My takeaways from GoodFellows’ “Deep Thoughts”

It was great watching this conversation on GoodFellows and I took away two main things from it. The first was how a solid work ethic of diligence and loyalty to the company and co-workers would triumph over any changes or deterioration in work environments and the second was that AI-generated content was actually similar to the basic sets of information anyone would need to have in order to function well as a desirable citizen.

From about 6:03 to about 7:14 in the original conversation. How much does the work environment, i.e., in-person, offline, hybrid, etc, affect productivity levels, personal fulfillment levels at the workplace? As always, my take is that the more important factors determining whether or not workplace productivity is high are whether workers are diligent and committed to making the company and their co-workers succeed, how loyal they are to the company and how committed they are to fulfilling their part of the covenant made with the company and all stakeholders. Technological and “ergonomic” improvements help, of course, but those are neutral and can increase the levels of commitment, trust, etc, or accelerate the downward plunge into “make-work”. The portion referred to is immediately below.


From about 24:10 to about 26:22, there is some discussion about how AI-generated content would affect academia and indeed, probably many other fields like economics and so forth. The concern here is with how much “original thinking” there would be, since any one or any student could simply deliver a prompt to the AI setup and have the AI write a rather good essay for him to submit. The same could be said for legal papers, legal judgments and pronouncements, government policy formulation, restaurant reviews and so forth. These are also mentioned in other portions of the conversation. The portion referred to is immediately below.


Continuing with my thoughts on AI being used to generate what was supposed to be “one’s own work”, my take is that should not AI-generated essays or papers or proposals or policy formulations, etc, be akin to a basic storehouse of knowledge that we would want eight-year-olds to have even as they start becoming wiser via using whatever knowledge they have coupled with parent-guided interactions with the world? One can be functionally literate and numerate but still lack wisdom to be valued as a citizen. In other words, whatever one’s output ought to shimmer with how much one has internalized the information which has been imparted, digested, assimilated and then manifested in thought, word and deed. In other words, one is not simply parroting or quoting erroneously the words and the work of another, but displaying genuine understanding and skillful application to various situations. Uncommon Knowledge’s Peter Robinson did say that although all President Reagan’s speeches were written by speechwriters and that President Reagan almost never changed any parts of the speeches written by the speechwriters, they were nevertheless HIS speeches when he delivered them. In other words, when President Reagan looked at what the speechwriters delivered, it resonated with what was already in him and the scripts simply acted as memory joggers or guideposts to keep him on track. There are a few videos on that “Tear down this wall speech”, one of which can be found here:

Another example of how one can take even an AI-compiled essay or similar piece of work and make it one’s own is how “Behavioural Profiles” like DISC or others can be generated even a few decades ago by any IT system suitably programmed to do so. Persons undergoing a DISC profiling assessment would simply type in responses to “forced-choice” statements and a 24-page report would be generated instantly. Participants reading their reports have always, or at least usually, agreed with whatever report was given. This was because the reports were generated based on thousands, probably millions, of reports generated globally and the system was programmed to synthesize basic behavioural style summaries and even generate generic case-study-like examples of how each participant would respond in any given situation. Of course, for best results, a good coach would be able to help participants realize more clearly what they would need to do to enhance “strengths” and mitigate towards ameliorating “weaknesses”.

That’s what came to me when I was watching the video. Do help yourself to it here:

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