How will generative AI impact the future of work?

Generative artificial intelligence is the new favorite of Silicon Valley. But what exactly is it? And what does it mean for the future of work for you and me? Experts believe that generative AI will soon enter the workplace, predicting that by 2023, generative AI will be able to combine scientific papers with visual design models Combined, by 2030 it will be able to write, design and code better than human professionals in the field.

However, few of us have a clear idea of ​​how this will play out. How will it all begin? That’s why it’s important to delve into what technology is and isn’t.

As far as the insurance industry is concerned, it is believed that generative AI will not kick every creative worker out of their job, but it will change how they do their jobs and where their time and energy will be focused. .

Here’s what generative AI can and can’t do, and how it will impact the way we work:

What is generative AI?

Generative AI is essentially a very, very advanced form of predictive text. Generative AI allows users to insert text prompts and get a piece of art, a blog post, or a sarcastic response to a question.

But how does it generate this information? Has it become smart? Does it have an algorithm that responds to any worldly input?

Advanced artificial intelligence models have digested hundreds of billions of words. Today, they can predict the most likely combinations of words and phrases. This allows generative AI to suggest words you might want to type next. While you can ask generative AI to tell us a joke, it can only respond using the data set it has processed. Therefore, although the AI ​​robot seems to understand the instructions, it is not actually comparable to "understanding". It's more like a well-designed autocompletion.

For example, if you ask a generative artificial intelligence robot and give it the prompt 2 2=, it will respond with "2 2=4". But that's not because it has an internal algorithm, like a calculator, that handles your requests. It just deduced from the entire internet that the most likely answer to 2 2 is indeed 4. In this case, this is also factually correct.

In other words, an excellent auto-completion function can be very efficient. It basically takes our unstructured thoughts, notes and drawings and produces something beautiful. A rough brainstorm can become a first draft of an article. While these results may be great, they are not the final product and should not be considered finished products.

Will generative artificial intelligence change the way work is done?

In short, yes, but it may be subject to natural limitations.

The first step in integrating artificial intelligence into the workplace is understanding its limitations. After acquiring billions of data points, AI has the theoretical intelligence of an adult but the realistic judgment of a two-year-old. This means that it's great at following directions, but has a hard time knowing when or if it's correct.

Take a simple task, list key points on a topic and write a blog post. Generative AI can do this very well. But it doesn’t know who its readers are or what buzzwords will keep them glued to it.

I don’t even know what blog posts I have written before, nor what subtle differences caused the performance improvement. It also doesn’t know when to do something completely new because what it’s doing now simply isn’t producing results. Everything it knows is learned from what others have written online.

This lack of context goes even further. While AI can look and sound human, it doesn't actually know what world we live in. For example, Generative Pretrained Transformer 3, or GPT-3 for short, is a generative AI model that uses deep learning to generate human-like text. But GPT-3 was trained on an Internet index from 2016. Ask it who the president of the United States is and it will tell you it’s Donald Trump. If you ask it to reference pop culture, it's likely to become outdated. It will perform the task blindly, but may spit out responses that are simply incorrect.

When this type of misinformation appears authoritative and well put together, it has the potential to cause massive damage within large enterprises whose assets are often in Circulated without context.

Because of this, generative AI can now only be trusted for very clearly defined activities. And, only use a powerful custom framework to guide it and review anything before deploying it. That’s not to say this technology won’t be a game changer. But if you’re a CEO hoping that AI will replace the thinking of your best employees, that’s unlikely to happen anytime soon.

How to use generative ai?

I believe that artificial intelligence will not replace most jobs in the short term. But by taking on less mentally demanding but time-consuming tasks, it frees up workers to do things that AI can’t do and require advanced human insight, empathy and critical thinking. Here are three examples:

1. Write faster

Generative AI can speed up the writing process from article to website copy. We can write down some bullet points on the core message and run it through a copy-like program and get two-thirds of the way there in a matter of seconds. It may take a few rounds of review and editing later, but it can still save time. This means more time can be spent digging deeper into stories, analyzing which topics generate interest, and meeting people in person.

2. Improve customer service

Customer-facing roles also have multiple uses for generating AI. Employees can get the text of any conversation, and AI can quickly filter out useless details in conversations.

3. Quickly launch product mockups

Product designers can use generative artificial intelligence to create basic creative visual mockups without spending hours in front of a computer. By building basic scaffolding in the early stages, the technology can give workers more time to creatively explore with clients before feedback and revisions are made.

When you see these three examples, what do they have in common? Well, all of these very useful tasks still assume that one is designing the work to be done. Because AI still hasn’t created an original idea. What this brings, by contrast, is a deeper relationship with the customer and converting that into clearly defined units of work that AI can help execute.

This is the true value of generative AI in the workplace, removing time-consuming tasks that don’t require employees’ brainpower, freeing up time to handle all the “non-automatable” things, and interact with potential customers Interact, find out what motivates them, brainstorm about their individual needs, adapt the product to meet their goals, and learn from examples.

I believe every workplace needs to clear up misconceptions about generative AI so we can capture its power and not use it irresponsibly thinking it will replace those Advanced tasks. It won’t replace humans, but it will revolutionize the future of work and free up people’s precious time to do the work that really matters.

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