Generative artificial intelligence is the new favorite of Silicon Valley. But what is it really? And what does it mean for you and me in the future of work? Experts believe that generative artificial intelligence will soon enter the workplace, predicting that by 2023, generative AI will be able to combine scientific papers and visual design models. Combined, by 2030 it will write, design and code better than human professionals in the field.
However, few of us have a clear idea of how this is going to play out. How will it all start? 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 work, but it will change the way they do their work and where their time and energy will be focused.
Here’s what generative AI can and cannot do, and how it will affect the way we work:
What is Generative Artificial Intelligence?
Generative AI is essentially a very, very advanced form of predictive text. Generative AI allows users to plug in 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? Is it getting smart? Does it have an algorithm to respond to any worldly input?
Advanced AI models have digested hundreds of billions of words. Today, they can predict the most likely combinations of words and phrases. This allows the generative AI to suggest words you might want to type next. While you can ask a generative AI to tell us a joke, it can only respond using the data sets it has processed. Therefore, although AI robots seem to understand instructions, they cannot actually be compared with “understanding”. It’s more like an elaborate autocompletion.
For example, if you ask a generative AI bot, and give it the prompt 2+2=, it will respond with “2+2=4”. But it’s not because it has an internal algorithm, like a calculator, that processed your request. It just extrapolated from the entire Internet that the most likely answer to 2+2 is indeed 4. In this case, it is also factually true.
That said, a good autocompletion can be very efficient. It basically takes our unstructured thoughts, notes and drawings and produces something beautiful. A rough brainstorm can become the first draft of an article. While these results may be great, they are not final products and should not be considered finished products.
Will generative artificial intelligence change the way work is done?
In short, yes, but it may be limited by nature.
The first step in incorporating AI into the workplace is understanding its limitations. After being fed billions of data points, the AI has the theoretical intelligence of an adult but the real-world judgment of a two-year-old. That means, it’s good at following directions, but has a hard time knowing when or if it’s right.
Take the simple task of making a bullet point on a topic and then writing a blog post. Generative AI can do a great job at this. But it doesn’t know who the reader is, or which buzzwords will catch the reader’s attention.
Not to mention what blog posts have been written before, or what nuances triggered the performance improvements. It also doesn’t know when to do something completely new, because what it’s doing now simply won’t produce results. Everything it knows is learned from what other people have written online.
This lack of context weakness goes even further. While AI can look and sound like a human, it doesn’t actually know what world we live in. For example, Generative Pretrained Transformers 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 Donald Trump. If it were asked to reference pop culture, it would likely be outdated. It will perform tasks blindly, but may spit out responses that are not correct at all.
When this type of misinformation appears authoritative and well put together, it has the potential to cause great damage within large corporations whose assets often circulate without context.
Because of this, generative AI can only be trusted to undertake very clearly defined activities today. And, only use a robust custom framework to guide it and see anything before deployment. That’s not to say the technology won’t be a game-changer. But if you’re a CEO looking to AI to replace the minds of your best employees, that’s unlikely to happen anytime soon.
How to take advantage of generative AI?
I believe AI will not replace most jobs in the short term. But by taking on non-brain-intensive but time-consuming tasks, it can free up workers to do things that AI can’t do, which 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 a few bullet points on the core message and run it through a copy-like program and do it two-thirds of the way in seconds. It may take several rounds of review and editing afterwards, but it still saves time. That means more time can be spent digging deeper into stories, analyzing which topics spark interest, and meeting people.
2. Improve customer service
Customer-facing roles also have multiple uses for generating AI. Employees can get the text of any conversation, and artificial intelligence can quickly filter out useless details in the conversation.
3. Quick start product model
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 at an early stage, before feedback and revisions, the technique can give workers more time for creative exploration with clients.
When looking at 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. In contrast, what is brought is a deeper relationship with the customer and translated into well-defined units of work that AI can help execute.
This is the real value of generative AI in the workplace, removing time-consuming tasks that don’t require employees’ brainpower, freeing up time for all the “non-automatable” things, engaging with potential customers, finding out what motivates them, targeting them personally Brainstorm needs, adjust products to meet their goals, and learn from examples.
I believe every workplace needs to dispel misconceptions about generative AI so we can harness 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, giving people back precious time to do the work that really matters.
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