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Human Behavior

Robert Kirby: Where are the grown-ups in Washington? – Salt Lake Tribune

I forced myself to watch the State of the Union address and the final days of the impeachment proceedings against President Donald Trump. Post-traumatic stress doesnt even begin to cover the result.

There is a bit of hope. I used to be the most immature person I know. Today, I am far more mature than most of Congress.

Granted, this is nothing to brag about, because so is the average high school detention class, a car full of circus clowns and perhaps even the participants in a soccer riot.

Trump emerged as the gloating victor, Nancy Pelosi as the thwarted kindergartner. Not only was I embarrassed to be an American, but for a while there I also wished that I belonged to a different species.

Thats government. When people dont get what they want for Christmas, out come the tantrums.

I appreciate that we all are entitled to our own political opinions. But as someone more interested in human behavior than politics, I tend to travel both sides of the road. Behavior says a lot more than ideals.

For example, when it comes to politics, Im more of a Rep. Ben McAdams guy than a Sen. Mitt Romney guy. But guts are guts and should be noted.

As near as I can tell, the most mature person in the mess was Romney. It takes a lot of strength to defy your associates over your conscience.

I dont have much of a conscience. But people I know and respect who do have told me that it took a lot of courage for Romney to do what he did in casting a guilty vote against the president.

On Thursday, Trump acknowledged that he has done things wrong in his life, but and heres the kicker never intentionally. Meaning any wrongdoing he ever committed was entirely by accident.

Ha! If this is true and its not hes the only person in the world who has ever caused a single problem simply by not paying attention. That alone should disqualify him for the job of president.

Unlike Trump, Ive done a lot of things wrong almost all of them on purpose, including some of which Im still rather proud.

But Im not the president of the United States, any of its lesser leaders, a well-respected religious figure, a beacon of hope to the downtrodden or much of a good neighbor. Hell, I cant even drive well. Very little should be expected of me.

I couldnt make it all the way through Trumps self-congratulatory speech Thursday. Had there been even a hint of look what we got away with in the blathering to friends and supporters, I might have stuck with it.

On the other hand, I didnt bother to watch any of House Speaker Pelosis wrapup of how things came off the rails. After her grade-school stunt following Trumps State of the Union address, she should stick to paper shredding instead of government.

Then again, shes entitled to express her opinion. I wouldnt blame anyone for tearing up this column. Just make sure its real paper and not your computer monitor.

Maybe Pelosi should take a note from the president and claim that tearing up his speech was entirely unintentional.

Its not her fault that her hands went off by accident.

Originally posted here:
Robert Kirby: Where are the grown-ups in Washington? - Salt Lake Tribune

Human Behavior

Science Hasn’t Refuted Free Will – Boston Review

Image: 9DreamStudio

A growing chorus says that science has shown free will to be an illusion. But it actually has offered arguments in its favor.

When we walk into a coffee shop, we think it is up to us whether to have an espresso, cappuccino, or strawberry-toffee-flavored latte with soymilk. Similarly, when we think about more serious matterswhich job to apply for, whether to get married, or whether to sacrifice our self-interest to do the morally right thingwe tend to think those choices are up to us, too. Of course, what we do is constrained by our environments, means, and habits. We are susceptible to subconscious influences and nudges, as psychologists and marketing experts know too well. But there still seems some room for choice. When I had my coffee this morning, I could have had a tea instead. This, in a nutshell, is the idea of free will: people have the capacity to choose and control their own actions.

An increasing number of popular science writers and some scientists are telling us that free will is an illusion.

Yet an increasing number of popular science writers and some scientists are telling us that free will is an illusion. The author Sam Harris and the biologist Jerry Coyne are just two prominent examples. When asked by Edge What scientific idea is ready for retirement? Coyne, for instance, volunteered free will, writing, Our thoughts and actions are the outputs of a computer made of meatour braina computer that must obey the laws of physics. Recently this line of thinking has even made it into popular writings by scholars in the humanities, as well. In his latest book, 21 Lessons for the 21st Century (2018), the historian Yuval Noah Harari speculates that in the age of big data, free will will likely be exposed as a mythand that this, in turn, has significant ramifications, among them that liberalism might lose its practical advantages.

According to the skeptics, human actions arent the result of conscious choices but are caused by physical processes in the brain and body over which people have no control. Human beings are just complex physical machines, determined by the laws of nature and prior physical conditions as much as steam engines and the solar system are so determined. The idea of free will, the skeptics say, is a holdover from a nave worldview that has been refuted by science, just as ghosts and spirits have been refuted. You have as little control over whether to continue to read this article as you have over the date of the next total solar eclipse visible from New York. (It is due to take place on May 1, 2079.)

Such free-will skepticism may not yet be embraced by the general public. Nor is it new; the philosophical debate about whether free will is compatible with determinism stretches back centuries, and the modern scientific debate has been roiling at least since the famous neuroscience experiments on the alleged neural causes of voluntary actions conducted by Benjamin Libet in the 1980s. Still, this skepticism makes trouble for some deeply held views about ourselves. The idea of free will is central to the way we understand ourselves as autonomous agents and to our practices of holding one another responsible.

Lawyers, for example, are well aware of that, and the questions that neuroscience raises for the law have become a growing area of study in legal scholarship. How, for instance, could we blame and punish people for something they did not do out of their own free will? When an avalanche harms someone, it would not occur to us to blame the avalanche: unlike you and me (at least as most people see it), it is not a moral agent capable of responsibility. When a person harms another, we hold that person responsible. If the skeptics are right, this is a mistake. In both the human case and the avalanche, the skeptics say, the harm results from physical processes inside a heap of atoms and molecules.

The idea of free will, the skeptics say, is a holdover from a nave worldview that has been refuted by sciencejust as ghosts and spirits have been refuted.

Some free-will skepticsincluding Harris and Coyne but also the philosophers Derk Pereboom and Gregg Carusowelcome these implications. They point out that, as a society, we are far too obsessed with responsibility, punishment, and retribution. Many of the worlds criminal justice systems are inhumane as well as counterproductive. The skeptics have a point here, but one can support criminal justice reform while holding on to ones belief in free will. Human dignity and restorative justice should be reasons enough to focus more on rehabilitation and reintegration of offenders and on tackling the social background conditions of crime. Giving up on the idea of free will, by contrast, would have other unsettling implications, independently of anything to do with blame and punishment. For example, how could we sincerely deliberate about important choices if we didnt take ourselves to be free in making those choices? The philosopher Immanuel Kant already understood this problem when he noted that we must view ourselves as free when we engage in practical reasoning.

It is important to ask, then, whether free will can be defended against the skeptical voices, or whether, instead, its defenders are clinging to a superstition. I think that science has not refuted free will, after all. In fact, it actually offers arguments in its defense.

Contemporary free-will skepticismat least of the kind that appeals to scienceis part and parcel of a reductionistic worldview, according to which everything is reducible to physical processes. If we look at the world from the perspective of fundamental physics alone, then we will see only particles, fields, and forces, but no human agency, choice, and free will. Human beings, like everything else, will look like subsystems of a large impersonal physical universe. Of course, skeptics say that this is, in fact, what science implies. To suggest that human beings are anything beyond physical systems would be to revert to seventeenth-century metaphysics, the sort of mind-body dualism endorsed by Ren Descartes from which modern science has moved on.

Science has not refuted free will, after all. In fact, it actually offers arguments in its defense.

But it is a mistake to equate science with reductionism. Science does not force us to think of humans as nothing more than heaps of interacting particles. To the contrary, in the sciences of human behaviorfrom anthropology and psychology to economics and sociologyit is standard practice to think of people as intentional agents with a capacity for making choices and responding intelligently to their environments. Scholars in these fields explain human actions by depicting people as choice-making agents with beliefs and desires, goals and plans, on the basis of which they decide which actions to pursue. Different academic fields spell out the details in different wayswith different levels of emphasis on, for instance, the relationship between individual and structural factors influencing human actionsbut the general supposition of intentional agency is nonetheless present in all of them. This explanatory practice does not assume anything supernatural. It just reflects the fact that agency, intentionality, and choice are essential postulates if we wish to make sense of human behavior. So, the first point to note is that science would have a hard time explaining human behavior if it didnt view people as choice-making agents.

To illustrate, think about how we answer familiar questions about humans. Why does someone who has made an appointment normally show up? Why does a taxi driver take you to your specified destination? Why do consumers respond to price changes? Why do people support the political movements they do? In each case, the picture of humans as choice-making agents helps us to give the answer. The behaviors in question are readily intelligible if we think of people as having agency, intentionality, and choice. They are faced with different options, look at these options from their perspective, and select one of the options in a goal-directed and more or less intelligible manner, even if the resulting choices are not always fully rational. If we thought of people as mere physical machines, we would miss the intentional, goal-directed nature of their actions and get overwhelmed with physical details. We wouldnt see the forest for the trees. It would be like trying to explain investors market transactions, voters electoral choices, or peoples cultural activities from the perspective of particle physics. Physics and even physiology are not the right approaches for explaining human behavior in its full rangeholistically,we might say. At most, they can give us some insights into the mechanisms by which agency is generated in physical organisms. This is not to belittle those insights. Human agency and choice are among the most remarkable phenomena the physical world has produced, and as scientists and philosophers will acknowledge, there is much more to be explained. But this does not justify a reductionistic approach according to which the phenomena themselves are overlooked and get to be discounted.

Science does not force us to think of humans as nothing more than heaps of interacting particles.

Now, once we think of human beings in this nonreductionistic way, we are actually presupposing some form of free will, though liberated from supernatural undertones. That there is such a presupposition in our explanations of human behavior is seldom acknowledged, perhaps because free will is such a controversial concept and the practitioners of the relevant sciences may be reluctant to get drawn into metaphysical debates unless strictly necessary. However, free will, soberly speaking, can be defined as the capacity for intentional agency, choice among alternative possibilities, and control over the resulting choices. This capacityit should be clearis presupposed when scientists depict people as choice-making agents, whether in anthropology, psychology, economics, or sociology.

The skeptics will object that all this is at best a useful fiction, at worst a harmful one. At any rate, they will say, the free-will presupposition is not literally true. But consider how scientists settle questions about what is and is not real.

Why do scientists accept gravity and electromagnetism as real, but not ghosts and spirits? The answer is that science must refer to gravity and electromagnetism to explain physical phenomena, and these properties are indispensable ingredients of a coherent theory of the world, while postulating ghosts and spirits is not only useless but also prone to introducing all sorts of incoherencies. Generally, to figure out whether some entity or property is real, scientists ask two questions: first, is postulating the entity or property necessary for explaining the world, and second, is it coherent with the rest of our scientific worldview? If the answer to both questions is yes, then the entity or property meets the reality check, and scientists feel ready to include it in their inventory of the world, at least provisionally.

If the human and social sciences must postulate intentional agency and choice to explain human behavior, then those properties pass the first part of the scientific reality test: they are explanatorily indispensable.

This test, a version of Occams Razor, can be applied not just to physics. It also supports the reality of higher-level entities and properties such as ecosystems, institutions, and poverty. These, too, must be accepted as real if we wish to explain our world, and they are ingredients of a coherent scientific worldview, even if fundamental physics does not speak about them. When we think about free will through the lens of this test, we get a new perspective. If the human and social sciences must postulate intentional agency and choice to explain human behavior, then those properties pass the first part of the scientific reality test: they are explanatorily indispensable.

What about the second partcoherence with the rest of our scientific worldview? Here, the skeptics will object that if the fundamental laws of physics are deterministiclike the mechanisms of a precise clockworkthen there is no hope of rendering the notion of choice-making coherent. At any point in time, there will be only one possible future sequence of events, given the physical past. Traditionally, physical theoriesfrom Isaac Newtons classical mechanics to Albert Einsteins theories of relativityhave tended to represent the world this way.

Furthermore, even though indeterminism and randomness seemed to enter physics with the emergence of quantum mechanics (at least on the well-known Copenhagen interpretation), it is still an open question whether future, more advanced theories will retain this indeterminism. Einstein was famously unconvinced by the idea of indeterministic physical laws when he said, God does not play dice. Given that determinism has not been conclusively ruled out by science, therefore, we cant count on quantum mechanics to defend free willnot to mention that quantum indeterminacies would probably be a farfetched source of free will anyway. Indeed, hard determinist skeptics insist that we never have any real choices. When you appeared to make a choice about whether to read this essay, only one option was genuinely available (reading it, as you are doing right now); the other option never existed.

These are subtle issues, but deterministic physical laws arguably do not preclude forks in the road within human agency. An agents future choices can be open at a psychological level even if the underlying physics is deterministic. Though this may sound counterintuitive, the distinction between determinism and indeterminism cannot be drawn independently of the level of description at which we are looking at the world. A system can behave deterministically at one levelsay, the microphysical oneand indeterministically at anothersay, the level associated with some special science: chemistry, biology, meteorology, and so on.

Deterministic physical laws arguably do not preclude forks in the road within human agency. An agents future choices can be open at a psychological level even if the underlying physics is deterministic.

Physicists themselves recognize this point in the field of statistical mechanics, which describes how indeterministic macro phenomena can result from deterministic micro processes. The weather, for instance, is a macro system that behaves indeterministically even though the atmosphere consists of a large number of individual molecules that each movearound according to deterministic laws of motion. At a macro level, then, the Earths atmosphere can be thought of as indeterministic, despite being deterministic at a micro level. As the philosopher of physics Jeremy Butterfield puts it, a systemsmicro- and macro-dynamics need not mesh. And, I would argue, such emergent indeterminism is not just apparent. It is best interpreted not as epistemicdue to incomplete information about the worldbut as ontic: a feature of what the world is like. So, to cut a long story short, the sciences give us the resources to show that forks in the road in human decision-making can co-exist with determinism in physics. Of course, the openness of human choices is not just a phenomenon of statistical mechanics; it comes from option availability as described by our best explanatory theories of human decision-making.

For the time being, then, the hypothesis of free will is corroborated by the sciences of human behaviour. Free will, for the purposes of the human and social sciences, boils down to agency, intentionality, and choice, which are well-supported and indeed explanatorily indispensable ideas. Denying free will would be warranted only if these ideas werent needed for explaining human behavior or if they were somehow incoherent, which they arent.

To be sure, future science might vindicate a reductionistic approach and explain human behavior without representing people as choice-making agents. But science doesnt seem to be heading that way. So far, psychology, broadly speaking, has resisted reduction and has been augmented but not replaced by neuroscience. Just as we wouldnt deny the reality of ecosystems, institutions, and poverty merely because fundamental physics doesnt refer to them, so there is no reason to deny the reality of agency, choice, and free will either. The skeptics mistake is to assume a reductionistic picture of humans that is neither mandated by science, nor adequate for understanding human behavior.

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Science Hasn't Refuted Free Will - Boston Review

Human Behavior

Scientists are racing to model the next moves of a coronavirus that’s still hard to predict – Science Magazine

This model shows the most probable routes that the novel coronavirus will take tospread from the international airport in Beijing to airports around the world. Bubble size represents relative risk at each airport.

By Jon CohenFeb. 7, 2020 , 6:15 PM

Beyond China itself, Thailand is the country that most likely will have people who arrive at one of its airports with an infection by the novel coronavirus (2019-nCoV) that has sickened more than 30,000 people. So says the latest update of a global risk assessment model created by a team of researchers from the Humboldt University of Berlin and the Robert Koch Institute that relies on air travel data.

Next on the teams list is JapanOsakas international airport, interestingly, is more at risk than Tokyoswhich is followed by South Korea, Hong Kong, and then the United States. Russia likely has more infected people flying in than India, Germany (mainly the Frankfurt and Munich airports) is the most vulnerable country in Western Europe, and Ethiopia is the only sub-Saharan African country to break into the top 30 of virus-threated countries.

So, how seriously should this model, and the dozens of other computer simulations of the outbreak, be taken? Scientists studying the 2019-nCoV outbreak are getting plenty of data to groundtruth and tweak their models. As of yesterday, for example, the most confirmed cases outside of mainland China were in Japan (45), Singapore (28), Thailand (25), Hong Kong (24), and South Korea (23). That could be considered a partial success for the Berlin model, but it also reflects that this is a dynamic outbreak that upends assumptions at a blinding speed; for example, the airport in Wuhan, China, the outbreaks epicenter, was closed on 23 January, which radically altered airline exportation of the virus, and today there are 61 confirmed cases on a cruise ship off the coast of Japan.

This is not so much a tool for making quantitative predictions, says Dirk Brockmann, a physicist at Humboldt who leads the modeling team. Public health officials and policymakers have to develop an intuition because this virus is something unknown. Models can help you develop an intuition.

A flurry of models of the 2019-nCoV outbreak have been shared on websites, preprint servers, and in peer-reviewed journals, and many attempt to do far more than just sharpen hunches about where infected air travelers are going to land. If they have robust enough data, models can forecast the rate at which an outbreak will grow and help predict the impact of various interventions. When you start to include disease dynamics and population information, theres more information than just intuition, says Alessandro Vespignani, an infectious disease modeler at Northeastern University.

The centerpiece of many outbreak/infectious disease/pathogen models is the basic reproduction number, or Ro (pronounced R zero or R naught). Its essentially how many people each infected person can infect if the transmission of the virus is not hampered by quarantines, face masks, or other factors. Modelers also look at the incubation time, which is how long it takes for the virus to cause symptoms. The serial interval factors in the time between a person developing symptoms and a contact becoming ill. In this young outbreak, unknowns riddle every model. The current estimate for 2019-nCoVs incubation time has been hard to pin down with the U.S. Centers for Disease Control and Prevention, suggesting theres a range of 2 to 14 days. There are many things that should be carefully weighted at this point, and thats why the modeling has difficulties, Vespignani says.

One of the first models to come outby a group at Imperial College London on its website on 17 Januarylooked at confirmed infections outside China to infer the number of infections that likely had occurred in Wuhan. At the time the group released that model, Wuhan had only reported that 41 illnesses were caused by the virus, and the model estimated that by 12 January, the infection had actually sickened 1723 people in the city. Those estimates, which were startling at the time, seem quaint now: As of 5 February, there were 27,619 confirmed cases, and a modeling study by the University of Hong Kongs Joseph Wu and colleagues that was published online by The Lancet on31 January estimated that Wuhan alone had 75,815 cases by 25 January.

Many of the early calculationsincluding the initial airport analysis done by Brockmanns teamlost all meaning after Wuhan shut down public transportation. That was just over 2 weeks ago, which seems like 2 years ago now, Vespignani says.

One of the most vexing mysteries at the moment that can undermine modeling is whether people with 2019-nCoV who do not have symptoms can transmit an infection. Its possible that there are infected people who never become ill but still transmit. There also may be infected people who transmit before they develop symptoms. Most of the fate of the epidemic is in this element, Vespignani says.

The viral diagnostic tests being used to confirm cases now typically are only done on people seeking care because they are ill. One way to find asymptomatic or presymptomatic cases is to examine peoples blood for signs of an immune response to 2019-nCoV. To know the full extent of spread youd like to collect blood samples from contacts of infected people and do the same 2 weeks later and see if theyve developed antibodies to the virus, says Marion Koopmans, whose team at Erasmus Medical Center is racing to develop an antibody test for 2019-nCoV. That gives you a better estimate of spread without symptoms.

Models may also become sharper as researchers have a finer understanding of the epidemiology of infected cases, which means details about their location, health, age, and gender. Those data can help modelers make more reliable assumptions about factors like incubation time. To that end, computational epidemiologist Moritz Kraemer at the University of Oxford has spearheaded an unusual effort to compile a line list of confirmed cases by sifting through government reports, the medical literature, reliable media accounts, and social media. Line lists contain incredibly useful information that are not visible in aggregated case counts, Kraemer says. Unfortunately, line list data are rarely available during outbreaks and until now only routinely collected by governments that do not share them openly.

This line list, which has more than 15,000 cases on it now, documents everything thats public about infected individuals. His group has already used the data in a study that assesses the capacity of countries in Africa to detect and respond to cases; two of the five most vulnerable countries on the continent, Ethiopia and Nigeria, have what they call variable capacity to respond to the outbreak. A modeling study by a different group used the data to assess transmission dynamics, concluding that once a place has three cases, there is more than a 50% chance the virus can become established in the population.

On top of needing better data, models also suffer from how their forecasts are interpreted by journalists or the public. Robin Thompson, a mathematical epidemiologist at Oxford who has modeled the outbreak, contends many news stories have garbled descriptions of Ro, the basic reproduction number, and exaggerated the risk of spread. Its being misused in this outbreak, Thompson says.

Most estimates for 2019-nCoV calculate that Ro is between two and threethat an infected person will infect two or three others. But this is just an average. Some infected people, by chance, wont transmit the virus to anyone else. The real question from a population standpoint is what is the probability with an Ro of, say, 2.2, that there will be sustained transmission of the virus? With this new virus, Thompson calculates theres a 54.5% chance of sustained spread starting from a single infected person if nothing, for example a vaccine, prevents transmission.

Ro does not change during an outbreak: A virus has a certain, fixed contagiousness factormeasles, for example, more easily spreads between people than influenza. But even in the absence of a vaccine, human behavior and the environment itself can alter the likelihood of spread. Hospitals isolate infected people or they choose to stay home. A further decrease also often occurs as an outbreak matures and many people become immune because of previous exposure, reducing the number of susceptible hosts. Hand washing, wearing protective garb, and social distancing can also reduce transmission rates. A climactic shift, like winter becoming spring, may affect the ability of a respiratory virus to transmit through the air.

In the lingo of modelers, what matters most is not the unchanging basic reproduction number of Ro, but what they somewhat unimaginatively refer to as the reproduction number, or R, that factors in these other variables. R is constantly in flux. Heres an example of R, expressed as a percentage: Thompson calculates that if 50% of infected symptomatic people are isolated and 20% are asymptomatic, then the risk of sustained transmission is 24.2%.

The take home message from this R analysis is that countries other than China still have a good chance of containing 2019-nCoV. Early on in an outbreak, you can take advantage of the fact that theres this probability of the thing fading out, Thompson says. And if you can isolate the few infected people you have very quickly, then the probability of this fading out is much higher.

Ultimately, models are a science-based attempt to inform public health policy. Take travel restrictions. Wu says he doubts that restricting travel from Wuhan will have any impact on spread within China at this point. He points to calculations by an international team of scientists that the Wuhan travel restrictions, which those researchers described as the largest quarantine in human history, delayed spread to other cities in China by just 2.91 days. Keeping Wuhan locked down now would not make a difference for [epidemiological] curves for other cities in China now, Wu says. Now, social distancing there is essential.

Hong Kong, which has 24 confirmed cases to date, waited until today to close its own borders to people from mainland China. The public had asked the government to reduce the flow from the mainland, and the government had different reasons for not wanting to do that, Wu says. Public health is a priority, but the economy is also a major concern. If it cuts people flow, it can also cut the supply chain of necessary products to Hong Kong.

So the balance between public health and politics factor in to 2019-nCoVs spreadwhich means a refined understanding of Ro and R, incubation time, the serial interval, and other variables can only sharpen a models predictive powers to a point. As most every honest modeling paper cautions, There are limits to this analysis.

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Scientists are racing to model the next moves of a coronavirus that's still hard to predict - Science Magazine

Human Behavior

Girija Kaimal and art positivity – Drexel University The Triangle Online

While there has long since been a presumed connection between creating art and happiness, Drexel professor Girija Kaimals research proves it.

Drexel Universitys Girija Kaimals extensive research in art therapy was featured in National Public Radios Life Kit newsletter and podcast last month.

Life Kit, which focuses on health, money, parenting and life skills, published two back-to-back articles featuring Kaimals research. Making Art Is Good for Your Health. Heres How To Start A Habit gave readers six ways to make creativity a healthy life-long habit, while Feeling Artsy? Heres How Making Art Helps Your Brain focused on the science behind what happens to your body when you make art and why it is so therapeutic.

Kaimal is an associate professor at Drexel University and is listed as an expert in research in the Creative Arts Therapy Department, but she did not originally go to school for therapy, she said. She was torn between getting an undergraduate degree in design or psychology, unaware that art therapy was even an option. It combined the interests she was struggling to choose between.

I ended up choosing design, but part of me was very eager to do psychology. I was always curious about human behavior and very curious about why people do what they do. Im still fascinated by it everyday, Kaimal said.

Kaimal completed her Masters in Art Therapy from Drexel in 2001 and her doctorate in Human Development and Psychology from Harvard University. She practiced art therapy and worked with youth, HIV patients and in hospitals before returning to Drexel in 2013, researching and teaching for the program she graduated from.

Kaimal considers herself an artist to this day, working mostly with natural media like tree bark, leaves and clay reimagining and repurposing her materials. After receiving her Bachelor of Arts in design, she finally discovered art therapy.

Although this is not the first time that Kaimals work has been featured in the media, she was particularly excited about the responses the Life Kit focus solicited. People reached out to her to let her know that the articles had helped or in some way empowered them.

When asked about how she felt seeing her work published, Kaimal was ecstatic. That made me very happy, its sort of why we do this, its to empower people to get out there and do their thing. I didnt know art therapy was a thing, but when I discovered it, it made a lot of sense to me so when I discovered art therapy, I felt like it was a perfect combination of my interest in art and connecting it to psychology.

As Kaimal told NPR, art can reduce stress and improve your mood, and it benefits those who are willing to try. Someone who is eager to learn more about themselves and wants to share their experience but doesnt always have the words for it, art therapy is really perfect for that, because sometimes we can express ourselves in ways we dont always have words for, Someone struggling with communication.

As Kaimal mentioned in the NPR article, you dont need to be incredibly skilled to consider yourself an artist. She has worked with clients who possess a broad range of artistic skillsets.

Someone who comes in with a perception that theyre not skilled they are the ones I find surprise themselves. Other times there are people who come in and they might not be so happy with the final product because they set a higher bar for themselves and I try to remind them about what the project means, what they got out of it, not as much about the outcome, Kaimal stated.

In both cases, Kaimal said that she finds that most people leave with a sense of relief in having the ability to express themselves in a nonjudgmental way. While she is not aware of any current art therapy services for Drexel students, she thinks that it would be a great addition to the school.

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Girija Kaimal and art positivity - Drexel University The Triangle Online

Human Behavior

Fueled by ‘Eco-Anxiety,’ Majority in US Believe Climate Crisis Most Crucial Issue Facing Society: Poll – Common Dreams

New polling results published Thursday revealed that a majority of U.S. adults believe climate change is the most important issue facing society, have made an effort to reduce their contribution to the global crisis, and are willing to vote for a candidate based on their position on the topic.

Among those aged 1834, 47% indicated that "the stress they feel about climate change affects their daily lives."

The American Psychological Association (APA) surveyconducted in December 2019 by the Harris Pollcomes on the heels of Iowa's first-in-the-nation caucuses for this year's presidential race, where entrance polling showed that the climate crisis was the second-most important issue to caucusgoers, behind healthcare.

According to the online APA poll, 56% of respondents said climate change is the most important issue, 60% have changed a behavior to cut their contributionsuch as reducing waste, using renewable energy, and altering transportation or diet choicesand 62% are willing to vote for a political candidate based on their climate position.

The survey showed that people were most motivated to change their behavior based on a desire to preserve the planet for future generations (52%) and after hearing news reports about the climate crisis and its impacts like more devastating extreme weather (43%). APA also found that respondents, particularly those aged 1834, are stressed about how the planetary emergency impacts their lives.

More than two-thirds of all adults surveyed (68%) said that they have at least a little "eco-anxiety," which Oxford Dictionaries defines as "extreme worry about current and future harm to the environment caused by human activity and climate change." Among those aged 1834, 47% indicated that "the stress they feel about climate change affects their daily lives."

In a statement announcing the poll results, APA chief executive officer Arthur C. Evans Jr. said that "the health, economic, political, and environmental implications of climate change affect all of us. The tolls on our mental health are far reaching."

"As climate change is created largely by human behavior," Evans added, "psychologists are continuing to study ways in which we can encourage people to make behavioral changesboth large and smallso that collectively we can help our planet."

The number of young American adults stressed about the climate crisis, as captured in the APA's new survey, could have an impact on upcoming political contests in the United Sates, including the Democratic presidential primary race and the general election in November.

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The nation is still waiting on the final outcome of the Iowa caucuses due to a debacle with collecting and reporting the results. However, the data released so far from 97% of precinctswhich are "riddled with inconsistencies and other flaws," according to a New York Times analysisshow Sen. Bernie Sanders (I-Vt.) leading the popular vote while effectively tied with former South Bend, Indiana Mayor Pete Buttigieg when it comes to state delegates.

Entrance polling from Iowa reported by the Washington Post showed that 21% of caucusgoers said climate change was the "most important issue" in the vote. That compared with 42% who said healthcare, 18% who said income inequality, and 13% who said foreign policy. That polling also showed 37% of participants were first-time caucusgoers and the youth voter share rose a third from 2016.

Responding to those results in a statement Tuesday, the youth-led Sunrise Movementwhich endorsed Sanders last monthsaid that "we don't yet know everything that happened last nightbut we do know this: there is a broad, widespread mandate for the Green New Deal, and Iowans turned out in force last night to make sure presidential candidates don't forget it."

"We're particularly proud of the historic levels of turnout among young people who caucused last night, many of whom were brought into the movement by our efforts to engage them in college classes and high school gyms across the state," Sunrise said. "The level of youth turnout and concern about climate change in the Iowa entrance polls is incredible It's a major mark of success for our Iowa team's work these past six months. They got 7,000 young people to pledge to vote for the Green New Deal, organized hundreds of volunteers, and canvassed thousands of people across the state."

Now, all eyes are on New Hampshire, which will hold the nation's second nominating contest on Feb. 11. The Sunrise Movement took to Twitter Thursday to share a report from The New Republic entitled "The Youth Climate Movement Comes to New Hampshire."

As The New Republic reported Wednesday:

Many of the volunteers and organizers spoke of the difficulty balancing urgency and sustainability in building a youth movement. Climate anxiety can be either a motivating or paralyzing factor. "Sometimes you're thinking ahead about the future, and then you're like, Oh, but is that even going to exist then?" said Esther, 16, from New Jersey. "Like, fuck, New York City is going to be underwater in 50 years, according to these reports."

Though it takes a personal toll, a sense of urgency may be needed to address the climate crisis, the report noted. "The only time that we have seen substantial change in society," Dana Fisher, a professor at the University of Maryland who studies the environment and American protest movements, said, "is when there is this extreme sense of risk that either comes from a true disaster or a sense that a disaster is looming."

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Fueled by 'Eco-Anxiety,' Majority in US Believe Climate Crisis Most Crucial Issue Facing Society: Poll - Common Dreams

Human Behavior

Is Carb Addiction Real? All You Need to Know – Healthline

Arguments surrounding carbs and their role in optimal health have dominated discussions of the human diet for nearly 5 decades.

Mainstream diet fads and recommendations have continued to change rapidly year after year.

At the same time, researchers continue to discover new information about how your body digests and responds to carbs.

Therefore, you may still be wondering how to include carbs in a healthy diet, or what makes some carbs so hard to say no to at times.

This article reviews the current research on whether carbs are addictive, and what that means for their role in the human diet.

Carbohydrates are one of the main macronutrients your body needs.

In fact, of all the macronutrients, carbs are arguably the most important source of energy for your bodys cells, tissues, and organs. Not only do carbs produce energy, but they also help store it (1).

Still, serving as a good source of energy isnt their only function. Carbs also serve as a precursor to ribonucleic acid (RNA) and deoxyribonucleic acid (DNA), transport molecular data, and aid cell signaling processes (2).

When you think of carbs, often the first types of foods that come to mind are refined carbs like cakes, cookies, pastries, white bread, pasta, and rice.

Their chemical makeup includes three primary elements carbon, hydrogen, and oxygen.

However, many healthy foods are also carbs, such as fruits, vegetables, legumes, and whole-grain breads, pasta, and rice.

Carbs are one of the main macronutrients required by your body. Theyre needed for many functions, including producing and storing energy.

You may have noticed that it can be hard to resist junk food at times, especially carbs that are high in refined sugar, salt, and fat.

Many people have wondered if this is a matter of willpower, behavioral or psychological traits, or even brain chemistry.

Some people have even begun to question whether carbs could be addictive in the same way that other substances or behaviors can be (3, 4).

One major study revealed strong evidence that high-carb meals stimulate regions of the brain that are associated with cravings and rewards (5).

This study found that men with obesity or excess weight displayed higher brain activity and greater reported hunger after eating a high-GI meal, compared with a low-GI meal (5).

GI stands for glycemic index, a measure of how the carbs in a meal affect blood sugar levels. A food with a high GI increases blood sugar levels more dramatically than a food with a low GI.

This suggests that the human urge for refined carbs could have much more to do with brain chemistry than initially believed.

Additional research has continued to support these findings.

Some researchers have gone so far as to suggest that refined carbs in the form of fructose have addictive properties that closely resemble those of alcohol. Fructose is a simple sugar found in fruits, vegetables, and honey.

These scientists found that, like alcohol, fructose promotes insulin resistance, abnormal fat levels in your blood, and liver inflammation. Plus, it stimulates your brains hedonic pathway (6).

This pathway triggers appetite and influences food intake through a system of pleasure and reward rather than being based on true physical hunger or actual energy needs.

Not only do insulin resistance, inflammation, and abnormal fat levels increase your risk of chronic disease, but repeated stimulation of the hedonic pathway may reset the level of fat mass your body wants to preserve, contributing to increased body weight (7, 8, 9).

High-GI carbs that promote rapid changes to insulin and blood sugar levels also appear to affect dopamine levels. Dopamine is a neurotransmitter in your brain that sends messages between cells and influences the way you feel pleasure, reward, and even motivation (10).

Furthermore, some research in rats shows that granting periodic access to sugar and chow food mix may produce behavior that closely mirrors the dependency often seen with drug abuse (11).

A second study used a similar model, allowing rats periodic access to a 10% sugar solution and a chow food mix followed by a period of fasting. During and after the fast, the rats displayed anxiety-like behaviors and a reduction in dopamine (12).

Its important to note that most of the experimental research conducted thus far on carbs and addiction has taken place in animals. Therefore, additional and more rigorous human studies are needed (13, 14).

In one study, women ages 18 to 45 who were prone to emotional eating episodes were more likely to choose a carb-rich drink over a protein-rich one after being induced into a sad mood even when blinded from which drink was which (15).

The connection between carb-rich foods and mood is just one theory as to carbs may sometimes be addictive (16).

On the other hand, some researchers are not convinced that carbs are truly addictive (17).

They argue that there are not enough human studies and believe that most of the research in animals suggests addiction-like behaviors from sugar only in the context of periodic access to sugar specifically rather than from the neurochemical effect of carbs in general (18).

Other researchers conducted a study in 1,495 university students in which they assessed the students for signs of food addiction. They concluded that total calories in a food and unique eating experiences were more influential on calorie intake than sugar alone (19).

Further, some have argued that many of the tools used to evaluate addictive-like eating behaviors rely on self-assessment and reports from people participating in the study, which leaves too much room for subjective misunderstandings (20).

Some evidence suggests that high-carbs meals may stimulate different types of brain activity than low-carb meals. Particularly, carbs appear to affect the areas of the brain related to pleasure and reward.

In 2009, researchers at Yale developed the Yale Food Addiction Scale (YFAS) to provide a validated measurement tool to assess addictive eating behaviors (21, 22).

In 2015, researchers from the University of Michigan and the New York Obesity Research Center used the YFAS scale to measure addiction-like eating behaviors in students. They concluded high-GI, high fat, and processed foods were most associated with food addiction (23).

The chart below shows some of the most problematic foods for addictive eating and their glycemic load (GL) (23).

GL is a measure that considers both the GI of a food as well as its portion size. When compared to GI, GL is typically a more accurate measure of how a food impacts blood sugar levels.

With the exception of cheese, each of the top 10 most addictive foods according to the YFAS scale contains significant amounts of carbs. While most cheese still provides some carbs, it isnt as carb-heavy as the other items on the list.

Moreover, many of these foods are not only high in carbs but also refined sugar, salt, and fat. Plus, theyre often eaten in highly processed forms.

Therefore, there may still be much more to uncover about the relationship between these types of foods, the human brain, and addictive-like eating behaviors.

The most addictive types of carbs are highly processed, as well as high in fat, sugar, and salt. They also typically have a high glycemic load.

Even though research shows that carbs display some addictive properties, there are many techniques you can use to overcome cravings for carbs and other junk foods.

One of the most powerful steps you can take to stop carb cravings is simply to plan for them ahead of time.

Having an action plan in mind for those moments when cravings hit may help you feel prepared and empowered to pass up carb-laden junk foods and make a healthier choice instead.

As far as what your action plan should entail, keep in mind that there is no right or wrong answer. Different techniques may work better or worse for different people.

Here are a few ideas you can try:

Various techniques may help fight off carbs cravings. These include physical activity, staying hydrated, familiarizing yourself with trigger foods, and filling up on healthy fruits, vegetables, and proteins.

Carbs are your bodys primary source of energy.

Some carbs, such as fruits, vegetables, and whole grains, are very healthy. Other carbs can be very processed and high in salt, sugar, and fat.

Early research on carbs does suggest that they might display addictive-like properties. They appear to stimulate certain parts of the brain and even influence the types and amounts of chemicals your brain releases.

However, more rigorous research in humans is needed to uncover exactly how these mechanisms in the brain are affected by carbs.

Some of the most addictive carbs appear to be highly processed junk foods like pizza, chips, cakes, and candies.

However, there are various techniques you can try to combat carb cravings. Consider testing out a few to learn what works best for you.

Read more here:
Is Carb Addiction Real? All You Need to Know - Healthline

Human Behavior

Biased AI Is Another Sign We Need to Solve the Cybersecurity Diversity Problem – Security Intelligence

Artificial intelligence (AI) excels at finding patterns like unusual human behavior or abnormal incidents. It can also reflect human flaws and inconsistencies, including 180 known types of bias. Biased AI is everywhere, and like humans, it can discriminate against gender, race, age, disability and ideology.

AI bias has enormous potential to negatively affect women, minorities, the disabled, the elderly and other groups. Computer vision has more issues with false-positive facial identification for women and people of color, according to research by MIT and Stanford University. A recent ACLU experiment discovered that nearly 17 percent of professional athlete photos were falsely matched to mugshots in an arrest database.

Biased algorithms are linked to discrimination in hiring practices, performance management and mortgage lending. Consumer AI products frequently contain microinequities that create barriers for users based on gender, age, language, culture and other factors.

Sixty-three percent of organizations will deploy artificial intelligence in at least one area of cybersecurity this year, according to Capgemini. AI can scale security and augment human skills, but it can also create risks. Cybersecurity AI requires diverse data and context to act effectively, which is only possible with diverse cyber teams who recognize subtle examples of bias in security algorithms. The cybersecurity diversity problem isnt new, but its about to create huge issues with biased cybersecurity AI if left unchecked.

Put simply, AI has the same vulnerabilities as people do, wrote Greg Freiherr for Imaging Technology News. Algorithms are built on sets of business logic rules written by humans. AI can be developed to perpetuate deliberate bias or, more often, it mirrors unconscious human assumptions about security risks.

Everyone has unconscious biases that inform judgment and decision-making, including AI developers. Humans tend to have a shallow understanding of other demographics and cultural groups, and the resulting prejudices can shape AI logic for security in many areas, including traffic filtering and user authentication. Language biases can shape natural language processing (NLP) rules, including spam filtering.

Business logic is a permanent part of an AIs DNA, no matter how much training data is used. Even machine learning (ML) algorithms built for deep learning cant escape built-in biases. Biased rules within algorithms inevitably generate biased outcomes, wrote IBM Security VP Aarti Borkar for Fast Company.

An AIs decision-making abilities are only as effective as its training data. Data is neutral until it is filtered through human bias. By the time data reaches an algorithm, there are usually strong traces of human prejudice. Bias can be created by preprocessing teams through a variety of factors, such as data classifiers, sampling decisions and the weight assigned to training data.

Biased training data can corrupt security outcomes. Anti-biased preprocessing is necessary to ensure adequate sampling, classification and representation.

Humans and technology have become cybersecurity collaborators. Cybersecurity contributors train AI to create better security outcomes through a lens of personal knowledge and experience, but humans can quickly contribute to algorithm bias, especially in teams with poor diversity. Varied perspectives are needed to leverage cybersecurity AI in fair, balanced ways.

Diverse teams can recognize the specific risks of biased AI and minimize its impact. Cognitive diversity can contribute to the production of fair algorithms, help curate balanced training data and enable the supervision of secure AI.

CISOs need to create more internal diversity, but getting there isnt going to be easy. Its time to collaborate on the issues that perpetuate biased security culture and flawed AI. The problem is too complex for one person or strategy to solve alone.

Hiring and internal promotions dont guarantee cognitive diversity. Security leaders need to create an inclusive workplace culture. Getting newly hired talent up-to-speed on AI can require training and likely a reevaluation of existing learning strategies as well. Microinequities are prevalent in corporate learning programs, so maintaining an equal playing field means implementing accommodations for learners with varied languages, cultures, ages and levels of dependency on assistive technologies.

Once newly hired or promoted talent is trained, its time to figure out how to retain women, minorities and other candidates, as well as how to remove any barriers to their success. Women in security are disproportionately likely to feel stressed at work and leave the industry, and both women and minorities receive lower wages and fewer promotions.

Biased performance management practices are part of the problem, as workplace cultures and policies can be especially detrimental to women and minorities. For example, an absence of flex-time policies can disproportionately hurt women.

Equal pay and equal opportunity are needed to retain and engage with diverse perspectives. The security industry desperately needs to double-down on creating a culture of self-care and inclusion. Removing barriers can improve anti-bias efforts and produce other positive effects as well. After analyzing 4,000 companies data, researcher Katica Roy discovered organizations that move the needle closer to gender equity even experience an increase in revenue.

Women in cybersecurity are dramatically underrepresented, especially in light of their overall workforce participation. However, true cognitive diversity may require significant changes around policy and culture. CISOs face the dual challenge of fixing cyber team culture and starting cross-functional conversations about equity. Collaboration between security, HR, risk, IT and other functions can create ripples of change that lead to more inclusive hiring, performance management and policies.

Bias is nothing new. Humans [have bias] all of the time, AI strategist Colin Priest, vice president of AI Strategy at DataRobot, told Information Week. The difference with AI is that it happens at a bigger scale and its measurable.

Its probably impossible to create artificial intelligence without any biases. A risk-based approach to governing AI bias is the most practical solution. The first step is to create a clear framework of whats fair, which shouldnt be filtered through a narrow lens of experience. Individuals with diverse perspectives on AI, technology, data, ethics and diversity need to collaborate on governance.

Remember, minimize is not the same as remove. A risk-based framework is the only pragmatic way to put AI governance into practice. Resources should be directed toward mitigating biases in artificial intelligence with the greatest potential impact on security, reputation and users.

Priest recommends creating a job description for AI to assess risks. This isnt a sign that robots are coming for human jobs. Rather, position descriptions are a solid baseline for understanding the purpose of cybersecurity AI and creating performance metrics. Measurement against KPIs is an important part of any governance strategy. Monitoring AI can prevent biases that slowly degrade the performance of cyber algorithms.

Checking personal biases is rarely comfortable. Industry leaders have a biased perspective on AI innovation, especially compared to regulators and researchers who focus on safety. True cognitive diversity can create uncomfortable friction between competing values and perspectives. However, a truly balanced solution to AI bias is going to require collaboration between industries, academia and the government.

IBM Chair and CEO Ginni Rometty recently called for precision regulation and better collaboration between AI stakeholders on CNBC. For example, legislation could determine how the technology is used instead of AI capabilities or characteristics.

You want to have innovation flourish and youve got to balance that with [AI] security, said Rometty.

Alphabet CEO Sundar Pichai recently expressed a similar point of view, asking European regulators to consider a proportionate approach.

Creating more effective frameworks for AI anti-bias and safety means being open to conflicting ideas. Security leaders should prepare for productive friction, and more importantly, join global efforts to create better frameworks. Industry perspectives are critical to supporting the IEEE, the European Commission and others in their efforts to create suitable frameworks.

Third-party data can be a valuable tool for cybersecurity AI, but its not risk-free. Your organization could be absorbing the risk of third-party biases embedded in training data.

Organizations will be held responsible for what their AIs do, like they are responsible for what their employees do, wrote Lisa Morgan for Information Week. Knowing your data vendors methodology and efforts to mitigate training data bias is crucial. Anti-bias governance must include oversight into third-party data sources and partnerships.

Its officially time to target the talent pipeline and cybersecurity diversity. Women are dramatically underrepresented in cybersecurity. According to UNESCO, gender diversity rates drop even lower among cyber leadership and roles at the forefront of technology, such as those in cybersecurity AI. Minorities have fewer opportunities for equal pay and opportunities.

The opportunity gap starts early. According to UNESCO, girls have 25 percent fewer basic tech skills than their male peers. Creating a fair future for artificial intelligence and a diverse talent pipeline requires that everyone pitch in, including industry security leaders. Everyone benefits from efforts to create a more skilled, confident pipeline of diverse cyber talent. Nonprofits, schools and educational groups need help closing the STEM skill and interest gap.

Creating more diverse cyber teams isnt a goal that can be accomplished overnight. In the meantime, security teams can gain diverse new perspectives by collaborating with nonprofits like Women in Identity, CyberReach and WiCys.

Frameworks, tools and third-party experts can help minimize bias as organizations work toward better talent diversity. Open-source libraries like AI Fairness 360 can identify, measure and limit the business impact of biased algorithms. AI implementation experts can also provide experience and context for more balanced security AI.

Last fall, Emily Ackerman almost collided with a grocery delivery robot at her graduate school campus. She survived, but she had to force her wheelchair off a ramp and onto a curb. AI developers hadnt taught the robot to avoid wheelchairs, which put disabled people on the line as collateral.

Designing something thats universal is an extremely difficult task, said Ackerman.But, getting the shorter end of the stick isnt a fun experience.

Sometimes, AI bias can even reinforce harmful stereotypes. According to UNESCO research, until recently, a mobile voice assistant didnt get offended by vicious, gender-based insults. Instead of pushing back, she said, Id blush if I could! In more extreme instances of bias like Ackermans experience, AI can be life-threatening.

Cognitive diversity can create better security. Diverse teams have diverse ideas and broad understandings of risk, and varied security perspectives can balance AI bias and improve security posture. Investing in artificial intelligence alone isnt enough to solve sophisticated machine learning attacks or nation-state threat actors diverse human perspectives are the only way to prepare for the security challenges of today and tomorrow.

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Biased AI Is Another Sign We Need to Solve the Cybersecurity Diversity Problem - Security Intelligence

Human Behavior

From Animals to Human Society: What We Learn When Women Lead – Discover Magazine

Theres something amiss with The Lion King aside from talking, singing animals. Disneys smash hit of stage and screen tells the tale of young male lion Simbas rise to power. But, in the real circle of life, lionesses lead.

Related females band together for life, as the primary hunters and warriors. Transient males join to mate but contribute little else to a prides success.

The lion queens, however, are an exception. Among mammal species that live in social groups, only about 10 percent have strong female leaders. They include another fierce predator, killer whales, as well as bonobos, famous for their peaceful promiscuity.

Humans, on the other hand, are part of the mammal majority: Our leaders are mostly male. Less than 7 percent of Fortune 500 CEOs are female. Worldwide, fewer than two dozen women are heads of state or government, including Germanys Angela Merkel and New Zealands Jacinda Ardern. In about 90 percent of nonindustrial societies studied by anthropologists, only men hold political posts.

Its undeniable that males have more sway across institutions, societies and mammal species. But what explains those lionesses, literal and figurative the females who lead? A multidisciplinary movement to study these outliers is gaining momentum. From hyena clans to corporate hiring culture, researchers are charting the pathways and barriers to female power among mammals, including our own species.

Bullies, warriors and wise matriarchsIn the dry, thorny forests of Madagascar, Verreauxs sifaka lemurs leap between trees with gravity-defying ease. For these primates, theres no question which sex is dominant.

Females beat up the males, says anthropologist Rebecca Lewis of the University of Texas at Austin. To avoid smacks to the face and bites, males call out submissively when females approach a chattering chi chi chi chi, which is the equivalent of bowing down, says Lewis. At trees laden with edible fruit, its ladies first: If a male climbs up, the feasting female may aggressively lunge or glare, and hell often retreat to the ground.

(Credit: Monika Hrdinova/Shutterstock)

But tensions escalate during the dry season, when food is so scarce the animals lose up to 20 percent of their weight. Theyre just really suffering during this time, says Lewis, who leads a wildlife research station in Madagascar.

One source of sustenance is the fatty baobab fruit. Its thick shell takes sifakas a half-hour to gouge open with their teeth. As a female works to free her own meal, she keeps an eye on nearby males. When one of them breaks open the shell, she claims the fruit like a schoolyard bully, slapping him to surrender.

He might even hold onto the fruit while shes eating just crying the whole time because he doesnt want to lose it, says Lewis.

Eventually he goes on to crack another. She takes that one, too.

During the dry season in Madagascar, baobab trees provide a crucial source of sustenance for Verreauxs sifaka lemurs: thick-shelled fruit. (Credit: Maxwell De Araujo Rodrigues/Dreamstime)

Few mammal females attain this degree of dominance defined by biologists as an animals ability to subordinate another through force or threat. Among the roughly 5,400 mammal species, in just a couple of dozen do females routinely outrank males during dominance contests. These include spotted hyenas and two types of naked mole rat, but lemur species make up the bulk of the list. For more than 20 species of lemurs, including Verreauxs sifaka, female rule is the rule, not the exception.

The fact that females are socially so powerful in [lemur] societies shows us that more traditional division of sex roles is not some inevitable destiny of mammalian biology, says Peter Kappeler, a zoologist at the University of Gttingen in Germany. That gives rise to all kinds of questions, why that might be the case, why lemurs are so different.

One obvious consideration is what Kappeler and others call the lemur syndrome: Females have traits that are typical of males in other mammal species. Their external genitalia are elongated, appearing more penislike, and their bodies are the same size or slightly larger than a males. With a mass difference of less than 10 percent, both sexes would belong to the same weight class in boxing. Lady lemurs also display so-called masculine behaviors: play tussling, marking territory with scent glands and intimidating subordinates with feigned or real cuffs and bites.

A similar pattern is found in African spotted hyenas: Females are larger and stronger, with masculinized vaginas and clitorises that resemble scrotums and penises. High-ranking females keep order in clans of up to 130 members, and comprise the front lines during wars against rival hyena clans or lions.

Not every social mammal species led by females has the same structure. For spotted hyenas, females are warriors that take on rival clans and lions. (Credit: S100apm/Dreamstime)

But body size and pseudo-penises arent enough to explain power dynamics in these species. Nor are hormones: Although pregnant hyenas and lemurs show elevated testosterone levels, most of the time adult females have lower concentrations than males a puzzling finding scientists are investigating.

A 2019 Nature Ecology and Evolution paper on spotted hyenas suggests that disproportionate social clout, rather than physical strength, fuels female dominance. Its authors analyzed 4,133 encounters between mixed or same-sex hyenas, which ended with one animal exerting dominance and the other retreating, cowering or otherwise signaling defeat. Over 75 percent of the time in all matchups, victory went to whichever animal had more potential allies close enough to call for backup. And, in spotted hyena society, high-ranking females have the most allies.

Another 2019 study, published in the International Journal of Primatology, looked at several hundred dominance contests between sifaka lemurs of varying ages. Although adult males bow down with the deferential chi chi chi chi to adult females, males of all ages get into conflicts with juvenile females. The researchers found juvenile females won about a quarter of the bouts and adolescents about half, regardless of body size. Adult females who had offspring past weaning age triumphed nearly 100 percent of the time. Sexual maturity and successful motherhood give these females status.

The findings challenge the idea that malelike traits gave rise to female dominance in these species. Perhaps female power, attained through social support or reproductive outcomes, led to lemur syndrome and its hyena equivalent.

Female orcas are among the few mammals that live decades past menopause, often leading their pods, especially in times of scarcity. (Credit: Ivkovich/Dreamstime)

Lewis, a co-author of the 2019 lemur study, has pushed researchers to look beyond physical dominance when investigating power relations. In her other articles, she contends that power ones ability to make another creature do something can be reached by alternate means or expressed in other ways.

Leadership is a special kind of power: influence over the entire group. Dominant animals can be leaders, capable of directing collective action. Or they may just be lone bullies at the baobab tree.

Strong female leadership is even more rare than female dominance among mammals. A 2018 study in Leadership Quarterly reviewed 76 social species in four decision-making contexts: collective travel, foraging and conflicts within or between groups. Defining leaders as individuals that routinely called the shots in at least two of these realms, the researchers identified eight species run by females: ruffed and ring-tailed lemurs, spotted hyenas, killer whales, African lions, bonobos and two types of elephant.

It looks like there are these independent evolutionary events where the set of circumstances gave rise to strong female leaders, says lead author Jennifer Smith, a biologist at Mills College.

For spotted hyenas and two lemur species, dominance certainly plays a role. But the other five species took different pathways to leadership. Female elephants and killer whales can live into their 80s in matrilineal societies, comprising up to four generations of mothers and offspring. With the most accumulated wisdom about local resources and dangers, female elders lead group movement and food pursuits. It makes so much incredible sense, says Smith. These long-lived females with great knowledge of course they should be the leaders.

In contrast to some species where physical dominance is the rule, peaceful bonobos form alliances. (Credit: Andrey Gudkov/Dreamstime)

Killer whales, or orcas, are also one of the few species in which females live decades past menopause. Orca communities especially follow these grandmothers (or great-grandmothers) during hard times, like when salmon prey are scarce, according to a 2015 study in Current Biology.

Meanwhile, female lions and bonobos derive strength from numbers. In both species, allied females fend off bigger, stronger males. Kinship unites the lionesses, but bonobos form coalitions of nonrelatives, which groom and fondle each other. Females of this chimpanzee species, through their cooperative social alliances, are in a way civically larger and more influential than one male, Smith explains.

Bias, biology and breaking through

Inthe 1970s, a review of historical descriptions of 93 nonindustrial societies found only about 10 percent permitted women to hold political posts and women were generally less powerful than male counterparts. Contemporary scholars attribute this in part to the mentality of past researchers: Ethnographers predominately men from Western patriarchies documented leadership in male-dominated domains like war, and overlooked female authority in economic, domestic and other spheres.

But even in more recent, less-biased research, it hits you in the face how disparately represented men and women are in positions of leadership, particularly more overt political leadership, says Christopher von Rueden, an anthropologist at the University of Richmonds Jepson School of Leadership Studies.

Consider the Tsimane, indigenous people of the Bolivian Amazon, who subsist on wild foods and garden-scale farming. Although Tsimane lack formal leaders, certain individuals have a greater voice in village affairs. In a 2018 Evolution and Human Behavior paper, von Rueden and colleagues found that, at community meetings, less than 10 percent of comments came from women. And when Tsimane ranked fellow villagers based on their ability to influence debates and manage projects, the average male score was higher than the scores of 89 percent of the women.

Among the Tsimane people of the Bolivian Amazon, political leadership is predominately, but not exclusively, male. Physical size, level of education and number of allies are factors in predicting political sway, and women do occasionally emerge as leaders in this nonindustrial society. (Credit: National Geographic Image Collection/Alamy)

And yet, consistent with global surveys, Tsimane political leadership is predominately but not exclusively male. Some women leaders exist among them.

Probing the data further, von Ruedens team found factors beyond a Y chromosome that predicted political sway, including a persons size, education and number of allies. The authors concluded that these qualities, rather than gender per se, elevated individuals to become leaders. It just so happens that Tsimane men generally place higher on those metrics than do women. For example, the female participants received, on average, 3.9 years of formal schooling, compared with 5.8 years for men. While physical differences are essentially set, gaps in education and social capital are not. Indeed, in another study of a more remote Tsimane village, the third-highest leader was a well-educated woman who had studied in a larger town.

Through his research, von Rueden seeks to explain how the evolution of sex differences affect access to leadership across human societies a topic fraught with potential land mines, he admits. Evolutionary anthropologists, including von Rueden, think the answer lies at the intersection of biological sex differences and the particular history, customs and environment of any given society.

Thanks to our mammalian roots, women bear and nurse babies. Men are generally larger and stronger just considering upper-body strength, 99 percent of women have less arm muscle mass than the average man. These biological realities set the stage for sexual division of labor, common across cultures. Men tended to take on riskier endeavors, like battles and big-game hunts, which require coalitions and hierarchical coordination. Tethered to children and homes, women assumed a greater share of domestic responsibilities, forming fewer but more intimate social ties.

From this evolutionary background, sex-based stereotypes emerged, which then became amplified or dampened by the particularities of a given society. For example, its been proposed that the invention of the plow deepened gender divisions because its use requires substantially more upper-body strength than hoe or stick tilling. This relegated men to fields and women to household labor. According to a 2013 Quarterly Journal of Economics study, the plows effects persist. The authors compared farming styles of more than 1,200 nonindustrial societies with gender beliefs of their modern descendants. The analysis found that descendants of plow-farmers have fewer women in the workforce and politics, and less-favorable views about gender equality. For example, in Pakistan, where earlier societies relied on the plow, only 16 percent of agricultural workers are women, compared with 90 percent in Burundi, which had traditional hoe tilling.

Understanding the evolution of male-skewed leadership, says von Rueden, puts us in a better position to act on behalf of putting more women in positions of power.

Theres a lot of catching up to do. In the U.S., while women make up half the entry-level workforce, their presence dwindles on each step of the corporate ladder, comprising just a quarter of senior managers, 11 percent of top earners and 5 percent of CEOs in S&P 500 companies, according to a 2019 report by Catalyst, a womens leadership nonprofit.

Based on metrics like wage gap, share of labor force and percentage of women working, gender equality rose beginning in the 1960s, peaked in the 90s and then stagnated for the past two decades.

Siri Chilazi, a fellow at the Women and Public Policy Program at Harvard University, says company policies and structures are part of the problem as are individual biases. For example, results of an experiment published in 2014 in the Proceedings of the National Academy of Sciences found that investors preferred entrepreneurial pitches from men, rating their presentations as more persuasive, logical, and fact-based than those from women. The catch: The content was identical, word for word.

Decades ago, major American symphonies changed their systems to blind auditions and saw significant increases in the number of women hired. (Credit: Stokkete/Dreamstime)

A now-classic analysis, published in 2000, underscores such biases. In the 1970s and 80s, major U.S. symphonies changed their auditions so musicians played behind a curtain that concealed their identity. Prior to the policy shift, less than 10 percent of new hires were women. Afterward, the number of female musicians in all orchestras increased exponentially most drastically for the New York Philharmonic, where, following the change, about 50 percent of new hires were women.

As Chilazi sees it, research has a clear message for organizations trying to level out gender ratios in leadership: Company policies are much easier to change and much easier to de-bias than our human brains.

Research runs thin when it comes to what is arguably the ultimate glass ceiling: elected national leadership. Starting in 1960 with Sri Lankas Prime Minister Sirimavo Bandaranaike, 115 women have served as president, prime minister or chancellor of 75 countries, from Brazil to Bangladesh. But, as in the business world, gender gains rose steeply through the 1990s and then recently reversed course.

The small number of women who have led their nations include Sri Lankas Sirimavo Bandaranaike (left) and Germanys Angela Merkel (right). (Credit: Elpisterra/Shutterstock; Everett Collection Historical/Alamy)

Oklahoma State University political scientist Farida Jalalzais research shows female executives tend to serve in systems with both a president and prime minister, often holding the weaker of the posts. Rather than popular vote, most are appointed by legislatures or winning parties, and into unstable posts that can be challenged. (Recall the no-confidence votes Theresa May faced in the U.K. Parliament.) Another factor: The majority hail from political families often the wives or daughters of former leaders.

Jalalzai notes that, while 2016 U.S. presidential candidate Hillary Clinton, the wife of a former president, fit this profile, the U.S.s presidency is a single, powerful head of state, rather than part of a power-sharing dual leadership system. The Oval Office is a tough glass ceiling to crack.

According to Jalalzai, although Clinton failed to win the presidency, the campaign may have shifted perceptions about who can assume the office. A record number of women entered the 2020 Democratic primary, for example. People didnt take her loss as the lesson that women shouldnt be competing for this, she says. It showed us, really, the opposite.

Jalalzai found similar effects globally, looking at public opinion surveys taken by 62,000 individuals from over 40 countries. In the 11 nations with female executives during the 2018 studys time frame, people were more accepting of female leaders, interested in politics and likely to vote, especially female respondents.

Other researchers have focused on local elections with corroborating results. In a 2018 Leadership Quarterly paper, researchers found that after the election of female mayors, those municipalities saw more women assuming top- and middle-management positions in public organizations. A study published in 2012 in Science considered the consequences of a 1993 Indian law that mandated that a random third of West Bengal villages reserve their chief councilor seat for an elected woman. Based on more than 8,400 surveys conducted in 495 villages, the researchers found that having a woman councilor for two election cycles improved aspirations for girls to pursue higher education and politics. The girls also spent more years in school and fewer minutes per day on domestic chores.

The studies suggest that, while gender equality does not beget female leaders, the reverse may be true: Women in high offices promote gender equality, either directly through policies and appointments, or indirectly by acting as a prominent reminder that women can lead.

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From Animals to Human Society: What We Learn When Women Lead - Discover Magazine

Human Behavior

Cybersecurity AI is ready for prime time: why the skeptics are wrong – fifthdomain.com

Federal leaders looking at artificial intelligence offerings to strengthen the cybersecurity of their systems are often met with a confusing array of hype that leads to misunderstanding and all too often to inertia. And, as government decision-makers are well aware, cyber threats against public sector systems are increasing daily and growing in sophistication.

Unfortunately, overhype about artificial intelligence in cybersecurity only reinforces our human tendency to resist change. Remember how government IT leaders were slow to see the real benefits of cloud technology?

In just the same way, some federal agency IT experts, even in the face of rising threats to their systems, remain reluctant to examine the commercial off-the-shelf (COTS) applications using AI at scale.

Perhaps a brief review of what cybersecurity AI is and is not will be helpful. For starters, confusion (and often inadvertent misinformation) is centered on descriptions about how AI is used.

Cyber AI is not big data alone. Machine learning is not possible using deficient data sets. With consumer-facing AI-based tools such as voice-activated home assistants like Amazons Alexa, the Google Assistant or Apples Siri, we see how large data sets of consumer behavior - Alexa, tell me an apple pie recipe - leverage forms of AI known as deep machine learning or artificial narrow intelligence.

Similarly, for cyber AI, training the data set is essential. Ideally these are solutions that can learn, train, and reliably identify constantly moving threats like complex malware and other file-less attack patterns that are increasingly more common . Its critical to remember that AI is not a panacea yes, effectively training AI algorithms at scale can prevent future attacks, but the human element is still necessary to thwart cyber actors.

Cyber AI also is not laboratory AI alone. One of the clearest distinctions between cyber and other types of AI is whether its functionality can be accomplished in the real world outside the perfect conditions of the laboratory setting. For instance, claims about accuracy and false positive rates should always be interrogated in light of sample sizes. As an example, an AI model that learns only about breach attempts in the financial sector cannot be adequately applied to the intricacies of guarding protected health information in hospitals.

A solution is only as good as the data

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For cybersecurity AI to meet the challenges facing federal IT leaders, the data must be relevant to the evolutionary nature of the of threatscape, the increasing demands that the agencys mission is placing on its systems and the risks posed by the human element from within the agencys walls.

For example, it is well understood that many cyber breaches result from human error. A good cyber AI solution can analyze human behavior to anticipate mistakes and correct them proactively as part of the scanning and response functions. To that end, data must be constantly refreshed in order to keep pace with the agencys requirements - addressing both the internal environment along with changes in the external threat conditions.

Our experience tells us that the power of cyber AI is unleashed by:

The Need for Speed

Equally important, as we found in our 2019 Global Threat Report, is the importance of speed.

The report identified that breakout times (the time it takes an adversary to move beyond their initial foothold within a network to when they successfully gain broader access) of the most dangerous groups targeting U.S. government agencies have continued to shrink year over year. Russian-identified hacker groups led the way with a breakout time of less than 19 minutes.

These shrinking attack windows bolster the case for the 1-10-60 Rule: One minute to detect an incident or intrusion; 10 minutes to determine if the incident is legitimate and determine next steps (containment, remediation, etc.); and 60 minutes to eject the intruder and clean up the network.

Taking cybersecurity to the next level, as described in this perhaps deceptively simple rule is possible. The cybersecurity AI solutions that can help to accomplish this objective must utilize the power of vast data sets in a shared cloud environment, set up to collect, analyze and interpret events in real time. No overhype just the right data, smart vision, and a mission to stop breaches faster.

James Yeager is vice president for public sector and healthcare at CrowdStrike.

Originally posted here:
Cybersecurity AI is ready for prime time: why the skeptics are wrong - fifthdomain.com

Human Behavior

Neoliberalism and the Coronavirus – CounterPunch

Photograph Source: Studio Incendo CC BY 2.0

In This Changes Everything, Naomi Klein notes that the TV sets owned by Americans were manufactured in China with the energy input from coal-burning. Those carbon emissions are logged in Chinas ledger. The trucking to bring the TV to your towns big box outlet is logged in the U.S.s ledger. However, the transoceanic shipping that brought the set from Shenzhen to Los Angeles is not logged under any countrys ledger.

Americans may point fingers at China for burning coal, but who is watching that TV? Not the migrant worker who mined that coal. Not the laborer in the Congo who mined the rare earth elements for the electronics. Not the steelworker in the foundry in Wuhan. Not the factory worker who sorted transistors into sockets. Not the Filipino merchant seaman on the cargo ship. Not the Sikh driver of the 18-wheeler. Not the grandma who greets you at the entrance of the big box outlet. Not the Chinese worker whose cough from the air pollution keeps him up at night. Now, whats this? A fever, too?

We mention ledgers because capitalism is all about externalizing costs. Some people (because corporations are legally people) dont take responsibility for their carbon footprint. Some people scrape the surface off the earth to get at their lithium. Some polluters dont take responsibility for the health costs of their effluent. The shorthand definition of neoliberalism is capitalism on steroids. No longer does capital have to exploit workers in its own country. It can scour the world for the cheapest, most exploitable labor. Just pay them shit, since they live in shithole countries anyway. No longer does capital have to fret about environmental regulations in its own country. Just manufacture those goods someplace where the government says air that you cant see through, or water that is green from algae is A-OK. Those goods end up a continent away, but as long as the shipping costs are cheap (burn, baby, burn), it makes more profit than employing local people for what they think is a livable wage.

Klein notes that in the decades since the 1997 Kyoto protocol, global carbon emissions have continued to grow. Rather, with free market globalization, reflective of the dominant neoliberal ideology and enacted through investor rights agreements the basis of the world economy has become predicated on greater and greater fossil fuel combustion as capital seeks less expensive labor, goods are shipped in ever increasing volume between continents, and the cost of environmental destruction is externalized.

Paul Krugman notes that over a quarter of the manufacturing in the world takes place in China. China is the workshop of the world. That means coal-burning air pollution and lots of asthma, chronic obstructive pulmonary disease, and lung cancer at a young age for the Chinese. As China continues to burn coal for energy, millions more of its citizens will die prematurely of respiratory diseases. An estimated 366,000 deathswere attributedto coal-burning in 2013.

In sum, the strategy of wringing every last dollar out of child, prison, and slave labor for the sake of private profit is nearing the point of diminishing returns. Unleashing a fatal virus from bats into humans is a negative return. By wrecking the neoliberal-driven global economy, 2019-nCoV may just push the world into embodying that final section of the post-climate catastrophe, post-Ebola, post-rat fever world of David Mitchells The Bone Clocks. The question is, do you find the final section pessimistic or optimistic?

Much has been made of how the novel coronavirus made the host species jump from its probable natural reservoir in bats to humans. The clustering of many of the early cases among workers at a market that sold wildlife for food is indicative. The cross-species jump is indicative of the further encroachment of humans on the remaining pockets of nature.

Wuhan, generally cited to have 11 million residents, served as a large population in which the virus could transmit before breaking out for the rest of China. Many of its large contingent of migrant workers and students left for their home towns before the Lunar New Year holiday (scheduled for Dec 24-30). The mayor of Wuhan, presumably referring to the larger metropolitan area, noted that 5 million had left Wuhan prior to the imposition of quarantine on Dec 23, leaving a population of 9 million. While China is known to closely surveil its individual citizens, many migrant workers who are registered in their home provinces cannot be tracked so closely.

Since it infects the respiratory tract, the novel coronavirus is presumably spread by droplet coughing, sneezing. Most viral respiratory infections are also spread by personal contact: shaking hands with an infected person, then touching your face. Is it spread by fomites (touching a surface touched by an infected person)? We dont know yet.

The definitive work on The Origins of AIDS (2012), by Jacques Pepin, draws upon viral genomics, primatology, tropical medicine, and the history of colonialism and postcolonialism. Pepin carefully reconstructs how a zoonotic virus entered the human population and how it was amplified into a global pandemic by large-scale social and political economic forces. He outlines how human behavior abetted the evolutionary success of HIV, defined (from the perspective of the virus) as spreading to an increasingly larger number of hosts. HIV is not very contagious. It can only be transmitted through sexual contact and sharing of blood (injection drug use, transfusions). Its initial symptoms are minor, however, and the long period in which it lies dormant (on the order of a decade) before manifesting as opportunistic infections or cancers, allows it to be unknowingly transmitted to others. By incorporating itself into the genome of human cells and mutating constantly, HIV makes itself difficult to cure.

The novel coronavirus that appeared in Wuhan, Hubei Province, China in late 2019 has a different strategy to infect a large number of hosts. Firstly, it is pretty contagious. Early studies from China indicate that each infected individual is infecting more than two other people. The virus likes crowded places, like China.Thus far, it appears to be less deadly than its coronavirus cousins, SARS-CoV (which caused Severe Acute Respiratory Syndrome) with 23% mortality, or MERS-CoV (which causes Middle East Respiratory Syndrome) with 10% mortality. So far, the novel coronavirus appears to have approximately a 2% mortality, though this rate will likely be lowered as more patients with minimal or perhaps no symptoms are identified. From the viruss perspective, it doesnt help your cause if youre too deadly because you then kill your host before your person gives the virus the virus to another person. A 2% mortality rate is quite worrisome, though. Most influenza pandemics have a mortality rate of <0.1%. The Great Influenza pandemic of 1918-1919, which had an estimated mortality rate of < 2.5%, killed 50-100 million worldwide.

So, we now have new virus exploiting the vulnerabilities that humans set up for themselves by buying into the neoliberal program. Viruses are barely even a life form. They dont thrive or propagate unless they take over the cells of their hosts. Who invited them to infect us humans anyway? Those people that eat weird food like bats? Wait, who invited those strange people anyway? Those slant-eyes, those carriers of the virus? Wait until we get white supremacy bound up with keeping out them foreigners. Wait, theyre there already.

But if we think about it Im afraid that slant-eye or round-eye, short- or long-nose, light- or dark-skin, its us watching that TV.

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Neoliberalism and the Coronavirus - CounterPunch