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TagBig Data

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White swan mask on black wooden surface. Empty space.

New Book Takes Aim at Phantom Patterns “Detected” by Algorithms

Human common sense is needed now more than ever, says economics professor Gary Smith

Pomona College economics professor Gary Smith, author with Jay Cordes of The Phantom Pattern Problem (Oxford, October 1, 2020), tackles an age-old glitch in human thinking: We tend to assume that if we find a pattern, it is meaningful. Add that to the weaknesses of current artificial intelligence and “Houston, we have a problem,” he warns: The scientific method tests theories with data. Data-mining computer algorithms dispense with theory and search through data for patterns, often aided and abetted by slicing, dicing, and otherwise mangling data to create patterns. Gary Smith, “Phantom patterns: The big data delusion” at IAI News (August 24, 2020) Many of the patterns so detected are obviously spurious, for example: A computer algorithm for evaluating job…

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Aerial view of New York downtown building roofs. Bird's eye view from helicopter of cityscape metropolis infrastructure, traffic cars, yellow cabs moving on city streets and crossing district avenues

Microsoft Flight Simulator: Promise and Problems of Big Open Data

For some software, bad data doesn’t matter; for other software, working off of month-old data could be life-threatening

Last week, Microsoft released its critically acclaimed Microsoft Flight Simulator, to much cheering and applause. The game creates a photorealistic journey across the planet. Artificial intelligence combines multiple data sets to create a magnificent virtual experience of flying through the world. The data comes from satellite maps for terrain and texture information and OpenStreetMap to add three dimensional information to city data, such as building heights and other information. Combining all these data sources generates a 3D world using a variety of AI photogrammetry techniques. The program then streams this world to you as you fly through it. Additionally, the system streams in real-world weather data, so that the weather experienced in any part of the world is transmitted to…

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Which Career-Limiting Data Mistake Are YOU Most at Risk For?

Award-winning data science author Gary Smith says the odds depend on your relationship to the data

Dr. Smith thinks that the most dangerous error is putting data before theory. Many data-mining algorithms that are now being used to screen job applicants, price car insurance, approve loan applications, and determine prison sentences have significant errors and biases that are not due to programmer mistakes and biases, but to a misplaced belief in data-mining.

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The Danger AI Poses for Civilization

Why must Google be my helicopter mom?

If I have a coffee cup with “AI inside,” it’s probably connected to the Internet, which is just another way of saying that my coffee cup is transmitting data to some company’s servers about my coffee drinking habits. Whatever benefit the app provides will come at a cost to my autonomy, privacy, and competence as a person.

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Photo by Chris Yang

Technology Centralizes by Its Very Nature

Here are some other truths about technology, some uncomfortable ones

To see what I mean about centralization, consider a non-digital tool, say, a shovel. The shovel doesn’t keep track of your shoveling, read your biometrics, and store a file on you-as-shoveler somewhere. It’s a thing, an artifact. So you see, the new digital technology is itself the heart of the surveillance problem. No Matrix could be built with artifacts.

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How To Fool Facial Recognition

Changing a couple of pixels here and there can stump a computer

Both computers and humans can be fooled by patterns that appear significant but really aren’t. But the bigger the computer, the more random patterns it can find in the vast swathes of data processed.

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2019 AI Hype Countdown #2: Big Data Is Our Crystal Ball!

The biggest problem is that human behavior is not as predictable as the models imply

Many models are ridiculously simplistic, making the results worse than worthless. They become a way of solidifying biases.

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Bingecast: Is Cheese Consumption Causing Deaths from Tangled Sheets?

Those dealing with data must always remember “If you torture data long enough, it will confess to anything.” The answers that computers give must themselves be questioned. Robert J. Marks and Gary Smith address artificial intelligence, spurious correlations, and data research on Mind Matters. Show Notes 01:34 | Introduction to Gary Smith, the Fletcher Jones Professor of Economics at Pomona…

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2019 AI Hype Countdown #9: Hype Fought the Law and…

Autonomy had real software but the hype around Big Data had discouraged Hewlett Packard from taking a closer look

Autonomy CFO Sushovan Hussain was sentenced this year to a five year prison term and a ten million dollar fine because he was held “ultimately responsible for Autonomy's revenues having been overinflated by $193m between 2009 and the first half of fiscal 2011.”

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Can a Big Data Program Be Society’s Crystal Ball?

Can a program with enough data on all of us predict our future?

Even fans admit that, if the program works, bad actors can use it just as easily as New Scientist’s virtuecrats.

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The Golden Age of the Web?—A Dissent

What happened to the collaborative culture, decentralized markets, and wisdom of crowds that bestsellers prophesied fifteen years ago?

Remembering the prophecies for the web in the halcyon days of ten or (better) fifteen years ago is strangely painful and disorienting, like a hangover, largely because we so silently abandoned its ideals.

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Bingecast: Business Intelligence and AI Accounting

Robert J. Marks and Jeremiah Marks talk about business intelligence and AI accounting. Business intelligence affects you daily from advertising and solicitation to how much you pay for tickets to watch the Dallas cowboys. How do companies use business intelligence? Technology has almost entirely replaced the travel agent and many brick and mortar stores. Could high tech tools like robots…

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The US 2016 Election: Why Big Data Failed

Economics professor Gary Smith sheds light on the surprise result

Some of the stuff that made a difference, they couldn’t put in a computer. Some people say, if you can’t measure it, it doesn’t count but sometimes the things that count can’t be measured.

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Big Data Can Lie: Simpson’s Paradox

Simpson’s Paradox illustrates the importance of human interpretation of the results of data mining

Simpson’s Paradox illustrates the need for seasoned human experts in the loop to examine and query the results from Big Data. Could AI be written to perform this operation? Those who say yes are appealing to an algorithm-of-the-gaps.

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Your Phone Knows Everything Now

And in a world where no data is anonymous, yours may be sold to the highest bidder
Your location can be a useful guide to your buying habits, whether or not you want to buy anything or think anyone has any business snooping on you to find out. Read More ›
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camera record on crane in production on studio and light to stage for entertainment industry

1: IBM’s Watson Is NOT Our New Computer Overlord

AI help, not hype: It won at Jeopardy (with specially chosen “softball” questions) but is not the hoped-for aid to cancer specialists
One problem that has dogged Watson has nothing to do with AI or medicine. The journalism around the introduction of projects like Watson is long on the Gee Whiz! An Electronic Brain! It Won at Jeopardy! And it is short on systematic inquiry as to outcomes versus goals. Read More ›
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Chess game business strategy concept

Can Big Data Beat the Humans Who Compile It?

A computer pioneer bets no: Human intelligence augmented by artificial intelligence will always beat artificial intelligence alone. Is he right?
The bottom line is that Brooks’ Bet and his IA>AI inequality principle is a good reality check in the face of fears and hype about what AI will do in the future. Read More ›
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Data graph on monitor showing correlation

Study Shows Eating Raisins Causes Plantar Warts

Sure. Because, if you torture a Big Data enough, it will confess to anything
Enormous data sets compiled by Big Data methods have a higher probability of meaningless correlations than smaller ones compiled by traditional methods. More than ever, common sense is needed. And common sense only comes from programmers writing their own common sense into the software. Read More ›
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Can Big Data Help Make Your Book a Best Seller?

It’s more likely to help you picture your odds more clearly and clarify your goals
What does Barabási’s Big Data tell us that we couldn’t just guess? Well, for one thing, that there is a “universal sales curve” which means that a book’s only chance of making the list is shortly after publication. Read More ›
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Quantity vs Quality: Can AI Help Scientists Produce Better Papers?

What happens when scientists simply can't read all their peers' papers and still find time for original research?
Quantity is definitely a solved problem. STM, the “voice of scholarly publishing” estimated in 2015 that roughly 2.5 million science papers are published each year. Some are, admittedly, in predatory or fake journals. But over 2800 journals are assumed to be genuine. Read More ›