Inferring the correlation between X and Y, or writing an article in a magazine. Between these two tasks, which one can only be done by a human, and which can be done by a machine? It would seem like the answer is fairly straightforward isn’t it? Inferring a correlation between two variables is math. Of course a human could do it. But that would be tedious and time consuming. It would be easier to just let the machine do that, because it can. But writing an article? That is an art. It takes creativity and imagination to write, surely only a human would be capable of doing something like that? Oh how far technology has come.

In May 2020 researchers unveiled the latest advancement in Natural Language Processing (NLP). Dubbing it Generative Pre-trained Transformer 3 (GPT-3). In technical terms GPT-3 is “an autoregressive language model with 175 billion parameters”. In kinder terms, it is a machine learning model that has been pre-trained using a large dataset to “learn” how to write like a human (autoregressive language model). And It has a lot of parameters that can be finely tuned by a user to speak in a very specific way (175 billion parameters). So once given a prompt, like a question, GPT-3 is able to return a response that would sound like it is coming from a human. It has become so proficient at this that authors, and multiple reviewers, have asserted that it is almost indistinguishable from a human response.

It is worth noting though that GPT-3 is able to accomplish this feat because it has analyzed the frequency of how certain words appear next to each other. As an example, GPT-3 may “know” that the word “grapes” is frequently used with words like eat, sweet, fruit, purple, and/or wine. But it doesn’t actually fully comprehend the fact that a grape is a sweet purple fruit that we can either eat or turn into wine.

But despite these faults GPT-3 is making great inroads. And a whole crop of different applications that use it as a foundation are cropping up. I was recently made aware of one such new application called Headlime. A company that is using GPT-3 to help companies produce articles for publication.

So I thought we could have a bit of fun with this new application. The way that Headlime works is that the user is meant to give the GPT-3 model a few keywords and a prompt to get started. And then using that as input, Headlime will then produce a few model-generated paragraphs as output. What would those output look like compared to a human writing from the same prompts?

To find out, I asked a friend of mine to give me a prompt. I will then pass this prompt to the GPT-3 model to write a few paragraphs on the topic; while I will also be doing the same. We can then compare the two and see which one is better.

In the interest of fairness I wrote my paragraphs immediately after seeing the prompt, and finished within 30 minutes. I’ll then post both outputs, but I won’t say which one is which. And then we can vote on which one is the better written paragraph.

So this is the prompt (c/o my friend Paul Sedille):

Output A:

Output B:

To see who wrote which article, check the end of the post!

GPT-3 is being heralded as the next great leap for NLP technology. But it is not without its risks. Like any tool NLP has the potential to be misused; so much so that the authors of the original paper that introduced GPT-3 spent a considerable section of their paper talking about possible misuse of their algorithm, as well as its biases that could negatively impact different demographics.

Moving forward we need to be conscious of how new technology like GPT-3 can impact society. We need to be aware of how tools like these can be used to cause ill. But we also need to work towards making the tool itself more equitable for all.

Technology has the potential to be a great equalizer in society, but it also has the potential to further grow inequality with misuse. So let’s make sure that it is for the former, rather than the latter.

The algorithm wrote A. I wrote B.

Banner image credit to mikemacmarketing

Consultant, tech-geek, and D&D enthusiast (read: addict)

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