What I Learned about AI Note #2: The Two Types

(I learn about AI so that I can invest my time and money effectively in it. I write these notes to collaborate, participate in discussions, provide and get help, and most importantly, to solidify my learnings.)

We are most excited by generative AI after the release of ChatGPT which literally dropped AI into the hands of the public in an easy to play manner. It has been so popular that in less than a year it has spawned a new job category known as “prompt engineering”. Students can now take courses on the topic from reputable institutions.

Before generative AI though, we already had predictive AI. We did not call it that mostly using terms like analytics, business intelligence, personalization, and several others. However, this has been behind the scenes and not directly exposed to the public. Also, this has been around for many years. We have known about it but have never got overly excited by it.

There is a simple reason why generative AI has become so popular so quickly. It is in front of our eyes. It is real. It is a fact. We see the output immediately. The 2 key outputs of generative AI are instantaneous. These 2 outputs are:

1.??????Search results

2.??????Content creation

We are already adept at learning through searching. We perform searches regularly in our daily lives. Generative AI takes it to the next level because using good prompts one can learn about things in an easier to use and concise format. We can keep prompting to go deeper and deeper to know more about any topic.

Predictive AI, on the other hand, has more nuanced and nebulous output. We inherently do not trust predictions because we have seen many predictions made in daily lives by pundits not come true. Or not come true in a timely manner. And we live in a world of instant gratification. So, it is hard for us to track predictions that are made for the future and give those much thought.

Yet, it is predictive AI that can do the most good (and maybe the most harm as well). I am not discounting the benefits and value that generative AI delivers. I completely agree that it is going to enhance and increase productivity, creativity, social engagement and also give rise to new jobs like it is already doing.

But I see the next iterations of predictive AI delivering potentially game-changing benefits. Think about better weather forecasting and improving efficiency of renewable energy sources and consumption to tackle climate change. Or predict areas of food and water shortages in advance so that these can be risk managed by relief organizations better. Or better and early disease diagnosis, prevention, and plan for interventions.

These may sound esoteric and far-fetched, but the fact is we are already making huge progress in these areas. The gains in these areas are just not instantaneous and easily visible to us. I will continue to invest in these areas in my own small way and will bring these to more light in my future notes.?