Generative AI: A Personal Exploration

I wanted to take a closer look at generative AI for this module because this is something that has been on my radar for the past year. It almost seems like it doesn’t matter what field of work you associate with, generative AI has caused disruption in one way or another.

It marks a watershed moment as the general public witnesses firsthand the transformative impact of artificial intelligence on their daily lives.

Exploration – The Ultimate Tutor

I’ve personally used ChatGPT a lot since its release and one of the ways I’ve found it to be most helpful was in explaining really hard topics. It’s almost like having a tutor that you can ask anything to, any amount of times you want. Moreover, chatGPT has numerous ways of explaining topics so you’re bound to find something that clicks.

So here’s a good example, the Merge Sort Algorithm is a numbers sorting algorithm that is commonly used by Computer Scientists. The workings of this particular algorithm are complicated and people who are interested in learning do struggle to get a hold of how the algorithm works.

To demonstrate, I asked chatGPT to explain the algorithm to me like a 5-year-old, and this is what I got:

Now this is just one example of how ChatGPT can break stuff down for you like some of the best educators on the planet. However, while the tool has proven to be incredibly helpful to me. I can’t deny there have been some very valid concerns.

Ethical concerns

Transparency:

one of the very first things that comes to mind is transparency. People have been using AI-generated content without citations and this sends the wrong message. Transparency will help build trust and will encourage people to put in the effort of their own, as well as figure out how they can better themselves with the help of these tools.

Bias:

these tools have been known to fall under the trap of forming biases if given the wrong input and pushed into a certain direction constantly. Monitoring this is crucial to prevent the reinforcement of stereotypes and the unintentional promotion of discriminatory content.

What ChatGPT has to Say

In a strange turn of events, we’re now going to look at what generativeAI tools themselves have to say about ethical concerns surrounding generativeAI.

  • Concern: Generative AI models can inadvertently learn biases present in training data, leading to the generation of biased or unfair content. (OpenAI, 2023).
  • Impact: This bias can perpetuate stereotypes, discrimination, and inequalities, especially when the training data reflects existing societal biases. (OpenAI, 2023).
  • Concern: Generative AI could be misused for malicious purposes, such as creating deepfake content, spreading misinformation, or generating harmful narratives. (OpenAI, 2023).
  • Impact: This misuse poses a threat to individuals, organizations, and society as a whole, leading to potential harm and loss of trust. (OpenAI, 2023).

At the end of the day, I think we need to look at generative AI as what it is intended for and that is a tool. We shouldn’t use it to replace our rolls nor should we avoid it in fear. If we can add the missing morals that currently can not be implemented within these technologies, I think we’ll be able to go a long way.