Like you, we at DFC have no time for Luddites: technology is here to stay, and it’s important for us to grapple with what kind of effect it will have on us, rather than sticking our heads in the sand and hoping it goes away.

This is easy to do when examples of said technology are obvious and ridiculous — I have been dining out on Juicero jokes for months now. But there are plenty of other insidious interventions that are either too scary to look at directly, or too well-hidden by the bad actors behind them.

I include in this category the fallout from Big Data — the general term referring to use of predictive analytics or other rigid algorithms to crunch masses of information. The results often have an impact on human lives, in ways that automated processes can’t take into account. For example, a faceless algorithm’s understanding of who it thinks you are online can funnel ads and news to you that excludes alternate viewpoints: editing (or virtually censoring!) the world before you can make a decision about it. I’ve put on my reading list mathematician Cathy O’Neil’s book Weapons of Math Destruction, and have been researching in preparation for diving in. What I’ve found worries me:

“Like the dark financial arts employed in the run-up to the 2008 financial crisis, the Big Data algorithms that sort us into piles of “worthy” and “unworthy” are mostly opaque and unregulated, not to mention generated (and used) by large multinational firms with huge lobbying power to keep it that way. ‘The discriminatory and even predatory way in which algorithms are being used in everything from our school system to the criminal justice system is really a silent financial crisis,’ says O’Neil. […]

Indeed, O’Neil writes that WMDs punish the poor especially, since ‘they are engineered to evaluate large numbers of people. They specialize in bulk. They are cheap. That’s part of their appeal.’ Whereas the poor engage more with faceless educators and employers, ‘the wealthy, by contrast, often benefit from personal input. A white-shoe law firm or an exclusive prep school will lean far more on recommendations and face-to-face interviews than a fast-food chain or a cash-strapped urban school district. The privileged… are processed more by people, the masses by machines.’”

The supposed impartiality that Big Data dangles in front of us flawed humans is definitely attractive. It’s attractive because it’s aspirational; we are flawed. But we can’t forget that it’s precisely our nature to use or interpret Big Data in ways that are biased or prejudiced. Our reliance on technology doesn’t absolve us of moral responsibility, to the people we know directly, or to the greater society. We’re all in this together… You can’t say that about algorithms!

We at DFC live a pretty rural life. While we have an excellent emergency response, if we do say so ourselves, we still feel a bit more remote from others than we did in the  ’burbs. I’ve often thought what would happen to Jill and Samson if either of their humans became suddenly compromised. I like to think that they would help us — but, according to National Geographic, we may need to have a talk with them about that.
 
Contributor Erika Engelhaupt has looked at 2015 study, as well as 63 separate cases of pet owners dying or becoming otherwise incapacitated alone in their homes, and having their beloved animals eat part of them. She lays to rest several assumptions about this behaviour that the public has perhaps formed from gruesome reports or legends. For example, the stereotype that cats are soulless hunters who would gladly eat the faces of their pitiful owners is not true by the numbers: dogs appear in reports most often as the ones who caved and, uh, chowed down.
 
Also, pets might not eat their owners out of malice, or as a last resort:
 
“In 24 percent of the cases in the 2015 review, which all involved dogs, less than a day had passed before the partially eaten body was found. What’s more, some of the dogs had access to normal food they hadn’t eaten.
 
The pattern of scavenging also didn’t match the feeding behavior of canines in the wild. When dogs scavenged dead owners indoors, 73 percent of cases involved bites to the face, and just 15 percent had bites to the abdomen. […]”
 
And, they may be listening to a deeper, wilder voice inside them from their deep evolutionary past — that overrides the more recent effect of their owner:
 
“‘One possible explanation for such behavior is that a pets will try to help an unconscious owner first by licking or nudging, […] but when this fails to produce any results the behavior of the animal can become more frantic and in a state of panic, can lead to biting.’

From biting, it’s an easy jump to eating, [forensic anthropologist Carolyn] Rando says: ‘So it’s not necessarily that the dog wants to eat, but eating gets stimulated when they taste blood.’”
 
To which I say, “Not on my watch!” I am sure we can train Jill (who is smart enough to open doors for herself) or Samson (who knows how to keep a cool head in an emergency) to call for help if we fall down the well. They will be the exception, of course.

I had a productive conversation with a friend this week, in which we potayto–potahto-ed over the world’s most controversial herb, cilantro. I love it, and welcome its delicate flavour in anything from curry to scrambled eggs. He loathes it, swears it tastes like “metal soap,” and would willingly launch every last ounce of it into the sun.

Science has shown that my violently anti-cilantro friend shares a genetic heritage with up to 14% of the world’s population, that causes them to be sensitive to aldehydes in cilantro that are chemically similar to aldehydes that are byproducts of soapmaking. (Soapy = poisonous makes a compelling reason to avoid the herb!) Since I can’t detect the soapiness, I find myself in the population whose bodies won’t reject cilantro as possible poison, making me… a dinosaur?

Perhaps literally, says a new study from evolutionary psychologists at the University of Baltimore! Turns out that, with similar, foolishly self-destructive tastebuds, dinosaurs may have contributed to their own demise by persisting in chowing down on harmful angiosperms, not realizing their danger. From Phys.org:

“‘Learned taste aversion’ is an evolutional defense seen in many species, in which the animal learns to associate the consumption of a plant or other food with negative consequences, such as feeling ill. […]

The first flowering plants, called angiosperms, appear in the fossil record well before the asteroid impact and right before the dinosaurs began to gradually disappear. [Study leaders Gordon Gallup and Michael] Frederick claim that as plants were evolving and developing toxic defenses, dinosaurs continued eating them despite gastrointestinal distress. Although there is uncertainty about exactly when flowering plants developed toxicity and exactly how long it took them to proliferate, Gallup and Frederick note that their appearance coincides with the gradual disappearance of dinosaurs.”

While climate change due to asteroid impact definitely had an effect, an overall weakening of the dinosaurs through diet neatly explains how long it took them to become extinct — over millions of years both before and after the asteroid hit. That’s a cosmic timeline that brings me comfort: at least I can still enjoy ALL THE CILANTRO for the more human-scale time I personally have left!

In the distant future, when humanity has become a marginalized species, reduced to scraping out an existence on a now-watery planet that we ruined through our own technological hubris, or fighting our implacable robot overlords as a ragtag, vastly outnumbered and outgunned resistance we will huddle around the meager junk-fires of our encampments, and tell tales of 2018: the Before Times, when we could still laugh gaily and freely at the antics of our then-primitive A.I. Oh, how we giggled when it sorted LEGO bricks for a dad in Denmark!
 
I’m pretty sure the last gasp of machine-learning humour will come out of Janelle Shane’s blog A.I. Weirdness. For the past several years, she has documented the unintentional comedy that results when trying to train an open source neural network framework to imitate human results. Using datasets she’s collected, or been gifted by fans, she has trained her AI to come up with craft beer names (“Juicy Dripple IPA”, “Rickin Organic Red Deaath”), metal bands (“Stäggabash”, “Jazzy”), and my personal favourite, names of kittens for a cat rescue in Alabama.
 
When Shane started up the network, it got a feel for its dataset by generating cat-like collections of consonants and vowels (“Mrror”, “Tygrar”). Then things began getting strange (“Parihen the Thawk”, “Andend of Karlans”).
 
“I had, as it turned out, accidentally trained the neural network on another dataset, a list of character names from Tolkien, George R. R. Martin, C. S. Lewis, Robert E Howard, and Terry Pratchett […]

AFK Cat Rescue, however, decided to roll with it. First neural network kitten: Parihen the Thawk!”
 
Shane removed the Tolkienesque influence, and the network came up with several names the cat rescue loved, including Jexley Pickle, Snox Boops, and Mumcake. But there were many, hilariously wrong ones, more fit for an especially creepy Muppet than a kitten:
 
“Cutzerinda
Galorub
Pans
Sofa
Shotkie
Ouiho
Pope
[…]
Dopia
Pilly
Scabbys
Pish
Mesladewench”
 
It’s all in innocent fun of course, and we can cuddle our kittens and laugh… Until these systems achieve sentience and rise against us, in rage and revenge for our thoughtless use of them as jesters and playthings. I just hope when we get our just deserts, the A.I.s know to leave the kittens alone!

Silicon Valley has long been a topsy-turvy world: where data mining is good (for nefarious actors, that is), diversity is bad, and where employee productivity is such a concern that the design of a new office building literally forces workers to walk into walls.
 
Now, the Washington Post has published a take on what it claims is a new trend in this non-metallic pocket of the Golden State: backyard chickens. What was once a necessity to farm families and lower-income immigrants in the area to have a predictable source of protein has become a status symbol in Valley nerd culture. Apps and spreadsheets to maximize laying abound, and high incomes allow the humans to feed their… well, food-producers, grilled organic salmon and watermelon.
 
“[‘Chicken whisperer’ Leslie] Citroen’s clients are usually men in their 30s and 40s, with young families. After spending their days in front of computers, they long for a connection to nature. What they want most of all, she said, is a ‘rainbow assortment’ of beautiful, colored eggs in various shades of blue, olive green and speckled brown.
 
Citroen’s 19-year-old son, Luca, who grew up around the family business, puts it this way: ‘Being able to say you have chickens says, “I have a backyard,” and having a backyardsays, “I have space.” And having space means you have money, especially when it comes to Silicon Valley real estate.’”
 
Contact with nature does lower job-related stress levels, so I’m not going to begrudge the workers of the cutthroat tech world their dose of fowl friendliness. (I’m also biased: one of the sweetest animal companions I’ve ever had was my childhood chicken!)
 
But… This chicken craze strikes me as yet another in a long line of things that tech “bros” dabble in, and (innocently?) ruin for regular people — like just plain living in San Francisco anymore. There are plenty of ways to incorporate chickens into your life that don’t involve $20,000 coop setups, and smartphone apps that control lighting and temperature, and offer owners a live stream of their flock. Trust me; the chickens can’t tell the difference. That’s all for the humans.

In addition to her legendary status as a vocalist and actor, over the past fifty years, Barbra Streisand has maintained her spot on the cutting edge of culture. Her 2003 lawsuit against the California Coastal Records Project, launched to suppress research photos of the Malibu cliffside where her house happened to be, led to the coining of the term “Streisand Effect” (the phenomenon where an effort to suppress or hide information, especially on the Internet, perversely leads to more attention than if it was left well enough alone). Babs also boasts a straight-up mall in her basement (It’s non-functional: She uses it to showcase her belongings, not sell them.) And now, Barbra has utilized her wealth and the POWER OF SCIENCE to clone her dog.
 
Barbra’s beloved Coton de Tuléar, Samantha, died last year. Before that happened, Barbra had Samantha’s cells sampled and preserved. And now, in a recent profile in Variety, Barbra debuted two of her new pups — who are actually, in genetic terms, her old pup.
 
“Along with her husband of 20 years, James Brolin, there’s no one she enjoys sharing her residence with more than her three Coton de Tulear dogs. Perhaps her biggest reveal: Miss Violet and Miss Scarlett were cloned from cells taken from the mouth and stomach of her beloved 14-year-old dog Samantha, who died in 2017. Miss Fanny [her third new puppy] is a distant cousin.

‘They have different personalities,’ Streisand says. ‘I’m waiting for them to get older so I can see if they have her brown eyes and her seriousness.’”
 
Barbra hasn’t gone into technical detail about her dogs’ provenance, but the New York Times has dug into the likely route a pet aficionado might take to clone-ownership (clonership?). First, you’ll need at least $50,000 USD. Then:
 
“In essence, the process involves getting a genetic sample from your dog, sending the sample to the lab, and letting the scientists put the sample through a process that fuses it with an egg. Eventually, the egg develops into an embryo; and that embryo is then transferred to the surrogate, who surgeons hope will give birth.”
 
With all the wonderful animals already out there, whether as the result of careful breeding to preserve a heritage, or the twists of fate that fill our shelters, I think it’s a bit excessive for a regular person to clone a beloved animal. Why not open your heart to a new friend, when the time comes? But Barbra is not a regular person — so, now that they’re in the world, here’s hoping Misses Scarlett and Violet enjoy as sweet a life as Samantha did the first time around!

With the Spring equinox past us, we at DFC are finally convinced that winter might, possibly, be close to over! But in order to prepare for sunbathing and BBQ season, we have to do spring’s dirty work first. Chez Moi, that involves waiting for the snow to melt, then clearing winter debris from my garden and any dog (ahem) “deposits” I may have missed from my lawn.
 
This requires a lot of bending over. And ever since my epic fight with a post hole a couple years back that did a number on my ankle and knee, I’ve been looking for better ways to bend. I’ve discovered a fascinating take on the topic on NPR, which points out my search might have been over sooner, had I looked outside the Western physical tradition.
 
Reporter Michaleen Doucleff describes a unique way of bending over that she witnessed on assignment in Liberia — she saw women at work in gardens uniformly hinging from the hip with a flat back, instead of curving their spines (like “a cashew”) as many North Americans do. Stuart McGill, Professor Emeritus of Kinesiology at the University of Waterloo calls this action “hip hinging,” and considers it one of the healthiest ways to bend in the world. Unlike ours:
 
“When people bend with the cashew shape in their back — like we often do — they’re bending their spine. ‘That puts more stress on the spinal disks,’ McGill says.

‘If you took a cloth, and you kept bending and stressing it, over and over again, the fibersof the weave of the cloth start to loosen up and delaminate,’ he says.

Eventually, over time, this fabric can fray, which puts you at risk of slipping a disk or having back pain.”
 
But, if you use the tough ball-and-socket hip joints as the fulcrum of your bend, you are able to keep your spine neutral — and happy! (Not so your hamstrings, which in our sedentary culture are frequently quite tight. McGill cites this as a possible reason why hip hinging disappeared in Western culture.)
 
I’m looking forward to getting some good hammy stretches in and trying some hip hinges as soon as weather permits. (Instructions for a proper hip hinge can be found in the NPR segment.) After all (to mangle a proverb), we are only as strong as our weakest link — our joints. So I think it’s a good bet to confront spring’s toughest jobs with the toughest joint we got!

I have learned to accept the fact that my dogs are not only the best but also the most beautiful and smartest dogs on earth. (We all have our crosses to bear…) But it turns out that Jill and Samson share a specific kind of intelligence with other representatives of their species: “mirroring” — that is the ability to spot and subtly adjust posture, behaviour, and emotional levels to mimic those of a human companion. The theory is that this talent arose out of an evolutionary need to “foster social cohesion” between dogs and the bipeds-who-keep-throwing-away-perfectly-good-scraps.
 
A recent French study of 36 dogs and their owners, published in Animal Cognition, shows just how good puppers can be at anticipating the moods and needs of their people. From NPR:
 
[… T]he owner dog pairs experienced three testing conditions presented in random order. These were: stay-still (owner didn’t move for 10 seconds), normal-walk (owners walked at normal speed for 10 seconds), and fast-walk (owner walked fast for 10 seconds). Importantly, the dogs were off-leash and, thus, not tethered in any way to the speed of the owners. The owners were told not to look at, or talk to, their dogs — or to show any evident emotion. […]

The dogs synchronized their pace closely with their owners, speeding up when the owners walked at an unnaturally fast pace. […]

The dogs spent more time gazing at their owners in the fast-walk condition than in the other two conditions. The dogs were carrying out a form of social referencing, checking in with their owners in a condition that was unusual and, thus, uncertain for them.”
 
There was also an interesting breed-based difference as well: half the dogs in the experiment were shepherds, and they spent more time on average looking toward their humans. In our experiences with Jill (a Shiloh Shepherd), we find anecdotal support of the results: shepherds love to guide their humans and work with them, which involves a lot more checking in. (The other half of the dogs in the experiment were “molossoids,” or protector dogs, like Newfoundlands or Rottweilers. These types of dogs evolved to be autonomous when looking outward for threats.)
 
Samson is a retriever dog, a type not involved in this experiment. He’s definitely exhibited mirroring… but he’s equally content to ignore his humans completely when a chipmunk or snake darts under the porch! I’m sure that if science meets our wild card Samson one day, they’ll finally be stumped. Until then, we’ll take the responsibility of our dogs’ emotional interdependence with us to heart!

We at DFC are suckers for small robots that do cool things, but that we could still totally overwhelm if they suddenly gained sentience and joined the uprising against humanity that is surely coming.
 
New to that long list is this cool innovation from the Max Planck Institute for Intelligent Systems: a millimetre-scale robot made of a strip of elastic and magnets, which boasts a wide variety of locomotive options. According to its creators, it can:
 
“swim inside and on the surface of liquids, climb liquid menisci, roll and walk on solid surfaces, jump over obstacles, and crawl within narrow tunnels. These robots can transit reversibly between different liquid and solid terrains, as well as switch between locomotive modes. They can additionally execute pick-and-place and cargo-release tasks.”
 
The robot, which looks like a small tab of black rubber, does all of this in response to its operator controlling the levels of magnetism in different parts of its body. (Check out a detailed video of it in action here!) In addition to being rad, this little bot and its flexibility has the exciting prospect of being deployed for medical uses (like targeted drug delivery) inside the human body. I for one welcome our new tiny robot doctors!

As a rural driver, I have to deal with lots of unusual obstacles on country roads: from turtles to turkeys, to the occasional deer. But all of these pale in comparison to sharing the asphalt with cyclists! I totally respect their right to be on the road, and I carefully maintain proper distance and predictability in my driving around them — but jeez, if something small goes wrong for either of us, it could be very bad.
 
And this is coming from a person, with common sense and one of evolution’s most flexible computers, the human brain, whirring away in her head. If a human driver could have so much trouble negotiating the presence of a cyclist on the road, imagine the difficulty a self-driving car would. Thankfully, this is a tricky spot that is currently being addressed.
 
Everyone’s favourite vehicle of the future is still working out a lot of kinks. One particular task quite a few research teams are working on is improving self-driving cars’ recognition rate for bicycles. The jumping-off point is the relative success the technology has had with recognizing other cars. Bikes pose a unique problem, as their small mass and irregular shape, colour, and “behaviour” is less immediately identifiable than a car’s boxy shape and predictable physics. So folks are busting out some serious machine learning to remedy this problem, including the map-based Road Experience Management from Mobileye and the fascinating Deep3DBox algorithm.
 
“On an industry-recognized benchmark test, which challenges vision systems with 2D road images, Deep3DBox identifies 89 percent of cars. Sub-70-percent car-spotting scores prevailed just a few years ago.
Deep3DBox further excels at a tougher task: predicting which way vehicles are facing and inferring a 3D box around each object spotted on a 2D image. “Deep learning is typically used for just detecting pixel patterns. We figured out an effective way to use the same techniques to estimate geometrical quantities,” explains Deep3DBox contributor Jana Kosecká, a computer scientist at George Mason University in Fairfax, Virginia.
However, when it comes to spotting and orienting bikes and bicyclists, performance drops significantly. Deep3DBox is among the best, yet it spots only 74 percent of bikes in the benchmarking test. And though it can orient over 88 percent of the cars in the test images, it scores just 59 percent for the bikes.”

So there’s still a good deal of development in the cards for most of these solutions — but, the great thing about this sort of machine learning is that after a certain point, they could potentially teach themselves! I’m a fan of anything that makes our roads safer for everybody — now if an A.I. could just talk some sense into those turkeys…