Week 5 - Adopting AI

     



    I skipped a chapter in Todd Kelsey's Surfing the Tsunami, but the content in Chapter 4 was mostly an aggregation of fixed sources. Given that most people can perform their own research and opinion on AI, it was not necessary I cover it.

    However, Chapter 5 covers adopting AI, and this is something that I think some nuanced thoughts on might be appreciated. I do agree with Kelsey on working with AI or rather integrating AI tools into your workflow but not because it will make you irreplaceable and that you will start to play a part in managing it. Rather, because it makes you more productive as a worker and is simply easier. Consumers really have limited choice in resisting how technology moves and what companies want in their product. That is, companies often do not always do what the consumer wants or in fact the consumer does not know what they want.

    For example, at the time of writing AI is being ham-fisted into about every product imaginable partly so that they can say they are an AI company, but also because they are not quite sure of where its usefulness is best used. As a side note, machine learning is a subset of AI, and is extremely focused on extracting patterns from data for a very specific purpose. This type of AI companies has found very useful, and consumers have had no say in the development of these things because they have a very well-defined and thought-out use. However, Large Language Models, do not have a well-defined use case yet are being stuck into things like GroupMe, Microsoft's Recall, and Chegg among other things.

    This is not to say that Large Language Models are not useful at all, but that they are exceedingly good enough at multiple things and it seems companies are eager to leverage their broad capabilities without fully understanding or defining their optimal use cases. This scattershot approach can lead to mixed results—some applications may enhance user experiences, while others may feel forced or unnecessary.

    Large Language Models (LLMs), like GPT-4, excel in various tasks such as generating text, summarizing information, translating languages, and even assisting with customer service. These capabilities make them attractive to companies looking to innovate quickly. However, without a clear and strategic implementation plan, these integrations can sometimes appear superficial or fail to meet user needs effectively.

    The enthusiasm for AI and ML technologies is understandable given their potential to revolutionize industries. Yet, it's crucial for companies to invest the time in understanding where these tools can genuinely add value. For instance, while an LLM might enhance customer support by providing instant, coherent responses, its application in a platform like GroupMe might not significantly improve user interaction if the users do not need advanced language processing features. Companies might focus more on the novelty of AI rather than on developing solutions that address real problems. This can lead to a disconnect between what is technologically possible and what is practically beneficial for consumers.

    I think you should avoid the approach that companies do and use it everywhere. Strategically implement it into your life.

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