Dana Blankenhorn

Beating Jim Crow

What Republicans in the South are trying to do is to reimpose the political and social order that went by the name of Jim Crow.

Between the 1877 withdrawal of federal troops, and the 1964 Civil Rights Act, the South had a social order based on racism and the misogynistic tenets of the Southern Baptist Church. This required strict separation of the races, and the sexes. Blacks were either exiled to the North or condemned to lives of brutality. It wasn’t slavery. In many ways it was worse.

What sustained Jim Crow was a leaky economic boycott by the North. Atlanta tried to resist it, with economic exhibitions, with education, then with social pressure. (To learn more about the struggle, read anything by or about W.E.B. Dubois (1867-1963).)

The “white” history of this period, from Henry Grady’s New South Speech to the story of Coca-Cola, is much less heroic.  What businesses mainly did was treat the South as a colony. Tobacco and cotton drew a price, but most of the value went elsewhere. What modernity came in, starting in the early 20^th century, was a century-old order of textile manufacture, drawn from New England by cheap labor. The South remained backward.

The status quo was protected by white race riots, by lynching, and by laws like Georgia’s “county unit system,” which prevented liberals from ever winning statewide by requiring candidates to win a majority of its 159 counties. This was defended by poor white farmers, the “wool hat boys”  whose muscle, and guns, maintained segregation.

The North built railway networks, utility systems, then scaled high-margin manufacturing. The South didn’t. That is, until the advent of air conditioning which, combined with the Civil Rights movement, blew the whole thing up.

The AI Silly Season

We’re currently in the “silly season” of hype over “Generative AI,” machine learning programs whose output can be text, code, pictures, audio, or video.

There’s a lot of experimentation and there are a ton of bad takes.

Here’s how it’s going to go.

There are two things to know.

First, any software requires training before it becomes useful. Right now programs like ChatGPT are creating garbage. Interesting garbage, but garbage. As people learn how to get value from these tools, however, there will be huge jumps in productivity. The timing and size will differ from industry to industry, and from organization to organization. But it will happen. People will be able to do more, high-quality work in less time. This won’t reduce the need for people. It will give people more things to do.

Beating Moore’s Law

I spent 20 years, off and on, researching Moore’s Law, its history, and how it worked. 

As I wrote my book, and rewrote it twice more, most industries succumbed to its charms, its promise of productivity. Journalism succumbed. Retailing succumbed. So did distribution and management.

Three industries have not yet succumbed, and I have a chapter in the book devoted to them.

These are health care, the law, and education.

It’s not that there aren’t solutions. Law libraries are obsolete. So, too, college libraries. Health care has finally surrendered to electronic records, lured by sweet, sweet stimulus cash.

But final costs, and prices, have gone up in all these areas.

It’s politics.

States refuse to define what graduates need, and unions insist teachers must give the lesson, not just test and tutor. Courts have used technology to pile more work on lawyers and judges. Time is money. Doctors have used their gatekeeping function to stop standardization of treatment, while drug companies have used regulatory capture to create pricing based on the value of your life.

Run on the Bank

The collapse of Silicon Valley Bank may prove to be a bigger story than it appears.

The reason goes back to a story I ran away from, the 1981 collapse of the Houston oil industry.

I didn’t intend to run away. I finally got a job at a daily in Birmingham, Alabama. It was a job I’d hold only 4 months before being fired. But I left Houston June 1, 1981. The collapse began soon after.

As in this case, the Fed had telegraphed what it was going to do. Paul Volcker was going to raise interest rates until inflation gave up, just as Jerome Powell is doing now. Inflation was much higher than, double digits in fact. Add to that the Reagan Administration jawboning the Saudis for lower oil prices and it was a perfect storm.

Publishing is Community

I call March 3 Firing Day.

I lost both my career’s jobs on March 3. In 1983 I was dumped by the Atlanta Business Chronicle. In 1997 I was dumped by CMP Media. Other than those brief periods, I’ve been a freelance all my life.

Had I stayed at ZDNet, a full-time gig I left in 2010, I would have lost my job this Firing Day, as Red Ventures dropped tech journalists from ZDNet and CNet.  

I’m told the culprit is ChatGPT, which can deliver conversational text from descriptive inputs. But it’s really Search Engine Optimization (SEO). SEO is designed to attract Google to content, to maximize its audience. If your content is listed first in Google, people will click on it. If it’s on the 5^th page of a Google search, they’ll never find it.

This is a fine strategy for mass media. But it sucks for journalism. I know because I still work for people who traffic in SEO.

That 2002 Feeling

The last tech crash began in 2000 and I was in the center of it, a mid-career writer with a specialty called Internet Commerce.

That year saw denial and bargaining.

The next year saw anger and depression.

It was only in 2002 that acceptance came.

We know what followed. Talented programmers worked on open source projects and standards bodies created what became the Cloud. When proprietary advantage became worthless, and there seemed there was nothing to do, people worked together with technical goals in mind rather than just financial ones.

It was a slow build. In 2002 my gross income was zero dollars. In 2003 it was zero dollars. I got interested in what’s now the Machine Internet, which I christened the World of Always On, and in 2004 I finally made a few dollars. The next year I was asked to cover Open Source, and my career took off. For a time.

I’ve mentioned before how, in every photo of a stock market crash the people in it look similar. Similar age, similar backgrounds. They’re different people. Those who watched the 1987 crash were different from those who saw the 2000 crash, different from those who saw 2008, different from those who saw 2022.

Fire Sundar Pichai

Recessions are good for markets.

They show us where the rot is, where the poor performers are.

This current one is no exception. It revealed that some of our Cloud Czars, the companies dominating the global economy with hyperscale datacenters paid for with cash flow, aren’t as clothed in gold as they seem. Some are downright naked.

Early this month, I identified one source of rot and urged Jeff Bezos to fire Amazon.Com CEO Andy Jassy. But it’s also time for two other founders to get back in the game. Larry Page and Sergey Brin need to push out Sundar Pichai.

Pichai is the kind of numbers-oriented manager Wall Street loves, but Silicon Valley should despise. He’s the kind of go along, get along guy who can make the trains run on time, but completely lacks vision. In technology this is a fatal flaw.

It’s obvious in how he dealt with artificial intelligence, the new hotness of 2023.

This is not about firing an ethicist. It’s a more basic failure to see where things were going, and deploy the necessary resources to get there. 

Why Clouds Will Win the Streaming Wars

Since long before the streaming crash began, I predicted its Big Three would end up being Apple, Google, and Amazon.Com.

Not Netflix. Not Disney. Not Comcast or Paramount or Warner Brothers.

The Cloud Czars.

As usual, I was early to the story. But it has long been clear that, when push comes to shove in streaming, money talks. The coming result was easy for me to see and the story was easy to do.

Of the three Cloud Czars, Amazon is the best-positioned. They have the front-end technology with the Fire Stick, which has one-third of the U.S. market. They have Prime Video, which becomes a huge value if you use the Amazon store. They can re-sell every other streamer’s stuff and make money. They’re also global, something only Netflix and Disney among their competitors can lay claim to.

ChatGPT

Hate to rain on y’all’s parade but…ChatGPT is not the best thing since sliced bread. It’s not the Macintosh. It’s not the iPhone.

It’s software that translates search requests and results into what seems like plain English. Whether it’s useful depends on the input it gets. Garbage in, garbage out.

That doesn’t mean ChatGPT is Bitcoin or blockchain. It makes search accessible again. But it also makes search messy again. It creates imprecision in a world of 1s and 0s. Not that there’s anything wrong with that. Humans are imprecise. We’re messy. And it is fun to see computer output seem as imprecise and messy as we are.

It’s very easy to get a lie out of ChatGPT. Ask it about a subject where there are lots of lies on the Internet. They will appear in your answer. ChatGPT doesn’t have a filter. Yet.

Where Computing Happens

I met my first computer in 1976, in the basement of Herman Brown Hall, on the campus of Rice University in Houston.

The computing happened in a big room, separated from me by a window. I passed a stack of punch cards, tied with a rubber band, through the window. They came back along with my output. Which usually said the program had died on Line 3.

By the time I got out of journalism school, two years later, computing was moving to desktops. A neighbor bought a $20,000 Cromemco machine that could run 3 terminals. She hired friends to work at the terminals, transcribing court records. I think they got 50 cents a page. Computing had come home.