it’s not just technology that discriminates against people with accents. It’s also other people. Mass media and globalization are having a huge effect on how people sound. Speech experts have documented the decline of certain regional American accents since as early as 1960, for example, in favor of a more homogenous accent fit for populations from mixed geographic areas. This effect is exacerbated when humans deal with digital assistants or operators; they tend to use a voice devoid of colloquialisms and natural cadence.

Or, in other words, a voice devoid of an identity and accent.

As voice recognition technology becomes better, using a robotic accent to communicate with a device stands to be challenged — if people feel less of a need to talk to their devices as if they are machines, they can start talking to them as naturally as they would a friend. And while some accent reduction coaches find their clients use voice assistants to practice neutralizing their thick foreign or regional accents, Lisa Wentz, a public speaking coach in San Francisco who works in accent reduction, says that she doesn’t recommend it.

That’s because, she tells me, most of her clients are aiming for other people to understand them. They don’t want to have to repeat themselves or feel like their accents prevent others from hearing them. Using devices that aren’t ready for different voices, then, only stands to make this feeling echo.

My mother and I set up her Alexa app together. She wasn’t very excited about it. I could already imagine her distrust and fear of a car purported to drive by the command of her voice. My mother would never ride in it; the risk of crashing would be too real. Still, she tried out a couple of questions on the Echo.

“Alexa, play ‘Que sera sera,’” my mother said.

“I can’t find the song ‘Kiss your ass era.’”

My mom laughed, less out of frustration and more out of amusement. She tried again, this time speaking slower, as if she were talking to a child. “Alexa, play ‘Que sera sera.’” She sang out the syllables of sera in a slight melody, so that the device could clearly hear “se-rah.”

Alexa understood, and found what my mom was looking for. “Here’s a sample of ‘Que sera sera,’ by Doris Day,” she said, pronouncing the sera a bit harsher — “se-raw.”

The 1964 hit started to play, and my mother smiled at the pleasure of recognition.

 

 

Original article here

14 Sep 2023
Comments: 0

Why You Should Cultivate a Fluid Sense of Self

If you want to learn something about change there is no better place to look than evolution. Nothing represents a continuous and unrelenting cycle of order, disorder, and reorder on a grander scale. For long periods of time, Earth is relatively stable. Sweeping changes—warming, cooling, or an asteroid falling from space, for example—occur. These inflection points are followed by periods of disruption and chaos. Eventually, Earth, and everything on it, regains stability, but that stability is somewhere new.

During this cycle, some species get selected out. Others survive and thrive. Species in the latter group tend to have high degrees of what evolutionary biologists call “complexity.” Complexity is comprised of two elements: differentiation and integration. Differentiation is the degree to which a species is composed of parts that are distinct in structure or function from one another. Integration is the degree to which those distinct parts communicate and enhance each other’s goals to create a cohesive whole.

Consider Homo sapiens (you and me), by far the most abundant and widespread species of primate. we have large frames, four limbs, opposable thumbs, body temperature that is somewhat resistant to external conditions, good vision and hearing, digestive tracts that can accommodate a variety of nutrients, and the capacity for language and understanding. In other words, we are a highly differentiated species. But we also have enormous brains and advanced nervous systems that integrate all of these parts into a cohesive whole. The combination of these qualities—widespread differentiation and strong integration—makes us a decidedly complex species. Our complexity is how we got here today and why, hopefully, we’ll stick around for at least a bit longer.

Though change at the individual level, the primary concern of my new book Master of Change, is different than change on an evolutionary scale, there is still much we can learn from evolution’s foundational principles, lessons that apply to the horizons of our own lives. If we want to survive and thrive during ongoing cycles of change and disorder, then we, too, can benefit from developing our own versions of complexity.

As a matter of fact, there is a psychological construct called self-complexity. Essentially, it says that the key to a strong and enduring identity—one that is equal parts rugged and flexible, that can navigate the inevitable changes we all face—is to diversify your sense of self.

The more you define yourself by any one activity, the more fragile you become. If that activity doesn’t go well or something changes unexpectedly, you lose a sense of who you are. But with self-complexity, you have develop multiple components to your identity.

We all can wear many hats: examples include writer, spouse, artist, parent, employee, neighbor, entrepreneur, baker, and creative, to name just a few. Take an inventory of your own identities. Are there any upon which you are over-reliant for meaning and self-worth? What would it look like to diversify your sense of self? Even if you desire to go “all in” on a certain endeavor, you’ve got to ensure that you don’t leave others completely behind.

I’ve come to use the metaphor of a house for identity. If your house only has one room in it, and that rooms floods, you are going to be very disoriented. But if your house has multiple rooms, you can seek refuge in the others while you weather the storm. It’s okay to put spend a lot of time in one room—so long as you have other rooms available when the one you are currently pouring yourself into changes.

For example: there are times when I lean heavily into each of my main identities—father, husband, writer, coach, friend, athlete, and neighbor. I’ve learned that keeping all of these identities strong ensures that when things don’t go well in one area of my life I can rely on the others to pick me up, which helps me to stay grounded and navigate whatever challenge I am facing.

What you want to do is challenge yourself to integrate the various elements of your identity into a cohesive whole. This allows you to emphasize and de-emphasize certain parts of your identity at different periods of time. The result is a fluid sense of self.

Unlike other types of matter, fluid contains both mass and volume but not shape. This allows it to flow over and around obstacles, changing form while retaining substance, neither getting stuck nor fracturing when unforeseen impediments manifest on its path. Cultivating a fluid sense of self allows you to do the same. By developing and nurturing multiple parts of your identity, you can more easily navigate change.

A large body of research shows that when there is too great a fusion between one’s identity and their pursuit, then anxiety, depression, and burnout frequently result. This is especially true for athlete’s during periods of change and transition, when one’s dominant—and all to often, sole— sense of identity feels at risk. Yet while it may be heightened for athletes, it’s a pattern that holds true in all lines of work and all walks of life: if you want to be excellent and experience something fully, then you’ve got to go all in, but only to a point. If your identity becomes too enmeshed in any one concept or endeavor—be it your age, how you look in the mirror, a relationship, or your career—then you are likely to face significant distress when things change, which, for better or worse, they always do.

None of the above is permission to be laissez-faire or go through the motions. Caring deeply about the people, activities, and projects you love is key to a rich and meaningful existence. The problem is not caring deeply; it is when your identity becomes too rigidly attached to any single object or endeavor.

 

 

 

Original article here

 

 

06 Sep 2023
Comments: 0

So…How Do Adults Make New Friends?

In approximately one month and 10 days, I’ll be on my way to making one of the larger decisions of my adult life (so far, anyway); I’m moving to Austin, Texas, approximately 2,000 miles and one hell of a road trip away from my family and almost my entire friend group back in New York. While I have many questions about my move—chief among them, “How much should a mattress cost?” and “Will everyone hate me for being a Brooklyn transplant?”—nothing has loomed larger in my mind than the question of friendship, or, more specifically, how a full-grown adult goes about making new friends with no partner or kids to act as built-in buffers.

Of course, a big move is hardly the only circumstance in which an otherwise reasonably socialized adult might find herself craving new friendships. The COVID-19 pandemic shrunk our social circles considerably, with many of us spending the last year-plus in the company of family and only our absolute closest BFFs. As the world slowly reopens, it stands to reason that we might want to seek out new connections—and feel somewhat unsure about where to start (especially as COVID-19 rates continue to climb in many cities).

Anxiety about friend-making isn’t so uncommon, according to clinical psychologist and friendship researcher Dr. Miriam Kirmayer, although some of these nerves may be linked to misconceptions about how meaningful friendships actually come about. “There does seem to be, for many people, this belief that friendships should just happen—whether we’re in a new city or a new phase of life—and that our people, so to speak, will magically show up. As beautiful as that is, that isn’t the reality for most people,” explains Kirmayer. “My best advice is to be very intentional with how we approach making friends; seek out opportunities, experiences and activities where we are likely to meet new people with whom we share something in common. My second piece of advice is to try and choose wisely, or, in other words, choose opportunities where we will have more frequent interactions, because we know that friendships often require that frequency of interaction in order to develop.”

Conventional wisdom has it that you should pick popular yet slightly off-the-beaten path activities, like a running group or a knitting club, to meet new people. But what about those of us for whom a good Friday night hinges on the strength of a gummy edible and the availability of a new episode of The Bold Type on Hulu? I’m not trying to paint myself as a total couch potato, but…let’s just say my social style is definitely on the “chill” side, not so much the “go hiking and meet new people on top of a mountain at 7:00 a.m.” side. My quest for new friendships almost feels like dating, something I’m meh at yet very enthusiastic about, except that I don’t have a great frame of reference for what “success” would look like. Does friendship success equal a hangout invite? A standing Saturday-night bar crawl? Godparent-ing each other’s children? How will I know when I’ve cracked it, socially speaking?

For some people, social success—however they define it—can spring from a source as prosaic as social media. Mijal Tenenbaum, 27, moved to Los Angeles with only a few loose acquaintances at her disposal. She DM-ed one of them on Twitter and invited them out to brunch, and while that plan never came to be, Tenenbaum’s new friend did invite her to Disneyland, of all places. Today, the two are best friends, and Tenenbaum’s advice to people in similar situations (whether they’re in a new city or just feeling socially stagnant) would be: “If you get good vibes from an acquaintance or Twitter mutual, reach out and give them a chance! Even if you’re a little insecure and you don’t know them well, just go for it.”

For Hannah Smith, 27, friendship began at home—quite literally—when she moved to San Francisco in 2019 without knowing anyone. Smith sublet three different rooms through Craigslist before she finally signed a month-to-month lease in the perfect place (which she also found through Craigslist), eventually turning a roommate from her final apartment into one of her best friends. “Low-commitment living situations can be a great way to get to know people in a new place,” says Smith, although she adds that this strategy might be somewhat complicated by the ongoing effects of COVID-19.

One popular method for friend-making endorsed by Kirmayer is volunteering, which is exactly how Courtney Gustafson, 31, ended up meeting her two best friends. “During the pandemic, I happened upon a colony of feral cats, started caring for them, made them an Instagram, and then two different people reached out to offer help with the cats,” says Gustafson. “The three of us turned out to be around the same age and have a lot in common, and now we are a cat rescue/best friend team of 3!”

Ultimately, there’s no perfect way to predict the success of a new friendship. After all, you could join a volunteer effort or a cooking club and meet absolutely nobody you bond with, or you could meet your all-time, Elena Ferrante–novel–level soulmate at a random party you almost skipped. Still, as more people get vaccinated and life ever-so-creepingly returns to “normal,” it’s worth thinking about whether the friendships in your life are giving you what you need and want. If they’re not, maybe you should DM that cool-seeming Twitter person, sublet with a friendly acquaintance, or bond over a mutual love of feral cats—because after all, without true and lasting friendships, who would have the courage tell us when we were being annoying on the internet?

 

 

Original article here

 

 

 

02 Sep 2023
Comments: 0

This Is Where Your Childhood Memories Went

We called them fairy rocks. They were just colorful specks of gravel—the kind you might buy for a fish tank—mixed into my preschool’s playground sand pit. But my classmates and I endowed them with magical properties, hunted them like treasure, and carefully sorted them into piles of sapphire, emerald, and ruby. Sifting the sand for those mystical gems is one of my earliest memories. I was no older than 3 at the time. My memory of kindergarten has likewise been reduced to isolated moments: tracing letters on tan paper with pink dashed lines; watching a movie about ocean creatures; my teacher slicing up a giant roll of parchment so we could all finger-paint self-portraits.

When I try to recall my life before my fifth birthday, I can summon only these glimmers—these match strikes in the dark. Yet I know I must have thought and felt and learned so much. Where did all those years go?

Psychologists have named this dramatic forgetting “childhood amnesia.” On average, people’s memories stretch no farther than age three and a half. Everything before then is a dark abyss. “This is a phenomenon of longstanding focus,” says Patricia Bauer of Emory University, a leading expert on memory development. “It demands our attention because it’s a paradox: Very young children show evidence of memory for events in their lives, yet as adults we have relatively few of these memories.”

In the last few years, scientists have finally started to unravel precisely what is happening in the brain around the time that we forsake recollection of our earliest years. “What we are adding to the story now is the biological basis,” says Paul Frankland, a neuroscientist at the Hospital for Sick Children in Toronto. This new science suggests that as a necessary part of the passage into adulthood, the brain must let go of much of our childhood.

Sigmund Freud gave childhood amnesia its name in the early 1900s. He argued that adults forgot their earliest years of life in the process of repressing disturbing memories of sexual awakening. While a handful of psychologists saw merit in this claim, the most commonly accepted explanation for childhood amnesia was that children simply couldn’t form stable memories until age 7—even though there was little evidence to support this idea. For nearly 100 years, psychologists assumed that memories of infancy did not endure because they were never durable in the first place.

The late 1980s marked the beginning of a reformation in child psychology. Bauer and other psychologists began to test infant memory by performing a series of actions—such as building a simple toy gong and striking it—and then waiting to see if a child could imitate the actions in the right order, after a delay ranging from minutes to months.

 

“Mice performed worse on certain kinds of memory tests after living in a cage with a running wheel.

 

This work laid bare the contradiction at the heart of childhood amnesia: Infants can create and access memories in their first few years of life, yet most of these memories eventually vanish at a rate far beyond the typical forgetting of the past we experience as adults.

Maybe, some researchers thought, enduring memories require language or a sense of self, both of which we lack as infants. But although verbal communication and self-awareness undoubtedly strengthen human memories, their absence could not be the whole explanation for childhood amnesia. After all, certain animals that have large and complex brains relative to their body size—such as mice and rats—but do not have language or, presumably, our level of self-awareness, also lose the memories they make in infancy.

Perhaps, then, researchers reasoned, the paradox had a more fundamental physical basis that was common to people and other big-brained mammals. The question was, what?

Between birth and our early teens, the brain is still laying down some of its fundamental circuitry and thickening its electrical pathways with fatty tissue to make them more conductive. In a massive surge of growth, the brain sprouts innumerable new bridges between neurons. In fact, we have far more links between brain cells in our earliest years than we end up with in adulthood; most are pruned away. All that excess brain mass is the wet clay from which our genes and experiences sculpt a brain to suit its particular environment. Without such limber brains, young children would never be able to learn as much as quickly as they do.

As Bauer and others discovered, this adaptability comes with a price. While the brain undergoes this prolonged development outside the womb, the large and complex network of disparate brain regions that collectively create and maintain our memories is still under construction, Bauer explains, and not as capable of forming memories as it will be in adulthood. As a consequence, the long-term memories formed in our first three years of life are the least stable memories we ever make and highly prone to disintegrating as we age.

In early 2018, Frankland and his colleagues published a study indicating another way the brain relinquishes our childhood memories: not only do they degrade, but they also become concealed. A few years back, Frankland and his wife Sheena Josselyn—also a neuroscientist at the Hospital for Sick Children—started to notice that the mice they studied performed worse on certain kinds of memory tests after living in a cage with a running wheel.

 

“Our earliest memories are often insoluble blends of genuine recollections, narratives we sponged up from others, and imaginary scenes dreamt up by the subconscious.

 

As the couple knew, exercise on a running wheel promotes neurogenesis—the growth of whole new neurons—in the seahorse-shaped hippocampus, a brain region that is essential for memory. But while neurogenesis in the adult hippocampus likely contributes to the ability to learn and remember, Karl Deisseroth of Stanford University and others had suggested that it might also necessitate a certain amount of forgetting. Just as a forest has room for only so many trees, the hippocampus can hold only so many neurons. New brain cells might crowd the territory of other neurons or even replace them altogether, which could in turn break or reconfigure the small circuits that likely store individual memories. Perhaps, then, the especially high rate of neurogenesis in infancy was partly responsible for childhood amnesia.

To put this notion to the test, Frankland and Josselyn transferred infant and adult mice from the plastic shoebox-sized cages they had known all their lives to larger metal cages they had never seen before. In these new containers, they zapped the rodents’ feet with mild electric shocks. The mice quickly learned to associate the metal cages with the shocks, stiffening with fear whenever they were returned to those enclosures.

While baby mice began to forget about this connection after a single day—relaxing when they found themselves in the shock cages—adult mice never forgot about the danger. But when adults ran on a hamster wheel after the shocks—thereby stimulating neurogenesis—they started to mirror infants in their forgetfulness. Prozac, which also encourages neural growth, had the same effect. Conversely, when the researchers hindered neurogenesis in infant mice with drugs or genetic engineering, the young animals formed much more stable memories.

To get a really close look at how neurogenesis might change memory, Frankland and Josselyn used a virus to insert a gene encoding a green fluorescent protein into the DNA of the mice’s newly sprouted brain cells. The glowing dye revealed that the new cells were not replacing old ones; rather, they were joining existing circuitry. That suggests that, technically, the many little circuits of neurons that store our earliest memories are not wiped out by neurogenesis. Instead, they are thoroughly restructured, which probably explains why the original memories become so difficult to recall. “We think it’s an accessibility issue,” Frankland says, “but it’s sort of a semantic issue too. If a memory becomes impossible to access, then it is effectively erased.”

This restructuring of memory circuits means that, while some of our childhood memories are truly gone, others persist in a scrambled, refracted way. Studies have shown that people can retrieve at least some childhood memories by responding to specific prompts—dredging up the earliest recollection associated with the word “milk,” for example—or by imagining a house, school, or specific location tied to a certain age and allowing the relevant memories to bubble up on their own.

But even if we manage to untangle a few distinct memories that survive the tumultuous cycles of growth and decay in the infant brain, we can never fully trust them; some of them might be partly or entirely fabricated. Through her pioneering research, Elizabeth Loftus of the University of California, Irvine has demonstrated that our earliest memories in particular are often insoluble blends of genuine recollections, narratives we sponged up from others, and imaginary scenes dreamt up by the subconscious.

In one set of groundbreaking experiments conducted in 1995, Loftus and her colleagues presented volunteers with short stories about their childhood provided by relatives. Unbeknownst to the study participants, one of these stories—about being lost in a mall at age 5—was mostly fiction. Yet a quarter of the volunteers said they had a memory of the experience. And even when they were told that one of the stories they had read was invented, some participants failed to realize it was the lost-in-a-mall story.

When I was a toddler, I got lost in Disneyland. Here is what I recall: It was December and I was watching a toy train loop through a Christmas village. When I turned around, my parents had disappeared. Dread dripped down my body like cold molasses. I began blubbering and wandering the park, searching for them. A stranger approached me and took me to a giant building filled with TV screens playing feeds from security cameras all over the park. Did I see my parents on any of the screens? I did not. We went back to the train where we found my parents. I ran into their arms, overcome with joy and relief.

Recently, for the first time in quite a while, I asked my mom exactly what she remembers about that day in Disneyland. She says it was spring or summer and that she and my family last saw me beside the remote control Jungle Cruise boats, not the railroad near the entrance of the park. As soon as they realized I was missing, they went straight to the Lost and Found Center. A park official had indeed discovered me and brought me to the center, where I had been placated with ice cream.

It was unsettling to have what I thought was a pretty accurate memory so thoroughly contradicted, so I asked my mom to search our family photo albums for some hard evidence. All she could find were pictures from an earlier trip. We will probably never have any tangible proof of what happened. We are left with something far more elusive: those tiny embers of the past, embedded in our mind, twinkling like fool’s gold.

 

 

 

 

Original article here

26 Aug 2023
Comments: 0

How to Thrive When Everything Feels Terrible

We’re surrounded by negativity everywhere we turn. The news we read, social media we peruse, and conversations we have and overhear. We absorb stress from our family, friends, and coworkers. And, it’s taking a toll.

The Mighty, a community platform (founded by Mike) that provides health information and brings people together around specific health issues, has surveyed more than 70,000 readers and community members since March around their awareness, perceptions, and experience with the coronavirus crisis. In September, respondents reported their top three emotions were frustration, worry, and anger. The number of respondents choosing anger as one of their top emotions has more than doubled since March — rising from 20% then to 45% in September.

Negativity can have toxic effects. In fact, Christine’s research has shown over and over that we falter when exposed to negativity or rudeness. Witnessing rudeness interferes with our working memory and decreases our performance. Mere exposure to rude words reduces our ability to process and recall information. We tend to shut down, stop communicating, and cease being helpful to others. Dysfunctional and aggressive thoughts (and sometimes actions) skyrocket.

Fortunately, Christine’s research also shows that there is a productive way to counter those effects. It’s called thriving — the psychological state in which people experience a sense of both vitality and learning. Thriving individuals are growing, developing, and energized rather than feeling stagnated or depleted.

In studies conducted across a range of industries, Christine has found that people who experience a state of thriving are healthier, more resilient, and more able to focus on their work. When people feel even an inkling of thriving, it tends to buffer them from distractions, stress, and negativity. In a study of six organizations across six different industries, employees characterized as highly thriving demonstrated 1.2 times less burnout compared with their peers. They were also 52% more confident in themselves and their ability to take control of a situation. They were far less likely to have negativity drag them into distraction or self-doubt.

So how do you increase your thriving especially when it feels like you’re drowning in negativity? Our research points to some tactics.

Avoid negativity. Pay attention to what you’re ingesting: what information you chose to read, the media you consume, the music you listen to, the people you choose to spend time with, and the people you look up to. Negativity seeps into our pores through these sources. So make simple choices away from negativity and toward positivity.

Watch what you say out loud. Negative language is particularly insidious and potent. Be mindful of what you’re thinking and saying. Yes, those around you influence you and your mood, but we have more control over our thoughts and feelings than anyone else. And what we say out loud also carries significant weight. According to Trevor Moawad, a mental conditioning coach who works primarily with elite athletes, it’s ten times more damaging to our sense of thriving if we verbalize a thought than if we just think it.

So, think twice about how you’re framing and speaking about a situation. Instead of saying, “This is the worst I’ve ever seen,” or “It’s catastrophic,” (or “devastating” or “terrible”), tweak your language to be more neutral. You might say, “This situation is challenging,” which recognizes the opportunity for growth or learning. You can — and should — acknowledge the truth, while minimizing its power to drag you down.

Adopt a neutral mindset. Negative thoughts and worries take us off track. We’re more likely to struggle on basic tasks. Long term, repetitive negative thinking is associated with cognitive decline and Alzheimer’s disease. It also hurts others because they are then exposed to our negativity. Of course, it’s all too easy to dwell on toxic people or situations. We might play the blame game, ruminate, or overanalyze the situation. It’s far better to adopt a proactive mindset, focusing on what we can control and what we should do next.

Moawad suggests using neutral thinking — a nonjudgmental, nonreactive way of assessing problems and analyzing crises. This includes staying in the moment, reacting to each moment as it unfolds, and keeping your focus on how you can influence your next action. Don’t get sucked into analyzing past failures or hijacked by future fears or thoughts. Take one play at a time.

Practice gratitude consistently. There is a lot to be said about the benefits of gratitude. Gratitude reduces our stress, makes us happier, and helps us reach our goals. Routinely feeling grateful increases the social support we receive, which further reduces stress and its negative effects. It’s especially powerful when practiced alongside neutral thinking. Seattle Seahawk quarterback and Super Bowl winner Russell Wilson has talked about how he has used this combination to navigate the death of his father, a gut-wrenching Super Bowl loss, the impact of Covid on his life and profession, and other challenges. Wilson says that with an “attitude of gratitude” you can be thankful for a challenge, and get through it.

His advice spurred our family to think about some of the positives that the pandemic brought. For example, like many families, we started a weekly Zoom meeting, uniting family members spread across the globe that hadn’t been in regular touch previously.

Manage your energy. You can also increase your resilience in the face of negativity and encourage thriving by exercising, eating well, and getting enough sleep — all things we know we’re supposed to do but we often fail to when we’re bombarded with negativity. When we exercise, our muscles pump “hope molecules” into our bodily systems that are good for our mental and physical health. You can amplify these effects by exercising outside, with others, or to music.

Healthy eating also helps you stave off negativity. How well do you respond to frustration when you’re hungry? We lack the self-control required to respond patiently. Sleep is also important. A lack of it impairs self-regulation and self-control, which can produce more negativity. Research has linked poor sleep to frustration, impatience, hostility, anxiety, low levels of joviality, lower levels of trust, workplace deviance, and unethical behavior. Sleep deprivation also hurts the relationship between leaders and their followers, and diminishes how much help people provide to others.

Seek out positive relationships — inside and outside of work.  Christine’s research found that de-energizing relationships — in which one person possesses an enduring, recurring set of negative judgments, feelings, and intentions toward another person — have four to seven times greater impact on an employee’s sense of thriving than energizing, positive relationships. To offset these effects, surround yourself and spend more time with energizers — the people in your life who make you smile and laugh, and lift your spirits.

You may not be able to stop the flow of negativity in your life, especially right now, but you can resist its toxic effects by making smart choices about who and what you surround yourself with, the mindset you adapt, and the information you consume. Not only will you be better off because of these choices — those around you will too.

 

 

Original article here

23 Aug 2023
Comments: 0

You’re Never Too Old to Regain Lost Muscle. And You Can Do It at Home.  

Pandemic life had a way of revealing our weaknesses. For those of us of a certain age, I mean that literally. If you are feeling like certain household activities — toting groceries, hoisting children, moving furniture, carrying laundry — are more difficult than they were in the past, you aren’t alone. And you aren’t imagining it.

This isn’t a new phenomenon; it just wasn’t until the 1800s that many of us lived long enough to experience this decline. For me, it started a few years ago, when I noticed that lifting an air conditioner, carrying a child up to bed or bringing in a load of firewood seemed harder than they once did. I summoned excuses for each difficulty (“Darned kid gained 20 pounds today!”), but now, at age 54, I’m ready to concede: I simply can’t lift as much as I once could.

Starting sometime in our 30s (the data aren’t precise), we lose up to 8 percent of our muscle mass per decade, a decline called sarcopenia, along with up to 30 percent of our strength and power. This leaves us weaker, less mobile and — especially after we cross age 50 — more vulnerable to injury from falls and similar accidents.

But it doesn’t have to be that way. Men and women can regain some of that lost muscle mass and, importantly, stay strong enough to enjoy youthful activities well into their winter years, experts say. The key is strength training.

“I have people who start in their 60s, 70s and even 80s,” says Jordan Metzl, a sports medicine physician at Hospital for Special Surgery in New York. “Building and maintaining strength is one of the most important things you can do at any stage of life, and it’s extremely important after age 50.”

Why? Strength training improves your “economy of movement,” Metzl says, meaning the amount of energy you expend to complete a task, and it “offloads joints, so you can do the same amount of work with less pain and lower risk of injury. You’re essentially getting more juice out of your muscles.” Metzl is personally vested in this quest: He has run 35 marathons and competed in Iron Man triathlons, and he says he aspires, even as he approaches his mid-50s, “to keep going forever.”

But what if your marathons are measured in Netflix episodes or you just need to jump-start an engine that’s been accumulating rust for years? Again, you’re not alone, says Dixie Stanforth, associate professor of instruction in the University of Texas at Austin’s Department of Kinesiology and Health Education.

“Most people are professional sitters,” she says. As a result, many muscles in the front of our bodies — namely our hip flexors and chest muscles — become short and tight. That shuts off signals to their corresponding anterior muscles — the glutes and upper back — to keep working, so those areas become weak and inhibited. All the sitting we’re doing at home could be making things worse.

The first thing to do if you’re starting or resuming strength training, says Stanforth, a 60-year-old personal trainer and “avid athlete,” is to target major muscle groups, especially the glutes and back.

“Glutes are tremendously important, because they activate the ‘rear chain’ of the body and can produce a lot of power for movement,” Stanforth says. Rear chain muscles are critical for posture, balance, running, jumping and — yes — lifting heavy things. To strengthen those muscles, Stanforth says squats, rows and leg presses are all good, because they engage the core and require movement in multiple joints.

She advises strengthening front-facing muscles (chest, abs, biceps and quadriceps, for example), but also devoting extra time to stretching them because of how tight they become in our daily, deskbound lives. “Many people might consider a 1:2 ratio of exercises” — that is, double your strengthening time for rear-chain muscles — “but all of the major muscles [including biceps, calves and triceps] should be trained.”

And, before you even ask: Just about every exercise you can do in a gym you can do at home — albeit with some modification. Homebound strength exercises that don’t require equipment include squats (with or without weight); chair dips; pushups; pullups; planks; lunges; burpees; and step-ups. If you have canned goods or empty milk or drink containers (a gallon of water weighs approximately eight pounds), you can use them for strength training.

Both Stanforth and Metzl recommend building muscle by performing a high number of reps of a lighter weight — i.e., one you can lift at least 15 times before failure, the fitness term for can’t . . .  do . . .  one . . .  more.

Data show that straining to perform fewer repetitions of much heavier weights greatly increases the risk of injuries to cartilage, tendons and ligaments, without offering much benefit over lighter weights. A 2017 meta-analysis of 21 studies, published in the Journal of Strength and Conditioning Research, found that people who engaged in strength training regimens for at least six weeks, performing exercises to failure, showed similar muscle cell growth regardless of whether they did high reps of low weights or fewer reps of heavy weights.

“Fatigue is fatigue no matter how you get there,” Stanforth says. “I recommend [sets of] a significant number of reps — 15, 20, 30 — and you’ll see all the gains that you would with heavier weights.” Encouragingly, studies also show that you’ll reap most of the gains from just one set of each exercise, so you can safely skip the oft-recommended second and third sets.

As for how often to train, the weekly guidelines for generally healthy people age 50 and older aren’t any different from those for other demographics: Strength train two to three days, engage in aerobic activity at least five days at moderate intensity, or at least three days a week at high intensity, and perform a stretching routine at least two days a week.

Metzl takes this up a notch by incorporating high-intensity interval training, or HIIT — short, punishing bursts of activity usually lasting 30 to 90 seconds with recovery breaks in between. “I do HIIT with people in their 70s and 80s,” he tells me. “We all change over the decades, but I don’t want people to be afraid of intensity.”

In fact, Metzl says, people should be increasing intensity as we age to “better stimulate all the cells in our bodies.” He cited a 2017 study published in the journal Cell Metabolism that showed that high-intensity training significantly improved how the body converts macronutrients into energy. But, he said: “For some people, a sprint is intense. For others, it’s walking up the stairs.”

For those who can perform them, Metzl suggests burpees, jump squats and lunges, which he says deliver full-body functional training. “Burpees utilize every muscle in your body. They’re high intensity and tremendously effective.” And, Metzl says, you’ll still reap a benefit from burpees if you opt to step — not jump — your feet back when dropping into the push-up position at the nadir of the exercise.

Stuart Phillips, director of the Physical Activity Center of Excellence at McMaster University in Hamilton, Ontario, says that older people who regularly strength train can expect to see significant gains in strength and power, but not necessarily muscle mass. Still, the benefits of a training regimen — and the extended period of physical independence that comes with them — should be enough to motivate us all, he adds. “It’s about quality of life, and that’s not a function of muscle mass, but of strength/power.”

And, as Stanforth says, “exercise is better than any drug” in sustaining bone and countering the increased risk of osteoporosis that comes with age. “It helps tremendously. But we do have to be smarter about how we apply the dose as we age.” So, do it right, and we’ll feel stronger, and smarter for it, every day — and have one less thing to worry about.

 

 

Original article here

19 Aug 2023
Comments: 0

What Socrates Can Teach Us About AI

If Socrates was the wisest person in Ancient Greece, then large language models must be the most foolish systems in the modern world.

In his Apology, Plato tells the story of how Socrates’s friend Chaerephon goes to visit the oracle at Delphi. Chaerephon asks the oracle whether there is anyone wiser than Socrates. The priestess responds that there isn’t: Socrates is the wisest of them all.

At first, Socrates seems puzzled. How could he be the wisest, when there were so many other people who were well known for their knowledge and wisdom, and yet Socrates claims that he lacks both?

He makes it his mission to solve the mystery. He goes around interrogating a series of politicians, poets, and artisans (as philosophers do). And what does he find? Socrates’ investigation reveals that those who claim to have knowledge either do not really know what they think they know, or else know far less than they proclaim to know.

Socrates is the wisest, then, because he is aware of the limits of his own knowledge. He doesn’t think he knows more than he does, and he doesn’t claim to know more than he does.

How does that compare with large language models like ChatGPT4?

In contrast to Socrates, large language models don’t know what they don’t know. These systems are not built to be truth-tracking. They are not based on empirical evidence or logic. They make statistical guesses that are very often wrong.

Large language models don’t inform users that they are making statistical guesses. They present incorrect guesses with the same confidence as they present facts. Whatever you ask, they will come up with a convincing response, and it’s never “I don’t know,” even though it should be. If you ask ChatGPT about current events, it will remind you that it only has access to information up to September 2021 and it can’t browse the internet. For almost any other kind of question, it will venture a response that will often mix facts with confabulations.

The philosopher Harry Frankfurt famously argued that bullshit is speech that is typically persuasive but is detached from a concern with the truth. Large language models are the ultimate bullshitters because they are designed to be plausible (and therefore convincing) with no regard for the truth. Bullshit doesn’t need to be false. Sometimes bullshitters describe things as they are, but if they are not aiming for the truth, what they say is still bullshit.

And bullshit is dangerous, warned Frankfurt. Bullshit is a greater threat to the truth than lies. The person who lies thinks she knows what the truth is, and is therefore concerned with the truth. She can be challenged and held accountable; her agenda can be inferred. The truth-teller and the liar play on opposite sides of the same game, as Frankfurt puts it. The bullshitter pays no attention to the game. Truth doesn’t even get confronted; it gets ignored; it becomes irrelevant.

Bullshit is more dangerous the more persuasive it is, and large language models are persuasive by design on two counts. First, they have analysed enormous amounts of text, which allows them to make a statistical guess as to what is a likely appropriate response to the prompt given. In other words, it mimics the patterns that it has picked up in the texts it has gone through. Second, these systems are refined through a process of reinforcement learning from human feedback (RLHF). The reward model has been trained directly from human feedback. Humans taught it what kinds of responses they prefer. Through numerous iterations, the system learns how to satisfy human beings’ preferences, thereby becoming more and more persuasive.

As the proliferation of fake news has taught us, human beings don’t always prefer truth. Falsity is often much more attractive than bland truths. We like good, exciting stories much more than we like truth. Large language models are analogous to a nightmare student, professor, or journalist; those who, instead of acknowledging the limits of their knowledge, try to wing it by bullshitting you.

Plato’s Apology suggests that we should build AI to be more like Socrates and less like bullshitters. We shouldn’t expect tech companies to design ethically out of their own good will. Silicon Valley is well known for its bullshitting abilities, and companies can even feel compelled to bullshit to stay competitive in that environment. That companies working in a corporate bullshitting environment create bullshitting products should hardly be surprising. One of the things that the past two decades have taught us is that tech needs as much regulation as any other industry, and no industry can regulate itself. We regulate food, drugs, telecommunications, finance, transport; why wouldn’t tech be next?

Plato leaves us with a final warning. One of the lessons of his work is to beware the flaws of democracy. Athenian democracy killed Socrates. It condemned its most committed citizen, its most valuable teacher, while it allowed sophists—the bullshitters of that time—to thrive. Our democracies seem likewise vulnerable to bullshitters. In the recent past, we have made them prime ministers and presidents. And now we are fueling the power of large language models, considering using them in all walks of life—even in contexts like journalism, politics, and medicine, in which truth is vital to the health of our institutions. Is that wise?

 

 

Original article here

15 Aug 2023
Comments: 0

3 Simple Habits That Can Protect Your Brain from Cognitive Decline

You might think that the impact of aging on the brain is something you can’t do much about. After all, isn’t it an inevitability?

To an extent, as we may not be able to rewind the clock and change our levels of higher education or intelligence (both factors that delay the onset of symptoms of aging). But adopting specific lifestyle behaviors–whether you’re in your thirties or late forties–can have a tangible effect on how well you age. Even in your fifties and beyond, activities like learning a new language or musical instrument, taking part in aerobic exercise, and developing meaningful social relationships can do wonders for your brain. There’s no question that when we compromise on looking after ourselves, our aging minds pick up the tab.

THE AGING PROCESS AND COGNITIVE DECLINE

Over time, there is a build-up of toxins such as tau proteins and beta-amyloid plaques in the brain that correlate to the aging process and associated cognitive decline. Although this is a natural part of growing older, many factors can exacerbate it. Stress, neurotoxins such as alcohol and lack of (quality and quantity) sleep can speed up the process.

Neuroplasticity–the function that allows the brain to change and develop in our lifetime–has three mechanisms: synaptic connection, myelination, and neurogenesis. The key to resilient aging is improving neurogenesis, the birth of new neurons. Neurogenesis happens far more in babies and children than adults. A 2018 study by researchers at Columbia University shows that in adults, this type of neuroplastic activity occurs in the hippocampus, the part of the brain that lays down memories. This makes sense as we respond to and store new experiences every day, and cement them during sleep. The more we can experience new things, activities, people, places, and emotions, the more likely we are to encourage neurogenesis.

With all this in mind, we can come up with a three-point plan to encourage “resilient aging” by activating neurogenesis in the brain:

  • GET YOUR HEART RATE UP

Aerobic exercise such as running or brisk walking has a potentially massive impact on neurogenesis. A 2016 rat study found that endurance exercise was most effective in increasing neurogenesis. It wins out over HIIT sessions and resistance training, although doing a variety of exercise also has its benefits.

Aim to do aerobic exercise for 150 minutes per week, and choose the gym, the park, or natural landscape over busy roads to avoid compromising brain-derived neurotrophic factor production (BDNF), a growth factor that encourages neurogenesis that aerobic exercise can boost. However, exercising in polluted areas decreases production.

If exercising alone isn’t your thing, consider taking up a team sport or one with a social element like table tennis. Exposure to social interaction can also increase the neurogenesis, and in many instances, doing so lets you practice your hand-eye coordination, which research has suggested leads to structural changes in the brain that may relate to a range of cognitive benefit. This combination of coordination and socializing has been shown to increase brain thickness in the parts of the cortex related to social/emotional welfare, which is crucial as we age.

  • CHANGE YOUR EATING PATTERNS

Evidence shows that calorie restriction, intermittent fasting, and time-restricted eating encourage neurogenesis in humans. In rodent studies, intermittent fasting has been found to improve cognitive function and brain structure, and reduce symptoms of metabolic disorders such as diabetes. Reducing refined sugar will help reduce oxidative damage to brain cells, too, and we know that increased oxidative damage has been linked with a higher risk of developing Alzheimer’s disease. Twenty-four hour water-only fasts have also been proven to increase longevity and encourage neurogenesis.

Try any of the following, after checking with your doctor:

  • 24-hour water-only fast once a month
  •  Reducing your calorie intake by 50%-60% on two non-consecutive days of the week for two to three months or on an ongoing basis
  • Reducing calories by 20% every day for two weeks. You can do this three to four times a year
  • Eating only between 8 a.m. to 8 p.m., or 12 p.m. to 8 p.m. as a general rule

 

  • PRIORITIZE SLEEP

Sleep helps promote the brain’s neural “cleaning” glymphatic system, which flushes out the build-up of age-related toxins in the brain (the tau proteins and beta amyloid plaques mentioned above). When people are sleep-deprived, we see evidence of memory deficits, and if you miss a whole night of sleep, research proves that it impacts IQ. Aim for seven to nine hours, and nap if it suits you. Our need to sleep decreases as we age.

Of course, there are individual exceptions, but having consistent sleep times and making sure you’re getting sufficient quality and length of sleep supports brain resilience over time. So how do you know if you’re getting enough? If you naturally wake up at the same time on weekends that you have to during the week, you probably are. If you need to lie-in or take long naps, you’re probably not. Try practicing mindfulness or yoga nidra before bed at night, a guided breath-based meditation that has been shown in studies to improve sleep quality. There are plenty of recordings online if you want to experience it.

Pick any of the above that work for you and build it up until it becomes a habit, then move onto the next one and so on. You might find that by the end of the year, you’ll feel even healthier, more energized, and motivated than you do now, even as you turn another year older.

 

 

Original article here