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How To Be Spiritual In A Material World
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07 Jun 2023
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The length of Earth’s days has been mysteriously increasing, and scientists don’t know why

Atomic clocks, combined with precise astronomical measurements, have revealed that the length of a day is suddenly getting longer, and scientists don’t know why.

This has critical impacts not just on our timekeeping, but also things like GPS and other technologies that govern our modern life.

Over the past few decades, Earth’s rotation around its axis – which determines how long a day is – has been speeding up. This trend has been making our days shorter; in fact, in June 2022 we set a record for the shortest day over the past half a century or so.

But despite this record, since 2020 that steady speedup has curiously switched to a slowdown – days are getting longer again, and the reason is so far a mystery.

While the clocks in our phones indicate there are exactly 24 hours in a day, the actual time it takes for Earth to complete a single rotation varies ever so slightly. These changes occur over periods of millions of years to almost instantly – even earthquakes and storm events can play a role.

It turns out a day is very rarely exactly the magic number of 86,400 seconds.

The ever-changing planet

Over millions of years, Earth’s rotation has been slowing down due to friction effects associated with the tides driven by the Moon. That process adds about 2.3 milliseconds to the length of each day every century. A few billion years ago an Earth day was only about 19 hours.

For the past 20,000 years, another process has been working in the opposite direction, speeding up Earth’s rotation. When the last ice age ended, melting polar ice sheets reduced surface pressure, and Earth’s mantle started steadily moving toward the poles.

Just as a ballet dancer spins faster as they bring their arms toward their body – the axis around which they spin – so our planet’s spin rate increases when this mass of mantle moves closer to Earth’s axis. And this process shortens each day by about 0.6 milliseconds each century.

Over decades and longer, the connection between Earth’s interior and surface comes into play too. Major earthquakes can change the length of day, although normally by small amounts. For example, the Great Tōhoku Earthquake of 2011 in Japan, with a magnitude of 8.9, is believed to have sped up Earth’s rotation by a relatively tiny 1.8 microseconds.

Apart from these large-scale changes, over shorter periods weather and climate also have important impacts on Earth’s rotation, causing variations in both directions.

The fortnightly and monthly tidal cycles move mass around the planet, causing changes in the length of day by up to a millisecond in either direction. We can see tidal variations in length-of-day records over periods as long as 18.6 years. The movement of our atmosphere has a particularly strong effect, and ocean currents also play a role. Seasonal snow cover and rainfall, or groundwater extraction, alter things further.

Why is Earth suddenly slowing down?

Since the 1960s, when operators of radio telescopes around the planet started to devise techniques to simultaneously observe cosmic objects like quasars, we have had very precise estimates of Earth’s rate of rotation.

A comparison between these estimates and an atomic clock has revealed a seemingly ever-shortening length of day over the past few years.

But there’s a surprising reveal once we take away the rotation speed fluctuations we know happen due to the tides and seasonal effects. Despite Earth reaching its shortest day on June 29 2022, the long-term trajectory seems to have shifted from shortening to lengthening since 2020. This change is unprecedented over the past 50 years.

The reason for this change is not clear. It could be due to changes in weather systems, with back-to-back La Niña events, although these have occurred before. It could be increased melting of the ice sheets, although those have not deviated hugely from their steady rate of melt in recent years. Could it be related to the huge volcano explosion in Tonga injecting huge amounts of water into the atmosphere? Probably not, given that occurred in January 2022.

Scientists have speculated this recent, mysterious change in the planet’s rotational speed is related to a phenomenon called the “Chandler wobble” – a small deviation in Earth’s rotation axis with a period of about 430 days. Observations from radio telescopes also show that the wobble has diminished in recent years; the two may be linked.

One final possibility, which we think is plausible, is that nothing specific has changed inside or around Earth. It could just be long-term tidal effects working in parallel with other periodic processes to produce a temporary change in Earth’s rotation rate.

Do we need a ‘negative leap second’?

Precisely understanding Earth’s rotation rate is crucial for a host of applications – navigation systems such as GPS wouldn’t work without it. Also, every few years timekeepers insert leap seconds into our official timescales to make sure they don’t drift out of sync with our planet.

If Earth were to shift to even longer days, we may need to incorporate a “negative leap second” – this would be unprecedented, and may break the internet.

The need for negative leap seconds is regarded as unlikely right now. For now, we can welcome the news that – at least for a while – we all have a few extra milliseconds each day.

 

 

Original article here

 

 

29 May 2023
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The big idea: why colour is in the eye of the beholder

In February 2015, a Scottish woman uploaded a photograph of a dress to the internet. Within 48 hours the blurry snapshot had gone viral, provoking spirited debate around the world. The disagreement centred on the dress’s colour: some people were convinced it was blue and black while others were adamant it was white and gold.

Everyone, it seemed, was incredulous. People couldn’t understand how, faced with exactly the same photograph of exactly the same dress, they could reach such different and firmly held conclusions about its appearance. The confusion was grounded in a fundamental misunderstanding about colour – one that, despite mounting evidence to the contrary, shows little sign of disappearing.

For a long time, people believed that colours were objective, physical properties of objects or of the light that bounced off them. Even today, science teachers regale their students with stories about Isaac Newton and his prism experiment, telling them how different wavelengths of light produce the rainbow of hues around us.

But this theory isn’t really true. Different wavelengths of light do exist independently of us but they only become colours inside our bodies. Colour is ultimately a neurological process whereby photons are detected by light-sensitive cells in our eyes, transformed into electrical signals and sent to our brain, where, in a series of complex calculations, our visual cortex converts them into “colour”.

Most experts now agree that colour, as commonly understood, doesn’t inhabit the physical world at all but exists in the eyes or minds of its beholders. They argue that if a tree fell in a forest and no one was there to see it, its leaves would be colourless – and so would everything else. To put it another way: there is no such thing as colour; there are only the people who perceive it.

This is why no two people will ever see exactly the same colours. Every person’s visual system is unique and so, therefore, are their perceptions. About 8% of men are colour-blind and see fewer colours than everyone else; a small number of lucky women might, thanks to a genetic duplication on the X chromosome, be able to distinguish many more than the rest of us.

Animals inhabit very different chromatic worlds too. Most mammals are red-green colour-blind; bulls might be famous for their hatred of red capes, but the colour itself is invisible to them – they are actually enraged by the fabric’s movements. By contrast, most reptiles, amphibians, insects and birds perceive more colours than us. Bees see ultraviolet light, discerning elaborate patterns in flowers that we cannot perceive, while snakes see infrared radiation, detecting the warm bodies of prey from a distance.

 

People generally name only the colours they consider socially or culturally important

 

“Colour,” Umberto Eco once said, “is not an easy matter.” It is indeed elusive and illusive. Pretty much everything we take to be self-evident about it really isn’t self-evident at all. Scientists have shown that the sky isn’t blue, the sun isn’t yellow, snow isn’t white, black isn’t dark and darkness isn’t black.

One cause of the problem – or perhaps its symptom – is language. In English we divide colour space into 11 basic terms – black, white, red, yellow, green, blue, purple, brown, grey, orange and pink – but other languages do things differently. Many don’t have words for pink, brown and yellow, and some use one word for both green and blue. The Tiv people in west Africa use only three basic colour terms (black, white, red), and at least one Indigenous community has no specific words for any colours, only “light” and “dark”.

The vocabulary of these languages isn’t dictated by the prismatic spectrum but, once again, by what is happening inside their speakers’ heads. People generally name only the colours they consider socially or culturally important. The Aztecs, who were enthusiastic farmers, used more than a dozen words for green; the Mursi cattleherders of Ethiopia have 11 colour terms for cows, and none for anything else.

These differences might even influence the colours they see. Debates about linguistic relativity – the extent to which our words shape our thoughts and perceptions – have been rumbling on for decades, and while many scholars have overstated the case for it, some have found persuasive evidence that if you don’t, say, have a word for blue, you will probably find it harder to distinguish.

The meanings of colour are no less socially constructed, which is why a single colour can mean completely different things in different places and at different times. In the west white is the colour of light, life and purity, but in parts of Asia it is the colour of death. In America red is conservative and blue progressive, while in Europe it’s the other way around. Many people today think of blue as masculine and pink as feminine, but only a hundred years ago baby boys were dressed in pink and girls in blue.

When all of this is taken together – the subjective nature of visual perception, the complicating influence of language, the role that social life and cultural traditions play in filtering our understandings of colour – it becomes really rather difficult to reach a conclusion different from that of the 18th-century philosopher David Hume: that, in the end, colour is “merely a phantasm of the senses”.

The ancient Egyptian term for “colour” was iwn – a word that also meant “skin”, “nature”, “character” and “being”, and was represented in part by a hieroglyph of human hair. To the Egyptians, colours were like people – full of life, energy, power and personality. We now understand just how completely the two are entangled. That’s because every hue we see around us is actually manufactured within us – in the same grey matter that forms language, stores memories, stokes emotions, shapes thoughts and gives rise to consciousness. Colour is, if you’ll pardon the pun, a pigment of our imaginations.

 

 

 

Original article here

27 May 2023
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The Dutch solution to busyness that captivated the world

The Hague, where I live, has 11km of gorgeous coastline with rolling dunes and sandy beaches. In summer, I often see locals in Scheveningen or Kijkduin (the city’s most famous beaches) sunbathing, strolling in nature or riding their bikes, then sitting down on one of the many benches available. Sometimes, they’re reading or chatting with their friends, but just as often, they’re engaging in niksen.

Niksen is a Dutch wellness trend that means “doing nothing”. It first caught the attention of the world in 2019 as a way to manage stress or recover from burnout. At the time, many people were complaining about exhaustion and depression caused by overwork and were looking for solutions – which is why concepts such as Japanese ikigai or Danish hygge also entered the English lexicon. As a linguist myself, I loved the idea that you could express the whole concept of doing nothing in one short and easy-to-pronounce word.

In my book Niksen: Embracing the Dutch Art of Doing Nothing, I define it as “doing nothing without a purpose” – so not scrolling on Facebook or engaging in meditation. Whereas mindfulness is about being present in the moment, niksen is more about carving out time to just be, letting your mind wander wherever it wants to go. And as we’re slowly recovering after the pandemic, it’s important to rethink the way we work and spend our time.

Linguistically, niksen (doing nothing) is a verb created from “niks“, which means “nothing”.

“It fits with the tendency of the Dutch language to create verbs out of nouns. From from ‘voetbal’ (football) to voetballen (playing football), from ‘internet’ to internetten, from ‘whatsapp‘ to whatsappen etc. I think this is something that happens in Dutch in particular,” said Monique Flecken, a psycholinguist at the University of Amsterdam, who researches how the languages we speak affect the way we see the world. Essentially, it’s much less work to say “niksen” instead of “to do nothing”. “The Dutch are a practical, direct people and their language reflects that,” she said.

In the Netherlands, the word can be used in a variety of ways, both positive and negative. Flecken said: “A parent might say to their kid, “Zit je weer te niksen?” (Are you doing nothing again?). And I would also say ‘lekker niksen’, which translates to ‘delicious doing nothing’, when talking about an evening blissfully free of any tasks or work.”

To Thijs Launspach, a psychologist, TEDx speaker and author of the book Crazy Busy: Staying Sane in a Stressful World, niksen means “doing nothing or occupying yourself with something trivial as a way of enjoying your own time. Not doing nothing entirely but doing as little as possible,” he said, pointing out that this mostly applies to elderly people who have more unstructured free time. Younger generations, on the other hand, are more stressed out than ever – even in the Netherlands, a country traditionally applauded for its work-life balance.

 

It’s not necessarily bad to be for a moment in a state of stress, where you’re really on and focused. The problem is when this is getting out of hand

 

There are plenty of reasons for that. “Our lives and our jobs have become increasingly complex. We tend to spend a lot of time with computers. There is a lot of pressure on being the best version of yourself, be it in our jobs, or the expectations of parents [or] from social media. There is a lot of pressure to perform,” Launspach said.

Of course, some stress can be good, as Leiden University psychology professor Bernet Elzinga points out. “It’s not necessarily bad to be for a moment in a state of stress, where you’re really on and focused. The problem is when this is getting out of hand,” she said. But niksen can help with that. “When you do nothing, you connect to your default mode network. And that network is responsible for mind-wandering and reflection,” Elzinga explained.

Paradoxically, niksen can also make us more productive, simply because breaks allow our brains to rest and come back with better focus and sustained attention. This is probably why, while the Dutch don’t work long hours, they tend to be very efficient at work. Working overtime is not encouraged due to the “just be normal, that’s already crazy enough” attitude prevalent in the Netherlands – a nod towards the country’s honest and egalitarian culture.

And it seems to work: the Dutch are a creative nation. Just think of all the famous painters like Rembrandt, Vermeer or Escher, as well as the innovative solutions the Dutch have found to battle the recurring threat of floods, such as huge dams and floating houses.

The Dutch also like to enjoy life, as shown by the word lekker. This means “delicious” but can be used to refer to anything nice and pleasant, like lekker warm(deliciously warm), lekker slapen (sleeping deliciously), and, of course, lekker niksen, or “deliciously doing nothing”. This available architecture of leisure makes it more possible for people to do nothing more easily.

Locals like spending their time in active ways, such as cycling or hiking, allowing time for clearing the mind. And each time the sun comes out, the Dutch flock to cafes and terraces en masse, even in the winter. For me, these are perfect places for doing nothing.

However, Launspach is not a fan of doing nothing as a stress-preventing measure. “I’m a little bit sceptical of the idea that you should create a buffer between you and stress. I don’t know if that’s even possible in the way that we live and work now,” he said.

Elzinga believes that it’s much better to do some sort of physical activity to distract you from your daily worries, preferably in nature. But luckily, in the Netherlands, there is a way to combine all these things – niksen, nature and movement.

While the country is not commonly known for its natural resources , the Dutch appreciate the little natural areas they have. Many dune areas – my favourite thing about The Netherlands – are a part of a large network of hiking and cycling routes crisscrossing the country. Even in large cities such as Rotterdam, The Hague or Amsterdam, you’re never too far away from a trail.

In a cooperation with the Dutch Railway system, Wandelnet – a foundation devoted to creating and maintaining hiking routes – has created NS Wandelingen, a system of hiking routes that are easy to reach by train or other public transport. They range between 7km and 22km in length, making them perfect for a day trip. And given the many benches along the way, it’s even possible to fit in a little niksen break.

This leisure time is possible for the Dutch because the Netherlands is a country with an excellent welfare system, and while people tend to work hard, they also take (and are granted) many days off.

“Having a good social support system, having lower stress level relates to feeling secure and in balance. So, I wouldn’t overestimate the importance of that,” said Elzinga.

And with everything going on in the world – the Covid-19 pandemic, the war in Ukraine – relieving stress is more important than ever.

 

 

Original article here

22 May 2023
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How To Worry Less And Enjoy Your Life More

 

Did you know that worrying is like a rocking chair?

It gives you something to do, but it doesn’t get you anywhere.

Excessive worrying is exhausting and can become a great waste of time and energy. It puts your mind in overdrive and distracts you from doing the more important things, as well as preventing you from having a healthy, happy life.

Most people worry on a regular basis, as a natural part of life. However, the worry habit can become problematic when it becomes too intense and chronic. Some people even worry about worrying. When you are plagued by thoughts that are persistent and out of control, they end up causing interference and paralysis in your daily life.

The bad news is that constant worrying eventually takes a toll on your emotional and physical health, as well as your self-esteem, relationships, and career. When you keep hitting the panic button, the stress response is triggered, which leads to fear, then more stress and anxiety, and then more worry. An endless worry cycle is created.

The good news is that worrying is a mental habit that can be broken. You can train your brain to stay calm and remain positive. You are in charge of your thoughts and imagination. How you choose to use your mind is your responsibility. Do you continue to misuse your imagination and keep focusing on the negative or do you choose to switch to the positive?

The reason most people worry too much is often rooted in fear – ultimately a fear of something happening that cannot be controlled. When we anticipate something negative happening in the future, it is based on irrational thoughts. We are afraid of the worst-case scenario, as we have allowed our minds to wander too far on the negative side.

9 Practical Tips To Minimize Worrying 

  • Learn to distinguish between what you can control in life and what you can’t. The things you can change need an action plan with a list of concrete steps you can take to solve the problem. And for the things you cannot change, you need to learn acceptance. The Serenity Prayer sums it up perfectly: “God, grant me the serenity to accept the things I cannot change, the courage to change the things I can, and the wisdom to know the difference.”
  • Recognize your trigger points. Find out the source of your worries and gain a clearer picture of what’s driving them. Your worries will start losing power, and you will start regaining control of your mind. Self-awareness is the first step to changing your mindset.
  • Re-frame your thoughts and change your perspective. Instead of saying, “I can’t handle this,” become more self-confident and start believing that you can handle it. Make a list of the negative messages you are feeding your mind and replace them with positive affirmations. Make sure you challenge those thoughts. No amount of worrying will make life any more predictable.
  • Break the worry cycle by limiting your worrying time. Schedule a worry time each day to keep the worry contained and prevent it from contaminating your whole day. Sit down for 15 minutes and make a list of all the things you want to worry about, and then proceed to worry about them. At the end of the exercise, you will come to the realization that worrying is futile. You can become more mindful of your thoughts and where you place your energy. Choose to focus on what really matters in your life and become more productive.
  • Get up and move. Take a 20-minute walk. Stretch out and do some yoga. Exercise is a productive activity that can interrupt your worries and shift your body’s energy. It releases endorphins, which get rid of the tension and break the cycle.
  • Breathing exercises, meditation and relaxation techniques also interrupt your train of thoughts and calm the body’s response to stress. This dynamic trio helps relax your body, guide your thoughts, and keep them from getting caught up in worries.
  • Ground yourself in the present. Become mindful of your thoughts and activities. Make time to unplug and take a look at the bigger picture. Ask yourself if what you are worrying about is really going to matter in five years from now. If not, let it go and don’t spend more than five minutes worrying about it. If it does matter, then make a list of one or two things you can do now to solve the problem. Keep in mind, you may not resolve the whole problem right then and there, but at least your thoughts will be clearer and calmer, and you will be able to move forward by focusing on what matters instead of worrying about things that don’t really matter.
  • Stop overthinking and dwelling on your worries by finding a healthy distraction like reading a good book, watching a funny movie, listening to great music, taking up hobbies that you enjoy, or doing something different, such as trying a new recipe.
  • Build a support network. Enlist the help of your trusted friends and family. By sharing your thoughts and tuning into your feelings, it can help you process them as you feel supported. In some cases, chronic worry can be a symptom of GAD or generalized anxiety disorder. You can seek the help of a therapist or join a support group. Don’t keep your worries to yourself. This will cause them to build up and become overwhelming.

Next time you catch yourself worrying, instead of pressing the panic button, reach for the pause button and ask yourself, “What’s important now?” Coach Lou Holtz came up with the acronym W.I.N. or What’s Important Now. This enables you to prioritize your decisions, choices and actions. The antidote for worrying is to maintain calm, clarity, and focus. Also, by having a grateful mind, you can look for the positive in every situation.

Strengthen your mind by learning to turn off those worrying thoughts and regain control. Look at life from a less fearful and more balanced perspective.

 

 

Original article here

18 May 2023
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Chat GPT is about to revolutionize the economy. We need to decide what that looks like.

 

 

Whether it’s based on hallucinatory beliefs or not, an artificial-intelligence gold rush has started over the last several months to mine the anticipated business opportunities from generative AI models like ChatGPT. App developers, venture-backed startups, and some of the world’s largest corporations are all scrambling to make sense of the sensational text-generating bot released by OpenAI last November.

You can practically hear the shrieks from corner offices around the world: “What is our ChatGPT play? How do we make money off this?”

But while companies and executives see a clear chance to cash in, the likely impact of the technology on workers and the economy on the whole is far less obvious. Despite their limitations—chief among of them their propensity for making stuff up—ChatGPT and other recently released generative AI models hold the promise of automating all sorts of tasks that were previously thought to be solely in the realm of human creativity and reasoning, from writing to creating graphics to summarizing and analyzing data. That has left economists unsure how jobs and overall productivity might be affected.

For all the amazing advances in AI and other digital tools over the last decade, their record in improving prosperity and spurring widespread economic growth is discouraging. Although a few investors and entrepreneurs have become very rich, most people haven’t benefited. Some have even been automated out of their jobs.

Productivity growth, which is how countries become richer and more prosperous, has been dismal since around 2005 in the US and in most advanced economies (the UK is a particular basket case). The fact that the economic pie is not growing much has led to stagnant wages for many people.

What productivity growth there has been in that time is largely confined to a few sectors, such as information services, and in the US to a few cities—think San Jose, San Francisco, Seattle, and Boston.

Will ChatGPT make the already troubling income and wealth inequality in the US and many other countries even worse? Or could it help? Could it in fact provide a much-needed boost to productivity?

ChatGPT, with its human-like writing abilities, and OpenAI’s other recent release DALL-E 2, which generates images on demand, use large language models trained on huge amounts of data. The same is true of rivals such as Claude from Anthropic and Bard from Google. These so-called foundational models, such as GPT-3.5 from OpenAI, which ChatGPT is based on, or Google’s competing language model LaMDA, which powers Bard, have evolved rapidly in recent years.

They keep getting more powerful: they’re trained on ever more data, and the number of parameters—the variables in the models that get tweaked—is rising dramatically. Earlier this month, OpenAI released its newest version, GPT-4. While OpenAI won’t say exactly how much bigger it is, one can guess; GPT-3, with some 175 billion parameters, was about 100 times larger than GPT-2.

But it was the release of ChatGPT late last year that changed everything for many users. It’s incredibly easy to use and compelling in its ability to rapidly create human-like text, including recipes, workout plans, and—perhaps most surprising—computer code. For many non-experts, including a growing number of entrepreneurs and businesspeople, the user-friendly chat model—less abstract and more practical than the impressive but often esoteric advances that have been brewing in academia and a handful of high-tech companies over the last few years—is clear evidence that the AI revolution has real potential.

Venture capitalists and other investors are pouring billions into companies based on generative AI, and the list of apps and services driven by large language models is growing longer every day.

 

Will ChatGPT make the already troubling income and wealth inequality in the US and many other countries even worse? Or could it help?

 

Among the big players, Microsoft has invested a reported $10 billion in OpenAI and its ChatGPT, hoping the technology will bring new life to its long-struggling Bing search engine and fresh capabilities to its Office products. In early March, Salesforce said it will introduce a ChatGPT app in its popular Slack product; at the same time, it announced a $250 million fund to invest in generative AI startups. The list goes on, from Coca-Cola to GM. Everyone has a ChatGPT play.

Meanwhile, Google announced it is going to use its new generative AI tools in Gmail, Docs, and some of its other widely used products.

Still, there are no obvious killer apps yet. And as businesses scramble for ways to use the technology, economists say a rare window has opened for rethinking how to get the most benefits from the new generation of AI.

“We’re talking in such a moment because you can touch this technology. Now you can play with it without needing any coding skills. A lot of people can start imagining how this impacts their workflow, their job prospects,” says Katya Klinova, the head of research on AI, labor, and the economy at the Partnership on AI in San Francisco.

“The question is who is going to benefit? And who will be left behind?” says Klinova, who is working on a report outlining the potential job impacts of generative AI and providing recommendations for using it to increase shared prosperity.

The optimistic view: it will prove to be a powerful tool for many workers, improving their capabilities and expertise, while providing a boost to the overall economy. The pessimistic one: companies will simply use it to destroy what once looked like automation-proof jobs, well-paying ones that require creative skills and logical reasoning; a few high-tech companies and tech elites will get even richer, but it will do little for overall economic growth.

Helping the least skilled

The question of ChatGPT’s impact on the workplace isn’t just a theoretical one.

In the most recent analysis, OpenAI’s Tyna Eloundou, Sam Manning, and Pamela Mishkin, with the University of Pennsylvania’s Daniel Rock, found that large language models such as GPT could have some effect on 80% of the US workforce. They further estimated that the AI models, including GPT-4 and other anticipated software tools, would heavily affect 19% of jobs, with at least 50% of the tasks in those jobs “exposed.” In contrast to what we saw in earlier waves of automation, higher-income jobs would be most affected, they suggest. Some of the people whose jobs are most vulnerable: writers, web and digital designers, financial quantitative analysts, and—just in case you were thinking of a career change—blockchain engineers.

“There is no question that [generative AI] is going to be used—it’s not just a novelty,” says David Autor, an MIT labor economist and a leading expert on the impact of technology on jobs. “Law firms are already using it, and that’s just one example. It opens up a range of tasks that can be automated.”

Autor has spent years documenting how advanced digital technologies have destroyed many manufacturing and routine clerical jobs that once paid well. But he says ChatGPT and other examples of generative AI have changed the calculation.

Previously, AI had automated some office work, but it was those rote step-by-step tasks that could be coded for a machine. Now it can perform tasks that we have viewed  as creative, such as writing and producing graphics. “It’s pretty apparent to anyone who’s paying attention that generative AI opens the door to computerization of a lot of kinds of tasks that we think of as not easily automated,” he says.

 

Generative AI could help a wide swath of people gain the skills to compete with those who have more education and expertise.

 

The worry is not so much that ChatGPT will lead to large-scale unemployment—as Autor points out, there are plenty of jobs in the US—but that companies will replace relatively well-paying white-collar jobs with this new form of automation, sending those workers off to lower-paying service employment while the few who are best able to exploit the new technology reap all the benefits.

In this scenario, tech-savvy workers and companies could quickly take up the AI tools, becoming so much more productive that they dominate their workplaces and their sectors. Those with fewer skills and little technical acumen to begin with would be left further behind.

But Autor also sees a more positive possible outcome: generative AI could help a wide swath of people gain the skills to compete with those who have more education and expertise.

One of the first rigorous studies done on the productivity impact of ChatGPT suggests that such an outcome might be possible.

Two MIT economics graduate students, Shakked Noy and Whitney Zhang, ran an experiment involving hundreds of college-educated professionals working in areas like marketing and HR; they asked half to use ChatGPT in their daily tasks and the others not to. ChatGPT raised overall productivity (not too surprisingly), but here’s the really interesting result: the AI tool helped the least skilled and accomplished workers the most, decreasing the performance gap between employees. In other words, the poor writers got much better; the good writers simply got a little faster.

The preliminary findings suggest that ChatGPT and other generative AIs could, in the jargon of economists, “upskill” people who are having trouble finding work. There are lots of experienced workers “lying fallow” after being displaced from office and manufacturing jobs over the last few decades, Autor says. If generative AI can be used as a practical tool to broaden their expertise and provide them with the specialized skills required in areas such as health care or teaching, where there are plenty of jobs, it could revitalize our workforce.

Determining which scenario wins out will require a more deliberate effort to think about how we want to exploit the technology.

“I don’t think we should take it as the technology is loose on the world and we must adapt to it. Because it’s in the process of being created, it can be used and developed in a variety of ways,” says Autor. “It’s hard to overstate the importance of designing what it’s there for.”

Simply put, we are at a juncture where either less-skilled workers will increasingly be able to take on what is now thought of as knowledge work, or the most talented knowledge workers will radically scale up their existing advantages over everyone else. Which outcome we get depends largely on how employers implement tools like ChatGPT. But the more hopeful option is well within our reach.

Beyond human-like

There are some reasons to be pessimistic, however. Last spring, in “The Turing Trap: The Promise & Peril of Human-Like Artificial Intelligence,” the Stanford economist Erik Brynjolfsson warned that AI creators were too obsessed with mimicking human intelligence rather than finding ways to use the technology to allow people to do new tasks and extend their capabilities.

The pursuit of human-like capabilities, Brynjolfsson argued, has led to technologies that simply replace people with machines, driving down wages and exacerbating inequality of wealth and income. It is, he wrote, “the single biggest explanation” for the rising concentration of wealth.

A year later, he says ChatGPT, with its human-sounding outputs, “is like the poster child for what I warned about”: it has “turbocharged” the discussion around how the new technologies can be used to give people new abilities rather than simply replacing them.

Despite his worries that AI developers will continue to blindly outdo each other in mimicking human-like capabilities in their creations, Brynjolfsson, the director of the Stanford Digital Economy Lab, is generally a techno-optimist when it comes to artificial intelligence. Two years ago, he predicted a productivity boom from AI and other digital technologies, and these days he’s bullish on the impact of the new AI models.

Much of Brynjolfsson’s optimism comes from the conviction that businesses could greatly benefit from using generative AI such as ChatGPT to expand their offerings and improve the productivity of their workforce. “It’s a great creativity tool. It’s great at helping you to do novel things. It’s not simply doing the same thing cheaper,” says Brynjolfsson. As long as companies and developers can “stay away from the mentality of thinking that humans aren’t needed,” he says, “it’s going to be very important.”

Within a decade, he predicts, generative AI could add trillions of dollars in economic growth in the US. “A majority of our economy is basically knowledge workers and information workers,” he says. “And it’s hard to think of any type of information workers that won’t be at least partly affected.”

When that productivity boost will come—if it does—is an economic guessing game. Maybe we just need to be patient.

In 1987, Robert Solow, the MIT economist who won the Nobel Prize that year for explaining how innovation drives economic growth, famously said, “You can see the computer age everywhere except in the productivity statistics.” It wasn’t until later, in the mid and late 1990s, that the impacts—particularly from advances in semiconductors—began showing up in the productivity data as businesses found ways to take advantage of ever cheaper computational power and related advances in software.

Could the same thing happen with AI? Avi Goldfarb, an economist at the University of Toronto, says it depends on whether we can figure out how to use the latest technology to transform businesses as we did in the earlier computer age.

So far, he says, companies have just been dropping in AI to do tasks a little bit better: “It’ll increase efficiency—it might incrementally increase productivity—but ultimately, the net benefits are going to be small. Because all you’re doing is the same thing a little bit better.” But, he says, “the technology doesn’t just allow us to do what we’ve always done a little bit better or a little bit cheaper. It might allow us to create new processes to create value to customers.”

The verdict on when—even if—that will happen with generative AI remains uncertain. “Once we figure out what good writing at scale allows industries to do differently, or—in the context of Dall-E—what graphic design at scale allows us to do differently, that’s when we’re going to experience the big productivity boost,” Goldfarb says. “But if that is next week or next year or 10 years from now, I have no idea.”

Power struggle

When Anton Korinek, an economist at the University of Virginia and a fellow at the Brookings Institution, got access to the new generation of large language models such as ChatGPT, he did what a lot of us did: he began playing around with them to see how they might help his work. He carefully documented their performance in a paper in February, noting how well they handled 25 “use cases,” from brainstorming and editing text (very useful) to coding (pretty good with some help) to doing math (not great).

ChatGPT did explain one of the most fundamental principles in economics incorrectly, says Korinek: “It screwed up really badly.” But the mistake, easily spotted, was quickly forgiven in light of the benefits. “I can tell you that it makes me, as a cognitive worker, more productive,” he says. “Hands down, no question for me that I’m more productive when I use a language model.”

When GPT-4 came out, he tested its performance on the same 25 questions that he documented in February, and it performed far better. There were fewer instances of making stuff up; it also did much better on the math assignments, says Korinek.

Since ChatGPT and other AI bots automate cognitive work, as opposed to physical tasks that require investments in equipment and infrastructure, a boost to economic productivity could happen far more quickly than in past technological revolutions, says Korinek. “I think we may see a greater boost to productivity by the end of the year—certainly by 2024,” he says.

 

Who will control the future of this amazing technology?

 

What’s more, he says, in the longer term, the way the AI models can make researchers like himself more productive has the potential to drive technological progress.

That potential of large language models is already turning up in research in the physical sciences. Berend Smit, who runs a chemical engineering lab at EPFL in Lausanne, Switzerland, is an expert on using machine learning to discover new materials. Last year, after one of his graduate students, Kevin Maik Jablonka, showed some interesting results using GPT-3, Smit asked him to demonstrate that GPT-3 is, in fact, useless for the kinds of sophisticated machine-learning studies his group does to predict the properties of compounds.

“He failed completely,” jokes Smit.

It turns out that after being fine-tuned for a few minutes with a few relevant examples, the model performs as well as advanced machine-learning tools specially developed for chemistry in answering basic questions about things like the solubility of a compound or its reactivity. Simply give it the name of a compound, and it can predict various properties based on the structure.

As in other areas of work, large language models could help expand the expertise and capabilities of non-experts—in this case, chemists with little knowledge of complex machine-learning tools. Because it’s as simple as a literature search, Jablonka says, “it could bring machine learning to the masses of chemists.”

These impressive—and surprising—results are just a tantalizing hint of how powerful the new forms of AI could be across a wide swath of creative work, including scientific discovery, and how shockingly easy they are to use. But this also points to some fundamental questions.

As the potential impact of generative AI on the economy and jobs becomes more imminent, who will define the vision for how these tools should be designed and deployed? Who will control the future of this amazing technology?

Diane Coyle, an economist at Cambridge University in the UK, says one concern is the potential for large language models to be dominated by the same big companies that rule much of the digital world. Google and Meta are offering their own large language models alongside OpenAI, she points out, and the large computational costs required to run the software create a barrier to entry for anyone looking to compete.

The worry is that these companies have similar “advertising-driven business models,” Coyle says. “So obviously you get a certain uniformity of thought, if you don’t have different kinds of people with different kinds of incentives.”

Coyle acknowledges that there are no easy fixes, but she says one possibility is a publicly funded international research organization for generative AI, modeled after CERN, the Geneva-based intergovernmental European nuclear research body where the World Wide Web was created in 1989. It would be equipped with the huge computing power needed to run the models and the scientific expertise to further develop the technology.

Such an effort outside of Big Tech, says Coyle, would “bring some diversity to the incentives that the creators of the models face when they’re producing them.”

While it remains uncertain which public policies would help make sure that large language models best serve the public interest, says Coyle, it’s becoming clear that the choices about how we use the technology can’t be left to a few dominant companies and the market alone.

History provides us with plenty of examples of how important government-funded research can be in developing technologies that bring about widespread prosperity. Long before the invention of the web at CERN, another publicly funded effort in the late 1960s gave rise to the internet, when the US Department of Defense supported ARPANET, which pioneered ways for multiple computers to communicate with each other.

In Power and Progress: Our 1000-Year Struggle Over Technology & Prosperity, the MIT economists Daron Acemoglu and Simon Johnson provide a compelling walk through the history of technological progress and its mixed record in creating widespread prosperity. Their point is that it’s critical to deliberately steer technological advances in ways that provide broad benefits and don’t just make the elite richer.

From the decades after World War II until the early 1970s, the US economy was marked by rapid technological changes; wages for most workers rose while income inequality dropped sharply. The reason, Acemoglu and Johnson say, is that technological advances were used to create new tasks and jobs, while social and political pressures helped ensure that workers shared the benefits more equally with their employers than they do now.

In contrast, they write, the more recent rapid adoption of manufacturing robots in “the industrial heartland of the American economy in the Midwest” over the last few decades simply destroyed jobs and led to a “prolonged regional decline.”

The book, which comes out in May, is particularly relevant for understanding what today’s rapid progress in AI could bring and how decisions about the best way to use the breakthroughs will affect us all going forward. In a recent interview, Acemoglu said they were writing the book when GPT-3 was first released. And, he adds half-jokingly, “we foresaw ChatGPT.”

Acemoglu maintains that the creators of AI “are going in the wrong direction.” The entire architecture behind the AI “is in the automation mode,” he says. “But there is nothing inherent about generative AI or AI in general that should push us in this direction. It’s the business models and the vision of the people in OpenAI and Microsoft and the venture capital community.”

If you believe we can steer a technology’s trajectory, then an obvious question is: Who is “we”? And this is where Acemoglu and Johnson are most provocative. They write: “Society and its powerful gatekeepers need to stop being mesmerized by tech billionaires and their agenda … One does not need to be an AI expert to have a say about the direction of progress and the future of our society forged by these technologies.”

The creators of ChatGPT and the businesspeople involved in bringing it to market, notably OpenAI’s CEO, Sam Altman, deserve much credit for offering the new AI sensation to the public. Its potential is vast. But that doesn’t mean we must accept their vision and aspirations for where we want the technology to go and how it should be used.

According to their narrative, the end goal is artificial general intelligence, which, if all goes well, will lead to great economic wealth and abundances. Altman, for one, has promoted the vision at great length recently, providing further justification for his longtime advocacy of a universal basic income (UBI) to feed the non-technocrats among us. For some, it sounds tempting. No work and free money! Sweet!

It’s the assumptions underlying the narrative that are most troubling—namely, that AI is headed on an inevitable job-destroying path and most of us are just along for the (free?) ride. This view barely acknowledges the possibility that generative AI could lead to a creativity and productivity boom for workers far beyond the tech-savvy elites by helping to unlock their talents and brains. There is little discussion of the idea of using the technology to produce widespread prosperity by expanding human capabilities and expertise throughout the working population.

 

Companies can decide to use ChatGPT to give workers more abilities—or to simply cut jobs and trim costs.

 

As Acemoglu and Johnson write: “We are heading toward greater inequality not inevitably but because of faulty choices about who has power in society and the direction of technology … In fact, UBI fully buys into the vision of the business and tech elite that they are the enlightened, talented people who should generously finance the rest.”

Acemoglu and Johnson write of various tools for achieving “a more balanced technology portfolio,” from tax reforms and other government policies that might encourage the creation of more worker-friendly AI to reforms that might wean academia off Big Tech’s funding for computer science research and business schools.

But, the economists acknowledge, such reforms are “a tall order,” and a social push to redirect technological change is “not just around the corner.”

The good news is that, in fact, we can decide how we choose to use ChatGPT and other large language models. As countless apps based on the technology are rushed to market, businesses and individual users will have a chance to choose how they want to exploit it; companies can decide to use ChatGPT to give workers more abilities—or to simply cut jobs and trim costs.

Another positive development: there is at least some momentum behind open-source projects in generative AI, which could break Big Tech’s grip on the models. Notably, last year more than a thousand international researchers collaborated on a large language model called Bloom that can create text in languages such as French, Spanish, and Arabic. And if Coyle and others are right, increased public funding for AI research could help change the course of future breakthroughs.

Stanford’s Brynjolfsson refuses to say he’s optimistic about how it will play out. Still, his enthusiasm for the technology these days is clear. “We can have one of the best decades ever if we use the technology in the right direction,” he says. “But it’s not inevitable.”

 

 

Original article here

 

 

15 May 2023
Comments: 0

Crying can teach you a lot about yourself  

 

 

Here is a non-exhaustive list of things that have made me cry: Any time I must chop, dice, or mince ingredients; a group of sea lions barking in the sun; sad music; receiving a free hot dog; the film 500 Days of Summer; a messy house.

The one emotion tying all of these experiences together, according to Ad Vingerhoets, an emeritus professor at Tilburg University and one of the world’s preeminent experts on crying, is a sense of powerlessness. Even in the context of positive tear-jerking events — like encountering a very small puppy or watching your best friend walk down the aisle at their wedding — there is a feeling of overwhelm, Vingerhoets says. “You also feel small and helpless and humble,” he says.

Humans come into the world crying, and we never really stop. As babies, we cry in order to get attention from our parents, signaling to them that we’re angry or scared or in pain or hungry or tired. In childhood and adolescence, we cry from physical pain, like a scraped knee, but as we develop empathy in our teenage years, external catalysts — like books, movies, and other people’s pain — elicit tears. As we get older, we may be moved to tears by beauty, awe, wonder, and sentimentality, says Lauren Bylsma, an associate professor of psychiatry and psychology at the University of Pittsburgh.

For some people, the well of tears has run dry. The stereotype that criers are seen as weaker or less masculine contributes to the well-trodden notion that boys (and men) don’t cry. Indeed, women report crying more frequently than men and with shorter gaps in between crying episodes than men. Then, there’s that thorny feeling of vulnerability associated with sobbing; to betray the veneer of stoicism is deeply uncomfortable for some, to admit you need help can be seen as a failure.

But have you ever stopped to consider why you’re crying? The root cause of the sadness or overwhelm? What about what you can learn from your tears? Mining the depths of your emotions can shed light on deeper insecurities, fears, pleasures, and relationship complications.

What our tears tell us

The presence of tears signals one basic message, says Randolph Cornelius, a professor of psychological science at Vassar College: I need help. “We’re asking other people to aid us,” he says. Research suggests tears are so effective at eliciting help because criers are seen as sadder, more helpless, less aggressive, and in need of interpersonal connection. According to one of Vingerhoets’ 2017 studies, people are more likely to offer help to a crying person compared to just a sad person with a dry face. “Recognizing that people [are] crying and in need of help is a pretty automatic process,” Cornelius says.

Throughout the entire lifespan, some of the most common triggers of tears, Vingerhoets says, are bereavement, heartache, and homesickness. (Though women do cry more often in general over more mundane and conflict-driven situations, “the difference between the sexes is not that big” when it comes to these main motivators of crying, Vingerhoets says.) Then there are the positive cries: Weeping not just over a separation, but a reunion; crying out of relief and not fear; shedding tears when receiving a gift, not only when having it taken away. “All of these negative situations that provoked tears, they all seem to have their opposite,” Vingerhoets says, “which also induces tears.”

We receive the most support when we cry in front of a partner or a friend, Bylsma says, someone who is best equipped to console and emotionally support us. Research shows that the presence of visible tears can also bring people closer together and promote social bonding. “If you are stressed, it’s important that you receive social support from others,” Vingerhoets says, “because that can buffer the negative effects of stress on your well-being.”

Subliminally or not, we may realize that turning on the waterworks gets us what we want. “I have a 10-year-old grandson and he can turn crying on and off,” Cornelius says. “Kids learn how to manipulate adults and so that stays with us.” Much has been written about the weaponization of tears, especially by white women, in order to protect privilege and garner sympathy. Research finds that fake criers are seen as manipulative, less reliable, less warm, less competent, and less accepted as friends, colleagues, or neighbors. But usually, Cornelius says, adults keep their tears in check, having learned the socially appropriate places to cry (in private, on the side of the road when you have a flat tire) and opting not to cry at our desks at work when we feel frustrated. That is, unless the situation is uniquely overwhelming, Cornelius says, like in the face of an unexpected tragedy.

Why the context of the cry matters

Popular convention maintains that crying is a cathartic experience, that we feel cleansed and weightless following a good weep. “That’s not always the case,” Bylsma says, “and it really depends on various contextual factors.” We’re likely to reap the most benefit from crying if we can shed a few tears in a safe place, Bylsma says. “We found in research if someone were to cry in a place where it might be embarrassing, where people might react in a negative way, like crying in front of people you don’t know well in a workplace setting, for example, someone’s going to feel worse after crying,” she says, “versus if you cry in a more supportive environment, like in front of a partner or friend that you’re more likely to have a benefit from.”

In one of Vingerhoets’ and Bylsma’s studies, they found that people who are depressed, anxious, or experiencing burnout cry more, but they did not feel relief after crying. Those who felt shame and embarrassment were less likely to feel better following a cry, too. People find more catharsis after crying when the situation that made them weepy was controllable — like a fight with their partner — as opposed to an uncontrollable event, like a death.

Bylsma also notes that chronically suppressing tears is associated with negative emotional effects, like less empathy and emotional support, based on surveys. So if you feel the need to cry in the middle of a work meeting, try to get yourself to a bathroom and let it out. On the contrary, for those who have no reason to cry and forgo weeping for a long time, even years, there’s no harm in that, Vingerhoets says. However, persistent bouts of crying and ruminating over the same issues might be a sign you need to change your approach to crying, Bylsma says. Try seeking the help of a therapist or mental health professional who can help you cope.

What crying reveals 

Regardless of what made you cry, whether it be a sad movie or a beautiful sunset, there is a deeper meaning. The presence of tears reveals what matters to you. “Sometimes our tears are signals to ourselves about the significance of events,” Cornelius says.

Consider the last time you cried. Was it an argument? An exhausting day? A delicious cupcake? What about those situations stirred up emotions? In the moment of the crying episode, try to process what, exactly, is making you cry, Cornelius says. “We do have an inner drive to know ourselves,” he says. “I think recognizing our emotions, giving them their due, allows us to do that.” Over time, you may recognize patterns in your emotions: I feel resentful in these situations, those comments make me feel embarrassed.

Having this bit of insight can help you reframe the situation: This isn’t an argument about taking out the trash, it’s an argument about respect. Sometimes tears can help reveal these underlying messages.

“When you have a realization about yourself, and that allows you to see yourself in a different way, you do feel empowered,” Cornelius says.

 

 

Original article here

10 May 2023
Comments: 0

5 Ways to Future-Proof Your Career in the Age of AI

Since last fall, artificial intelligence — in particular ChatGPT and its recently unveiled successor, GPT-4 — has taken center stage in conversations about the future of business, work, and learning. ChatGPT became the fastest-growing consumer application in history — outpacing Instagram and even TikTok — and Google lost $100 billion in market cap after a botched AI product demonstration raised questions about its ability to compete.

The stakes are high, not just for companies, but also for individuals hoping to navigate potentially massive implications for their own careers. For years, pundits have assured us that the key to surviving AI disruption was leaning into creativity and other (theoretically) unique human skill sets. But the new wave of AI is rapidly demonstrating that it can do far more than crunch numbers and analyze data: It can also create professional-level art and design (see DALL-E and Midjourney, among others) and create articles and copywriting that could displace many journalists and marketers.

We believe it’s no longer useful to debate whether this tool is “smarter “or “better” than us. The tools are here, and they’re already being widely used. What matters to us — Tomas, the author of the new book I, Human: AI, Automation, and the Quest to Reclaim What Makes Us Unique, and Dorie, a consultant and keynote speaker on personal branding and career development — is how we can better ourselves by using them.

Of course, there are nearly infinite tactical applications for AI. For instance, we can speed up our productivity by using GPT-4 or other tools (such as Microsoft’s Bing, which now integrates GPT-4, or its recently launched Copilot for all things work) to assist with brainstorming, creating drafts of emails, or performing rapid and complex research.

But above and beyond specific use cases, we’re interested in exploring the question of whether there might still be strategies that professionals can deploy to generate unique value, even as AI begins to showcase its prodigious (and exponentially increasing) power. In other words, what can we do personally to stave off the displacement that may happen as a result of AI and future-proof ourselves in the age of intelligent machines? Here are five strategies we find especially critical.

Avoid predictability.

It’s important to remember that AI isn’t generating new insights; it’s a prediction engine that merely guesses the most likely next word. At the micro-level, it’s helpful: “thank” is indeed often followed by “you.” But at a macro level, its suggestions tend to homogenize, and they’re only as good as the wisdom of the crowds, which is often the exact opposite of wisdom. In the famous words of Oscar Wilde, who would probably not have been a heavy user of ChatGPT: “Everything popular is wrong.”

And yet, this aspect of generative AI can be a powerful tool if you use it right. For instance, if you want to understand how most people think or feel about something, including their prejudices and misconceptions, you can use GPT-4 to access this common knowledge — or ignorance. But if we simply deploy the tools without question, their algorithms and nudges may turn us into more predictable creatures who eventually all start to sound the same.

Consider that whenever we let Gmail autocomplete our searches or emails, we relinquish a bit of originality and uniqueness, turning AI’s prediction into a self-fulfilling prophecy that makes us more predictable. While GPT-4 is a powerful tool for ideation and initial drafts, if you want to stand out, you may be better served (in some cases) by doing the opposite of what it suggests, because you’ll be bucking conventional wisdom. Just as some corporations have recognized that boilerplate “corporate speak” turns off customers, we may discover the advantage of sounding like ourselves — and embracing our own personality, serendipity, and unpredictability — when everyone else is turning to AI.

Hone the skills that machines strive to emulate.

There’s no question: GPT-4 has been trained to be respectful and polite (especially now that previous — ahem — vulnerabilities have come to light). Its responses display empathy (“I am sorry my answer upset you”), self-awareness (“I’m just an AI model and my answers are based on training data”), and even creativity (producing ingenious haikus about inequality, impersonating Elon Musk, and generating an infinite number of cheese jokes in multiple languages). But — to reiterate — those responses are based on text prediction, and AI is not capable of experiencing or displaying the human version of these soft skills. As Tomas has argued extensively, humans are wired to respond to genuine emotions — so actually knowing and caring about what others think and feel, truly understanding yourself, and being capable of creating something machines cannot is an essential strategy to set yourself apart in the age of AI.

Double down on “the real world.”

GPT-4 — like AI in general — is confined to the digital world, inhabiting a virtual cage of 0s and 1s. Sadly, so are many human activities these days. But it’s essential to recognize that one thing AI can’t disrupt is our analog, in-person connections with others, so it’s important to carve out time and safeguard those. As Harvard Professor Arthur C. Brooks summarizes the research, “Technology that crowds out our real-life interaction with others will lower our well-being and thus must be managed with great care in our lives.” Artifacts of pre-pandemic life like having meals with colleagues, attending conferences, and initiating conversation with a stranger may seem less pressing now that we’ve gone so long without them. But they represent an opportunity to build connections and gain insights that simply aren’t possible through AI — and thus, they represent a unique competitive advantage we still possess.

In a similar vein, original research — actually talking to people and identifying new insights — becomes critical, because AI can only connect past dots and information it’s already been presented with. When you tap into information that isn’t (yet) online through your lived experience or novel interviews and conversations, you’re adding something genuinely new to the cultural conversation that wouldn’t be possible through AI.

Develop your personal brand. 

AI tools have reached sufficient quality that they may well decimate the lower and middle ends of the market in many professions (for instance, copywriters and designers on freelance marketplaces, or those who work with cost-conscious customers eager to shake off expenses in favor of a free option). In some cases, AI may even match the quality with professionals at the highest echelons — but it’s almost certain those industry leaders won’t get displaced, and it’s because of the strength of their brands. Just as art-world buyers will pay exponentially more for a “real Rembrandt” rather than an equally beautiful painting by one of his lesser-known contemporaries, corporate leaders will likely continue to pay a premium to work with people viewed as the “top of their field” — partly as a statement of quality, and partly as a brand statement about whom they associate with and what they value. As one example, even the local tire shop or florist can use AI to create a logo. But only those with discernment and real money — so the thinking goes — can afford to use an elite group of agencies. The rise of AI doesn’t change the fact, crucially tied to human nature, that branding matters.

Cultivate expertise.

GPT-4 and other AI technologies are prodigious researchers that can summon a cavalcade of facts almost instantly. Unfortunately, some of those facts aren’t true — a form of the “hallucinations” that have, heretofore, plagued AI. (Indeed, one reader contacted Dorie asking where he could locate one of Dorie’s Harvard Business Review articles that ChatGPT had referenced. Unfortunately, this particular article didn’t exist.) Thus, while AI is an extraordinarily valuable tool, it can’t always be trusted to deliver accurate results — at least at this point. That’s why it’s so valuable to develop recognized expertise in your field. Even if AI performs “first draft” functions, it still has to be double-checked by a trusted and reliable source. If that’s you, you’ll continue to be sought out because you have the authority to vet AI’s responses.

. . .

AI technology has the power to transform our professional lives — perhaps in the very near future. By following these strategies, we believe you can find ways to identify and provide unique value, even as GPT-4 and other technologies advance. Even in changing times, that’s the clearest path to career insurance for yourself.

 

 

 

Original article here

04 May 2023
Comments: 0

Eat fibre first – and ditch the juice: five quick and easy tips for a much healthier meal

 

Whilst researching my latest book, Food for Life, I learnt that we’re very short of practical advice on food choices which are the most important things we can do for our health (humans and our gut microbes) and also to help the planet. I also learnt that how we eat can be as important as what we eat. Here are my top five, practical everyday tips to help you make small but sustainable changes across the year that will be far better for you than a few weeks of crash dieting or restrictive eating.

Start your meal with fibre and a simple vinegar and extra virgin olive oil dressing

One of the simplest ways we can help our bodies thrive and prevent over-eating is to change the order in which we eat our food. Reaching for the bread basket or bowl of crisps at the start of a meal results in a rapid increase in blood glucose levels and a subsequent insulin response. This will likely leave you feeling tired, hungry and irritable just a few hours later. This is because glucose is rapidly absorbed from starchy foods, and this is even quicker on an empty stomach.

Why not start with a grilled vegetable platter, a selection of crunchy veggies or zesty fresh chopped herbs with a simple extra virgin olive oil and vinegar or lemon dressing. The extra acidity can reduce overeating on your next course, by reducing hunger signals and may also reduce harmful blood sugar spikes.

Choose high-quality, non-meat protein

This can be grains, legumes, fungi or sustainable seafood sources. The importance of good quality protein in our diet is well known but what is less understood is that the classic combination of “meat and two veg” is not the only way to ensure we get the protein we need. Smoked tofu is surprisingly tasty and can be added to salads and stir fries for added protein.

I realised that not all fish is that healthy for us or the planet, but shellfish, such as clams and mussels, are an untapped source of sustainable, nutrient-rich seafood protein. These small and delicious foods are packed with protein, zinc, iron and B vitamins, as well as choline and iodine, making them a great addition to our diet.

Another unsung hero group in our diet is mushrooms. Mushrooms can replace meat in many dishes, bringing umami flavour, nutrients, protein and even vit D, if left on a sunny shelf, with a satiating and satisfying texture plus a positive impact on the environment.

Choose your drinks wisely

Many of us find plain water a bit boring and Brits are world famous for their love of builder’s tea: the mix of black tea, milk and sugar can contribute quite significantly to our energy intake, especially when it’s the gateway to a biscuit or two.

Try some of these delicious swaps, to make your next drink choice healthier by choosing something polyphenol-rich, probiotic or both.

If you like hot drinks, simply opting for black coffee over your builder’s brew will make a big difference. Coffee is rich in polyphenols and contains fibre and won’t contribute to excess energy intake if you drink it black or with a drop of unsweetened plant or whole cow’s milk. Green tea, especially matcha powder, has a host of well-known benefits thanks to specific polyphenols, including green tea catechins and fibre.

For cold drinks, avoid fruit juices and soft drinks. Opt instead for unsweetened live kombucha, which has a natural fizz and flavour with the added benefit of probiotic strains and no added sugar as it is fermented by the microbes.

For a hearty, filling alternative to shop-bought milkshakes and smoothies, natural kefir (made yourself or shop-bought) is a delicious and healthier alternative for adults and children alike. Add some almonds for crunch or chopped fruit for different flavours.

Add colour to your plate

The colours in our plants are there thanks to chemicals called polyphenols, also known as phytonutrients. These chemicals are produced by plants to protect themselves against environmental stressors, including drought, cold weather, hot weather, insects and parasites. A great example of this is the dark red colour of the oranges which grow in the foothills of Mount Etna in Sicily, where the nights are very cold and the days are very hot and dry.

It turns out these protective chemicals are also helpful for humans. This is why you should aim to eat lots of different colourful plants, choosing variety over the same familiar favourites, like iceberg lettuce and apple.

Different polyphenols are beneficial for different things. Beetroot is well proven to improve blood pressure and post-exercise recovery. Black beans are a staple in some of the longest-living humans and are the beans richest in polyphenols. A great way of introducing polyphenols is also to opt for colourful versions of your favourites, such as sweet potato and purple potato, purple carrots and purple sprouting broccoli, too.

Make simple tweaks to your daily staples like bread and yogurt

Pick bread with high levels of fibre, seeds and no added sugar. Many supermarket breads have lots of added ingredients to make them last longer on the shelf and increase their palatability. True sourdough bread only needs a simple base of flour, with the sourdough starter, water and salt, which can be found in supermarkets (thanks to brands like Bertinet bakery) or can be made at a local bakery or at home. Choose to eat breads with whole grains, seeds and different types of flour, like dark rye, and always look for a high fibre content, rather than a healthy-looking label.

Before doing the ZOE programme, I thought my breakfast of muesli with skimmed milk was exactly what I needed for the day ahead. I soon learned that this breakfast, washed down with a glass of orange juice, pushed my blood sugar to diabetic levels and I quickly changed the menu. Adding mixed nuts and seeds to plain natural yoghurt with some polyphenol-rich berries is a great way to enjoy a nutritious breakfast that won’t spike your blood sugar.

Natural yoghurt is also a great way to introduce probiotics to your diet so, if you want to give your yoghurt an extra probiotic boost, simply add a splash of kefir. This is also great for those who don’t yet love the taste of kefir and want to find a way of including it in their diet. Kefir is also a great addition to soups and stews; just make sure you don’t actually cook the kefir as it will kill the live microbes.

Another easy way to include more fermented foods every day is to use miso paste, rather than stock cubes, to add flavour and umami to your dishes. Simply stir a teaspoon of miso into your pasta sauce or into your steamed greens or to add flavour to a fish recipe.

Finally, swapping white rice and white pasta with whole grains is an easy win. Replace white rice with pearled barley, choose buckwheat over couscous (which is just mini pasta balls), and enjoy spelt spaghetti instead of plain white spaghetti, keeping your favourite dishes but making them more nutritious with these simple tweaks.

 

 

Original article here

01 May 2023
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Who Invented the Measurement of Time?

In modern times, clocks underpin everything people do, from work to school to sleep. Timekeeping is also the invisible structure that makes modern infrastructure work. It forms the foundation of the high-speed computers that conduct financial trading and even the GPS system that pinpoints locations on Earth’s surface with unprecedented accuracy.

But humans have likely lived by some version of the clock for a very long time. The ancient Egyptians invented the first water clocks and sundials more than 3,500 years ago. Before that, people likely tracked time with devices that did not survive in the archaeological record—such as an upright stick in the dirt that acted as a primitive sundial—or no device at all, says Rita Gautschy, an archeoastronomer at the University of Basel in Switzerland.

“It’s really difficult to get a grip on when people started with timekeeping,” Gautschy says. Simply by observing the location of the sunrise and the sunset each day and by watching how high the sun reaches in the sky, a person can construct a primitive calendar. These early human efforts at understanding the flow of time left no trace at all, she says.

The oldest sundial on record came from Egypt and was made around 1500 B.C.E. It consisted of a simple upright stick and a roughly semicircular base divided into 12 pie-shaped sections. The shadow of the stick gave an approximate hour of the day. Other early sundials measured time by the length of a stick’s shadow as the sun moved across the sky rather than by the movement of the shadow across the base, Gautschy says.

“It’s a first step, and if you accomplish this step, you can do fine-tuning and also adapt to different months,” she says. Sundials must account for both time of year and latitude to be truly accurate.

During the night, ancient people could track time by the apparent movement of the stars from east to west, Gautschy says. And for measuring discrete units of time, they used water clocks. These were vessels that either had holes for water to flow out of at a constant rate or were filled from another vessel and had markings on the inside to indicate increments of time. The oldest surviving water clocks were found in Egypt and Babylon, and the earliest of these date to around 1500 B.C.E. In China historical records claim that water clocks were invented by the Yellow Emperor, or Huangdi, a half-historical, half-mythical figure said to have lived between 2717 and 2599 B.C.E., says Zheng-Hui Hwang, a mechanical engineer at National Cheng Kung University in Taiwan, who has written about the history of ancient Chinese timekeeping devices. The earliest Chinese water clocks were probably outflow devices and were known as louke. The unit ke divided the day into 100 equal segments from midnight to midnight. Over time, Hwang says, inventors made these clocks more sophisticated by equipping them with multiple water supply vessels or otherwise adjusting them to ensure the rate of water flow remained stable.

Water would eventually lead to some extremely sophisticated timekeeping: by the early 700s C.E., Tang Dynasty monks developed a mechanical clock powered by a water wheel, Hwang says. In 1194 Sung Dynasty official Su Song built on this design to develop a 40-foot-tall (12-meter-tall) mechanical clock powered by a water wheel that worked much like the mechanical clocks that would be invented in Europe some 200 years later.

The ancient Chinese timekeeping system also divided each 24-hour day into two-hour segments. This system was also seen in ancient Japan and Korea, according to a 2004 paper in Publications of the Astronomical Society of Japan.

In modern times, an hour is always the same length, but ancient peoples around the world operated with a more complex system, says David Rooney, a historian of technology, former curator of timekeeping at the Royal Observatory in Greenwich, London, and author of About Time: A History of Civilization in Twelve Clocks (W. W. Norton, 2021). Some ancient timekeeping systems divided the light portion of the day into 12 segments and the night into 12 segments, but because days and nights vary in length throughout the year except at the equator, these “seasonal hours” were different lengths from day to night and across the year.

“If your religion demands prayer time being linked to things like sunrise or sunset, or if you’re working in the fields, as most people did then, patterns of daylight and darkness matter more than this idea of a universal hour,” Rooney says.

Seasonal hours coexisted with universal hours until the 15th century in Europe and up until the 19th century in Japan, Rooney says. “We used to live with a much more complex—and rich and diverse—temporal culture,” he adds.

Religion was a major driver of the standardization of time across cultures, both across the year and day to day, Gautschy says. In ancient Mesopotamia, Anatolia (today approximately Iraq and Turkey) and Greece, people developed lunar calendars to track rituals and feast days, she says, whereas people in Egypt focused more on the solar calendar and also had a calendar based on the star Sirius. People of Islamic cultures, Rooney says, used water clocks to track prayer and fasting, whereas Christians developed the mechanical clock in 14th-century Europe as a way to schedule prayer.

The bottom line, Rooney says, is that humans have been temporal creatures for far longer than the industrial age—although not always happily. After the Romans installed their first public sundial in 263 B.C.E., he says, the Roman playwright Plautus objected to the new fad of timekeeping via a character in one of his plays: “The gods damn that man who first discovered the hours, and—yes—who first set up a sundial here, who’s smashed the day into bits for poor me! You know, when I was a boy, my stomach was the only sundial, by far the best and truest compared to all of these…. But now what there is, isn’t eaten unless the sun says so. In fact, town’s so stuffed with sundials that most people crawl along, shriveled up with hunger.”

It’s a strikingly modern thought for being 2,200 years old, Rooney says. “That could be written in the 21st century and spoken in any office,” he says, “that we’re under the tyranny of the clock.”

 

 

Original article here

28 Apr 2023
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Why Six Hours Of Sleep Is As Bad As None At All

Not getting enough sleep is detrimental to both your health and productivity. Yawn. We’ve heard it all before. But results from one study impress just how bad a cumulative lack of sleep can be on performance. Subjects in a lab-based sleep study who were allowed to get only six hours of sleep a night for two weeks straight functioned as poorly as those who were forced to stay awake for two days straight. The kicker is the people who slept six hours per night thought they were doing just fine.

This sleep deprivation study, published in the journal Sleep, took 48 adults and restricted their sleep to a maximum of four, six, or eight hours a night for two weeks; one unlucky subset was deprived of sleep for three days straight.

During their time in the lab, the participants were tested every two hours (unless they were asleep, of course) on their cognitive performance as well as their reaction time. They also answered questions about their mood and any symptoms they were experiencing, basically, “How sleepy do you feel?”

Why Six Hours of Sleep Isn’t Enough

As you can imagine, the subjects who were allowed to sleep eight hours per night had the highest performance on average. Subjects who got only four hours a night did worse each day. The group who got six hours of sleep seemed to be holding their own, until around day 10 of the study.

In the last few days of the experiment, the subjects who were restricted to a maximum of six hours of sleep per night showed cognitive performance that was as bad as the people who weren’t allowed to sleep at all. Getting only six hours of shut-eye was as bad as not sleeping for two days straight. The group who got only four hours of sleep each night performed just as poorly, but they hit their low sooner.

One of the most alarming results from the sleep study is that the six-hour sleep group didn’t rate their sleepiness as being all that bad, even as their cognitive performance was going downhill. The no-sleep group progressively rated their sleepiness level higher and higher. By the end of the experiment, their sleepiness had jumped by two levels. But the six-hour group only jumped one level. Those findings raise the question about how people cope when they get insufficient sleep, perhaps suggesting that they’re in denial (willful or otherwise) about their present state.

We Have No Idea How Much We Sleep

Complicating matters is the fact that people are terrible at knowing how much time they actually spend asleep. According to the Behavioral Risk Factor Surveillance System survey, as reported by the CDC, more than 35% of Americans sleep less than seven hours in a typical day. That’s one out of every three people. However, those who suffer from sleep problems don’t accurately estimate how much they sleep each night.

If you think you sleep seven hours a night, as one out of every three Americans does, it’s entirely possible you’re only getting six.

Research from University of Chicago, for instance, shows that people are as likely to overestimate how much they sleep as underestimate it. Another sleep study published in Epidemiology, indicates people generally overestimate their nightly sleep by around 0.8 hours. The same study also estimates that for every hour beyond six that people sleep, they overestimate sleep by about half an hour. If you think you sleep seven hours a night, as one out of every three Americans does, it’s entirely possible you’re only getting six.

So no one knows how much or little they’re sleeping, and when they don’t sleep enough, they believe they’re doing better than they are.

Even just a little bit of sleep deprivation, in this case, six rather than eight hours of sleep across two weeks, accumulates to jaw-dropping results. Cumulative sleep deprivation isn’t a new concept by any means, but it’s rare to find research results that are so clear about the effects.

Fixing Sleep: Easier Said Than Done

Figuring out how to get enough sleep, consistently, is a tough nut to crack. The same advice experts have batted around for decades is probably a good place to start: Have a consistent bedtime; don’t look at electronic screens at least 30 minutes before bed; limit alcohol intake (alcohol makes many people sleepy, but it can also decrease the quality and duration of sleep); and get enough exercise.

Other advice that you’ll hear less often, but which is equally valid, is to lose excess weight. Sleep apnea and obesity have a very high correlation, according to the National Sleep Foundation. What’s more, obese workers already suffer from more lost productive time than normal weight and overweight workers.

Other causes of sleep problems include physical, neurological, and psychological issues. Even stress and worry can negatively affect sleep. The CDC has called lack of sleep a health problem, and for good reason. Diet, exercise, mental health, and physical health all affect our ability to sleep, and in return, our ability to perform to our best.

Fixing bad sleep habits to get enough sleep is easier said than done. But if you’re functioning as if you hadn’t slept for two days straight, isn’t it worthwhile?

 

 

Original article here