^TagBig Data

Mirror reflection of pyrite crystal on black background

^{Type
post

Author
Gary Smith
Date
February 15, 2022

Categorized
Artificial Intelligence

Tagged
"poison medicine" problem, 2014 Brazilian election, Artificial Intelligence, Big Data, power poses}

Fool’s Gold: Even AI Successes Can Be Failures

_{Large doses of data, math, and computing power do not make a computer intelligent} _{Gary Smith

February 15, 2022

6

Artificial Intelligence}

I recently read this enthusiastic claim by a professional data miner: Twitter is a goldmine of data…. [T]erabytes of data, combined together with complex mathematical models and boisterous computing power, can create insights human beings aren’t capable of producing. The value that big data Analytics provides to a business is intangible and surpassing human capabilities each and every day. Anthony Sistilli, “Twitter Data Mining: A Guide to Big Data Analytics Using Python” at Toptal I was struck by how easily he assumes that large doses of data, math, and computing power make computers smarter than humans. He is hardly alone, but he is badly mistaken. Computer algorithms are really, really good at making mathematical calculations and identifying statistical patterns (what Turing winner Judea Pearl calls “just curve Read More ›

silhouette of virtual human on abstract technology 3d illustration

^{Type
podcast

Author
Robert J. Marks
Date
September 30, 2021

Tagged
Alan Turing, algorithmic intelligence, Algorithms, Artificial General Intelligence (AGI), Artificial Intelligence, Big Data, code-breaking, Colossus computer, Connectome, Data Mining, DeepMind, Ergodicity, front running, Gaming AI, Gaming AI (book), George Gilder, Gregory Chaitin, John von Neumann, Kurt Gödel, Lee Sedol, life after google, mind, Mind Brain, Mind-Brain Distinction, Nematode worm, Neural networks, protein folding, Ray Kurzweil, Robert J. Marks, stock market, Tony Stretton, Turing Machine, zettabyte}

George Gilder: An Economic Genius Talks About Gaming AI

_{Robert J. Marks

September 30, 2021

2}

George Gilder talks to Robert J. Marks about his book Gaming AI: Why AI Can’t Think but Can Transform Jobs. Show Notes Additional Resources

^{Type
post

Author
Heather Zeiger
Date
August 30, 2021

Categorized
Business and Finance, Data Privacy, Global Technology, Law

Tagged
Algorithms, Big Data, China, China Consumers Administration (CAC), Chinese Communist Party (CCP), consumer data laws, critical information infrastructure, Critical Information Infrastructure Security Protection Regulations, Cyberspace Administration of China (CAC), data privacy laws, Data Security Law, Didi Global Inc., European Union, Facial Recognition, General Data Protection Regulations (GDPR), Jack Ma, Personal Information Protection Law, Xi Jinping}

China’s Data Laws Restrict Businesses and Favor the State

_{The Data Security Law and the Personal Information Protection Law are part of the Chinese government’s plan to steer the private sector toward State goals} _{Heather Zeiger

August 30, 2021

8

Business and Finance, Data Privacy, Global Technology, Law}

In previous articles, I looked at how the Chinese government is reigning in China’s tech sector first of Jack Ma and Ant Group’s initial public offering on the Shenzhen and Hong Kong stock exchanges and then Didi Global, Inc. The Chinese government has since passed two data laws and released an update that clarifies the 2017 Cybersecurity Law. The result is better protections of citizens’ data from being used, exploited, or sold by private companies, and encroaching government presumption of the private sector in which the State has virtually unrestricted access to and jurisdiction over private companies’ data. Clarification of the 2017 Cybersecurity Law The Cyberspace Administration of China (CAC) gained oversight powers over other state agencies in 2014 under Xi Jinping. Jane Read More ›

Electronics Engineer Works with Robot Checking Voltage and Program Response time. Computer Science Research Laboratory with Specialists Working.

^{Type
post

Author
Denyse O'Leary
Date
April 5, 2021

Categorized
Artificial Intelligence, Business and Finance, Data Privacy, Military, Surveillance

Tagged
Ashton Carter, Big Data, Bureaucracy (and science advances), China, China (competitiveness in AI), Great Reset, Gregory Chaitin, Patent filings, Silicon Valley, U. S. Department of Defense, United States (competitiveness in AI), Walter Isaacson}

Has the United States Lost Silicon Valley?

_{Once on friendly terms with the U,S, Department of Defense, Silicon Valley must consider the views of its friends in China} _{Denyse O'Leary

April 5, 2021

8

Artificial Intelligence, Business and Finance, Data Privacy, Military, Surveillance}

Recently, we learned that China had, for the first time, surpassed the United States in AI patent filings: The development was revealed by Li Yuxiao, Deputy Head of the Chinese Academy of Cyberspace Studies at the 7th World Internet Conference (WIC), reports SCMP. With this, China is now bolstering its position of being a leader in AI. As per the report, China had filed more than 110,000 artificial intelligence patents last year, more than the patents filed by the United States but the number of patents filed by the country has not been disclosed. “China surpasses US for the first time in artificial intelligence patent filings” at TECHregister (November 27, 2020) Now, people have been claiming that innovative competitiveness is Read More ›

Digital binary code matrix background in graphic concept

^{Type
post

Author
News
Date
December 24, 2020

Categorized
Artificial Intelligence, Science

Tagged
Big Data, David Auerbach, Featured, Gary Smith, Jay Cordes, Phantom Pattern Problem (book), Phantom patterns}

Smith and Cordes’ Phantom Pattern Problem A Top 2020 Book

_{Published by Oxford in 2020, it deals with the “patterns” Big Data throws up that aren’t really there} _{News

December 24, 2020

5

Artificial Intelligence, Science}

David Auerbach has picked The Phantom Pattern Problem (2020) by Gary Smith and Jay Cordes as one of the top books of 2020 in the science and tech category. Auerbach, who describes himself as “a writer and software engineer, trying to bridge the two realms,” is the author of BITWISE: A Life in Code (2018). He has an interesting way of choosing books to recommend: Those that resist the “increasingly desperate and defensive oversimplification” of popular culture: I hesitate to mention too many other books for fear of neglecting the others, but I will say that of the science and technology books, several deal with subjects that are currently inundated with popularizations. In my eye, those below are notably superior Read More ›

^{Type
post

Author
Gary Smith
Date
December 23, 2020

Categorized
Medicine and Health

Tagged
Big Data, British Medical Journal Christmas edition, Featured, Friday the 13th paper, Hound of the Baskervilles Effect, Junk science, Surgeon's birthday effect}

The British Medical Journal’s Top Picks in Offbeat Medical Science

_{In its legendary Christmas edition, the Journal highlights interesting findings that are often junk science} _{Gary Smith

December 23, 2020

9

Medicine and Health}

The British Medical Journal (BMJ) is one of the world’s oldest and most prestigious medical journals. Each Christmas, they take time off from the usual dry academic papers and publish studies that are noteworthy for their originality: “We don’t want to publish anything that resembles anything we’ve published before.” Although the papers are unusual, BMJ’s editors state that: While the subject matter may be more light-hearted, research papers in the Christmas issue adhere to the same high standards of novelty, methodological rigour, reporting transparency, and readability as apply in the regular issue. Christmas papers are subject to the same competitive selection and peer review process as regular papers. The articles are often goofy, and four have won the dreaded satiric Read More ›

Data technology background. Big data visualization. Flow of data. Information code. Background in a matrix style. 4k rendering.

^{Type
post

Author
Gary Smith
Date
December 21, 2020

Categorized
Artificial Intelligence, Machine Learning

Tagged
Big Data, Bottomless bowls study, Brian Wansink, Cornell University, Daryl Bem, Data Mining, Data mining examples, Featured, Fishing expedition analysis, IgNobel prize, Nigel Richards, Retroactive recall}

Torturing Data Can Destroy a Career: The Case of Brian Wansink

_{Wansink wasn’t alone. A surprising number of studies published in highly respected peer-reviewed journals are complete nonsense and could not be replicated with fresh data} _{Gary Smith

December 21, 2020

8

Artificial Intelligence, Machine Learning}

Until a few years ago, Brian Wansink (pictured in 2007) was a Professor of Marketing at Cornell and the Director of the Cornell Food and Brand Lab. He authored (or co-authored) more than 200 peer-reviewed papers and wrote two popular books, Mindless Eating and Slim by Design, which have been translated into more than 25 languages. In one of his most famous studies, 54 volunteers were served tomato soup. Half were served from normal bowls and half from “bottomless bowls” which had hidden tubes that imperceptibly refilled the bowls. Those with the bottomless bowls ate, on average, 73 percent more soup but they did not report feeling any fuller than the people who ate from normal bowls. Eating is evidently Read More ›

Global virus and disease spread, coronavirus

^{Type
post

Author
News
Date
November 12, 2020

Categorized
Medicine and Health, Social Media

Tagged
Big Data, computer models, COVID-19, Featured, Imperial College London, Jay Richards, Media (traditional), Price of Panic (book), Statistical models, Tedros Adhanom, World Health Organization (WHO)}

Did Social Media Panic Drive Up the Damage from COVID-19?

_{Richards: It was, honestly, terrifying to watch important stories and studies get buried in real time on Google searches.} _{News

November 12, 2020

9

Medicine and Health, Social Media}

Last month, business studies prof Jay Richards, along with co-authors Douglas Axe and William M. Briggs, published a book with some controversial premises: One of them is that many popular COVID-19 fears are the overblown outcome of paying too much attention to social media as opposed to the facts that got lost in the uproar. And that we are paying the price now in human, as well as financial, costs. The Price of Panic: How the Tyranny of Experts Turned a Pandemic into a Catastrophe (October 2020) assembles a massive statistical case. But in this interview with Mind Matters News, Richards focuses on how it affected us: What we all thought was happening and why we thought so—a different story Read More ›

3D Rendering of binary tunnel with led leading light. Concept for data mining, big data visualization, machine learning, data discovery technology, customer product analysis.

^{Type
post

Author
News
Date
November 3, 2020

Categorized
Artificial Intelligence, Neuroscience, Science

Tagged
Big Data, Big Data Assumption, brain, computer, Featured, Gaming AI (book), Gary Smith, George Gilder, Modeling Assumption, Yuri Danilov}

The Brain Is Not a Computer and Big Data Is Not a Big Answer

_{These claims are mere tales from the AI apocalypse, as George Gilder tells it, in Gaming AI} _{News

November 3, 2020

4

Artificial Intelligence, Neuroscience, Science}

In Gaming AI, George Gilder (pictured) sets out six assumptions generally shared by those who believe that, in a Singularity sometime soon, we will merge with our machines. Some of these assumptions seem incorrect and they are certainly all discussable. So let’s look at the first two: • “The Modeling Assumption: A computer can deterministically model a brain.” (p. 50) That would be quite difficult because brains don’t function like computers: As neuroscientist Yuri Danilov said last year, “Right now people are saying, each synoptical connection is a microprocessor. So if it’s a microprocessor, you have 1012 neurons, each neuron has 105 synapses, so you have… you can compute how many parallel processing units you have in the brain if Read More ›

^{Type
podcast

Author
Robert J. Marks
Date
October 29, 2020

Tagged
Alan Turing, Artificial Intelligence, Big Data, Data Mining, Ergodicity, front running, Gaming AI (book), George Gilder, Gregory Chaitin, John von Neumann, Kurt Gödel, Life after Google (book), Mind Brain, stock market, Turing Machine}

Artificial Intelligence Gaming the Stock Market

_{Robert J. Marks

October 29, 2020

1}

What are some assumptions about artificial intelligence? How does artificial intelligence affect the stock market? George Gilder and Robert J. Marks discuss assumptions about artificial intelligence, the stock market, and George Gilder’s new book Gaming AI: Why AI Can’t Think but Can Transform Jobs (which you can get for free here). Show Notes Additional Resources

Artificial Intelligence. Composition on the subject of Future Technologies. 3d rendered graphics.

^{Type
post

Author
News
Date
October 23, 2020

Categorized
Artificial Intelligence

Tagged
Analog computers, Big Data, Charles Sanders Peirce, Featured, Gaming AI (book), Gary Smith, George Dyson, George Gilder, Interpretant, John Archibald Wheeler, Map vs. territory, Microcosm (book), Quantum Computing, Quantum Zeno effect, Robert J. Marks}

Why AI Geniuses Haven’t Created True Thinking Machines

_{The problems have been hinting at themselves all along} _{News

October 23, 2020

7

Artificial Intelligence}

As we saw yesterday, artificial intelligence (AI) has enjoyed a a string of unbroken successes against humans. But these are successes in games where the map is the territory. Therefore, everything is computable. That fact hints at the problem tech philosopher and futurist George Gilder raises in Gaming AI (free download here). Whether all human activities can be treated that way successfully is an entirely different question. As Gilder puts it, “AI is a system built on the foundations of computer logic, and when Silicon Valley’s AI theorists push the logic of their case to a “singularity,” they defy the most crucial findings of twentieth-century mathematics and computer science.” Here is one of the crucial findings they defy (or ignore): Read More ›

Abstract 3d render, geometric composition, yellow background design with cubes

^{Type
post

Author
News
Date
September 30, 2020

Categorized
Artificial Intelligence, Machine Learning, Science

Tagged
AI algorithms, Big Data, Carmen Reinhart, Featured, Gary Smith, Jay Cordes, Ken Rogoff, Meaningless patterns, Patterns, Phantom Pattern Problem (book), Science Journals}

Interview: New Book Outlines the Perils of Big (Meaningless) Data

_{Gary Smith, co-author with Jay Cordes of Phantom Patterns, shows why human wisdom and common sense are more important than ever now} _{News

September 30, 2020

5

Artificial Intelligence, Machine Learning, Science}

Economist Gary Smith and statistician Jay Cordes have a new book out, The Phantom Pattern Problem: The mirage of big data, on why we should not trust Big Data over common sense. In their view, it’s a dangerous mix: Humans naturally assume that all patterns are significant. But AI cannot grasp the meaning of any pattern, significant or not. Thus, from massive number crunches, we may “learn” (if that’s the right word) that Stock prices can be predicted from Google searches for the word debt. Stock prices can be predicted from the number of Twitter tweets that use “calm” words. An unborn baby’s sex can be predicted by the amount of breakfast cereal the mother eats. Bitcoin prices can be Read More ›

White swan mask on black wooden surface. Empty space.

^{Type
post

Author
News
Date
August 25, 2020

Categorized
Artificial Intelligence

Tagged
Big Data, Featured, Gary Smith, Jay Cordes, Patterns (in statistics), Phantom Pattern Problem (book)}

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

_{Human common sense is needed now more than ever, says economics professor Gary Smith} _{News

August 25, 2020

3

Artificial Intelligence}

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 Read More ›

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

^{Type
post

Author
Jonathan Bartlett
Date
August 25, 2020

Categorized
Artificial Intelligence, Arts & Culture

Tagged
Big Data, Ed Niedermeyer, Featured, Microsoft Flight Simulator, OpenStreetMap}

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} _{Jonathan Bartlett

August 25, 2020

5

Artificial Intelligence, Arts & Culture}

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 Read More ›

^{Type
post

Author
News
Date
February 23, 2020

Categorized
Business and Finance, Work

Tagged
9 Pitfalls of Data Science (book), Big Data, Featured, Gary Smith, Jay Cordes}

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} _{News

February 23, 2020

6

Business and Finance, Work}

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.

^{Type
post

Author
Analysis
Date
February 12, 2020

Categorized
Artificial Intelligence, Surveillance, Technocracy

Tagged
Big Data, China, Deep Learning, Technology}

Technology Centralizes by Its Very Nature

_{Here are some other truths about technology, some uncomfortable ones} _{Analysis

February 12, 2020

8

Artificial Intelligence, Surveillance, Technocracy}

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.

^{Type
post

Author
News
Date
January 2, 2020

Categorized
Artificial Intelligence, Business and Finance, Global Technology, Work

Tagged
___longform, Big Data, Facial Recognition, Featured, Gary Smith, Robert J. Marks}

How To Fool Facial Recognition

_{Changing a couple of pixels here and there can stump a computer} _{News

January 2, 2020

8

Artificial Intelligence, Business and Finance, Global Technology, Work}

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.

^{Type
post

Author
Jonathan Bartlett
Date
December 30, 2019

Categorized
Artificial Intelligence, Religion

Tagged
Big Data, computer models, Computer Simulation, simulation}

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} _{Jonathan Bartlett

December 30, 2019

5

Artificial Intelligence, Religion}

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

^{Type
podcast

Author
Robert J. Marks and Gary Smith
Date
December 26, 2019

Tagged
AI Delusion (book), Algorithm-of-the-Gaps, Artificial General Intelligence (AGI), Artificial Intelligence, Barack Obama, Big Data, Bill Clinton, Bob Dylan, Chamath Palihapitiya, Chinese Room, data analytics, Diederik Stapel, Douglas Hofstadter, Edward Leamer, Facial Recognition, Gary Smith, Hillary Clinton, IBM Watson, J. B. Rhine, John Ioannidis, John Searle, Neural networks, non-algorithmic, Oren Etzioni, Roger Schank, spurious correlations, stock market, Texas Sharpshooter Fallacies, The Winograd Schema Challenge, Zener cards}

Bingecast: Is Cheese Consumption Causing Deaths from Tangled Sheets?

_{Robert J. Marks and Gary Smith

December 26, 2019

3}

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 Read More ›