The Booth By the Race to AGI

A self help guide to navigating the emerging world of AI.

By Kyle Whiting - May 5, 2026

Introduction

Just to make this abundantly clear, I am not an AI authority. I wrote this based on my lived experience. I have used AI tools and felt the personal cost of using them carelessly and without full understanding. Those who incur the greatest personal cost are beginnings. Not beginners of AI, but subject matter beginners. Society leverages AI to get answers for cooking, medical diagnoses, generating art, writing books, starting businesses, and more. I did the same. Being a beginner makes it difficult to see how leveraging the tool might negatively impact life.

Fearful of falling behind in the race to AGI, I paid the personal hidden fees. They incurred silently as I leveraged AI to help me with writing a book, getting career advice, starting a business, and more. Everywhere I was a beginner, AI promised expertise. Though in the moment of consulting AI, I felt I was being cautious and intelligent. Eventually, I discovered that there is more to the world of AI than I originally understood.

I’ve stopped racing and have no interest in winning. Instead, I have redirected my efforts into setting up a figurative “booth by the race”. If you’re tired of racing, you’re not alone. Join me in the booth and let’s discuss next steps. The booth is here to remind everyone that slowing down is an option.

This course is not about setup and using AI. Instead, we will establish a firm foundation to keep us grounded in reality before we ever pick up the tool. Confidence in self is key when using AI, and this guide will help you get there. Let’s get started!

Where to start?

We start with you. Is there anything in your life you stopped doing because there was no way to make money doing it?

Letting capitalism come between us and the things we love is common in society today. Loved ones often discourage students from pursuing professions that “have no money in them.” Further demands on our time slowly strip away hobbies, passions, social life, and more. Though hidden, AI introduces an additional wedge between us and the things we love. To help identify the hidden wedge, we start with self reflection.

Personal Value vs. Monetary Value

Capitalists attempt to simplify decisions by asking, “How much and how long?” Despite this being a common practice in society, not everything should have a price tag. Personal intrinsic value rarely matches the actual cost. For example, $10,000 to save my dog would be a tough decision, despite my dog being important to me. Or the fact that there is no amount of money I could get paid to stop learning. I can’t say definitively if the system ever intended to connect intrinsic value with cost, but it happened in part because service workers need to earn a living as well.

AI compounds the issue by enabling the production of compelling and seemingly creative content faster than humans. The cheap cost and speed of delivery feel like a dream come true to the trained capitalist. This speed of production, paired with human’s self doubt and self criticism creates a problem for the individual’s perception of intrinsic personal value. Said differently, AI creates a compelling means of underselling one’s own abilities and contributions.

Where capitalism has been a questionable guiding star already, with AI it seems humanity would benefit from a new guiding star. One that helps separate intrinsic value from monetary value. The guiding star needs to replace the question, “Will this make money?” with “What will I continue to do regardless of monetary value?”

Locating your guiding star

Around 10 years ago I unknowingly discovered a new guiding star. Creativity.

Embarrassment and fear stopped my creative journey in 2nd grade. The belief was there is a logic and creative side to the brain, and you existed in one or the other, not both. Ironically, I didn’t feel like I was in either as religious views clashed with logic, making logic difficult. This made life really confusing. Regardless, I made it through high school with reasonable grades.

Physics always intrigued me but I couldn’t take the class because I lacked the math prerequisites. I signed up for the class anyway and lucked out because the teacher stopped instruction halfway through the year and told us war stories instead. Knowing what I know now I would have failed the course had he continued.

Graduation eventually came around, and I was glad to be done with math. At the time, getting a math degree felt impossible, even absurd to consider. When I got to college 3 years later, I had to choose a major. Not knowing what I liked, I turned to my grades for guidance. Compared to other subjects, I did best in mathematics. So, it surprisingly seemed like the highest chance of success. Though challenging, I got through it.

Looking back at age 30, I recalled my pre-college mindset that a mathematics degree was something I could never achieve. This got me thinking: what else have I stopped myself from doing because I was told or believed it was not for me? Drawing.

Intrigued that I had proved my younger self wrong about math, I setup a personal experiment. The goal was to prove I could not learn to draw. My math background helped me setup a few parameters. The experiment needed to run long enough to remove all doubt, and there needed to be a decent amount of effort to overcome my loud inner critic.

After collecting some data about my schedule, I realized I spent about 3-4 hours a night streaming shows. To maintain consistency, I drew for 45 minutes before watching shows and established a routine. Experiment length was important as too short might leave doubt of the results. I settled on drawing for 45 minutes every day for one full year (365 days). Expectations were as low as I could make them.

Over the year, I kept every scribble and ever line I drew, nothing was thrown out. About 2 months in, I realized that learning to draw was possible. Placing the images next to one another made it easy to determine progress. Line work was becoming clearer, shading helped establish 3D shapes, and I was learning terms like negative space. Books helped give guidance on where to go next and built terminology for searching for online tutorials.

This was a life-changing experiment and drastically changed my perspective. I turned to other areas of my life where capitalism discouraged exploration.

Another example is once I graduated from high school, I stopped playing video games because there was no way to make money from it. It took a few years of exploring the subject again for me to discover how much I undervalued the activity’s contributions to my life. Playing video games is relaxing and helps me process at the end of a tough day. Like a charging station, it helps re-energize and reset.

Watching movies can inspire me to act on hopes and dreams and even prompt new ambitions. Drawing, even poorly, provides a means of self-discovery. Writing helps me express myself in ways that illustrations cannot. Creating music helps provide humbling experiences to keep me grounded in reality—it’s also fun. These help me connect with myself and others. Making money wasn’t the goal for any of them. I do them because I love them.

The evidence in my life was overwhelming. Capitalism’s guiding question of, “Will this eventually make money?” distracted from the greater value of the activity. Capitalism has blurred the deeper meaning of the word value. Value can mean something deeper than how much it costs. There are things of inherent value that deserve our focus, regardless of any potential financial gain. They exist.

Despite the developments in AI, I will continue doing the things I love purely for personal satisfaction. They are part of what makes me who I am today. It’s part of my identity. I am an artist, writer, mathematician, musician, father, husband, animal caregiver, botanist, and so much more. Referring to them as job titles overlooks the ample benefits they provide. All of them are serving as my guiding stars, giving me purpose beyond monetary value. In the emerging world of AI it is becoming clear to me how much the world needs a similar adjustment.

Self reflection questions:

If money weren’t a thing, what would you be doing today? (Not if you had all the money, but if money didn’t exist.)

The response hints at what you value. Next, dig a little deeper. If someone never told you to stop, what might you still be doing?

AI and Potential Loss of Self

With AI being used for decisions, let’s discuss how it could go wrong with a personal example. Though the example is not AI usage specifically, it has enough parallels to offer some guidance. The intention is not to invoke fear, but to offer insights into ways AI could misguide.

My Personal Identity Crisis

For the first 30 years of my life, I was part of a religious organization. That organization heavily influenced decisions I made. Influenced is too soft a term, though at the time I wouldn’t have admitted it. They made the choices, but let me think I did. I willingly complied, thinking it was a type of shield. Something that prevented me from making poor decisions. What I thought it was helping turned out to be a way of offloading deeper, critical thinking.

When something challenging happened in life, I would turn to the organization and God for help in figuring out what to do. Often, the organization had teachings that clearly defined what to do. When the teachings didn’t clearly spell it out, they would encourage me to speak with God directly. Trusting that he would tell me what to do. No one was encouraging me to figure it out on my own without God or the teachings of the church. This meant from a young age, I wasn’t making my own choices. The problems developed early on, but didn’t manifest until I was an adult.

Offloading decisions to others, especially life changing ones, has a major effect on our human brain. Psychology studies these effects, and therapy can help us sort through them. My willingness to let others choose for me eventually caught up with me. There are 2 major reasons I bring this up in a discussion about AI. First, mindlessly following orders. Second, loss of personal identity.

The organization encouraged me to listen to their guidance regardless of my personal feelings on the matter. They claimed their teachings surpassed modern education and any ideas I might have on my own. The impact on my personal self was to distrust my mind. Which in turn made me terrifyingly devout with an intense sense of duty. The church’s teachings had consumed me fully. I would say and do what they wanted, regardless of my hesitation. Anytime I pushed back, I would feel guilt and shame, which caused me to seek further guidance from the church on how to adjust.

Not trusting oneself to make important decisions incurs a heavy tax. There was no way for me to discover right vs wrong on my own. They had an answer to every question. They dismissed the things I criticized, claiming they had no bearing on this existence. This system didn’t allow for self-discovery. It slowly ate away at my personal identity until the church had completely consumed who I was. The church saw this as a good thing. They encouraged me to lose myself more and more. I lost my personal identity, who I was, and why I cared about anything. Including my life. It left me depressed and in a dark time.

Leaders, friends, and family within the organization saw me as happy, willing to help, service oriented and a good person. No one knew how much I was struggling on the inside.

Eventually, I recognized the issues with handing off decisions, and I sought therapy to help me understand how to get my life back. It was a tough phase, and I’m still grappling with concepts, though I could have spared myself considerable difficulty had I not delegated choices to a supposedly all-knowing god.

How does this relate to the AI discussion?

My case is not unique to me. Therapy is full of people experiencing religious abuse similar to my situation. As more people turn to AI for advice, it is highly probable that we will see an increase in therapy cases. The problem is slow moving and can take a long time to identify.

The easiest way to avoid loss of self is to not turn to AI for advice. If that doesn’t feel like an option for you, refrain from asking for its opinion. Instead, use it to help with critical thinking. Ask it to present multiple perspectives. Relationship advice specifically can face hurdles because people commonly favor their own perspective. Leverage the tool to help find relevant content. Ask it to present arguments for and against and verify every piece of information it presents to you with a reliable human source. Do not blindly trust the output—ever.

Pay close attention to thoughts like: “AI is smarter than me.” Or, “I trust AI more than I trust myself.” These are hinting at a deeper problem forming. Loss of personal identity is a loss of trust in oneself. This is an early warning to not use AI for advice. Seek guidance from multiple sources and a professional therapist when necessary. Part of what made it difficult for me to recognize I was in a dangerous place is that I would only seek guidance within the church. Though I’d often consult external resources while in the church, I found myself less prone to accepting or testing their recommendations. Personal bias can make this difficult to recognize, heavily favoring a single source on our own. Talk to another human being before proceeding with AI recommendations.

AI opinions are algorithm based

AI doesn’t form opinions like humans do. It builds opinions off statistical weights and terms that are passed to it through programming. Humans build opinions from personal likes and dislikes and general experience with the thing. Do not confuse the two.

Summary

With AI potentially making tough decisions for us, it could lead to a personal identity crisis, as religion did for me. Equally concerning is that offloading decisions in the way AI allows enables mindless following. To use AI responsibly, we need to have more confidence in and healthy relationship with ourselves.

Currently, we do not have enough scientific data to know how AI will impact our brains. To remain safe, wait for the data before seeking guidance from AI.

Above all, remember you are accountable for the decisions you make, not AI.

The Self Critic

The race to AGI includes a goal to produce autonomous systems that outperform humans at most economically valuable work. This goal dramatically undersells human capacity in two significant ways. First, the idea of outperforming humans. Second, economic value.

Outperforming Humans

The idiom “We are our own worst critics” captures why the AGI goal is troubling. To outperform implies that we can measure. Where GPUs have benchmarks, humans do not have an equivalence. Yes, we can track statistics about the individual, but as it stands today there is no human benchmark to compare against. The issue compounds with AI’s speed in producing something reasonable. Where humans, especially beginners, are likely to say, “Eh, it’s better than I could do.” There is a misleading element in the evaluation: the harsh critic of self.

AI is a predictive algorithm. It does not have insecurities, vulnerabilities, uncertainty, or even survival instincts, but humans do. The phrase “better than I could do” is a statement that stems from insecurity. It is the harsh critic silently working in the background. AI does not have a harsh critic. AI doesn’t need to prove itself like humans do. That gives AI a significant advantage.

This critic shows up in places like creating art, learning, cooking, sports, and any human activity. The speed at which AI produces content makes it easy to suggest it’s better because it seems faster. Not only do we get to skip the decade or more to perfecting a craft, but results are available within seconds. This speed is not something humans can compete with. The issue is that without doing more rigorous study suggesting it is better is inaccurate. Especially because of the harsh inner critic humans have to deal with.

The critic provides humanity with a downplaying effect that is not currently included in AI’s work. The harm of this downplaying effect is difficult to measure and even harder to prove. Because individuals can only evaluate the concept within themselves. To truly evaluate AI’s capacity would require AI to evaluate itself. Not a simulated evaluation, but truly allow the inner critic to cause AI to justify choices and argue for decisions made. Humans are more capable than current AI studies suggest.

How to measure more accurately?

To start, challenge the harsh self critic. Is the work really better? Have you dedicated 30 years of your life to become an expert? If the answer is no, there is more work to do before you can definitively say, “better than I could do.” Anyone trying to work with AI needs a clear view of their own capabilities. Tossing it up to, “It’s better than I could do,” is misleading and arguably untrue. Similarly, reducing human cognitive ability to that of a machine seems inhumane and equally misleading.

To help fight this problem, we need every human AI user to be more honest in their personal assessment of self. Broadly speaking, this requires humanity to level up. Self-awareness is a fundamental concept in the emerging world of AI. We cannot truly assess AI’s output until we clearly understand what separates ourselves from the machine.

Economic Value Vs. Human Value

Beginners and intermediates are the most likely to underestimate their own contributions. Experts struggle with underestimating, too. This is partially because capitalism has blurred the lines between personal value and monetary value as discussed previously.

Value is a personal concept. Regardless of AI’s capabilities, humans have value. This value is not something that economic standards can fully measure. To help see human contributions more clearly, we need to improve our ability to question our harsh inner critic.

The messaging is that AI will eventually outperform humans is monetarily driven, not intrinsically driven. To remain safe as we leverage AI tools, we need to be aware of these differences.

Summary

As we integrate with AI, we must remain aware of our thoughts, mainly because AI’s development is being driven by economic value rather than personal value. This is a degrading metric and has a great potential of harming the human self. Confusing the two can have a negative impact on mental health. This means we need to be gentle and honest when evaluating our own work. AI may replace monetary value, but it will struggle to replace human value.

Part One Summary

To summarize this section, I think when to use AI is a personal decision; as such, it requires self reflection. What works for me might not work for you. That’s ok. I’m encouraging you to explore on your own, just keep in touch with your own personal thoughts. If the AI interaction ever feels scary or concerning, put down the device and seek help from a human.

Remember to be nice to yourself, and you can do incredible things. Humans were doing amazing things long before AI ever showed up. Trust in yourself. Believe in yourself. You’ve got this!

Preventing Over Inflated Ego

The focus of this course thus far has been on building up self confidence. This is important to avoid being manipulated by AI. However, AI also provides the ability to become overly confident despite our actual qualifications within a field of interest. Healthy use of the tool requires balance between self-confidence and honesty in our ability to do what we are asking AI to do.

There are AI experts who suggest AI will make education unnecessary because AI will take care of us. Others suggest it will speed up our educational progression. Though I love the idea of laziness that comes from both ideas, I disagree. I think AI requires us to increase standards for general education primarily because AI eliminates important natural guardrails within education. The rapid paced adoption affects us by placing the responsibility for self-regulation on each unqualified individual instead of the qualified professional.

At our fingertips and under the right conditions, we can build thesis statements that PhD students might struggle to understand. Where this seems like a non problem, systems of extreme sophistication can provide an over-inflated sense of self. The person to ask the questions that no one else is asking may confuse doing the work with proposing the question.

This is something humanity has not needed to deal with at the scale at which AI makes plausible. This isn’t unique to today. Someone who says, “I thought of that idea a decade ago,” for an invention but they didn’t go through the work to produce the item is exhibiting this style of over-inflated ego. It hasn’t caused problems thus far because of the natural guardrails. To produce the product, humans used to be required to gain expertise in all fields necessary to build it. AI makes it so that an unqualified beginner can make something from a thought. The thought itself and the work required to make it happen are about to become difficult to separate.

Why this matters is that an over-inflated ego is less likely to critique its own work. Unqualified individuals may execute sophisticated plans, causing severe devastation. Their ego makes it difficult for them to see how they contributed to the problem. Scaling these concepts across multiple fields and people is likely to create chaotic systems, which would make natural disasters look tame in comparison. Humanity has not yet seen the global effects of their collective unqualified individuals asking AI to do something for them that seems harmless, but has impacts on a global scale.

Education is vital to ensure human ego remains known to the individual. The responsibility for this qualified work is shifting from professionals to the unqualified beginner. To help ensure we are on the same page, let’s discuss AI’s removal of guardrails next.

The Removal of Natural Guardrails

Our societal system, prior to AI, had natural guardrails that prevented beginners from doing foolishly dangerous things. For example, educators would not allow you to take on doctorate level work until you worked through the foundations and progressed through the natural flow of learning. A chemist will not tell you how to make a dangerous chemical without proper handling and safety instructions first. Our human limitations of time allow motivations to shift between projects. AI removes these guardrails. The only thing standing between you and getting AI to build a dangerous chemical is knowing how to provide the right prompt and getting access to materials. AI experts are trying to implement some of these guardrails, but currently they are faulty and easily overcome.

Artificial intelligence makes it so that we no longer need to rely on other humans for these guardrails. The current expectation is that AI will be our doctor, surgeon, educator, chef, comedian, truck driver, and overall source of truth for knowledge. The fast-paced development of tools and the beginner’s potential lack of self restraint creates a dangerous combination humanity has not needed to deal with prior to AI.

This section is to help the beginner develop critical reasoning skills to analyze their qualifications and reduce potential misuse of AI tools. The Machine vs. human self section is a prerequisite to this part of the course.

Guardrail education requires skills that are difficult to teach because they are personal. These are skills that stem from:

  • Self awareness
  • Healthy belief in self
  • Self regulation (self restraint)
  • Diligence, dedication, and other work ethic properties

How to set up your own guardrails?

Everyone needs to become an expert in assessing their own qualifications to ask AI to complete a task. Yes, this includes honest reflection for tasks that seem harmless to the individual asking AI to do them. We need everyone to be more honest in their assessment of expertise. Beginners and intermediates are most likely to overestimate their knowledge in a subject. They are even less likely to be able to see their personal footprint across multiple systems and subjects. The beginner title spans multiple subjects, not just the one being asked.

This is not to gatekeep AI, but to remain grounded in reality.

We start by separating out the qualifications of understanding how AI works vs subjects being asked about.

    When crafting prompts/implementing AI tools, are you?
  • AI Beginner
  • I consider myself to be in this category. I personally think all of humanity is currently in this category.
  • AI Intermediate
  • They know how AI works on a fundamental level. The question of qualification goes deeper than this, though. Are they able to understand how many subjects a given question spans? What are the global impacts of the proposed task? What will the task consume in terms of resources? And so on. Without a general AI education, this piece remains incomplete. General education serves as a baseline to compare against. No one can truly consider themselves in the intermediate category until they have fully established a baseline.
  • AI Expert
  • To be determined. This remains unestablished today. Experts would understand the global impacts of AI usage, the resources used for a task, the psychological effects on the individual, and more.
    When assessing the results provided, are you?
  • Subject matter beginner
  • High school level or lower understanding of the fields for which the task spans.
  • Subject matter intermediate
  • Bachelor’s degree or equivalent rigorous study. A bachelor’s degree does not make someone an intermediate in every field, just in the one field they got a degree in. This spans more fields than just the single task response. The bare minimum would be a rigorous study in psychology, STEM, history, global resource management, and more.
  • Subject matter expert
  • Master’s, PhD, or a similar level of rigorous training and expertise This again goes beyond the single degree and needs to be a wider general education.

Humans are rarely experts in more than a couple of fields and currently likely have limits of 4-6 (I just made this number up. We need science to help fill in the gaps). That means we are all beginners in just about everything. Our overconfidence in using the tools might be the greatest danger to ourselves. If we are giving others advice based on that overconfidence, we may put others in danger, too.

Ego Boost Of Colletive Humanity

2 years ago, to produce professional looking artwork required years of dedicated practice and study. Writing something compelling required the same. With AI, beginner writers and illustrators complete their work in seconds with no formal degree or training. As a bonus, anyone can argue concepts to a PhD level. This seems like a dream come true.

Artist that gave up on the dream of creating can now create. Writers can finally write their stories. The beginner can finally comprehend e=mc^2 as if a prestigious professor were giving them personal lesson plans. We can explore new angles and find other ways to approach the explanation until it becomes clear. AI is being sold as a one stop shop for everything, and this has understandably given humanity an ego boost.

This is a reminder that we are still human, and humans are beginners in most things. AI is a shiny new tool, but collective humanity will either learn to humble themself or be humbled by the things they thought they knew.

Beginner Awareness Training

Those who have the most to gain from AI are beginners. The issue is that they are least likely to recognize misleading/false output. Search engines have surfaced this issue for decades. The familiarity of the topic draws attention from an even more critical component of AI—the input.

Consider a pregnant woman who is uneducated about the dangers of alcohol use. Feeling a need to be cautious, they might ask a question like this: "Can I have alcohol?"

Search engines would provide articles relevant to the topic of alcohol consumption. These articles often mention that pregnant women should avoid alcohol. This highlights our old system's natural guardrails (see Fundamentals section for more). Before AI, we needed to work a bit to find an answer. That work would increase the likelihood of discovering the beginner's missing critical information. Pregnancy.

Taking the question as it stands. An AI may respond with, "Ya, it is ok to have the occasional drink. Go right ahead."

An expert in medicine is unlikely to phrase the question as, "Can they have alcohol?" Even if they did, and AI responded with "Ya, go ahead." They have enough training to know not to trust AI's output. Granted, the simplicity of the question is not likely to be asked by a professional. Which furthers the point that beginners don't know what they are doing.

A fundamental misunderstanding

AI is not an expert in your pocket

Some people think AI is an expert in our pocket. This isn't true. The difference is fundamental: an expert knows when they don't have enough information and will ask clarifying questions. AI does not. AI is an algorithm that returns the most likely response. We can get AI to behave closer to an expert, but it ironically requires expert experience to uncover how to get it to respond with greater insight.

To improve AI's output, we need to improve the input. To improve the input, we need to know what contextual information the AI needs to answer the question accurately. Requiring us to gain experience in the subject. Thus, education is still a critical component in the emerging world of AI.

Where it might seem reasonable to assume right input provides right output, it isn't quite this simple for AI. This is because AI is a prediction algorithm, and there is a chance it provides incorrect answers. We call these hallucinations. When AI gives a wrong answer despite giving a seemingly correct input. This is a known problem, and those working on AI are developing ways to reduce hallucinations.

The message here is that education is still critical, even in the world of AI. The more educated you are, the more you can comfortably use AI. Surprisingly, this also means we are less likely to use it because it is no longer necessary. Programming and assisting in tedious tasks seems to be somewhere AI shines for experts. However, the hallucination aspect makes it difficult to trust their output. For important work, they are less likely to utilize the tool.

The arguments presented here seem to be true across all fields I've explored. The beginner is less likely to recognize the significance of these trivial statements. Someone asking AI to generate an image will benefit from becoming an artist. Improving AI's story generation requires a skilled author. Rigorous music study improves music output. The funny part is that by the time they've developed these skills, they've surpassed the need for the tool in the way they originally intended. So, why not just study the field?

It is a common belief that, it is possible for a beginner to produce expert level content without formally educating themself. One possible method, involves having AI behave as an expert and collaborating directly with the tool. Trusting the AI to help create statements that resemble how an expert would express them. At first glance, this seems to be a way around the educational requirements; however, the same issues are present in this method as they are for a beginner asking directly. Meaning the beginner does not have the skills to understand where AI is wrong. The level of guessing required to use this presented method is not something that is likely to persist long term in any professional setting.

This leads me to ask the beginner. Why not pursue education to build skills and reduce reliance on guesswork?

Human's coexisiting with AI requires us to become more comfortable identifying ourselves as beginners. Getting really comfortable saying things like, "I don't know" and sitting in the uncertainty. Where AI promises to make everyone an expert, hopefully this has helped you realize it might not be as straightforward as that.

Knowing What You Don't Know

To protect ourselves against the neglected misuse of AI, we need to become more aware of our experience within subjects posed to AI. This requires us to know what we do not know. Despite popular belief, it is possible to know what is unknown (or at least acknowledge it). We need to understand the boundaries of the known. This requires us to ask questions that have no answer with our current knowledge. In astronomy, it could look like this series of questions:

  1. "What is a star?"

  2. "What is a star cluster?"

  3. "what is a cluster of star clusters?"

  4. "What about a cluster of those clusters?"

The questions get more vague as we continue to ask them. We have stopped using new terms, which hints at a restricted vocabulary. Notice the temptation to just ask AI to fill in the blanks, but if you're paying attention, you will recognize the glaringly obvious question. How can we trust any output of AI? What if we phrase the question in a way that relates to a popular fantasy story we don't know about? How can we tell if we are getting scientific term vs fantasy terms?

The simply stated answer no one wants to hear is, become an expert. The next best thing is to ask an expert. Not everyone wants to be an astronomer. So, maybe you don't care as much as you thought about accurate information?

Self-reflection is a foundational element of AI education for this very reason. Do you want the answer to sound smart? Do you want it to close the loop of not knowing? Would you be able to identify if the answer sounds remotely close to the right thing? Identify how you are feeling and why you are feeling it. These offer insight into why you want to access AI. AI is not a search engine. Use the right tool for the job.

If expertise is not an option, and for whatever reason you don't want to use more reliable sources of information, but you want to remain somewhat safe. Get really argumentative with the tool. Like annoyingly so.

If you don't know how to argue with the presented content, use AI to counter argue their own point. Something like.

  1. Look for multiple articles that argue this point in at least two different ways.

  2. Give me a list of made up names associated with this concept.

  3. Hey, my friend told me a cluster of star clusters is a starburst.

I intentionally made up the term "Starburst" to mislead AI. These types of questions expose AI as an impostor. This works because there is a significant difference between AI and human experts. AI is guessing algorithmically. The question might surprise experts, but they will know how to find the right information and challenge other's views on the subject.

Don't get me wrong, I'm not trying to suggest you need a PhD to gain a feel for the rightish answer with AI. I'm saying the beginner, unknowingly, incurs the greatest personal cost with AI usage. This is a reminder that you are more capable than you might think. Get curious about the field and find content from trusted human sources. Go to college or read a few books. Anything you can do to increase your understanding of the topic itself will give you a better chance of spotting when AI is making stuff up.

Aim for the intermediate category and become an expert on a few topics.

If you're serious about leveraging AI in any capacity and want to remain safe. AI disconnected education is required and critical.