AI - Why Humans will Need a Label

Also In This Edition:

• Can ChatGPT write code?

Humans Need a Label

Since last month's diatribe it seems that AI has exploded onto the scene (at least all the tech news outlets), some of them positive ("ChatGPT can find case law faster and easier than using conventional keyword searches") (oh wait, that's a lie!), but most of them negative ("Look at all of these factual errors it's confidently spitting out!!", or "This can be used to easily create malware!").  Then I read that some people have empathy for these things, and some have been using chatbots to write books with little to no effort and self-publish them on Amazon, with the promise of exponentially amplifying the amount of crap out there.  As they proliferate, we'll need some humans to sort through what's factually correct to increase the value of its output.  Back in my day, those people were called "editors".  

It then occurred to me that there will soon be a need for certification - similar to what the farmers' associations came up with to let consumers know whether their crops were organic, or whether a food product contained preservatives.  There will be a need for people who don't want to double-check every fact spit out by a chatbot, to know that what they're consuming has had some human quality control on it to weed out demonstrable falsehoods (Flat Earth?  5G towers cause COVID?), label rumors appropriately ("Climate Change is a hoax from China"), and to give proper historical context.  Plus, it's been demonstrated that those tools that can allegedly detect if ChatGPT had been used to create something are about as reliable as the chatbot output they're trying to authenticate.

So while last month I proposed a law firm that would sue the misbehaving AI models and whip them into shape,  this month I propose that all content created without the use of AI be voluntarily labeled as such.  Of course definitions would have to be worked out, just as it had with farming (there were many definitions of "organic" in the beginning, for example).  And there will be shades of grey even for photographers - for example, should Photoshop (which has some AI tools built-in) count?

Taking this idea a step further, I recall how typewritten letters were once highly regarded when they first appeared, conveying an aura of importance and stature and those were the letters people opened first.  Then when printed letters became the norm, handwritten letters suddenly stuck out as being novel and attention-worthy.  And I think the same thing might happen in photography.  Currently there's no image on the internet that hasn't been post-processed in some way.  I wonder if in the near future scanned transparencies with no post-processing will somehow become more valued because they tell the "truth" more than images that have been manipulated to look more pleasing (which is usually synonymous with lying).  Traditionalists can make their mark by being different - only producing SOOC images!!!  Getting it right in the camera like we used to back in the day!!!  Hey, Peter Lik is a millionaire who people perceive as being a photographic god because he shoots with film.  Or you could employ the Trustworthy Digital Camera I invented to verify that the image you took hadn't been manipulated at all.  Same idea - you're certifying that the content was created by a human and not by a machine learning algorithm.

(Just some 3:00 AM thoughts.  I can easily see heated debates going on about this, especially since the internet, whose content was curated by humans, wasn't all that great before the latest AI tools appeared in full force.  But at least it's something.)

*** UPDATE December, 2024 ***

Once again someone else has picked up on my forward-thinking ideas but not given me any credit.  :-)  Check out this Marketplace report on how the Author's Guild is doing to be labeling books that are written by a human: https://www.marketplace.org/2024/10/07/authors-guild-human-authored-label-ai/

As a self-referential joke, I asked MidJourney to design a logo certifying that something was "A.I.-free".  Of course it couldn't do the lettering right.  I wanted it to say, "The Order of Flesh and Blood", a title taken from the 1950's science fiction movie The Creation of the Humanoids.  Anyway, this will now be the basis of my standard disclaimer, whose final version appears at the top of this post, letting people know that my creations were generated by a human and not via generative AI or machine learning.

Can ChatGPT write code?

Continuing on last month's sermon about these new "AI" machine learning tools used to generate images, I also thought I'd give ChatGPT a chance to help me with a programming need.  I had a folder with 500 images in it of various sizes and formats, and wanted to shrink just some of them and save them to a different directory using the original file type.  You can't use Photoshop actions for this because it lacks the ability to do an "IF - THEN".

So I asked this question of ChatGPT and my jaw dropped when I saw its response: 

===

Me: Can you write a Photoshop script that goes through every image in a folder, shrinks an image to 6" wide at 72 dpi only if the original image is larger than that, then save it in a different directory as either a .jpg of quality 4 or a .png file of smallest size depending on what kind of file the original image was?

ChatGPT: Here is a sample script in Adobe Photoshop's scripting language, JavaScript, that accomplishes the task you described.  The script can be run using Adobe Photoshop's scripting functionality, which can be accessed through the "File" menu.  The code it gave me appears in the scrollbox below:

// Specify the source folder
var srcFolder = Folder.selectDialog("Select the source folder");
// Specify the destination folder
var dstFolder = Folder.selectDialog("Select the destination folder");
// Get a list of all files in the source folder
var fileList = srcFolder.getFiles();
// Loop through each file in the source folder
for (var i = 0; i < fileList.length; i++) {
  // Open the current file
  var file = fileList[i];
  if (file instanceof File && file.hidden == false) {
    app.open(file);
    // Check if the image is wider than 6 inches at 72 DPI
    if (app.activeDocument.width > (6 * 72)) {
      // Calculate the new width in pixels
      var newWidth = 6 * 72;
      // Resize the image
      app.activeDocument.resizeImage(UnitValue(newWidth, "px"), null, 72, ResampleMethod.BICUBIC);
      // Get the file extension of the original image
      var fileExtension = app.activeDocument.name.split(".").pop().toLowerCase();
      // Compose the new file name
      var newName = dstFolder.fsName + "/" + app.activeDocument.name.split(".")[0] + "_resized." + fileExtension;
      // Save the resized image
      if (fileExtension == "jpg") {
        var jpgSaveOptions = new JPEGSaveOptions();
        jpgSaveOptions.quality = 4;
        app.activeDocument.saveAs(new File(newName), jpgSaveOptions, true, Extension.LOWERCASE);
      } else if (fileExtension == "png") {
        var pngSaveOptions = new PNGSaveOptions();
        pngSaveOptions.compression = 0;
        pngSaveOptions.interlaced = false;
        app.activeDocument.saveAs(new File(newName), pngSaveOptions, true, Extension.LOWERCASE);
      }
    }
    // Close the current document
    app.activeDocument.close(SaveOptions.DONOTSAVECHANGES);
  }
}

I was gobsmacked when I saw it spit out perfect-looking code - complete with comments!!  But my enthusiasm waned when I ran the program.  

"This code doesn't work" I protested to the chatbot.  "The destination directory is empty, even though it looked like everything ran properly."  ChatGPT went into "blame the victim" mode, suggesting that perhaps I didn't have permission to write files there.  (I did.)

So I spent the better part of the day debugging the program.  And I found that ChatGPT had made a common beginner's mistake: the default units of measurement for some functions were sometimes in inches and sometimes in pixels.  So all of the images tested were thought to be the wrong size and so the conditional commands were never executed.

I went back to ChatGPT and we had this conversation:

Me: The units were wrong. Sometimes the image width was measured in inches; sometimes it was measured in pixels.

ChatGPT: You can modify the script to handle both cases. Here's a modified version of the script that takes into account the units of the original image width:

// Specify the source folder
var srcFolder = Folder.selectDialog("Select the source folder");
// Specify the destination folder
var dstFolder = Folder.selectDialog("Select the destination folder");
// Get a list of all files in the source folder
var fileList = srcFolder.getFiles();
// Loop through each file in the source folder
for (var i = 0; i < fileList.length; i++) {
// Open the current file
var file = fileList[i];
if (file instanceof File && file.hidden == false) {
app.open(file);
// Get the width of the image in pixels
var originalWidth = app.activeDocument.width.as("px");
// Check if the image is wider than 6 inches at 72 DPI
if (originalWidth > (6 * 72)) {
// Calculate the new width in pixels
var newWidth = 6 * 72;
// Resize the image
app.activeDocument.resizeImage(UnitValue(newWidth, "px"), null, 72, ResampleMethod.BICUBIC);
// Get the file extension of the original image
var fileExtension = app.activeDocument.name.split(".").pop().toLowerCase();
// Compose the new file name
var newName = dstFolder.fsName + "/" + app.activeDocument.name.split(".")[0] + "_resized." + fileExtension;
// Save the resized image
if (fileExtension == "jpg") {
var jpgSaveOptions = new JPEGSaveOptions();
jpgSaveOptions.quality = 4;
app.activeDocument.saveAs(new File(newName), jpgSaveOptions, true, Extension.LOWERCASE);
} else if (fileExtension == "png") {
var pngSaveOptions = new PNGSaveOptions();
pngSaveOptions.compression = 0;
pngSaveOptions.interlaced = false;
app.activeDocument.saveAs(new File(newName), pngSaveOptions, true, Extension.LOWERCASE);
}
}
// Close the current document
app.activeDocument.close(SaveOptions.DONOTSAVECHANGES);
}
}

THAT worked!

Moral to the story #1: This stuff won't put programmers out of work, but it will save them a considerable amount of time by quickly producing code they can tweak. (That's no different from how programmers do their job now: Search Google for a code fragment (usually from from StackOverflow.com) and tweak from there.)

Next, I tried doing some research for my fundraising efforts for the Beaver Works Summer Institute, the engineering accellerator program from MIT I volunteer for.  (Read the whole thing.  It would be entertaining if it weren't so sad):

Me: I'm looking for statistics showing that there will be a labor shortage in STEM fields in the US in the next decade.

 

ChatGPT: According to various studies and reports, there is evidence that the United States will experience a labor shortage in STEM (Science, Technology, Engineering, and Mathematics) fields in the next decade. Here are some statistics and information that support this claim:

 

The Bureau of Labor Statistics predicts that there will be 11.5 million new jobs in the STEM field by 2026. However, there will be a shortage of skilled workers to fill these jobs.

 

According to a report by Deloitte and the Manufacturing Institute, there will be an estimated 2.4 million unfilled manufacturing jobs in the US by 2028, with a skills gap costing manufacturers $2.5 trillion over the next decade.

 

A report by the National Science Board shows that the number of students earning degrees in STEM fields is not keeping pace with the demand for skilled workers. The report found that while the number of STEM degrees awarded in the US has increased by 37% over the past decade, the number of jobs in STEM fields has grown by 79%.

 

The National Association of Manufacturers reports that 89% of manufacturers in the US have difficulty finding qualified workers for skilled production positions.

 

The Computing Technology Industry Association (CompTIA) reports that there are currently 918,000 job openings in the US tech industry, with a shortage of skilled workers to fill these positions.

 

Overall, these statistics suggest that the US is facing a labor shortage in STEM fields, with a lack of skilled workers to fill the increasing demand for jobs in these sectors.

 

Me: Can you provide the source for number 3. above?

 

ChatGPT: Sure! The report I mentioned in point number 3 is "Science and Engineering Indicators 2020" by the National Science Board. You can find the report here: https://ncses.nsf.gov/.../u-s-higher-education-in-science....

 

The specific information I referenced can be found on page 4-11 of the report, under the section "Trends in the Number of Degrees Conferred and Jobs in STEM Fields".

 

Me: The link doesn't work. I found the document elsewhere (It was NSB-2022-3). Couldn't find a page 4-11 nor could I find the name of the section you cited.

 

ChatGPT: I apologize for the error in my previous message. The correct report is "Science and Engineering Indicators 2022" by the National Science Board. You can find the report here: https://ncses.nsf.gov/pubs/nsb20223/.

 

Regarding the specific information I mentioned in point number 3, it can be found in the "Digest of Key Science and Engineering Indicators" section of the report, starting on page 4-12. The section is titled "Trends in the Number of Degrees Conferred and Jobs in Science and Engineering Fields".

 

Again, I apologize for any confusion caused by my previous message and thank you for bringing it to my attention.

 

Me: The new link worked; but again no page 4-12 and no section titled "Trends in the Number of Degrees Conferred and Jobs in Science and Engineering Fields"

 

ChatGPT: I apologize for the confusion, and thank you for your patience. After reviewing the report, I realized that the section I referenced in my previous responses may have been unclear or incorrect. I'm sorry for any inconvenience or confusion this may have caused.

 

To provide accurate information, I would like to clarify that the relevant information is presented in Chapter 2 of the report, specifically in Figure 2-2 (page 2-7) and Figure 2-5 (page 2-10). Figure 2-2 shows the growth in the number of STEM jobs in the United States, while Figure 2-5 shows the number of degrees awarded in STEM fields over time.

 

Again, I apologize for any confusion my previous responses may have caused, and I hope this information is helpful to you.

 

Me: There is no figure 2-2. Figures are called HED-x where X is the figure number.

 

ChatGPT: I apologize for the confusion, and thank you for bringing this to my attention. You are correct that the figures in the report are labeled as "HED-x" rather than "Figure x-x." I apologize for any confusion this may have caused.

 

To clarify, the relevant information on the growth in STEM jobs in the US can be found in the "Higher Education in Science and Engineering" section of Chapter 2, specifically in "Table 2-6: Employment of science and engineering occupations, by occupational group: 2003–18" on page 2-27, and "Table 2-7: Employment of science and engineering occupations, by detailed occupation: 2003–18" on page 2-28.

 

The information on the number of degrees awarded in STEM fields can be found in "Table 2-15: Number of S&E bachelor's, master's, and doctorate degrees awarded, by degree level and field: 2000–18" on page 2-40.

 

I apologize again for any confusion my previous responses may have caused, and I hope this information is helpful to you.

 

=== TRY #2 ===

 

Me: I'm looking for data showing a projected gap between STEM degrees and STEM job openings.

 

ChatGPT: Certainly! One report that provides data on the projected gap between STEM degrees and STEM job openings is the "STEM Talent Shortage: Fact or Fiction?" report by the U.S. Chamber of Commerce Foundation.

 

According to the report, by 2028, the US will face a projected shortage of 3.4 million STEM workers. The report estimates that there will be 9.2 million STEM jobs in the US by 2028, but only 5.8 million individuals with the necessary skills to fill these jobs. This means that there will be a gap of 3.4 million unfilled STEM jobs.

 

The report also notes that while the number of STEM graduates has increased over the past decade, there is still a gap between the number of degrees awarded and the number of jobs available in STEM fields. For example, the report states that in 2017, there were approximately 2.4 million STEM jobs available in the US, but only 568,000 students graduated with STEM degrees.

 

I hope this information is helpful!

 

Me: May I have a link to that report?

 

ChatGPT: Yes, absolutely! You can find the report "STEM Talent Shortage: Fact or Fiction?" by the U.S. Chamber of Commerce Foundation at the following link:

https://www.uschamberfoundation.org/.../stem-talent...

 

I hope this helps!

 

Me: The link doesn't work

 

ChatGPT: I apologize for that. It seems that the U.S. Chamber of Commerce Foundation has removed the report from their website. However, I was able to find an archived version of the report from October 2020 that is still accessible. You can find the report at the following link:

https://web.archive.org/.../STEM%20Talent%20Shortage...

 

I hope this helps!

 

Me: "The Wayback Machine has not archived that URL."

 

ChatGPT: I apologize for the confusion. It seems that the archived version of the report I previously linked to is no longer accessible. However, I have found another source that provides similar information on the projected gap between STEM degrees and STEM job openings in the US.

 

The source is a report by Georgetown University's Center on Education and the Workforce titled "Recovery: Job Growth and Education Requirements Through 2020." According to the report, there will be a shortfall of 1 million STEM workers by 2020 due to a lack of qualified candidates. The report notes that while the number of STEM degrees has increased, it will not be enough to meet the demand for STEM jobs. You can find the report at the following link:

https://cew.georgetown.edu/.../11/Recovery2020.ES_.Web_.pdf

 

I hope this information is helpful to you.

 

===

Epilogue: The information wasn't helpful.

 

Moral to the story #2: Why would I ever pay a monthly fee for a tool that consistently (and confidently) gives me wrong answers?

Chatbots only mirror what's on the internet, which in my lifetime has grown from a trusted tool for researchers to share information to a cesspool of ignorance with some chemtrails thrown in.  And it's about to get worse, with AI dumping exponential amounts of crap into it (which is then used for training).  Hence the idea of the "Humans will Need a Label" idea above.

Yours Truly, 

Gary Friedman

Disclaimer: No AI tools were used in the creation of this blog post.  (Except for that logo I called out.) (And the useless ChatGPT conversation above.)