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Should We Fear Artificial Intelligence?

by Dr. Chrissann Ruehle, DBA, MBA, CPM | AI Consultant and Strategist, & Management Faculty at Florida Gulf Coast University

Artificial Intelligence (AI) has become a part of our daily lives, even if we do not always realize it.

When we shop on Amazon, choose movies on Netflix, type emails in Microsoft Outlook, select music on Alexa, or use Google Maps for directions, we are interacting with AI. These applications are called “narrow AI” because they help us accomplish specific tasks. They examine our past behaviors and those of others to provide recommendations, generally aiming to make our lives easier and more efficient. Recently, sophisticated “broad AI” applications have helped track weather and monitor pandemics globally.

To address fears about AI, it is important to understand what it is and is not. Contrary to popular belief, AI is not new. It was developed in the late 1940s and has seen ups and downs in public interest and research funding since then. When most people hear “AI,” they think of “Generative AI,” but Traditional AI is broader. Traditional AI is rule-based, excels at analyzing data, and performs well-defined tasks. Generative AI, on the other hand, relies on unstructured data like social media posts and videos to create new content like mass communications, images, video, and audio.

Common AI Applications Image generated by Microsoft Co-Pilot and Dall-E3

So, what exactly is AI? Simply put, it is a software program designed to perform functions typically done by humans, like analyzing large data sets quickly and providing recommendations. The term “intelligence” is somewhat misleading because today’s AI is not truly intelligent as we commonly understand it. AI still relies on humans to provide detailed instructions and set expectations for the desired output. It is not smart enough to make decisions requiring critical thinking, emotions, or ethical awareness. Humans remain crucial in overseeing both Traditional and Generative AI.

Many AI programs use algorithms, which are just sets of directions for accomplishing specific tasks – like following a recipe to bake cookies. AI can be thought of as an umbrella term with various subcategories underneath.

Three important ones are:

  • Machine Learning (ML): This technology uses algorithms and large training data sets to build models and analyze big data sets quickly. ML can learn and refine its model based on input and feedback. It is often used in financial services, like when applying for loans.

  • Neural Networks: These programs process information similarly to the human brain, rapidly analyzing big data sets to identify patterns.

  • Chatbots and Virtual Agents: These programs interact directly with humans, receiving input, processing questions or instructions, and providing responses. They can adapt to different personalities and communication styles.

Given AI’s prevalence in our lives, should we fear it? While AI can enhance many aspects of our daily routines by freeing us from repetitive tasks, and allowing us to focus on being creative, strategic, and ethical, there are some concerns to consider. These include potential bias in training data sets, lack of transparency in algorithms, privacy concerns with personal data, and questions about accountability for algorithm failures.

It is important to develop a balanced perspective on this technology. We should be cautiously optimistic about AI, recognizing its benefits while being aware of potential risks. As we continue to integrate AI into our lives, it is crucial to stay informed and engage in discussions about its ethical implications and responsible use.

AI is a powerful tool that is already changing how we live and work. By understanding its capabilities and limitations, we can harness its potential while mitigating risks. As with any modern technology, education and open dialogue are key to ensuring AI benefits our local community and society as a whole.

Chrissann Ruehle Professional Headshot
2024-07-19T11:26:43-04:00July 21, 2024|News|

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