Artificial Intelligence Design inference Intelligent Design Peer review

Design inference: AI, ID, and detecting deceit

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In science papers:

Because forensic science is an example of intelligent design in action, ID inference tools must be summoned for assistance in this endeavor. William Dembski illustrated using ID principles within the class of designed objects in his recounting of the case of county clerk Nicholas Caputo, who was caught stacking the deck for his favored candidates by listing them at the top of the ballot more often than could be accounted for by chance. Today’s examples are even tougher to crack. Often there is no element of chance or natural law to eliminate. The research paper, the perpetrator, and the AI software are all intelligently designed. What then?

Tortured Phrases

A news feature in Nature speaks to the growing problem of fabricated research papers. Reporter Holly Else gives hope that there may be ways to detect malicious design: “strange turns of phrase may indicate foul play in science,” she begins …

Because AI cannot yet mimic the cultural nuances known by human writers, an AI algorithm programmed to replace words with synonyms can make a cultural faux pas. It has no problem replacing “cloud computing” with “haze figuring.” A human editor can detect the humor in a paper that speaks of “signal to noise” as “flag to commotion.” This lack of nuance in software can help integrity sleuths for now — until AI catches up.

Evolution News, “Detecting Malicious Intent in Undisputed Design” at Evolution News and Science Today (September 18, 2021)

In other words, the next iterations of science fraud will employ machine learning trained on enough of the internet to avoid such obvious goofs. We will need better, more sophisticated methods.

The opposite of fakery is integrity. Holly Else uses that word three times, referring to experts who sniff out examples of plagiarism, fabrication and cheating. They are overwhelmed at present. Is this a field where ID advocates can take the lead? Intelligent design theory already encompasses detection of intentionality, whether nefarious or benign. ID researchers would most likely agree that it’s better to have a mistake-ridden paper honestly trying to argue for Darwinism than a made-up paper by a plagiarist or computer program arguing for design.

Evolution News, “Detecting Malicious Intent in Undisputed Design” at Evolution News and Science Today (September 18, 2021)

But then, long before all this AI stuff happened, the first Sokal hoax was perpetrated, to warn us. Few heeded the warning.

Maybe an ID-friendly AI expert can help. But how sure are we all that the peer reviewed science industry really wants help at this point? We shall see.

You may also wish to read: Science sleuths catch authors using AI tool for plagiarism. Odd phrases like “counterfeit consciousness” instead of “artificial intelligence” began appearing in computer science journals, triggering an investigation. Both the researchers and publisher Elsevier determined that automatic reverse translation, to disguise plagiarism, was the likely source of the odd phrases.

One Reply to “Design inference: AI, ID, and detecting deceit

  1. 1
    polistra says:

    A better way to avoid deceit is to train the computers on reality.

    When students have their HANDS AND SENSES on real dissected frogs or real chemical reactions or real electronic circuits, they can’t be fooled by lies in the textbook or lecture.

    Do the same for the computer. Maintain a large set of ongoing lab setups for various physical subjects. Have the computer ASK REAL PEOPLE about a more subjective question, and REQUIRE IT TO ACCEPT THE ANSWER. No filters allowed. If the answer disagrees with fashion, fuck fashion. Take reality every time.

    As long as truth is defined by the granting agencies, the programmers and computers will favor official lies.

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