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Wild Mind Artisan Ales sued its former brewer. Then things got ugly. – City Pages

Another was its coolship, a long, shallow steel tub traditional to Belgian ale brewing. This coolship chills the wort (the mixture of malt and hot water, step one of beer-making) overnight in the open air, allowing bacteria and naturally occurring yeast to creep into the beer.

The resulting brew is always sour, often a little strange, and rare around these parts. (In awarding Best Brewery honors in 2019, City Pages called Wild Minds coolship sour program trailblazing.) A 2017 blog post on the brewerys website credits brewer Mat Waddell with wielding its coolship, the first one in Minnesota for spontaneous fermentation in the lambic style of brewing.

The website is outdated. Waddell left the brewery more than a year ago. And these days Wild Mind leaves writing about Waddell up to its lawyers.

Wild Mind started as a three-man operation. Tylor Johnson and Jason Sandquist had business backgrounds in property and commercial real estate. Waddell, who quit a job as an engineer with Medtronic and invested $40,000 in the brewery out-of-pocket, was the brewing brain.

In mid-December 2018, Waddell told Sandquist and Johnson he wanted out, and was taking a job with 3M. Exactly how Waddell explained his career change is still in dispute. Sandquist and Johnson took the announcement as news Waddell was leaving the brewing industry altogether. Waddell, in a response filed by his attorney, says he just wanted to resign from Wild Mind.

According to legal filings, Waddell negotiated a buyout of his 35 percent stake in the company for $150,000. Then, a few months later, his name and face resurfaced, this time as the head of the mixed culture line of sour beers at BlackStack Brewing in St. Paul. Pictures from a May 7, 2019 story on the Growlers website showed Waddell and the BlackStack crew sipping pints and smiling.

Two days later, attorneys at Chestnut Cambronne issued a letter accusing Waddell of sharing confidential information and trade secrets of Wild Mind. The letter laid out a slew of accusations against Waddell, including that hed deleted Wild Minds beer recipes, though not before reliable sources saw him photograph the recipes off a computer screen.

The letter ordered Waddell to return the recipes and cease and desist his new venture, which, it warned, may expose BlackStack to liability to say nothing of Waddell himself, who was officially put on notice that there is a dispute and potential litigation.

This was merely the first volley in a series of escalating exchanges that culminated in Wild Mind Artisan Ales, LLC, filing suit against Mat Waddell in December 2019, a year and a few days after hed told his former business partners he was leaving. Exposed to the open air, the relationships behind Wild Mind were just as surprisingand souras the mixtures in its prized coolship.

In the months since that first letter, the two feuding parties have only grown further apart in their understanding of the basic facts surrounding Waddells tenure at, and exit from, Wild Mind.

The brewerys complaint added new claims, including the sweeping allegation that Waddell had been grossly derelict and rarely present for most of the entire year before he left. Through this inattention, the brewery alleged, two batches of beer that either had not been checked or managed or had not been properly brewed had to be dumped by Waddells successor, at a loss of some $105,000 to the brewery.

The complaint also restated that Wild Mind no longer had access to its recipes, that Waddell purposely misled his partners about his future plans to avoid the inclusion of a non-compete provision, and that his collaboration with BlackStack necessarily requires disclosure of Wild Minds confidential information.

Waddells attorney, Aaron Thom, fired back with a response filed in January, rebutting most of the claims in the complaint. Wild Minds recipes are stored on software the company still has, his response says, and he hasnt shared any proprietary information through his work for BlackStack.

Waddell didnt stop there, layering on explosive counter-claims of his own:

That in three years, Waddell was underpaid on his expected salary of $55,000 by a total of roughly $76,000;

That one bartender quit after Johnson made inappropriate sexual advances toward her, and another quit after confronting Sandquist for taking and retaining tips, as he often did on weekend shifts;

That Waddell had started working different hours to avoid a toxic environment set by his partners, who lost their tempers and ridiculed him in public.

Sandquist and Johnson deny the allegations about their conduct through Wild Minds attorney, Emeric Dwyer, who said, It is unfortunate that Mr. Waddell [has] chosen to try and invent or embellish facts to embarrass members of the company to make dirty laundry public, and force the company into backing down on its claims.

Wild Minds key argument, that Waddell misrepresented his exit to avoid a non-compete clause, is not just semantics, Dwyer says. At its heart, it is a matter of, how do you protect a companys reputation and intellectual property?

The two sides met in court for the first time earlier this month for a hearing on two motions. Thom, Waddells attorney, argued Wild Mind should have to pay his legal fees upfront during the case. Wild Mind, meanwhile, pushed for monthly payments from Waddells buyout to instead be paid into the court, pending a settlement or ruling. The judge has 90 days to rule on both motions.

The buyout itself might be their next battleground: Waddell now believes $150,000 undervalued his share of the company, and his attorney says hes mulling the idea of rescinding that agreement to bargain for a better deal.

Waddell says opening a brewery was an epically great creative outlet for him, and made great connections for him within the local brewing community, but that he was happy to leave Wild Mind behindor so he thought.

I was back to being me, and it was wonderful, Waddell says of starting his new job at 3M. Then in May, when I got that first cease and desist letter, my heart just sank.

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Wild Mind Artisan Ales sued its former brewer. Then things got ugly. - City Pages

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LETTERS: COVID-19 on the mind | Letters – Waco Tribune-Herald

Helping out

While reading up more on the COVID-19 situation, I have seen the two major responses people have made. Some have chosen to take care of themselves at the expense of others. Some, but not all, of their decisions might be based on fear. The other response is reminiscent of Fred Rogers address made after the attacks on 9/11. He recalled his mother telling him to look for the helpers. You will always find people who are helping.

If you dont see helpers in your community, then take the opportunity to become one. I see helpers in my friends and some businesses willing to provide food to school children while schools are closed, or neighbors on social media offering some of their supplies to others who didnt get any at the store. Even as we take precautions on contact with each other to slow the viral spread, ways still exist to be a neighbor and a helper. There are plenty of supplies to go around if we all work together. Choose to be a helper.

Jake Myers, Robinson

President Reagan said: Government is not the solution to our problem. Government is the problem. Conservative Grover Norquist said: My goal is to cut the government in half in 25 years, to get it down to the size where we can drown it in the bathtub.

Trump advocated that the government was a collection of deep-state employees there to impose taxes and regulations that did not represent the people. Trump said his great brain could easily handle the economy, health care and trade. What we have now are acting secretaries, a hollowed-out State Department and Homeland Security. He has downsized the National Security Council. The acting director of National Intelligence has absolutely no experience in intelligence. He even hired a college senior (no experience) to work in the White House.

Trump was told of the impending virus last December. He elected to do nothing for months. Who needs experience and know-how? We are the ones who must deal with this colossal magnitude of incompetence and narcissism who never takes the blame for anything. He labeled COVID-19 as Democrats new hoax and said: One day, its like a miracle, it will disappear.

This president has no idea how government works. He has put the lives of all citizens at great risk because his great brain has no concept of what is happening or how to handle this looming catastrophe. Government is drowning in the Trump bathtub.

Randy Broussard, Belton

* * *

New York Gov. Andrew Cuomo announced a few days ago that the State of New York will contract with private laboratories to help administer coronavirus testing for New York residents. Cuomo stated: We are not in a position where we can rely on the CDC or the FDA to manage this testing protocol.

Its interesting that politicians, who have longed for the day when the government finally takes over and runs health care in this country, have awakened to the realization we cannot rely on government. Bernie Sanders has made a career of demonizing Big Pharma and would love to shut them down. But when we need test kits or a vaccine for a deadly virus, to whom do we turn? The government or the private sector? Andrew Cuomo was unequivocal: he turned to private labs.

We dont need clueless government bureaucrats trying to run our medical-care system anymore than we need them to grow our food.

David B. Anderson, Waco

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Council Installed Cameras with Facial Recognition on Football Pitch – Dublin Inquirer

Photos by Sean Finnan

Before the refurbishment of the football pitch at Bluebell Road in the west of the city, it was an anti-social blackspot, says Michael OShea, chairman of Inchicore Athletic FC.

That was our homeground and it was a grass pitch, and they were constantly getting cars burned on it and broken bottles, says OShea. It was in darkness all the time, so you never really seen who was on it.

After a refurbishment in November 2018 for Dublin City Council, a new artificial astroturf pitch was installed, as well as floodlighting and a new high-tech closed-circuit television (CCTV) security system.

I think its after drastically reducing the rate of anti-social behaviour in the area, says OShea.

Installed on the football pitch are Hikvision cameras, embedded with what is called deep learning technology, AI that trains on people visiting the pitch.

Its not totally clear how this AI works, how it identifies people, whether it has access to a database in order to identify people or whether it creates a database based off of recognising and storing peoples biometric data.

The technology is not something that the council should be using without carrying out a Data Protection Impact Analysis, says Elizabeth Farries of the Irish Council for Civil Liberties.

Hikvision cameras were installed in November 2018 to protect the councils investment in a new full-size all weather pitch at Bluebell Community Centre from anti-social behaviour, says a spokesperson for Dublin City Council.

Four cameras were installed at the new full-size, all-weather pitch at a cost of 9,416 plus VAT, according to council records released under the Freedom of Information Act.

According to the council, The information will be recorded on a local monitoring station in Bluebell Community Centre and out of hours by a Dublin City Council contracted security company, which will be encrypted and secure.

According to the website of CTS Tech, the firm that both supplied and installed the Hikvision CCTV system, a Hikvision deep in-mind NVR was included in the installation.

The Hikvision Deep in Mind NVR, according to the companys website, mimics human learning and memory processes by incorporating algorithms that improve video analytics performance, including the ability to identify human activity to a high degree of accuracy. This includes the capabilities of facial recognition.

The advantage of this technology, according to Hikvisions website, is that it will save costs by preventing false alarms triggered by things like animals, which regularly prompt unnecessary call-outs of security personnel.

Was this feature necessary? There wasnt an awareness of issues around deep learning technology so concerns werent raised at the time, says a spokesperson for Dublin City Council.

Eoin ODell, academic lawyer in Trinity College with an interest in General Data Protection Regulation, says theres always a tendency to over-engineer and buy the best technology that you can afford.

So they bought the best cameras they could afford. It turns out that it came with this additional feature, he says.

There may be a good reason for the cameras for purposes of security, says ODell. But whether the use of this specific technology is proportionate should have been analysed through a Data-Protection Impact Analysis, he says.

Dublin City Council didnt carry out a data-protection impact analysis for the installation of the cameras, according to documents released by the council under FOI.

When you are undertaking something thats going to have a significant impact on data protection or privacy, before you do it, you should undertake an assessment exactly how much of an impact its going to have and whether the impact is justified or proportionate, says ODell.

According to the Data Protection Commissions website, when an organisation collects, stores or uses personal data, the individuals whose data is processed are exposed to risks. These include this personal data being stolen, or being used for differing purposes.

A Data Protection Impact Assessment (DPIA) describes a process designed to identify risks arising out of the processing of personal data and to minimise these risks as far and as early as possible, says the commissions website.

Under GDPR, a DPIA is mandatory where data processing is likely to result in a high risk to the rights and freedoms of natural persons, continues its webpage on DPIAs. This, they say, is particularly relevant when a new data processing technology is being introduced.

In other words, with GDPR having been rolled out in May 2018, a DPIA should have been carried out before the cameras were installed.

The Data Protection Commissioner has said that people making good faith attempts to comply in circumstances where they dont quite achieve full compliance, there would be a little bit of give and take there, says ODell, whereas somebody that is deliberately flouting the rules, they would be less accommodating.

Its not just for such deep learning CCTV cameras that a DPIA would be needed, says ODell. Its generally needed for traditional CCTV cameras too to analyse whether or not their use is proportionate for reasons of security.

According to a spokesperson for Dublin City Council, a data-protection impact analysis is currently being undertaken retrospectively.

The cameras are currently turned and because of the unease around HKVision [sic] camera Dublin City Council will make arrangements to substitute the cameras with more traditional CCTV cameras, says a spokesperson for Dublin City Council.

Unease around Hikvision cameras is a result of their use for surveillance in China. Hikvision is a Chinese company, partly owned by the Chinese state, and one of the worlds leading manufacturers of surveillance technology, including that of facial recognition.

The council have yet to respond to queries as to whether similar cameras were installed in other places in the city without data-protection impact assessments being properly carried out.

Theres a danger, says ODell, that such technology creeps in without a proper conversation around whether its use is proportionate or not.

Its a classic example of mission creep, you put something in for a good reason and then you ramp up the use. So CCTV has a good underlying reason and then you expand and you expand and youve increased the level of surveillance to an almost impossible extent, he says.

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AI Fights the Pandemic (And How You Can Get Involved) – TDWI

AI Fights the Pandemic (And How You Can Get Involved)

A new AI challenge is poised to help fast-track research to mitigate the impact of COVID-19.

The spread of the novel coronavirus is now officially a pandemic, causing widespread disruption to normal life around the world. While hospitals ramp up capacity and governments encourage or mandate quarantines, the data and technology space is mobilizing to help.

New AI Challenge Announced

One opportunity is the COVID-19 Open Research Dataset Challenge (CORD-19), presented on Kaggle by a coalition that includes the Allen Institute for Artificial Intelligence (AI2), the Chan Zuckerberg Initiative, Georgetown Universitys Center for Security and Emerging Technology, Microsoft Research, the National Library of Medicine, and the White House.

The challenge calls on AI experts to create text and data mining tools that can help the medical community develop answers to high priority scientific questions about the coronavirus. The provided data includes over 29,000 scholarly articles about COVID-19 and related viruses. Exploring the literature with AI techniques could greatly accelerate researchers ability to understand the virus and find viable therapies.

Pulling this data together and making it ready for natural language processing (NLP) and machine learning has been the work of an extraordinary collaboration between public and private entities. According to coverage on ZDNet, Microsoft used its web-scale literature curation tools to pull together global scientific efforts and results. The NLM provided access to literature content, while the Allen Institute transformed the content into machine-readable [form]. The data set will continue to be updated as new research is published.

The projects approach grew out of the Allen Institutes existing work using NLP and machine learning to analyze large amounts of scientific literature. You can hear some key figures provide more background and context on a recent GeekWire Health Tech Podcast.

What Is Already Being Done?

Of course, the CORD-19 project isnt the only way to use data and AI to fight the coronavirus. DeepMind has already released preliminary findings about related protein structures predicted by deep learning. Understanding the protein structure of a virus can give scientists a starting point for developing vaccines or drug therapies.

VentureBeat recently reported on several AI and tech-driven initiatives , including robots wielding disinfectant mobilized in China, cameras with thermal sensors for fever detection, and deep learning models that might diagnose patients faster or predict outcomes.

Meanwhile, general COVID-19 data such as numbers of cases and demographic and regional statistics has become ubiquitous online, giving rise to hundreds of dashboards and data visualizations of varying quality. The impulse to understand the data has been so strong that Tableau released a set of guidelines for data visualization makers to help prevent those without a background in epidemiology from accidentally misleading the public.

An Opportunity to Contribute

Are you an AI specialist ready to jump in and contribute? Read the initial key questions, find out about the cash prizes, and access the data on Kaggle.

About the Author

Lindsay Stares is a production editor at TDWI. You can contact her here.

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AI Fights the Pandemic (And How You Can Get Involved) - TDWI

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54% of the People. 12% of the Plays. Atlanta, Do We Have a Problem? – The New York Times

You can see what the Alliances money buys. At its 650-seat Coca-Cola Stage, I caught a performance of Maybe Happy Ending, a charming, Broadway-ready new musical about robots in love by Will Aronson and Hue Park. That it featured a largely Asian-American cast suggested a successful effort to program and hire with inclusion in mind. At the 200-seat Hertz stage, Seize the King Will Powers hip-hop retelling of Richard III was preparing to open.

And though, yes, it was February, Susan V. Booth, the theaters artistic director, said her goal is to make the entire season of 11 shows welcoming to diverse audiences. Its not just white play, white play, black-history-month black play, white play, which is how regional theaters used to show they were woke, she said. Because if your programing arc is episodic, the same will hold true in your audience. Indeed, at many Atlanta theaters, black theatergoers and white ones barely intersect.

Whats absolutely crucial is whos doing the inviting, Booth added, pointing as an example to Pearl Cleage, the Atlanta-based black writer whose Blues for an Alabama Sky and What I Learned in Paris, among many others, have had their premieres at the Alliance. We set ticket expectations for Pearls new plays as if they were musicals because when Pearl is inviting, she packs out the house.

Even so, Booth, who is white, admitted that the Alliances audiences overall are not as diverse as shed like: something like 30 percent to 35 percent nonwhite. (On Broadway, the figure is closer to a quarter.) I did not observe even that much melanin the night I saw Maybe Happy Ending, despite its Korean setting but in any case, Booth said, statistical diversity is not the goal.

True. But its a good step, right?

The goal is that we sit cheek by jowl with as much of a breadth of human experience as we can, not erasing human difference but unearthing what unites us.

I certainly had that experience the next evening when I saw Jocelyn Biohs School Girls; or, the African Mean Girls Play at Kenny Leons True Colors Theater. Even though I was one of the few white people in the audience, the breadth of human experience by age and gender and style if not race was strongly represented. The audiences engagement with the play itself, a recent hit Off Broadway, was likewise palpable, with hoots and gasps and back talk that enhanced the comedy as well as the dramatic turns.

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54% of the People. 12% of the Plays. Atlanta, Do We Have a Problem? - The New York Times

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Gardener Jen Kennedy Plants With Palette and Purpose in Mind – Seven Days

Gardening has been described as an act of faith. In Vermont with its short growing season, uncertain weather and rocky soil the activity requires a special kind of fortitude, as well. And it helps to have the guidance of someone who's as hardy as the native plants. Someone like Jen Kennedy.

The Underhill resident, 37, has worked as a professional gardener in Chittenden County for almost 20 years. From designing new perennial beds to helping maintain established gardens, Kennedy does it all.

"There are definitely unique challenges when it comes to locations, what people like and what's going to look good in their garden," she said, "but I really enjoy that."

When she's not working on other people's gardens in season, Kennedy is busy tending her own. And although her white clapboard home and perennial-filled grounds may seem like a quintessential Vermont idyll, it wasn't always this way.

Twelve years ago, when Kennedy inherited her grandparents' homestead built in 1852 as a local school the property was in a state of disrepair. Her grandmother's flower beds were overgrown and neglected, while the backyard was littered with old cars, rusted fences, dismantled sheds and even an old forge. (Her grandfather, Roy Kennedy, was an artist and sculptor who had a thing for scrap metal.)

Kennedy has spent the last decade transforming her grandparents' eclectic artists' den into her own private paradise.

"It took a long time, but I had a vision and I just kept with it," she said.

Kennedy's work, in both her clients' gardens and her own, is equal parts restoration and creation. Consider the terraced perennial beds in front of her house, originally planted by her grandmother. Kennedy has diligently saved many of the plants, including the Dictamnusalbus (gas plant), Pulmonaria (lungwort) and Mertensia virginica (Virginia bluebells). But she's also added new varieties such as Nepeta sibirica (catmint) and Astilboides tabularis (shield leaf) to give the beds her personal touch.

Kennedy grew up just down the road and credits her grandmother with teaching her about plants. "I learned a lot from my grandmother, but mostly I learned to love gardening," she said.

Her grandparents didn't own a TV or a phone, so when Kennedy visited, they spent their time outside. "There was an emphasis on edible landscaping and foraging for wild foods," she remembered. "It was just part of life back then, but we've gotten away from it."

Tucked behind the house is a private pastoral landscape fringed with old-growth apple trees. The vegetable garden, a large circle in the center of the backyard, is looped with a thin electric fence to keep out the deer (who love Kennedy's hydrangeas and daylilies but leave the hyssop and thyme alone). A wooden pergola frames the entrance, and pea-stone paths separate the raised beds, which are hip-high to make planting and weeding easier.

This is not a garden of straight lines but rather a cheerful jumble of flowers, herbs and vegetables sweet peas, tomatoes, peppers, Brussels sprouts, rhubarb and garlic growing together in verdant harmony.

"It's not intentional," said Kennedy with a laugh. "I plant mostly by height and shading. I like to grow small amounts of several different things. There is a science to plant companions, but I haven't used it."

Kennedy is a proponent of creating outside "rooms" to extend indoor living space, and a walk around her property reveals delightful hidden nooks. A wooden arbor laden with leafy vines shades a large table and chairs on her backyard patio. Alongside a babbling brook, two Adirondack chairs and a small fire pit offer a perfect setting for making s'mores. Just beyond the vegetable garden, a hammock sways between two old maple trees.

Although a visitor might imagine whiling away summer afternoons reading a book and sipping iced tea in such outdoor spaces, Kennedy rarely slows down; she's a woman with a vision and a strong work ethic.

Kennedy first worked as a gardener during summers while she studied art at what was then called Johnson College, and it's been her main job ever since. It's clear that the principles of art, such as complementary colors, textures and contrast, inform her botanical philosophy. In particular, she thinks about the interplay of light and shade.

For example, Kennedy often plants the bright chartreuse foliage of Hakone (Japanese forest grass) to contrast with the deep purple foliage of Cimicifuga (snakeroot).

"It's art with plants. It's my sculpture," she explained.

Making art from growing things can take a long time, though. "I once heard that gardening is the slowest form of performance art, and I totally agree with that!" Kennedy said.

Every year, she becomes enamored of a different plant. Last summer, it was Eryngium yuccifolium (rattlesnake master), a tall, white wildflower with blossoms the size of golf balls. The year before, it was hostas. "They can do dry shade and look amazing. There aren't many plants that can do that," she said.

Using her deep knowledge of native plants, as well as her yearly plant passions, Kennedy approaches her clients' gardens like a sculptor approaches a slab of marble: with a keen eye for what needs to be moved, removed or added. Many of her clients work side by side with her, and she often gives them "homework" to do between her visits.

Kennedy said she especially enjoys working in "gardeners' gardens," because "they know it's hard work, so they really appreciate what I do."

Charlotte Wheater and Mary Jane Dickerson, both from Jericho, are two such gardeners who have weeded, shoveled and planted with Kennedy for almost two decades.

"I only have one other person who works as hard as I do, and that's Jen," said Wheater. "I think of her as Mother Earth. She has a love for the land and for what it provides. She's a marvel."

Dickerson credits Kennedy with helping her see her garden in a whole new way. "She sees the contours of the land and knows how to make the most of them," Dickerson said. "Gardening with Jen is nurturing for the body and the soul."

Ask this veteran artist gardener for advice, and she'll tell you to resist the temptation to buy all your plants at once. Instead, Kennedy suggests visiting multiple nurseries throughout the growing season to collect a variety of plants that will bloom at different times.

"A lot of the creativity happens at the nursery, because you get to see what's available and what looks good together," she said. She also advises growing something edible. "That's very rewarding, because anything you grow yourself just tastes better!"

Thanks to Kennedy's counsel, Dickerson now has "a riot of nasturtiums and all kinds of mint" for summer cooking, she said.

Full-time gardening doesn't leave a lot of time for other projects, such as home restoration. So, in the winter, Kennedy turns her attention to the interior of her unique home. Here, too, she continues to patiently clear out and clean up. Where there once was a warren of small, dark rooms piled high with her grandfather's art, there's now a bright and open space. Her grandfather's sculptures hang above the hearth of the massive stone fireplace, and his large paintings are stacked neatly on wooden shelves in the corner.

Next, Kennedy plans to paint the walls and whitewash the tongue-and-groove pine ceiling. For now, she's happy to sit on the floor and sort through paint samples in palettes that echo her lush gardens outside. Making a custom home, like creating a beautiful garden, takes time.

"This is the fun part," Kennedy said. "I'm not there yet not on the inside but I can't wait!"

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A History Book That Isn’t: Finding A Way To Teach Racism To A New Generation – OPB News

Authors Jason Reynolds, left, and Ibram X. Kendi spoke to students at a high school in Washington D.C. about their new book, Stamped: Racism, Antiracism and You.

NPR, Elissa Nadworny

After his award-winning book came out in 2016, Ibram X. Kendi heard from people everywhere, telling him it opened their eyes to a new way of looking athistory.

They were coming up to me and saying, It feels too late now. I wish I had read this in middle school, hesays.

Stamped from the Beginning: The Definitive History of Racist Ideas in America, follows five historical figures like the abolitionist William Lloyd Garrison and the activist Angela Davis and offers readers unwashed versions of who they were, and the role that racist ideas played in theirlives.

Kendi, an author and historian at American University, says history books in schools today too often dont offer students a deep enough perspective or account of who people were and what theydid.

Which led him to take up the challenge of those people who wished theyd learned these lessons in middle school: Give young people access to this history by collaborating with a writer who could take his facts (the history) and write it for a youngeraudience.

In his mind there was only one person to do it: the childrens book author, Jason Reynolds. When he let Reynolds in on this plan, he got a surprising answer:No.

History is not my thing. Im a fiction writer! Reynolds explains. But Kendi persisted, and eventually Reynolds caved. I realized [Kendi] believed in me more than I believed in myself, hesays.

Their new book is called Stamped: Racism, Antiracism, and You, and right from its first few pages the authors promise that, this is not a history book. Instead, they say, its a book that mixes past with present in a way that young adults can relateto.

History books are written with the idea of a student in mind, but not the idea of an actual young person themselves, says Reynolds. So this book sets out to do just that, and Reynolds says its filled with the things that I needed someone to say to me when I was 15 yearsold.

In a high school in Washington D.C., NPR met with the two authors and a group of high school students who had read the book. Our conversation has been edited for length andclarity.

Jason, why were you hesitant to say yes to Kendisrequest?

Reynolds: I wasnt sort of a top notch scholar, that I wasnt a part of sort of my story, my journey. And so if a scholar comes to you and asks you to sort of make an adaptation or translation of work that theyve poured themselves into, and you dont necessarily see yourself in the same playing field, it can be a littleintimidating.

Once you got to yes, then what? How do you write a remix of something that alreadyexists?

Reynolds: History books are written with the idea of a student in mind, but not the idea of an actual young person, just the person themselves. School is for a few hours a day. But, like, there arent history books written for that kid when school is over, when the bell has rung. And so thats sort of what Im thinking about this particular book: Can I make this something cool? Because theres currency in cool. There always has been, there always will be. It matters to them. It mattered to me. It still matters to me, right? If it aint cool Im probably not gonna rock with it. This is how I am. Im still that person. So I wanted to try to figure out how to make this really complex thing that has all this information that he gave the world, how do I take it and make it feel like a fresh pair ofJordans.

Before you read this book, what did you know about the history of racist ideas orracism?

Emani James, 10th grade: I go back to like Martin Luther King and Rosa Parks and Malcolm X, we dont ever learn about what happened before then. Who knew about the first person who was ever racist? Like, I didnt learn about that. And I wouldnt even think it was in the1400s!

With history, people like to cut off certain parts that they dont want to tell us. Like theyre not gonna tell us the deep, deep stuff. You know, like they just gonna tell us the deepstuff.

Do you feel like its because youreyoung?

James: I mean it partly is because were young. But us being young, we still have a greatmind.

So, Ibram, did you encounter folks who felt like students were too young to learn thishistory?

Kendi: There were times in which people would ask, are young people ready for this history? And it was a shocking question because its so foreign to me that anyone could not recognize how we have so many young, brilliant minds who even, you know, in seventh grade, let alone 10th grade, can understand this history. Not only understand it, but apply it to their own lives. They start to get more clarity about their own lives, they are able to understand their country. And so for me, this getting deep, deep, deep, that really actually protects our young people. So we think were protecting them by not getting deep. Were actually protecting them by getting deep, by allowing them to really understand this nationshistory.

In the book you have three categories that you put people and ideas in. What are those three categories and why use thatapproach?

Kendi: One of the things were trying to do with this book is provide people with the vocabulary of how to speak about and understand racism. Know what intimately racism is and how to identify it with language. What were trying to do is give people the ability to name what they see, what they experience, what they should beresisting.

So there are the segregationists, which Jason calls thehaters.

Reynolds: The haters. Segregationists are the haters. Everybody knows what a hater is. All right. Haters. Especially when I was in school. And I know its no different for yall. Haters are the people who hate you just cause you aint likethem.

Kendi: And then theres the assimilationist. Who are thelikers.

Reynolds: Likers. Your fake friends. I mean, everybody, got em, everybody knows them too. Everybody knows the phonies. And theyre basically the ones who like you, but they like you because you are like them. You know, that is contingent upon you being likethem.

Kendi: And then theres the anti-racists, who are thelovers.

Reynolds: And the lovers. Those are your day ones, as we say. Our ride or dies. The ones who love us for being like us. They love us for who we are, not for who they are, and not for who we are to them, but for who we are tous.

In the book, you apply these definitions to the ideas people have and often, the same people write about or speak about a combination of the three, meaning people can evolve andchange.

Kendi: If people say an assimilationist idea or anti-racist idea or segregationist idea, then you apply it, even if its somebody whos your hero. I also think we should give people the ability to change. So W.E.B. Du Bois was born in 1868 and he died literally the night before the March on Washington in 1963. Thats nine decades. What he was saying, particularly in the 1890s, was more along the lines of assimilationist ideas. But by the time he was in the 1930s and 1940s, he had transformed and was largely articulating anti-racist ideas. This is what we hope for people. We want people to change and we have to give people that ability to change, but also recognize who they were at an earliertime.

Reynolds: I did have friends be like, yo, so I dont know, man. What you said about Dr. King kind of hurt! And Im like, first of all, it wasnt me, blame it on Dr. Kendi. Those are my words, but thats all hisinformation.

I do think its important that we are honest about even our heroes. It doesnt make them any less heroes, nor does it make their contributions any less powerful. But it does help us sort of get into the nuances of it all. And it does also show how fluid some of that stuff was, and has been, and is, for a lot of us. But that we should always be aiming towardanti-racism.

James: Who is your target market for this? Is it really foreverybody?

Reynolds: I never write void of the scope in which Ive come. I was a young black person. It is natural for me to speak to young black people. The book is for everybody, but Id be lying if I said that I wasnt sort of imagining [Emanis] face. Theres certain things that I do want to say to black kids, right? Like that part in Chapter 6 when I write, Africans arent savages. Right. Thats for us. Were not savages. That was specifically foryou.

Amir Perkins, 11th grade: I was surprised there were black people who had racistideas.

Kendi: Right, youre talking about Leo Africanus. Just like you have black people today who tell white people what they want to hear in order to improve their standing among white people, black people were doing that back in the 1500s! For me, if anyone is saying that theres something wrong with black people, theyre saying a racist idea and it doesnt matter their skincolor.

Amir: As educated black men, when youre in a certain situation, do you sometimes feel as though white people are intimidated by yourstatus?

Reynolds: The thing about anti-racism that to me that sits at the core of who I am is that I should never have to make myself small for everyone else to feel comfortable about my existence. Right. Why? I earned it like everybody else earns it. And Im going to be proudly who I am in every space that I am, because I belong everywhere that I choose to go. Self-actualization is at the core of an anti-racist world.

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Graph theory suggests COVID-19 might be a small world after all – ZDNet

Is the spread of the respiratory infection known as COVID-19 happening in an "exponential" fashion?

That's been the general contention of the media, which, as a public service, have explained at some length the basics of fast-growing quantities, such as disease, to hammer home how something like a virus can double in cases in a matter of days.

However, the data on COVID-19 has a lot of puts and takes, and one of the factors not entirely considered is the graph of the infection. Graph theory has a lot to say about how phenomena can grow, such as the spread of infectious diseases. There are different graphs, or networks, of relations, and they can affect things such as the rate of propagation.

One particular recent work calls into question the notion of the exponential growth of the disease.

Scholars Anna Ziff and Robert Ziff, respectively of Duke University and the University of Michigan, earlier this month posted on the medrXiv pre-print server their curve-fitting exercise for COVID-19 confirmed cases and deaths, both in China and in the rest of the world, titled "Fractal kinetics of COVID-19 pandemic."

As the authors write, "in standard epidemiological analysis, one assumes that the number of cases in diseases like this one grows exponentially, based upon the idea of a fixed reproduction rate."

But that standard epidemiological view is not born out by the data. They found that while the numbers "display large growth, they do not, in fact, follow exponential behavior." Rather, the authors observed a period of initial exponential growth, followed by what's called a "power law," which is not the same thing.

Also: MIT's deep learning found an antibiotic for a germ nothing else could kill

"The behavior is clearly not linear as it would be for exponential growth," they write. "In contrast, we find that the data are very well fit by assuming a power-law behavior with an exponent somewhat greater than two."

The authors explain that growth by appeal to the notion of a "small world" network, where most people have only a small number of connections to other people, most of whom are neighbors within their community.

The small-world phenomenon was explored and revised substantially in the past two decades by graph theoretician Albert-Lszl Barabsi of Northeastern University, who runs The Center for Complex Network Research.

Anna L. Ziff and Robert M. Ziff argue the curve for deaths in China from Covid-19 isn't following the common "exponential" growth that mainstream epidemiology suggests; rather, it follows the "power law" of a "small world" network.

Barabsi popularized the application of power laws to graphs with his 2014 book Linked. In that volume, Barabsi pointed out that networks of infectious disease seem to follow a power law, whereby there is a steadily decreasing curve of connectedness between entities. For the vast majority of entities in a graph, such as, for example, the people who could potentially be infected, their connectedness dwindles at a rate that is less than exponential, the now-famous "long tail" that is familiar in internet content.

That doesn't mean disease can't spread fast, Barabsi wrote. But he hypothesized that the small-world network must have "hubs," just like the major internet sites, to amplify the spread of signals.

The point is that a lot of real-world networks, such as infectious disease, are not random networks where there is an even chance of any one person coming into contact with another. They have structure, and the dominant structure of those networks is that the vast majority of people have a sparse number of connections to local neighbors. A random network would imply exponential growth, whereas the so-called scale-free networks that Barabsi discovered do not.

Also: Google DeepMind's effort on COVID-19 coronavirus rests on the shoulders of giants

And something like that is identified in the Ziffs' paper. There is a tapering off that's been seen in the China data, they write, after an initial exponential curve. That suggests to them a "kind of small-world interaction network where individuals have many local neighbors and occasional long-range connections (such as caused by people traveling on trains, boats, and planes)."

The practical implication, if their model is correct, is that the speed of the disease is taking longer and longer to double in the number of deaths. Exponential growth is not maintained because "the number of susceptible individuals around an infected individual decays with time," as a result of the prospect that "Individuals already infected might face increased immunity and there are other individuals who might have had a mild infection that imparts immunity but without developing symptoms warranting testing."

"These various effects would inhibit the exponential growth of the virus."

The authors make a prediction, which is that starting from the 27th day of the outbreak, when there 1,669 deaths from COVID-19, according to data compiled by theWorld Health Organization, the number of deaths would double to approximately 3,340 on day 37, which was Feb. 22, double again to 6,680 on day 50, March 10, and double again to 13,350 on day 67, which would be March 27.

It turns out, the doubling has been slower than they predicted, with actual deaths on day 37 just 2,359, and the death toll for March 10th at only 4,012. The total now, as of March 16, stands at 6,606, according to the WHO.

The Ziffs offer some thoughts on variance from their model. "Deviations above this power-law behavior might indicate that the pandemic is expanding from the current level of control," they write, "while deviations below might indicate that the disease is starting to fade."

Of course, there is a lot of uncertainty in the data on COVID-19 cases, which the authors acknowledge.

"This analysis is early in the outbreak of COVID-19 and cannot predict the length of the outbreak nor the final fatality," they write.

But the main point should be that the course of the disease is showing something other than the exponential growth that is routinely being tossed around. "This is a large number of fatalities," the Ziffs observe, "but not nearly as large as if the growth were exponential."

Keep in mind, then, as you think about infectious disease, that a simple rate of spread of something has to contend with the graph structure of a network, and that can have effects that are not obvious and that bear examination.

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Answering the Question Why: Explainable AI – AiThority

The statistical branch of Artificial Intelligence has enamored organizations across industries, spurred an immense amount of capital dedicated to its technologies, and entranced numerous media outlets for the past couple of years. All of this attention, however, will ultimately prove unwarranted unless organizations, data scientists, and various vendors can answer one simple question: can they provide Explainable AI?

Although the ability to explain the results of Machine Learning modelsand produce consistent results from themhas never been easy, a number of emergent techniques have recently appeared to open the proverbial black box rendering these models so difficult to explain.

One of the most useful involves modeling real-world events with the adaptive schema of knowledge graphs and, via Machine Learning, gleaning whether theyre related and how frequently they take place together.

When the knowledge graph environment becomes endowed with an additional temporal dimension that organizations can traverse forwards and backwards with dynamic visualizations, they can understand what actually triggered these events, how one affected others, and the critical aspect of causation necessary for Explainable AI.

Investments in AI may well hinge upon such visual methods for demonstrating causation between events analyzed by Machine Learning.

Read more: How to Make AI Work in Extreme Conditions?

As Judea Pearls renowned The Book of Why affirms, one of the cardinal statistical concepts upon which Machine Learning is based is that correlation isnt tantamount to causation. Part of the pressing need for Explainable AI today is that in the zeal to operationalize these technologies, many users are mistaking correlation for causationwhich is perhaps understandable because aspects of correlation can prove useful for determining causation. In ascending order of importance, an abridged hierarchy of statistical concepts contributing to Explainable AI involves:

Causation is the foundation of Explainable AI. It enables organizations to understand that when given X, they can predict the likelihood of Y. In aircraft repairs, for example, causation between events might empower organizations to know that when a specific part in an engine fails, theres a greater probability for having to replace cooling system infrastructure.

Theres an undeniable temporal element of causation readily illustrated in knowledge graphs so when depicting real-world events, organizations can ascertain which took place first and how it might have affected others. This added temporal dimension is critical in establishing causation between events, such as patients having both HIV and bipolar disorder. In this domain, deep neural networks and other black-box Machine Learning approaches can pinpoint any number of interesting patterns, such as the fact that theres a high co-occurrence of these conditions in patients.

When modeling these events in graph settings alongside other relevant eventslike what erratic decisions individual bi-polar patients made relating to their sexual or substance abuse activitiesthey might differentiate various aspects of correlation. However, the ability to dynamically visualize the sequence of those events to see which took place before what and how that contributed to other events is indispensable to finding causation.

The flexibility of the knowledge graph schema enables organizations to specify the start and end time of events. When leveraging speech recognition technologies in contact centers for Sales opportunities, organizations can model when agents mentioned certain Sales products, how long they talked about them, and the same information for customers. Visual graph mechanisms can depict these events sequentially, so organizations can see which led to what. Without this temporal method, organizations can leverage Machine Learning to specify co-occurrence and correlation between products.

Nevertheless, the ability to traverse these events at various points in time allows them to see which products, services, or customer prototypes generate interest in other offerings. This causation is determinate for increasing the accuracy of machine learning predictions about how to boost sales with this information. As valuable as this capacity is, the more meritorious quality of such causation is that the explanation for these predictions is not only perfectly clear but also able to be visualized.

Causation is the basis for understanding the predictions of Machine Learning models. Knowledge graphs have visualizations enabling organizations to go back and forth in time to see which events are causative to others. This capability is vital to solving the issue of Explainable AI.

Read more: Is Artificial Intelligence the Next Stepping Stone for Web Designers?

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Answering the Question Why: Explainable AI - AiThority

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Adaptive Insights CPO on Why Machine Learning Is Disrupting Financial Services – Toolbox

Machine learning, in-memory computing, and democratization of data are important trends that are helping organizations operate with greater agility.

Data Analytics has helped organizations make informed business decisions. The increased usage of data analytics has resulted in the mainstreaming of enterprise-grade data management, data preparation, and data visualizations tools. In an interview with Toolbox, Bhaskar Himatsingka, Chief Product Officer at Adaptive Insights, talks how data-driven planning can help companies achieve strategic objectives, cloud performance management solutions and the importance of cloud-based planning systems. He also spotlights how machine learning (ML)has revolutionized cloud-based planning, and upcoming trends in data visualization.

In high school, I realized I wasnt smart enough to be a career mathematician, so I turned to Computer Science. After I came to the U.S. for post-graduate studies, I joined Oracle working on the database kernel team. Over the years, I moved from technical staff positions to CTO at Ariba, a SaaS procurement software company now owned by SAP, and later CTO at Change Healthcare. In 2016, I joined Adaptive Insights, where I lead the engineering, product management, and technical operations teams.

Too often, people learn about a certain technology and think, We need this. I believe thats the wrong approach. I like to use the analogy that when you go to the hardware store to buy a quarter-inch drill bit, what you really want is a quarter-inch hole. So, for a CTO or CIO, the focus should be on going to all the relevant stakeholders across the business and asking, What are we trying to accomplish? What problem are we trying to solve?

Ive seen firsthand that data-driven planning can help companies achieve strategic objectives and solve a lot of ongoing inefficiencies, but you have to start with the goal in mind.

Learn More: How AI Has Transformed the Role of a Chief Data Officer: LinkedIn CDO

It depends on what youre trying to achieve. It might be saving days or even weeks on a budget or monthly close, improving data integrity, increasing the number of people participating in planning and reporting, cutting in the time required to produce a report, and expanding the number of people throughout your organization actively modeling what-if scenarios and participating in decision-making. You can also tie many of these KPIs to key business metrics, like higher gross margin and reduced operating expenses.

The classic data readiness best practices are always advisable whenever implementing a new solution. Youll want to establish key metrics to ensure your data is relevant and business-ready; implement a data quality strategy; and then determine your integration strategy.

Data is often locked in separate systems and data lakes. Those silos live in your ERP, HCM, and elsewhere in your enterprise stack. So, any cloud-based CPM system absolutely must be platform-agnostic and offer easy and automated integration of data from all your various sources.

Learn More: CFO as Visionary: Using Digital Analytics to Power Strategy

When you process data entirely in memory, youre able to create and calculate far more complex models so people in a business can understand the implications of their actions. In-memory computing helps a cloud platform scale to meet the demands of a business as it grows. But memory isnt a blunt instrument; you need to use it efficiently to get the maximum value from it. For instance, when updating a large, complex model, its far better to recalculate only those cells that have changed. Doing it the old wayrecalculating the entire modelis unacceptably slow and a waste of resources.

Learn More: Top 6 Analytics Trends To Drive Data-Driven Decision Making

There have been so many. One great example is reporting. Only a few years ago, reporting was far more difficult and often involved a request to finance. Thats changed, and its become an empowering development in modern businesses. Another example is augmented analytics to automatically identify trends and opportunities, empowering both finance and business users with the capability to harness data in a way previously reserved for data scientists.

Cloud-based planning systems have transformed and democratized reporting. Now virtually anyone in the business can generateon demanda report that visualizes operational and financial performance for their function.

Learn More: Data Visualization Will Change How You Use Data

Were working to make machine learning (ML) a foundational aspect of modern, cloud-based planning. A powerful practical use of ML is its ability to serve as a reliable prediction engine for business planning.

Were seeing Machine Learning improve the ability of managers in finance or operations to accurately anticipate outcomes and even identify anomalies in your data that could otherwise lead you to make a bad decision. Scenarios like changing the price of a product or service, remapping sales territories, or adding headcountthese are important decisions in any business, and making them with confidence helps those businesses operate with agility.

Learn More: How Can Machine Learning Improve Risk Management?

Among the most important trends involve technology that helps organizations operate with greater agility. Weve already mentioned a couplemachine learning and in-memory computing. Another is the democratization of data that allows business users across the enterprise to collaborate in ways they never could before. This is all part of making planning intelligent and anticipatorymoving from simply understanding whats happening right now to predicting with a high degree of confidence whats likely to happen in the future.

About Bhaskar Himatsingka:

Bhaskar leads Adaptive Insights engineering, product management, and technical operations teams. Bhaskar brings more than 20 years of experience building teams, technology, and products. He joined Adaptive Insights from Change Healthcare where, as CTO, he developed a new technology roadmap, led the engineering team to re-architect the way the company stored and analyzed data, and oversaw the launch of successful new products. Prior to that, he spent more than 12 years at Ariba where, as CTO, Bhaskar led the effort to re-architect the companys on-premises products to launch its multi-tenant enterprise software as a service (SaaS) platform.

Bhaskar earned a masters degree in computer science from the University of Minnesota at Minneapolis, and he holds a Bachelor of Technology degree in computer science and engineering from the Indian Institute of Technology in Kanpur, India.

About Adaptive Insights:

Adaptive Insights, a Workday company, is powering a new generation of business planning. Driving business agility in a fast-moving world, Adaptive Insights Business Planning Cloud leads the way for people in companies to collaborate, gain insights, and make smarter decisions faster. Powerful modeling for any size organization, yet so easy for everybody who plans. Adaptive Insights is headquartered in Palo Alto, CA.

About Tech Talk:

Tech Talk is a Toolbox Interview Series with notable CTOs and senior executives from around the world. Join us to share your insights and research on where technology and data are heading in the future. This interview series focuses on integrated solutions, research and best practices in the day-to-day work of the tech world.

Do you think machine learning has played a major role in transforming business planning? Comment below or let us know on LinkedIn, Twitter, or Facebook. Wed love to hear from you!

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Adaptive Insights CPO on Why Machine Learning Is Disrupting Financial Services - Toolbox

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