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Company led by Google veterans uses AI to ‘nudge’ workers toward happiness - The Globe and Mail
The startup, Humu, is based in Google’s hometown and it builds on some of the people-analytics programs pioneered by the internet giant, which has studied things including the traits that define great managers and how to foster better teamwork.

Humu wants to bring similar data-driven insights to other companies. It digs through employee surveys using artificial intelligence to identify one or two behavioural changes that are likely to make the biggest impact on elevating a work force’s happiness. Then it uses e-mails and text messages to “nudge” individual employees into small actions that advance the larger goal.

At a company where workers feel that the way decisions are made is opaque, Humu might nudge a manager before a meeting to ask the members of her team for input and to be prepared to change her mind. Humu might ask a different employee to come up with questions involving her team that she would like to have answered.

At the heart of Humu’s efforts is the company’s “nudge engine” (yes, it’s trademarked). It is based on economist Richard Thaler’s Nobel Prize-winning research into how people often make decisions because of what is easier rather than what is in their best interest, and how a well-timed nudge can prompt them to make better choices.

Google has used this approach to coax employees into the corporate equivalent of eating their vegetables, prodding them to save more for retirement, waste less food at the cafeteria and opt for healthier snacks.

Using machine learning, Humu will tailor the timing, content and techniques of the messages it delivers based on how employees respond.

“Often we want to be better people,” said Laszlo Bock, Humu’s chief executive and Google’s former leader of what the company calls people operations, or human resources
Asha_Isaacs  artificial_intelligence  Google  happiness  machine_learning  Richard_Thaler  nudge  behavioural_economics  Laszlo_Bock 
january 2019 by jerryking
REWRITING HISTORY | More Intelligent Life
From INTELLIGENT LIFE magazine, November/December 2014
humanities  Stanford  Asha_Isaacs 
august 2015 by jerryking
How to Get a Job at Google, Part 2 - NYTimes.com
APRIL 19, 2014 | NYT| Thomas L. Friedman.

(1) “The first and most important thing is to be explicit and willful in making the decisions about what you want to get out of this investment in your education.”
(2) make sure that you’re getting out of it not only a broadening of your knowledge but skills that will be valued in today’s workplace. Your college degree is not a proxy anymore for having the skills or traits to do any job.

What are those traits? One is grit, he said. Shuffling through résumés of some of Google’s 100 hires that week, Bock explained: “I was on campus speaking to a student who was a computer science and math double major, who was thinking of shifting to an economics major because the computer science courses were too difficult. I told that student they are much better off being a B student in computer science than an A+ student in English because it signals a rigor in your thinking and a more challenging course load. That student will be one of our interns this summer.”

“What you want to do is say: ‘Here’s the attribute I’m going to demonstrate; here’s the story demonstrating it; here’s how that story demonstrated that attribute.’ ” And here is how it can create value. (Apply this also to cover letters).
howto  job_search  Google  Tom_Friedman  Lazlo_Bock  attributes  cognitive_skills  creativity  liberal_arts  résumés  new_graduates  coverletters  hiring  Managing_Your_Career  talent  grit  interviews  interview_preparation  value_creation  Jason_Isaacs  Asha_Isaacs  Jazmin_Isaacs 
april 2014 by jerryking
For ‘House of Cards,’ Using Big Data to Guarantee Its Popularity - NYTimes.com
February 24, 2013 | NYT | By DAVID CARR

Rick Smolan wrote “The Human Face of Big Data.” “
Netflix, which has 27 million subscribers in the nation and 33 million worldwide, ran the numbers. It already knew that a healthy share had streamed the work of Mr. Fincher, the director of “The Social Network,” from beginning to end. And films featuring Mr. Spacey had always done well, as had the British version of “House of Cards.” With those three circles of interest, Netflix was able to find a Venn diagram intersection that suggested that buying the series would be a very good bet on original programming.

Big bets are now being informed by Big Data, and no one knows more about audiences than Netflix....But there are contrarian opinions, "“Data can only tell you what people have liked before, not what they don’t know they are going to like in the future,” he said. “A good high-end programmer’s job is to find the white spaces in our collective psyche that aren’t filled by an existing television show,” adding, those choices were made “in a black box that data can never penetrate.” "...The rise of the quants has some worried about the impact on quality and diversity of programming. Writing in Salon, Andrew Leonard wonders “how a reliance on Big Data might funnel craftsmanship in particular directions. What happens when directors approach the editing room armed with the knowledge that a certain subset of subscribers are opposed to jump cuts or get off on gruesome torture scenes” or are just interested in sexual romps?

Netflix insists that actual creative decisions will remain in the hands of the creators. “We don’t get super-involved on the creative side,” Mr. Evers said. “We hire the right people and give the freedom and budget to do good work.” That means that when Seth Rogen and Kristen Wiig are announced as special guests on coming episodes of “Arrested Development,” it is not because a statistical analysis told Netflix to do so.

But there are potential conflicts. Given that Netflix is in the business of recommending shows or movies, might its algorithms tilt in favor of the work it commissions as it goes deeper into original programming? It brings to mind how Google got crossed up when it began developing more products, and those began showing up in searches.

And there are concerns that the same thing that makes Netflix so valuable — it knows everything about us — could create problems if it is not careful with our data and our privacy.
David_Carr  Netflix  data_driven  massive_data_sets  streaming  data  television  digital_humanities  Asha_Isaacs  quantitative  big_bets  white_spaces  original_programming  human_psyche  craftsmanship  Venn_diagrams  content_creators  algorithms  biases  the_right_people 
february 2013 by jerryking

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