Thursday, January 16, 2020

Fewer Jobless Americans Tap Unemployment Benefits

The U.S. work force’s reliance on unemployment insurance is dwindling amid tighter rules and a strong job market

By Sarah Chaney of The Wall Street Journal.

When I cover unemployment, I don't spend much time on how the unemployment insurance system works. This article has some good information on it. Excerpts:
"Last year, 28% of jobless people received benefits, down from 37% in 2000—a period of similarly low unemployment.

Among the main reasons, experts say: After the last recession ended, state legislatures passed policies reducing unemployment benefits and tightening eligibility requirements.

Ten states cut the duration of benefits, five adopted stricter work-search requirements and several trimmed the average weekly-benefit amount"

"A strong labor market also means many jobless people today quit their jobs voluntarily and so are ineligible for benefits in most cases.

The quitting rate was 2.3% for much of last year, well above 1.3% in the month after the recession ended in mid-2009"

"Some economists like Michael Farren, a research fellow at the right-leaning Mercatus Center at George Mason University, say the state unemployment-insurance cutbacks and policy changes have motivated jobless Americans to undertake faster searches for new work.

Absent the state changes, he said, “you end up with policies created in the crisis that may help smooth the passage through the crisis, but…actually help stall the recovery.”

Other economists say state unemployment systems aren’t providing unemployed people the support they need to find the best jobs possible while the labor market is humming.

“There are people who are having to make transitions in the economy at all times,” said Martha Gimbel, an economist at Schmidt Futures, a philanthropic initiative of longtime Google CEO Eric Schmidt. “If we aren’t helping them make the transition now in a strong economy, then they may be still left on the sidelines when a serious recession hits.”"

"States administer unemployment insurance programs and make determinations on eligibility for benefits, as well as the amount and duration of benefits, based on federal guidelines.

In the majority of states the benefits are funded by taxes on employers. A few states require employees to contribute.

Americans generally are eligible for jobless benefits if they are laid off while working in a position covered by unemployment insurance. Once they begin collecting benefits they must meet certain requirements, which vary by state, such as applying for a certain number of jobs a week.

Benefits typically expire in 26 weeks or less, depending on state laws.

In the wake of the 2008 crisis, several states turned to the federal government as a backstop for funding when they depleted their unemployment-trust funds.

As the economy improved, states that owed money to the federal government had to rebuild their trust funds. To do so, they could raise employer taxes or cut benefits—or some combination of the two. Many states opted to reduce benefits."

Tuesday, January 14, 2020

What if companies can't afford real models for their ads? Use AI generated fake pictures

See Dating apps need women. Advertisers need diversity. AI companies offer a solution: Fake people by Drew Harwell of Washington Post. Excerpts:
"Artificial intelligence start-ups are selling images of computer-generated faces that look like the real thing, offering companies a chance to create imaginary models and “increase diversity” in their ads without needing human beings.


One firm is offering to sell diverse photos for marketing brochures and has already signed up clients, including a dating app that intends to use the images in a chatbot."
"Icons8, an Argentina-based design firm that sells digital illustrations and stock photos, launched its online business Generated.photos last month, offering “worry-free, diverse models on-demand using AI.”
The site allows anyone to filter fake photos based on age (from “Infant” to “Elderly”), ethnicity (including “White,” “Latino,” “Asian” and “Black”) and emotion (“Joy,” “Neutral,” “Surprise”), as well as gender, eye color and hair length. The system, however, shows a number of odd gaps and biases: For instance, the only available skin color for infants is white.

The company says its faces could be useful for clients needing to jazz up promotional materials, fill out prototypes or illustrate concepts too touchy for a human model, such as “embarrassing situations” and “criminal proceedings.” Its online guide also promises clients they can “increase diversity” and “reduce bias” by including “many different ethnic backgrounds in your projects.”

Companies infamously have embarrassed themselves through haphazard diversity-boosting attempts, Photoshopping a black man into an all-white crowd, as the University of Wisconsin-Madison did on an undergraduate booklet, or superimposing women into group photos of men.
But while the AI start-ups boast a simple fix — offering companies the illusion of diversity, without working with a diverse set of people — their systems have a crucial flaw: They mimic only the likenesses they’ve already seen. Valerie Emanuel, a Los Angeles-based co-founder of the talent agency Role Models Management, said she worried that these kinds of fake photos could turn the medium into a monoculture, in which most faces look the same.
“We want to create more diversity and show unique faces in advertising going forward,” Emanuel said. “This is homogenizing one look.”

Icons8 created its faces first by taking tens of thousands of photos of about 70 models in studios around the world, said Ivan Braun, the company’s founder. Braun’s colleagues — who work remotely across the United States, Italy, Israel, Russia and Ukraine — then spent several months preparing a database, cleaning the images, labeling data and organizing the photos to the computer’s precise specifications.

With those images at the ready, engineers then used an AI system known as StyleGAN to output a flood of new photos, generating 1 million images in a single day. His team then selected the 100,000 most convincing images, which were made available for public use. More will be generated in the coming months.
The company, Braun said, signed three clients in its first week: an American university, a dating app and a human-resources planning firm. Braun declined to name the clients.

Clients can download up to 10,000 photos a month starting at $100. The models will not be paid residuals for any of the new AI-generated images built from their photo shoots, Braun said.
Another firm, the San Francisco-based start-up Rosebud AI, offers clients a chance at 25,000 photos of “AI-customized models of different ethnicities.” Company founder Lisha Li — who named it after an infinite-money cheat code she loved as a kid for the people-simulator game “The Sims” — said she first marketed the photos as a way for small businesses on online-shopping sites to invent stylish models without the need for pricey photography.
Her company’s source images came from online databases of free and uncopyrighted photos, and the system allows clients to easily superimpose different faces on a shifting set of bodies. She promotes the system as a powerful tool to augment photographers’ abilities, letting them easily tailor the models for a fashion shoot to the nationality or ethnicity of the viewer. “Face is a pain point that the technology can solve,” she said."

Related posts:

A fake job reference can be just a few clicks away.

Fake Economist Fools Portugal.

Slave Redemption in Sudan. (Fake slaves are sold to those who buy slaves and then give them their freedom)

Can A Product Work Just Because It's Expensive?. (fake medicine)

If It Pays To Have Friends, Can You Pay To Have Friends?. (you can hire fake boyfriends)

Study: Half of American Doctors Give Patients Placebos Without Telling Them.

Saudis grapple with fake street sweepers .

Rent a White Guy: Confessions of a fake businessman from Beijing (by Mitch Moxley in The Atlantic Monthly)

Can adding a phantom third story to their homes help families find a wife for their son?

Why do employers pay extra money to people who study a bunch of subjects in college that they don’t actually need you to know? Signaling

Mexicans buy fake cellphones to hand over in muggings
 
Conspicuous Consumption, Conspicuous Virtue, Thorstein Veblen (and Adam Smith, too!)

How does a company selling used luxury goods spot fakes? (signalling and conspicuous consumption).

Why do stores sometimes pay people to be fake shoppers?

Sunday, January 12, 2020

Rank-and-File Workers Get Bigger Raises

By Eric Morath and Jeffrey Sparshott of The WSJ. Excerpts:
"Pay for the bottom 25% of wage earners rose 4.5% in November from a year earlier, according to the Federal Reserve Bank of Atlanta. Wages for the top 25% of earners rose 2.9%. Similarly, the Atlanta Fed found wages for low-skilled workers have accelerated since early 2018, and last month matched the pace of high-skill workers for the first time since 2010.

“A strong labor market makes the bargaining power of lower-paid workers more like the labor market higher-wage workers experience during good times and bad,” Nick Bunker, economist with job search site Indeed.com, said."

"Average hourly earnings for production and nonsupervisory workers in the private sector were up 3.7% in November from a year earlier—stronger than the 3.1% advance for all employees"

"The unemployment rate for high school dropouts fell to 5.3% last month from 7.8% three years earlier. The rate for college grads is down to 2% from 2.4% in November 2016, and is slightly elevated relative to the late 1990s and early 2000s."

"Pay is also increasing for low-skilled work in states such as Georgia, where the minimum wage remains at the federal level of $7.25 an hour."

"The going rate for a warehouse worker in Atlanta is close to $15 an hour, up from $12 two years ago, he said. Some clients raised pay twice in the past year."

Friday, January 10, 2020

The percentage of 25-54 year-olds employed in 2019 was 79.95%, the higest level since 2001


Click here to see the BLS data. I averaged all the monthly figures. The data from the St. Louis Fed shows 80.0% for last year. Here is their graph. Click here to go to their page.



Here is their data:


Year
Annual%

Year
Annual%

Year
Annual%
1948
63.0

1972
69.5

1996
80.2
1949
62.1

1973
70.5

1997
80.9
1950
62.8

1974
70.8

1998
81.1
1951
64.4

1975
69.3

1999
81.4
1952
65.0

1976
70.6

2000
81.5
1953
65.3

1977
71.9

2001
80.6
1954
63.9

1978
73.6

2002
79.3
1955
65.2

1979
74.6

2003
78.8
1956
65.9

1980
74.3

2004
79.0
1957
66.0

1981
74.7

2005
79.3
1958
64.6

1982
73.5

2006
79.8
1959
65.6

1983
73.7

2007
79.9
1960
65.8

1984
75.8

2008
79.1
1961
65.3

1985
76.7

2009
75.8
1962
66.0

1986
77.3

2010
75.1
1963
66.4

1987
78.4

2011
75.1
1964
67.0

1988
79.2

2012
75.7
1965
67.7

1989
79.9

2013
75.9
1966
68.5

1990
79.7

2014
76.7
1967
69.0

1991
78.6

2015
77.2
1968
69.5

1992
78.3

2016
77.9
1969
70.0

1993
78.5

2017
78.6
1970
69.6

1994
79.2

2018
79.4
1971
69.0

1995
79.7

2019
80.0