A growth mindset helps you develop the skills you need to move into the future.
I was a new lawyer at a time when mergers and acquisitions were in full swing. Everywhere, companies were cannibalizing each other, capturing synergies and cutting costs. People were afraid of becoming obsolete and losing their jobs. An article was published in a women’s magazine that I will never forget. The concept, headlined “Transformation for Takeover,” was ridiculous. You may never know what’s going to happen, but if you wear the right clothes and have the right haircut, you can stand out and survive when an acquirer shows up, the article argues.
Yesterday’s M&A feels a lot like today’s AI, except the absurd articles are about robot takeovers rather than modifications. The truth is, despite the fear and hype, generative AI remains a mystery. A recent survey by McKinsey revealed that 63% of leaders feel that AI needs to play a key role in business, but 91% do not yet know how. Ta. At the same time, there is also a clear sense of crisis. Mercer reports that more than half of executives believe their businesses will disappear by his year 2030 if they don’t implement AI. Uncertainty and speed are scary bedfellows. 79% of Americans don’t trust companies to make responsible choices when it comes to implementing AI.
The majority of experts believe that AI will support, rather than replace, human performance. However, those who use AI are likely to be replaced by those who do not use AI. you have a choice. You can ignore AI until you better understand how it impacts your life. Or you can be proactive. There’s never been a better time to rely on a growth mindset to become an avid learner of this vast and fast technology. Here are five ways to build the skills you need to survive.
Get ahead of the learning curve
AI terminology is like a new language. Start by learning as much as you can. LinkedIn Learning alone has hundreds of free courses. You can also obtain certificates from online providers such as Coursera or MIT for a small investment. Knowledge is power, and with a little effort you can make your knowledge flexible.
Don’t just learn how AI works, explore where it works and where it doesn’t. Although AI holds promise, it is not without its pitfalls. For example, many companies use recruiting algorithms to find talent. Are you missing out on top talent because your algorithm is too narrow? Will it be flooded if it’s too broad? Understand how companies are successfully leveraging AI and where they stumble. Listen to podcasts and sign up for technology newsletters. Explore the philosophical and moral difficulties underlying the potential good and bad aspects of AI. Like Alice in Wonderland, embracing the rabbit hole means exploring at every turn. It’s amazing how much mastery you can become when you let your curiosity lead you.
Let’s experiment a lot
Adopting an experimental mindset is the best way to gain experience in the field. Start with non-exclusive work projects. Feed that into a larger language model like ChatGPT and ask what it adds. Encourage them to paraphrase their work for non-English speakers or rewrite it for non-experts. Because you’re experimenting with areas you already know, you can quickly assess the value of that input. You will also start looking at your work from different angles.
You don’t need to do much more to try this technology. Use AI to write a memoir in the style of your favorite author, or animate your doodles and children’s artwork. There’s a brand new platform that uses AI to turn still images into talking avatars. If you’re a history buff, you can also chat with historical figures. If creative endeavors aren’t your thing, the possibilities for experimenting with AI are endless.
Don’t accept AI at face value
Large language models can feel misleadingly expert when they communicate very human-like and produce data-rich answers in record time. But they can hallucinate, and when they lack training data, they fabricate responses based on plausible but false logic. And like humans, AI algorithms are known to rely on shortcut learning, leading to spurious correlations, amplifying discrimination, and producing unreliable results. Don’t accept AI output at face value. Challenge (their assumptions and yours) and triangulate with other research.
When I first started using ChatGPT, I looked for research-based insights along with relevant sources. Impressed by the results, I looked into the source and discovered that although the author and journal were real, the paper was not. When I asked ChatGPT where they found these sources, they said that these papers are not real, but if they were, they would be the kind of papers that should be cited. A colleague shared some great advice: “Treat the AI like his first-year intern.”
get better at asking questions
New technology creates new jobs. And AI is proving to be fertile ground. The World Economic Forum named Prompt Engineering (the art and science of asking the right questions) his #1 Job of the Future in 2023. By asking the right questions, you can learn from diverse perspectives. Using algorithms is no different. Better questions explore a wider range of possibilities and provide more output to find better solutions.
The most effective questions for humans are open-ended, curious, and personal. But when it comes to LLM, clarity is paramount. Frame the context of your research (report, strategy, job description, etc.) and the perspective you want from your LLM (specific perspective, specific profession, identity, etc.). Provide context for what you need and what you want to do with it, including examples, steps in the process, and even any reference materials you may need. Finally, describe the output in detail, including format and style. Good prompting techniques allow AI to handle the mechanical search for technical information, giving humans the freedom to access and organize a wealth of knowledge and combine new ideas even in the most technically complex situations. Allows rapid testing. When done well, this is a powerful human-machine partnership.
don’t go alone
In our eagerness to adapt, let’s not forget the superpower that makes humans more efficient than any machine: our ability to work and thrive in community. Throughout history, humans have harnessed our collective power to make sense of difficult challenges and new threats. By collaborating with others, you can experiment widely, discuss ethical implications, share results, and learn faster. And collaboration neutralizes the anxiety that comes with impending existential change. Within the organization, he expands the group of AI learners so they can participate in developing strategy rather than waiting to see where the chips fall. Build a broad and diverse learning community to collect the best and most diverse ideas. Together, you and your colleagues can be an integral part of your organization’s AI future.
Thankfully, you don’t have to transform to weather the AI storm. But that’s probably how you think. Now is not the time to wait and see. Even if it’s hard to imagine how generative AI will impact your work right now, the train is already rolling toward the tracks. Get ready now to stand out from the crowd and be ready for what’s to come. A deeper understanding of AI and its trajectory is one of the most effective job skills you can develop now and in the future. The only thing we know for sure is that AI will fundamentally change the world of work. Don’t wait for the path to clear, pave the way.
