Hitting the Books: How winning the lottery is a lot like being re-struck by lightning

A wise man once said, “never tell me the odds” but whether you’re calculating the chances of successfully navigating an asteroid field (3,720:1), shouting “Shazam” and having it work twice in a row (9 million:1), or winning the state lottery (42 million:1 in California), probabilities influence outcomes in our daily lives for events large and small alike. But for the widespread role they play in our lives, your average person is usually just pretty ok with accurately calculating them. As we see in the excerpt below from James C. Zimring’s latest title, Partial Truths: How Fractions Distort Our Thinking, our expectations regarding the likelihood of an event occurring can shift, depending on how the question is posed and which fraction is focused upon.

partial truths cover
Columbia University Press

Excerpted from Partial Truths: How Fractions Distort Our Thinking by James C. Zimring, published by Columbia Business School Publishing. Copyright (c) 2022 James C. Zimring. Used by arrangement with the Publisher. All rights reserved.

Mistaking the Likely for the Seemingly Impossible: Misjudging the Numerator

The more unlikely an event seems, the more it draws our attention when it does occur and the more compelled we feel to explain why it happened. This just makes good sense. If the world is not behaving according to the rules we understand, perhaps we misunderstand the rules. Our attention should be drawn to unlikely occurrences because new knowledge comes from our attempts to understand contradictions.

Sometimes what seems to be impossible is actually highly probable. A famous example of this is found with playing the lottery (i.e., the lottery fallacy). It is well understood that it is incredibly unlikely that any particular person will win the lottery. For example, the chance of any one ticket winning the Powerball lottery (the particular lottery analyzed in this chapter) is 1/292,000,000. This explains why so much attention is paid to the winners. Where did they buy their ticket? Did they see a fortune teller before buying their ticket, or do they have a history of showing psychic abilities? Do they have any special rituals they carry out before buying a ticket? It is a natural tendency to try to explain how such an unlikely event could have occurred. If we can identify a reason, then perhaps understanding it will help us win the lottery, too.

The lottery fallacy is not restricted to good things happening. Explanations also are sought to explain bad things. Some people are struck by lightning more than once, which seems just too unlikely to accept as random chance. There must be some explanation. Inevitably, it is speculated that the person may have some weird mutant trait that makes them attract electricity, or they carry certain metals on their person or have titanium prosthetics in their body. Perhaps they have been cursed by a mystical force or God has forsaken them.

The lottery fallacy can be understood as a form of mistaking one probability for another, or to continue with our theme from part 1, to mistake one fraction for another. One can express the odds of winning the lottery as the fraction (1/292,000,000), in which the numerator is the single number combination that wins and the denominator is all possible number combinations. The fallacy arises because we tend to notice only the one person with the one ticket who won the lottery. This is not the only person playing the lottery, however, and it is not the only ticket. How many tickets are purchased for any given drawing? The exact number changes, because more tickets are sold when the jackpot is higher; however, a typical drawing includes about 300 million tickets sold. Of course, some of the tickets sold must be duplicates, given that only 292 million combinations are possible. Moreover, if every possible combination were being purchased, then someone would win every drawing. In reality, about 50 percent of the drawings have a winner; thus, we can infer that, on average, 146 million different number combinations are purchased.

Of course, the news does not give us a list of all the people who did not win. Can you imagine the same headline every week, “299,999,999 People Failed to Win the Lottery, Again!” (names listed online at www.thisweekslosers.com). No, the news only tells us that there was a winner, and sometimes who the winner was. When we ask ourselves, “What are the odds of that person winning?” we are asking the wrong question and referring to the wrong fraction. The odds of that particular person winning are 1/292,000,000. By chance alone, that person should win the lottery once every 2,807,692 years that they consistently play (assuming two drawings per week). What we should be asking is “What are the odds of any person winning?”

In probability, the chances of either one thing or another thing happening are the sum of the individual probabilities. So, assuming no duplicate tickets, if only a single person were playing the lottery, then the odds of having a winner are 1/292,000,000. If two people are playing, the odds of having a winner are 2/292,000,000. If 1,000 people are playing, then the odds are 1,000/292,000,000. Once we consider that 146 million different number combinations are purchased, the top of the fraction (numerator) becomes incredibly large, and the odds that someone will win are quite high. When we marvel at the fact that someone has won the lottery, we mistake the real fraction (146,000,000/292,000,000) for the fraction (1/292,000,000) — that is, we are misjudging the numerator. What seems like an incredibly improbable event is actually quite likely. The human tendency to make this mistake is related to the availability heuristic, as described in chapter 2. Only the winner is “available” to our minds, and not all the many people who did not win.

Similarly, the odds of twice being struck by lightning over the course of one’s life are one in nine million. Because 7.9 billion people live on Earth, it is probable that 833 people will be hit by lightning twice in their lives (at least). As with the lottery example, our attention is drawn only to those who are struck by lightning. We fail to consider how many people never get struck. Just as it is unlikely that any one particular person will win the Powerball lottery, it is highly unlikely that no one will win the lottery after a few drawings, just given the number of people playing. Likewise, it is very unlikely that any one person will be twice hit by lightning, but it is even more unlikely that no one will, given the number of people in the world.

So, when we puzzle over such amazing things as someone winning the lottery or being twice struck by lightning, we actually are trying to explain why a highly probable thing happened, which really requires no explanation at all. The rules of the world are working exactly as we understand them, but we are mistaking the highly likely for the virtually impossible.

What to look for in an electric lawn mower

The days of the gas-powered lawn mower and leaf blower are numbered in California. Last October, Governor Gavin Newsom signed AB 1346, banning the sale of new gas-powered tools in the state by 2024, akin to its ban on new internal combustion vehicle sales by 2035.

And the Golden State is far from alone, “I think that the easier the manufacturers make it for other states to adopt the same sort of ban, the more states will do it,” University of Southern California environmental law professor Robin Craig told CBS. Lawmakers in Illinois and New York both are seeking to pass similar bills at the state level while cities like Brookline, Massachusetts; Montclair, New Jersey; and Burlington, Vermont, have all independently enacted seasonal bans of their own on gas-powered leaf blowers.

And it’s not just because internal combustion (IC) landscaping equipment is so loud — leaf blowers average 70 dB at 50 feet (the operator hears closer to 95-100 dB) while mowers start at around 85 dB — they are also significant emitters of greenhouse gasses. The California Air Resources Board (CARB) notes that running an IC mower for 1 hour emits the equivalent amount of carbon as driving a 2017 Camry 300 miles from LA to Las Vegas. Operating a 2-stroke leaf blower for the same amount of time produces the same amount of carbon as driving to Denver, roughly 1,000 miles from LA.

Western Cape, South Africa, Man wearing protective clothing and safety helmet trimming grass in a garden. (Photo by: Peter Titmuss/Education Images/Universal Images Group via Getty Images)
Education Images via Getty Images

That’s actually an improvement from what we saw in the ‘80s and ‘90s before California instituted CARB. Today’s small engines are 40 to 80 percent more efficient and cleaner burning than they were before the agency got its start but, regardless, there are still some 16.7 million small (sub-19kW) engines in California — that’s three million more than the number of light duty passenger vehicles currently operating in the state. And given that the average price of a gallon of gas in America is currently $4.37 (the highest since 2000, per AAA), running all those noisy, thirsty mowers and blowers is getting untenably expensive as well.

With a long, hot summer of high gas prices imminent and the writing on the wall for 2-stroke engines, what better time than now to electrify your lawn care equipment? But before you head down to your local home improvement center, here’s some advice on what to look for in an electric mower directly from the people who design them.

Man mowing the grass with a manual petrol lawnmower.
Catherine Falls Commercial via Getty Images

Gas or Electric

Much like the auto industry’s ongoing transition from IC engines to EVs, lawn care equipment makers have spent recent years investing heavily in battery-based systems and have seen the performance of these power plants rapidly improve to be practically on par with the gas engines they’re replacing — not to mention being quieter, less expensive to operate and generally better for the environment.

For example, your average electric mower or leaf blower is going to produce around 75 dB of noise (equivalent to a running washing machine) — granted, that’s only a 10dB difference between the gas and electric motors, but because decibels are measured along a logarithmic scale, it actually sounds nearly half as loud to the human ear. And unlike gas mowers, using an electric doesn’t require you to don hearing protection (though safety glasses are always a good idea). What’s more, electric engines (with their decided lack of moving parts) wear much more gently than their internal combustion counterparts: No spark plugs to replace, oil to change, gas-oil ratios to measure and pour.

“Many professional-grade battery-powered tools come equipped with a brushless motor, which is virtually maintenance-free,” Stihl battery product manager, Paul Beblowski, told Engadget via email. “With a battery — there’s no need to buy, transport, or store fuel. There’s no tune-up for an electric motor and no need to winterize.” Aside from sharpening the cutting blade once a season or so, all owners really need to do is ensure the battery gets recharged before their next mowing session.

Vintage photograph of a woman in shorts and a sleeveless blouse pushing a gas powered lawn mover in a suburban backyard next to a swimming pool. in the 1950s. (Photo by Found Image Holdings/Corbis via Getty Images)
Found Image Holdings Inc via Getty Images

That’s not to say gas mowers are overnight relics. There are still plenty of use cases in which going with a conventional mower makes more sense, like when you need to clear more than an acre of land, or have to cut through dense, damp underbrush on difficult terrain, or are cutting on a remote field far from power outlets (sit down, Lightning Pro). A given unit of gasoline is still 100 times more energy dense than even the bloodiest-edge battery technology.

When it comes to choosing between a corded versus battery electric mower, “buyers must evaluate the size of their yard, access to outlet, and overall need for convenience,” Beblowski said. “It would make most sense to use a battery-driven mower when there is no access to an outlet or the customer wants the convenience provided by not dragging a cord through their yard. In addition, if the user is mowing around their pool or other water sources, it would make sense to stay away from cords and rely on a battery-driven mower.”

Another thing to consider is that while corded mowers will never run out of power, the amount that they can draw from a standard outlet cannot exceed 15 amps and 1800 watts (15 amps because that’s the US regulation, 1800 watts = 15 amps x 120 volts) — that’s actually the theoretical maximum and will continually throw breakers with that much load, so electric mowers typically top out at 13 amps (and therefore 1500 watts). So, if you’re looking for a heavy duty, high performance mower, especially a riding rig, battery-based systems will largely be your only electrified option.

How electric motors work

Standing in the power tool aisle of your local, prepare to be inundated with signage and branding calling out various aspects of the electric motor’s performance like “13 amps of power!” or “70 minutes of runtime!” These are helpful metrics but can be misleading and finding the right ratio of volts, watts and amps in that electric mower is paramount to getting the most out of your lawn care investment.

Lawn mower. Works in the garden. Spring season. Outdoor activity
Elena Gromova via Getty Images

For those of us that slept through that day of high-school science class, a quick analogy of how electricity works: it’s like plumbing. The given rate of water flowing through a pipe — Wattage, the electrical equivalent of gallons per minute — is determined by the ratio between the water pressure (aka Voltage) and the diameter of the pipe that it’s flowing through (the circuit’s Resistance). If you want to increase the wattage (that is boost the flow of electrons or, by this analogy, have more gallons flow per minute) you either have to increase the water pressure (increase the circuit’s voltage) or widen the pipe (i.e. use a higher amperage wire which lowers resistance).

“A good measuring tool for batteries is watt-hours (comparable to the size of a gas tank),” said Guy Dekowski, Outdoor Senior Product Manager at Dewalt. “Battery watt-hours are battery voltage multiplied by amp hours. This is a good signal of how long the mower can potentially run.”

“It’s important to differentiate between voltage and the amount of work a tool can actually do,” Beblowski said, noting that equating voltage to a motor’s overall power is a common misconception. “While voltage is a factor, the true energy capacity of a battery is measured in watt-hours… the watt-hours tell you the power of the tool. So, if you have an 80-volt system and a 2 Ah battery, you’re looking at 160 watt-hours, but if you have a 36-volt system and a 5 Ah battery, the power is actually higher at 180 watt-hours.”

Unfortunately there is no hard and fast rule governing whether high voltage – low amp tools or low voltage – high amp tools are generally superior. “There are pros and cons to both configurations,” said Dekowski. “Generally higher voltage is capable of more power; however there are variables outside of voltage and current to consider. For example, the deck and blade design have an impact on performance.”

“Hills and the thickness of their grass,” are two yard feature factors users should consider, Dekowski continued. “If a user has an incline, a self-propelled mower may suit them best. The thickness of the grass also plays a factor in the runtime of their mower. In thicker grass, the mower will pull more power driving the need for a mower capable of longer runtime.”

What to look for in an electric mower

The size and shape of your lawn will also impact the size and style of the mower that you need. Pay attention to the mower’s deck size, that indicates how wide of a swath it can clear with each pass. You’ll clear your yard in fewer passes with a 21-inch deck than you will with a 14-inch, though the corollary to that is wider mowers tend to be heavier and less maneuverable than their skinnier counterparts.

If you’ve got a compact urban backyard that needs tending, you can more likely get away with just a small push mower such as the 14-inch Worx 40V, 4Ah Power Share. More expansive suburban yards will do well with a larger, perhaps self-propelled model like the 21-inch Stihl 36V, 6Ah RMA 510 or a 20-inch, 12-amp corded Greenworks mower, while rural homeowners might need something a bit more heavy-duty like Toro’s 21-inch 60V, 6Ah Super Recycler or this 42-inch, 75Ah rideable Ryobi.

“Twenty to 21-inch decks are the most popular for a couple reasons,” Dekowski said. “First, it helps keep the weight at a minimum but the deck is still large enough to minimize work. The other benefits are maneuverability and compactness for storage.”

Like any other tool purchase, when shopping for a new mower try to stick to established, reputable brands like Stihl, Stanley Black and Decker (which owns DeWalt), Makita, Ryobi, Toro, Hart, Greenworks and Sun Joe. Pricing is going to range anywhere from around $125 for a compact, corded unit for urban yards up to a couple thousand for a burly zero-turn riding mower.

A young girl in a straw hat is mowing a lawn in the backyard with an orange lawn mower. A woman gardener is trimming grass with the grass cutter. A lawnmower is cutting a lawn on a summer sunny day.
Zhanna Danilova via Getty Images

Regardless of which brand you choose there are a few features that you should look for in a quality electric mower:

  • Deck material: Avoid mowers with plastic decks. Sure you’ll save a few pounds in weight but those made with metal housings will stand up to the elements, kicked stones and general wear and tear for far longer than their plastic counterparts.

  • Comfortable handles: You’re going to be squeezing these things for the better part of an hour as you systematically amble around the yard, better make sure they’re not going to chafe.

  • Big wheels: Getting stuck in a rut is bad enough when it’s just in the metaphorical sense. Make sure it doesn’t happen where the neighbors can see by using a mower with 10-inch rear, 8-inch front ball bearing wheels, suggests Beblowski.

  • Height adjustment: As a rule of thumb, you should be taking off about a third of the grass’ total height every time you mow (chopping it to about 2 to 3¾ inches tall). However, weather and solid conditions will impact how fast the blades grow between cuttings so having a mower that can adjust its blade height is key to maintaining a healthy lawn. Look for a model that can span from 1 – 4-inches off the ground.

  • Beware the brush: Electric motors come in two flavors — brush and brushless. The former has a tendency to overheat and stall while the latter generates more power, less heat and requires basically zero maintenance. Guess which you should choose.

  • Bagging options: Your willingness to go back and rake the whole yard vs stop occasionally to empty clippings on to the compost pile is a pretty strong indicator of whether you should spring for a side discharge, mulching or bagging mower.

  • Accessorize: One of the biggest benefits of choosing a battery over a corded mower is that manufacturers designed their battery packs to work in a wide array of power tools and gadgets, from leaf blowers and limb loppers to snowblowers and soil tillers. So if you’re looking to update more than just your mower, maybe take a look and see what other gadgets its batteries are rated for use on.

With the long Memorial Day weekend just around the corner, now is the perfect time to get your yard trimmed up and ready for post-lockdown barbeque parties — as well as defensible for what’s sure to be an unrelenting wildfire season throughout the American West.

Cadillac’s Lyriq EV will start at $62,990

Cadillac has released more details about the vehicle and its features ahead of online orders reopening for its highly-anticipated Lyriq EV on May 19th. The crossover will start at $62,990 and just $2,000 more for its 4WD variant. What’s more, Cadillac is sweetening the deal by including either two years of unlimited public charging through EV Go or up to a $1,500 credit for a home charging unit through QMerit.

Orders will open for both the RWD and AWD versions at the end of this week. Customers will have two additional exterior paint options — Opulent Blue Metallic and Crystal White Tricoat — to choose from that happens. Customers should expect the RWD models to arrive first — it’s coming this fall after the summer production run of the Lyriq Debut Edition concludes. The AWD models should hit dealerships by early next year. Cadillac also unveiled the EPA-rated mileage of 312 miles for the RWD Lyric (no official word yet on the AWD version but assume it to be a bit lower). 

The company also announced on Monday that it is partnering with both charging station network EV Go and home charging system installers, QMerit, to help reticent buyers overcome their range anxiety through the judicious application of cash. Lyric shoppers will have their pick of two included charging options: two years of unlimited charging sessions at EV Go’s 850-plus stations or they’ll receive up to a $1,500 rebate for the installation of a Level 2 AC home charging unit. Opting for the public charging option will be faster (with a 190kW max rate on a Level 3 DC charger, the Lyric will add 76 miles of range in about 10 minutes) while the home charging method won’t require you to hang around a parking lot for 45 minutes while the Lyric’s batteries refill.  

Hitting the Books: Why we need to treat the robots of tomorrow like tools

Do not be swayed by the dulcet dial-tones of tomorrow’s AIs and their siren songs of the singularity. No matter how closely artificial intelligences and androids may come to look and act like humans, they’ll never actually be humans, argue Paul Leonardi, Duca Family Professor of Technology Management at University of California Santa Barbara, and Tsedal Neeley, Naylor Fitzhugh Professor of Business Administration at the Harvard Business School, in their new book The Digital Mindset: What It Really Takes to Thrive in the Age of Data, Algorithms, and AI — and therefore should not be treated like humans. The pair contends in the excerpt below that in doing so, such hinders interaction with advanced technology and hampers its further development.

Digital Mindset cover
Harvard Business Review Press

Reprinted by permission of Harvard Business Review Press. Excerpted from THE DIGITAL MINDSET: What It Really Takes to Thrive in the Age of Data, Algorithms, and AI by Paul Leonardi and Tsedal Neeley. Copyright 2022 Harvard Business School Publishing Corporation. All rights reserved.

Treat AI Like a Machine, Even If It Seems to Act Like a Human

We are accustomed to interacting with a computer in a visual way: buttons, dropdown lists, sliders, and other features allow us to give the computer commands. However, advances in AI are moving our interaction with digital tools to more natural-feeling and human-like interactions. What’s called a conversational user interface (UI) gives people the ability to act with digital tools through writing or talking that’s much more the way we interact with other people, like Burt Swanson’s “conversation” with Amy the assistant. When you say, “Hey Siri,” “Hello Alexa,” and “OK Google,” that’s a conversational UI. The growth of tools controlled by conversational UIs is staggering. Every time you call an 800 number and are asked to spell your name, answer “Yes,” or say the last four numbers of your social security number you are interacting with an AI that uses conversational UI. Conversational bots have become ubiquitous in part because they make good business sense, and in part because they allow us to access services more efficiently and more conveniently.

For example, if you’ve booked a train trip through Amtrak, you’ve probably interacted with an AI chatbot. Its name is Julie, and it answers more than 5 million questions annually from more than 30 million passengers. You can book rail travel with Julie just by saying where you’re going and when. Julie can pre-fill forms on Amtrak’s scheduling tool and provide guidance through the rest of the booking process. Amtrak has seen an 800 percent return on their investment in Julie. Amtrak saves more than $1 million in customer service expenses each year by using Julie to field low-level, predictable questions. Bookings have increased by 25 percent, and bookings done through Julie generate 30 percent more revenue than bookings made through the website, because Julie is good at upselling customers!

One reason for Julie’s success is that Amtrak makes it clear to users that Julie is an AI agent, and they tell you why they’ve decided to use AI rather than connect you directly with a human. That means that people orient to it as a machine, not mistakenly as a human. They don’t expect too much from it, and they tend to ask questions in ways that elicit helpful answers. Amtrak’s decision may sound counterintuitive, since many companies try to pass off their chatbots as real people and it would seem that interacting with a machine as though it were a human should be precisely how to get the best results. A digital mindset requires a shift in how we think about our relationship to machines. Even as they become more humanish, we need to think about them as machines— requiring explicit instructions and focused on narrow tasks.

x.ai, the company that made meeting scheduler Amy, enables you to schedule a meeting at work, or invite a friend to your kids’ basketball game by simply emailing Amy (or her counterpart, Andrew) with your request as though they were a live personal assistant. Yet Dennis Mortensen, the company’s CEO, observes that more than 90 percent of the inquiries that the company’s help desk receives are related to the fact that people are trying to use natural language with the bots and struggling to get good results.

Perhaps that was why scheduling a simple meeting with a new acquaintance became so annoying to Professor Swanson, who kept trying to use colloquialisms and conventions from informal conversation. In addition to the way he talked, he made many perfectly valid assumptions about his interaction with Amy. He assumed Amy could understand his scheduling constraints and that “she” would be able to discern what his preferences were from the context of the conversation. Swanson was informal and casual—the bot doesn’t get that. It doesn’t understand that when asking for another person’s time, especially if they are doing you a favor, it’s not effective to frequently or suddenly change the meeting logistics. It turns out it’s harder than we think to interact casually with an intelligent robot.

Researchers have validated the idea that treating machines like machines works better than trying to be human with them. Stanford professor Clifford Nass and Harvard Business School professor Youngme Moon conducted a series of studies in which people interacted with anthropomorphic computer interfaces. (Anthropomorphism, or assigning human attributes to inanimate objects, is a major issue in AI research.) They found that individuals tend to overuse human social categories, applying gender stereotypes to computers and ethnically identifying with computer agents. Their findings also showed that people exhibit over-learned social behaviors such as politeness and reciprocity toward computers. Importantly, people tend to engage in these behaviors — treating robots and other intelligent agents as though they were people — even when they know they are interacting with computers, rather than humans. It seems that our collective impulse to relate with people often creeps into our interaction with machines.

This problem of mistaking computers for humans is compounded when interacting with artificial agents via conversational UIs. Take for example a study we conducted with two companies who used AI assistants that provided answers to routine business queries. One used an anthropomorphized AI that was human-like. The other wasn’t.

Workers at the company who used the anthropomorphic agent routinely got mad at the agent when the agent did not return useful answers. They routinely said things like, “He sucks!” or “I would expect him to do better” when referring to the results given by the machine. Most importantly, their strategies to improve relations with the machine mirrored strategies they would use with other people in the office. They would ask their question more politely, they would rephrase into different words, or they would try to strategically time their questions for when they thought the agent would be, in one person’s terms, “not so busy.” None of these strategies was particularly successful.

In contrast, workers at the other company reported much greater satisfaction with their experience. They typed in search terms as though it were a computer and spelled things out in great detail to make sure that an AI, who could not “read between the lines” and pick up on nuance, would heed their preferences. The second group routinely remarked at how surprised they were when their queries were returned with useful or even surprising information and they chalked up any problems that arose to typical bugs with a computer.

For the foreseeable future, the data are clear: treating technologies — no matter how human-like or intelligent they appear — like technologies is key to success when interacting with machines. A big part of the problem is they set the expectations for users that they will respond in human-like ways, and they make us assume that they can infer our intentions, when they can do neither. Interacting successfully with a conversational UI requires a digital mindset that understands we are still some ways away from effective human-like interaction with the technology. Recognizing that an AI agent cannot accurately infer your intentions means that it’s important to spell out each step of the process and be clear about what you want to accomplish.

Google makes its AI assistant more accessible with ‘Look and Talk’

Google Assistant is already pretty handy, filling in your payment info on take out orders, helping get the kids to school on time, controlling your stereo systems’ volume and your home’s smart light schedules. At its I/O 2022 keynote today, company executives showed off some of the new features arriving soon for the AI.

The first of these is “Look and Talk.” Instead of having to repeatedly start your requests to Assistant with “Hey Google,” this new feature relies on computer vision and voice matching to constantly pay attention to the user. As Sissie Hsiao, Google’s VP of Assistant, explained on stage, all the user has to do is look at their Nest Hub Max and state their request. Google is also developing a series of quick commands that users will be able to shout out without having to gaze longingly at their tablet screen or say “Hey Google” first — things like “turn on the lights” and “set a 10-minute alarm.”

asdf
Alphabet

All of the data captured in that interaction — specifically the user’s face and voice prints, used to verify the user — are processed locally on the Hub itself, Hsiao continued, and not shared with Google “or anyone else.” What’s more, you’ll have to specifically opt into the service before you can use it.

According to Hsiao, the backend of this process relies on a half-dozen machine learning models and 100 camera and mic inputs — i.e., proximity, head orientation and gaze direction — to ensure that the machine knows when you’re talking to it versus talking in front of it. The company also claims that it worked diligently to make sure that this system works for people across the full spectrum of human skin tones. 

Looking ahead, Google plans to continue refining its NLP models to further enhance the responsiveness and fidelity of Assistant’s responses by “building new, more powerful speech and language models that can understand the nuances of human speech,” Hsiao said. “Assistant will be able to better understand the imperfections of human speech without getting tripped up — including the pauses, ‘umms’ and interruptions — making your interactions feel much closer to a natural conversation.”

Follow all of the news from Google I/O 2022 right here!

Google Maps adds an ‘Immersive View’ of major cities

Google Maps is getting an “Immersive View” that will offer users digitally rendered looks at major US cityscapes, Alphabet CEO Sundar Pichai told the audience at Google’s I/O 2022 keynote on Wednesday.  

The new feature uses computer vision and AI to blend Maps’ existing Street View function with aerial photography to create high-resolution models of the various buildings and urban features of a given location. “With our new immersive view, you’ll be able to experience what a neighborhood, landmark, restaurant or popular venue is like — and even feel like you’re right there before you ever set foot inside,” wrote Miriam Daniel, VP of Google Maps, in a blog post. What’s more, Maps’ other tools and features can be applied to the view as well, enabling users to see what the area looks like at different times of the day and varying weather conditions.

Immersive View will first be available for Los Angeles, London, New York, San Francisco and Tokyo later this year, with more cities to follow. The company also notes that its recently released eco-routing feature, which lets drivers in the US and Canada to pick the most fuel efficient route for their trip, has already been used to travel 86 billion miles and prevented the release of roughly half a million metric tons of carbon emissions.

Google isn’t the only company making its navigation systems more readable and user friendly. At WWDC 2021 last June, Apple rolled out a higher-fidelity version of its Maps app, offering added detail like elevation gradients, brighter road colors, more prominent location labels, and hundreds of custom icons for local landmarks.

Follow all of the news from Google I/O 2022 right here!

SLAC’s newest laser works best when it’s colder than outer space

After nearly a decade in development, the second iteration of the Linac Coherent Light Source (LCLS) at the DoE’s Stanford Linear Accelerator Center (SLAC) is nearly ready to start throwing photons harder than ever before. Dubbed the LCLS-II, this billion-dollar superconducting particle accelerator upgrade will produce X-rays 10,000 times brighter than those of its predecessor at a world record rate of 1 million pulses per second — all while working at a frosty negative 456 degrees Fahrenheit.

“In just a few hours, LCLS-II will produce more X-ray pulses than the current laser has generated in its entire lifetime,” Mike Dunne, director of LCLS, said. “Data that once might have taken months to collect could be produced in minutes. It will take X-ray science to the next level, paving the way for a whole new range of studies and advancing our ability to develop revolutionary technologies to address some of the most profound challenges facing our society.”

The original LCLS came online in 2009, shining a billion times brighter than the accelerator it replaced, but was limited to 120 pulses per second because the laws of physics limit the number of electrons that could be pushed simultaneously through the accelerator’s labyrinth of room-temperature copper pipes. But by replacing those pipes with more than three dozen cryogenic accelerator modules — interconnected strings of hollow niobium — cooled down to 2 Kelvin (4 degrees F above absolute zero), SLAC researchers can massively improve the accelerator’s output. 

“To reach this temperature, the linac is equipped with two world-class helium cryoplants, making SLAC one of the significant cryogenic landmarks in the U.S. and on the globe,” Eric Fauve, director of the Cryogenic Division at SLAC, said. “The SLAC Cryogenics team has worked on site throughout the pandemic to install and commission the cryogenic system and cool down the accelerator in record time.”

Once the electrons have passed through all 37 cryo modules and been sufficiently cooled, they’re energized and accelerated by a megawatt microwave to nearly the speed of light and fed through a string of undulator magnets that force the electron beam into a zig-zag pattern, generating X-rays. What’s more, the undulators can influence the type of X-ray that’s produced — either hard X-rays for material imaging, or soft X-rays primarily used to document energy flows and real-time chemical reactions.

The LCLS-II first hit the 2 Kelvin mark in mid-April and with Tuesday’s announcement is now ready to begin conducting research. That’s expected to happen later this year and could help us examine cutting-edge materials and biological processes in greater resolution than ever before, advance the state of the art in clean energy technology and even unlock the secrets of the quantum realm by imaging individual atoms.

IBM wants its quantum supercomputers running at 4,000-plus qubits by 2025

Forty years after it first began to dabble in quantum computing, IBM is ready to expand the technology out of the lab and into more practical applications — like supercomputing! The company has already hit a number of development milestones since it re…

Clearview AI agrees to limit sales of facial recognition data in the US

Notorious facial recognition company Clearview AI has agreed to permanently halt sales of its massive biometric database to all private companies and individuals in the United States as part of a legal settlement with the American Civil Liberties Union, per court records.

Monday’s announcement marks the close of a two-year legal dispute brought by the ACLU and privacy advocate groups in May of 2020 against the company over allegations that it had violated BIPA, the 2008 Illinois Biometric Information Privacy Act. This act requires companies to obtain permission before harvesting a person’s biometric information — fingerprints, gait metrics, iris scans and faceprints for example — and empowers users to sue the companies who do not. 

“Fourteen years ago, the ACLU of Illinois led the effort to enact BIPA – a groundbreaking statute to deal with the growing use of sensitive biometric information without any notice and without meaningful consent,” Rebecca Glenberg, staff attorney for the ACLU of Illinois, said in a statement. “BIPA was intended to curb exactly the kind of broad-based surveillance that Clearview’s app enables. Today’s agreement begins to ensure that Clearview complies with the law. This should be a strong signal to other state legislatures to adopt similar statutes.”

In addition to the nationwide private party sales ban, Clearview will not offer any of its services to Illinois local and state law enforcement agencies (as well as all private parties) for the next five years. “This means that within Illinois, Clearview cannot take advantage of BIPA’s exception for government contractors during that time,” the ACLU points out, though Federal agencies, state and local law enforcement departments outside of Illinois will be unaffected. 

That’s not all. Clearview must also end its free trial program for police officers, erect and maintain an opt-out page for Illinois residents, and spend $50,000 advertising it online. The settlement must still be approved by a federal judge before it takes effect.

“By requiring Clearview to comply with Illinois’ pathbreaking biometric privacy law not just in the state, but across the country, this settlement demonstrates that strong privacy laws can provide real protections against abuse,” Nathan Freed Wessler, a deputy director of the ACLU Speech, Privacy, and Technology Project, said in Monday’s statement. “Clearview can no longer treat people’s unique biometric identifiers as an unrestricted source of profit. Other companies would be wise to take note, and other states should follow Illinois’ lead in enacting strong biometric privacy laws.” 

Monday’s settlement is the latest in a long line of privacy lawsuits and regulatory actions against the company. Clearview AI was slapped with a €20 million fine by Italian regulators in March and £17 million in November by the UK, both for violations of national data privacy laws. Australia has been investigating the company’s scraping schemes since 2020 and, currently, a small group of US lawmakers are lobbying to ban Federal agencies from using Clearview’s services entirely. But given that the company boasted in February that it had amassed 100 billion images in its “index of faces,” the right to anonymity in America remains deeply in peril.

Hitting the Books: US regulators are losing the fight against Big Tech

Today’s technology landscape is dominated by a small cadre of massive corporations with the likes of Meta, Amazon and Google snapping up fledgling startups before they can grow into potential competitors, ignoring labor laws that don’t suit their immediate needs, and generally operating like the dystopian corpro-villains Johnny Mnemonic warned us about. Traditionally, state regulation has acted as a gentle brake against American industries’ more problematic tendencies, however the speed at which modern computing and communications technologies advance has overwhelmed the government’s capacity to, well, govern them. 

In their new book, Access Rules: Freeing Data from Big Tech for a Better Future, Viktor Mayer-Schönberger, Professor of Internet Governance and Regulation at Oxford, and Thomas Ramge, author of Who’s Afraid of AI?, argue passionately against the data-hoarding practices of today’s biggest tech companies and call for a more open, equitable means of accessing the information that these companies have amassed. One such method, explored in the excerpt below, involves addressing Big Tech’s monopoly power directly, as the Biden administration has in recent years, though the efforts have not been particularly effective. 

white background and that spinny loading symbol you get when you run more than 12 chrome tabs simultaneously. No not the beachball, the other one with the circle of blinky lines -- yeah that one, but make it rainbow colors. Same with the authors' names at the top, rainbow for that text too.
UC Press

Excerpted from Access Rules: Freeing Data from Big Tech for a Better Future by Viktor Mayer-Schönberger and Thomas Ramge, published by the University of California Press. © 2022 by Thomas Ramge and Viktor Mayer-Schönberger.

Early into his term, President Biden appointed Tim Wu, who had argued in favor of breaking up Facebook and written popular books on the dangers of Big Tech market concentration, to the National Economic Council as a special assistant to the president for technology and competition policy. Putting one of the most outspoken advocates of Big Tech trustbusting into a top advisory role is a powerful signal the Biden administration is taking a far more confrontational course.

Wu isn’t alone. His appointment was followed by the choice of Lina Khan for chair of the Federal Trade Commission (FTC). Khan’s youth — she was in her early 30s when nominated — belies her intellectual power and political credentials. A professor at Columbia Law School like Wu, Khan had authored influential papers on the need to fight Big Tech’s unchecked power. And she had explained why existing antitrust law was ill equipped to deal with Silicon Valley platform providers. But Khan isn’t just a Big Tech critic; she also offered a radical solution: regulate Big Tech companies as utilities, much like electricity providers or the venerable AT&T before telecom deregulation. With Khan at the FTC and Wu as advisor having the ear of the president, Big Tech could be in serious trouble.

Not just antitrust experts serving in government like Tim Wu and Lina Khan fear that the monopolistic structure of American tech dominance could turn into its Achilles heel. Think tanks and advocacy groups on both left and right have been joining the critics. Disruptive entrepreneurs and venture capitalists such as Elon Musk and Peter Thiel regard the well-rehearsed dance of Big Tech and venture capital with increasing skepticism, concerned that the intricate choreography is thwarting the next generation of disruptive founders and technologies. Taken together these voices are calling on and supporting regulators and legislators to prevent the most obvious cases of large companies removing potential competitors from the market by acquiring them—cases comparable to Facebook’s takeover of Instagram or Google’s acquisition of Waze. And they call on venture capitalists to take on the role for which Joseph Schumpeter originally conceived this class of investment capital, the role that the venture capitalists on Sand Hill Road in Menlo Park fulfilled up to the first decade of this century: financially support the bringing to market of new, radically better ideas and then enable them to be scaled up.

The antitrust tide is rising in the United States. And yet it’s questionable that well-intentioned activist regulators bolstered by broad public support will succeed. The challenge is a combination of the structural and the political. As Lina Khan herself argued, existing antitrust laws are less than useful. Big Tech may not have violated them sufficiently to warrant breaking them up. And other powerful measures, such as declaring them utilities, require legislative action. Given the delicate power balance in Congress and hyper-partisan politics, it’s likely that such bold legislative proposals would not get enough votes to become enacted. The political factions may agree on the problem, but they are far apart on the solution. The left wants an effective remedy, while the right insists on the importance of market forces and worries about antitrust action micromanaging economic activity. That leaves a fairly narrow corridor of acceptable incremental legislative steps, such as “post-acquisition lockups.” This may be politically palatable, but insufficient to achieve real and sustained success.

The truth is that the current game based on exit strategies works only too well for everyone involved, at least in the short term. The monopolists continue to increase their rents. Entrepreneurs get rich quickly. Venture capitalists reduce risk by optimizing their investments for exiting through a sale. And government? It too earns money on every “Goliath buying David” transaction. Preventing such transactions causes annoyance for everyone involved. Any politician mounting a serious attack on Big Tech USA exposes themselves to the charge of endangering the great successes of American technology companies on global markets—a charge few politicians could fend off.

Despite renewed resolve by the Biden administration to get serious against Big Tech overreach, substantial change still seems elusive in the United States. In contrast, European antitrust authorities have been far more active. The billion-dollar fines lobbed at US Big Tech by Commissioner Vestager’s team surely sound impressive. But, as we mentioned, most of them were reduced on appeal to an amount that the superstar companies with huge cash reserves and skyrocketing profits could easily afford. The European Parliament may not suffer from hyper-partisanship and be willing to strengthen antitrust rules, but their effectiveness is limited by the very fact that almost all Big Tech is not European. At best, Europeans might prevent US Big Tech from buying up innovative European start-ups; the necessary laws for this are increasingly being enacted. But that will do little to break Big Tech’s information power.

The challenge faced by European regulators is shared by regulators around the globe, from the Asian Tigers to the Global South: how can national regulators effectively counter the information might amassed by Silicon Valley superstars? Sure, one could prohibit US Big Tech from operating. But that would deprive the local economy of valuable services. For most nations, such binary disengagement is not an option. And for nations that to an extent can and have disengaged, such as China, their homegrown Big Tech companies confront them with similar problems. The huge fines levied on Alibaba in 2021 surely are surprising for outside observers, but they, too, are targeting symptoms, not the root cause of Big Tech’s power.

Sooner or later, regulators and legislators will have to confront the real problem of reining in Big Tech: whether we look at Draconian measures like breakups or incremental ones like fines and acquisition lockups, these target the symptoms of Big Tech’s information power, but do little to undo the structural advantages the digital superstars possess. It’s little more than cutting a head off Hydra, only to see a new one grow.

To tackle the structural advantage, we have to remember Schumpeter. Schumpeter’s nightmare was that the capacity for innovation would become concentrated within a few large companies. This would lead to a downward spiral of innovation, as major players have less incentive to be disruptive and far more reason to enjoy market power. Contrary to Schumpeter’s fear, this concentration process didn’t occur after World War II, mainly because entrepreneurs had access to abundant capital and could thrive on disruptive ideas. They stood a real chance against the large incumbents of their time, a role more than a few of them took on themselves. But money is no longer the scarce resource limiting innovation. What’s scarce today is access to data. More precisely, such a scarcity is being artificially created.

In the data economy, we’re observing a concentration dynamic driven by narrowing access to the key resource for innovation and accelerated by AI. The dynamic therefore turns on access to data as a raw material. Economic policy to counteract market concentration and a weakening of competition must focus on this structural lever.

If we want to avert Schumpeter’s nightmare, preserve the competitiveness of our economy, and strengthen its capacity for innovation, we have to drastically widen access to data — for entrepreneurs and start-ups and for all players who can’t translate their ideas into innovations without data access. Today, they can only hope to enter the kill zone and be bought up by one of the digital giants. If data flows more freely through broader access, the incentive to use data and gain innovative insights from it increases. We’d turbocharge our economy’s capacity for innovation in a way not seen since the first wave of Internet companies. We would also learn more about the world, make better decisions, and distribute data dividends more broadly.