Blind eye or OpenAI

Here we stand in the court of public opinion. Hear Ye! Hear Ye! Who here believes that AI should not be incorporated into our everyday lives, please speak up or forever hold your peace.

The hypothetical courthouse is silent, then there is gasp from the back. A man stands saying “I cannot not tolerate AI being this powerful”. The camera shot moves towards the judge, the judge slowly looks up ready to rule the fate of AI and his face comes into focus.

It’s Sam Altman . . . and scene.

Hello CUInsighters! I hope you enjoyed my dramatic introduction/monologue. Let’s get back on the topic. I believe there are many people in various industries who may feel they are not ready for AI. I believe some feel it would complicate their jobs or possibly eliminate them.

I have a more positive outlook on many of the concerns, let’s take a stab at many of the popular ones.

In most circles, this ranks #1 on the list. But if you dive deeper into this concept based on reality and not some far-fetched futuristic utopia, then this should help ease the mind of many. AI in its current state is a tool. Just like any other tool we encounter. The goal is to learn how to use it.

Most people who start their careers in the corporate sector and any sector start their first days in training. This training then progresses to on-the-job training where a peer or leader works closely with you and monitors how you grasp the process. Then it would eventually progress to you being on your own, utilizing internal tools/software to complete your daily job functions.

The AI skill concept is no different. Companies who incorporate AI into their business unfortunately can’t teach AI the innate culture that helps a business thrive. The soul and strategy of an organization is built by the people. AI remains a tool that can be helpful or let’s say streamline mundane tasks to help YOU become more efficient. That’s the good news, Here’s the bad news.

The first sector that has seen the most impact are Big Tech firms. Here are some of the reported numbers.

These are the companies that can integrate AI at the highest levels. Their infrastructure is more dependent on “do more with less” more than most sectors. For them, data, and data analysis is king. This is a perfect case example when smart builders build their peers out of jobs. It forces the job market to shift, to innovate and create new sectors that still require those replaced skillsets.

We are already seeing engineers leave big tech companies and embarking on their entrepreneurial startup dreams with a focus on AI. Guess who their target audience is? YOU!

Tip: If you have incorporated chatbots for customers, test them yourselves regularly.

Let’s talk a little about the next area of concern.

If you have ever tried using AI, most likely you have gone to the OpenAI website or directly to ChatGPT. I would bet my boss’s entire check (LOL!) that a high percentage of most new AI startups and even internal company engineers are using the ChatGPT API. They would be crazy not to, based on the daily improvement of their LLM.

The elephant in the room remains to be the potential inaccuracies AI could produce in prompt results. This is where the lack of control comes into play. In this current environment, you are only as good as your prompting ability. A one prompt entry will most likely never get you the answer you need. But most people using the AI tools don’t practice this, like the process I spoke about above with the new person starting their career. Your understanding of how to use AI likely becomes your responsibility. If you choose to put it off, the replacement theory may get closer to your reality . . . depending on the job role.

Tip: Prompt, analyze, prompt again, challenge the AI, and prompt again

Last but certainly not least.

AI tools that monitor productivity, analyze communication patterns, or track behavior can feel invasive, raising concerns about constant surveillance and misuse of personal data.

It is critical that organizations using AI ensure the proper questions are asked of the service provider. Companies must understand the source of API models and the limitations and bias impacting results or decisions.

I will leave with my top three things to ask about AI systems.

These are just a few.

I hope this article was helpful. Feel free to share. Keep learning—turning a blind eye to innovation could hinder your growth, whether as an individual or an organization.