Generative AI as a Tool and Not a Threat
By understanding generative AI, it can become less scary
There is an inordinate amount of hype around generative artificial intelligence (AI) right now, and a lot of it is negative.
A general fear is around the potential biased outcomes that could be created by generative AI. Companies are, with greater frequency, using open-source tools to make their own AI tools and this has people, including the government, concerned about the impact these tools could have when realized into use.
The foundation of generative AI tools are large language models (LLMs). LLMs are trained on enormous data sets. The source of the data is often unclear and the reasons behind the decisions made by AI tools based on this data can also be unclear. This causes anxiety.
Another concern is around cybersecurity. In fact, we are already seeing a rise in scams and fraud attempts in the last six months that could be attributed to generative AI. These scams are also becoming more realistic because of the use of generative AI. The scams feature less of the obvious signs of a scam, such as spelling and language errors, because they were created using generative AI tools.
Sign Up For Our Articles
"*" indicates required fields
Additionally, leaders are rightfully concerned about the impact of these tools on their organizations. First, a concern is around the impact of employees using these tools. Could sensitive intellectual property be leaked if an employee inputs it into a generative AI tool? This has already reportedly happened to large companies like Samsung. If it has happened to Samsung, it has likely happened to smaller companies but has either gone unreported or unknown.
Also, there is concern that the use of a generative AI tool could cause inadvertent harm, such as discrimination because of a biased AI tool being used to assist in the hiring process.
Finally, leaders, and many others, are concerned about the impact of AI on their jobs and careers.
Much of the negative hype around AI is around AI sentience or consciousness. Are we seeing the beginning of Skynet? This is not what leaders should be worried about. They should be more concerned with how these tools will impact their jobs and careers.
As an example, those in marketing should be wondering how AI could impact their careers when entire social media campaigns can be created by an artificial intelligence tool.
At the end of the day, generative AI tools are tools, and they should serve to help leaders have more time to do things such as build relationships. You, as a leader, must look at generative AI as a tool and not as a threat. You must understand how to use AI, but also how to do so safely.
In the past, we would ask if a potential employee had Microsoft suite experience. Now that is just assumed. In the future, we are going to assume that people have proficiency using AI tools.
There should be some worry about job loss. If not job loss, falling behind those around you with your ability to use these tools to increase the productivity and quality of your output.
If you let that happen to you, you could be at risk. You should get ahead of the curve, own it, and discover how to use the tools to go beyond your normal day-to-day function. You should be a person that knows all about AI and how to use the technology to advance.
You won’t be able to get outside of it. So, understand it, as much as you can. Because the learning curve is steep, it is easy to get discouraged or overwhelmed. Start with baby steps and try out the small ways you can use AI in your career and in your personal life.
There are some simple ways you can begin navigating the new normal.
The first is developing a good RIVERS OF INFORMATION® that contains high quality content around artificial intelligence trends and tools. Reach out to Future Point of View, at info@fpov.com, and we can offer you a list of trustworthy sources around artificial intelligence that you can use to quickly improve your IQ around AI.
The second way is to get your hands around the tools. You should be looking at the tools that are available and figuring out which ones you can use.
A good place to start to understand the tools that are available is Ai Valley. The website offers a curated directory of AI resources so you can see what is out there. A lot of the tools are free.
Whatever field you are in, go use ChatGPT, if you haven’t already. Input something from your field that you understand that others outside the field may not. (But make sure it is nothing sensitive because you don’t know where the data is going!) This will give you an idea of what ChatGPT knows versus what you know. Sometimes the responses are at a college level or a master’s level, but it can help you recognize that you have to add in your own knowledge as well. It is good to understand the capabilities and limitations of tools like ChatGPT.
If you are a graphic artist, go into a text to image generator like DALL-E or MidJourney. Generate some graphics that you would normally generate. See what the tool outputs. See what the differences are versus what you might generate yourself without the tool. Understand what you like about it and what you believe you would do better.
Understand it more as a tool and less as a threat.
One final thing is that as a leader, you should be developing a generative AI policy for your organization. This will allow you to regulate how your employees use generative AI tools and get ahead of the potential of them leaking sensitive or proprietary information or a tool causing inadvertent bias or discrimination.
We have a policy that we have created which you can use as a guide to build a generative AI policy within your own organization. Reach out to us at info@fpov.com and we will share the generative AI policy with you.
Change is hard. It is often scary. Generative AI is coming so rapidly, it is easy to get overwhelmed. But don’t let it scare you. Learn about it, try personally using the tools, and prepare your organization and yourself for the AI revolution.
About the Author
Dan Shuart is the Strategy and Advising Practice Lead for FPOV. He has 35 years of proven success in technology innovation working with a broad range of companies, from Silicon Valley start-ups to Fortune 100 companies. Dan has led innovation and transformation efforts for small enterprises and multi-national companies like Exxon, Fujitsu, and Bridgestone-Firestone. Learn more about Dan Shuart.