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About Lorien Pratt

Lorien Pratt has been delivering artificial intelligence solutions for her clients for over 30 years. These include the Human Genome Project, the Colorado Bureau of Investigation, the Department of Energy, and the Administrative Office of the US Courts. The inventor of the fields of machine learning Inductive Transfer and Decision Intelligence (DI), Pratt received the CAREER award from the National Science Foundation, an innovation award from Microsoft, and the Exemplary Research award from the Colorado Advanced Software Institute. Formerly a professor at the Colorado School of Mines, Pratt has given two TEDx talks, and cofounded her own company, Quantellia, in 2010, which offers machine learning, decision intelligence, and full-stack software solutions. Quantellia subsidiaries offer AI and DI-based banking, health care, and educational solutions. Previously a well-known technology analyst, Pratt has also authored dozens of academic papers, was invited editor for the journals Machine Learning and Connection Science , co-edited Learning to Learn, and wrote the Decision Engineering Primer. Today, Pratt delivers and builds solutions for multiple clients, is a five-star rated provider with the Harvard Innovation Lab’s Experfy platform, and is technology lead for the Buckminster Fuller-inspired Silicon Valley SimCenter. Recently covered on TechEmergence, on the JohnMac radio show, and by Bloomberg BNA, Pratt works from her home office in Denver and Quantellia HQ in Sunnyvale CA.

Has media reached a reality/complexity tipping point?

A landmark paper appeared last December in the National Science Review (summary).  It describes the complex interdependencies between climate, consumption, population, demographics, inequality, economic growth, migration, and more.  Written by an interdisciplinary team of 20 authors hailing from organizations worldwide including NASA, Johns Hopkins, and more, the paper explains that it is impossible to understand these systems in isolation.  There are important—and non-obvious—interactions.  Poverty impacts climate.   Inequity impacts the status of women.   Conflict impacts resource usage.  And much more.

The bottom line: our understanding of the world is no longer good enough.  We need to raise our game.

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Death by proxy

“This year, our priority is customer experience.  Everything we do must connect to that.”

“We’ll upgrade the network in a neighborhood when the bandwidth utilization exceeds 80%.”

“I’m going to get rich, then I’ll be happy.”

Good ideas, on the surface.  Problem is: they’re often wrong.

And they share a common thought pattern: the use of a proxy—a substitute—for what we actually care about.

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Responsibility, authority, and insanity

So this is pretty basic.  But it’s huge.

Problem: You are working at a bank and have been tasked with developing a new customer care program.  You’re making good progress, and reach out one day to a colleague for their ideas.  Word of the meeting gets around, and an executive walks into your office one day, assuming you’re floundering, and tells you what to do.

Problem: Your second grader is in trouble at school.  Teachers and other parents call you on the phone, asking you to fix the problem.  You are starting to develop some good ideas and making plans.  But one day, the school principal makes the decision to move your child to a special classroom.

Problem: You work on an automobile assembly line.  Your bonus depends on the quality of the cars you help to build.  You see a problem with a welding machine which would cost $100 to fix.  But management won’t approve the repair.

What’s the common pattern here?  It’s responsibility without authority: a good recipe for insanity.

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One link think

In the swirl of events, I’m often left wondering if there’s something deeper going on.  Our leaders seem to be increasingly missing the bigger picture.  A glimpse, here and there, into the underlying cause of dead ends we’ve reached: problems with capitalism, the media, politics, climate, conflict, health care.   Is there a common cause?

2016 might arguably be characterized as the year we all decided we’d had enough of government as usual.  Between Brexit, the Trump ascendancy, and the sheer energy behind the Bernie Sanders campaign, it seems that many are thinking, “enough is enough”.  And that’s the good news.  When disenfranchised groups have zero representation, then terrorism and revolt seem to be the inevitable outcomes.

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Pulling Back the Curtain on #MachineLearning Apps in #Business

Please enjoy this interview broadcast today with me and Daniel G. Faggella of TechEmergence.  I touch on intelligence augmentation (IA), machine learning in vision, text, and other domains, the emerging decision intelligence ecosystem, the limits of data, and how to hire a machine learning consultant.

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Artificial intelligence and human limits

Are we getting dumber?  Or is stuff just harder?

Both are true.  Between-silo problems are the new bottleneck.  We’re inundated with information, so we take cognitive short cuts.   And “wicked” problems keep getting wickeder.

Take this “invisible art” artist.  She sold a few.*

Real decisions are made in the heart, the gut, based on a good story.  So we’re vulnerable to master wizards: good story tellers.  And, often, we’ll do what they say.

It’s impossible to assemble hundreds of graphs and data visualizations in our heads to make good decisions. It’s a fiction that we can.  So we’re overwhelmed, take short-cuts, but it’s hard to admit.

The good news: we have new superpowers.

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From maker space to solver space

Conferences are for meetings.  Project teams build deliverables.  Data is for data scientists.  Online communities are for social contact.

Until now, when a new mix is emerging.  Can we solve difficult problems in a short-term conference setting?  Is there a new way to run a workshop, which is dynamic, data-driven, visual, collaborative?

I wrote a few months back about the Silicon Valley Sim Center: an initiative to bring a new way to solve “wicked” problems to Silicon valley.  And in an article in this month’s Wired called “Hey Silicon Valley, Buckminster Fuller has a lot to teach you by Sarah Fallon, she interviews Jonathon Keats about his new book on what Bucky has to say to Silicon Valley.*

And from “maker spaces” to “solver spaces”, a new way of working together to solve difficult problems is emerging.

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Necessary, but not sufficient

When asked “who created Apple?”, it’s tempting to say Steve Jobs did it.  The truth is that, although he may have been necessarily, he was not sufficient.

Similarly Bill Gates, who (as Malcolm Gladwell tells us in Outliers) experienced a unique confluence of circumstances that led to the founding of Microsoft.  Gates deserves tremendous credit, but alone he was not sufficient.

The brain likes to simplify, and history sometimes prefers to leave out the details for the benefit of a better story. Continue reading

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Decision intelligence for data center disaster planning

Much of the world’s information is handled in data centers: nondescript on the outside, indoors you’ll find a din of humming machine in acres of racks.  If an earthquake or other natural disaster should strike a data center, the cost can be enormous.

So spending money on risk mitigation strategies like earthquake-proofing makes sense.

But it’s a tricky balancing act: spend too much for a disaster that never happens, and it’s money down the drain.  Spend too littledatacenter, and a disaster can spell tremendous costs.

A decision model can help.  We built a demonstration of one shown in the video above, at the link here, and in the bottom of this article, for those viewing this online.

Give it a try, it takes about one minute: Continue reading

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