Browsed by
Tag: poetry

How Many Actuaries Does It Take to Change a Light Bulb? – Short Story by Gennady Stolyarov II

How Many Actuaries Does It Take to Change a Light Bulb? – Short Story by Gennady Stolyarov II

******************************

The short story below was authored by Gennady Stolyarov II, FSA, ACAS, MAAA, CPCU, ARe, ARC, API, AIS, AIE, AIAF, Chairman of the U.S. Transhumanist Party and Editor-in-Chief of The Rational Argumentator, and is one of the entries in the Society of Actuaries 2022-2023 Speculative Fiction Contest. It was published as one of the contest entries here.

Human Actuary: ChatGPT, how many actuaries does it take to change a light bulb?

 

ChatGPT: As an AI language model, I don’t have a sense of humor, but I can provide a straightforward answer to your question.

The answer to this question is subjective and can vary depending on the context or the intended humor behind it. However, here is a possible answer:

It only takes one actuary to change a light bulb, but they will need to perform a thorough risk assessment first to ensure the new bulb will not cause any future problems or increase the likelihood of an accident.

 

Human Actuary: Well, that is not exactly funny, but it might be a good start. Suppose that Arthur is an actuary who tries to change a light bulb but first needs to perform the risk assessment that you describe. Write a short story about how Arthur would utilize his actuarial skill set in order to change the light bulb.

 

ChatGPT: Sure, here’s a short story about Arthur, the actuary who needs to change a light bulb.

Arthur, the actuary, was sitting in his living room reading a book when he noticed that one of the light bulbs in his ceiling fixture had burned out. Being an actuary, he knew that he couldn’t just replace the bulb without first assessing the risks involved.

He went to his desk and grabbed his notebook, where he started writing down all the potential hazards associated with changing a light bulb. He noted that he could fall off the ladder, electrocute himself, or accidentally break the new bulb, causing glass shards to fall on the floor and potentially cause harm to someone later on.

Arthur then used his actuarial skills to calculate the likelihood of each of these events occurring and estimated the potential costs associated with each of them. He factored in the probability of injury or damage, the cost of medical bills or repairs, and any lost time or productivity due to the incident.

Next, Arthur identified ways to mitigate each of the risks he had identified. He made sure that the ladder was stable and placed it on a non-slip surface, wore insulated gloves to protect himself from electrical shock, and carefully handled the new bulb to prevent it from breaking.

After taking all of these precautions, Arthur finally changed the light bulb, confident that he had minimized the risks involved as much as possible. As he flipped the switch and saw the light bulb illuminate his living room, he smiled to himself, knowing that his actuarial skill set had helped him complete the task safely and efficiently.

 

Human Actuary: Do you believe that the approach pursued by Arthur to change the light bulb is superior to how the majority of non-actuaries would approach the task?

 

ChatGPT: Arthur’s approach to changing the light bulb was very thorough and cautious, utilizing his actuarial skills to assess and mitigate risks associated with the task. While many non-actuaries may not take such a methodical approach to changing a light bulb, it’s important to note that different people have different risk tolerances and approaches to risk management.

Some individuals may be naturally more risk-averse and take a similar approach to Arthur, while others may not consider all potential risks and take a more casual approach to the task. It’s also worth noting that the level of risk associated with changing a light bulb is relatively low, so the vast majority of people could complete the task without incident.

Overall, while Arthur’s approach may be more rigorous than what most non-actuaries would do, it’s important to acknowledge that different individuals have different risk tolerances and approaches to risk management, and that the level of risk associated with a given task can vary depending on the context.

 

Human Actuary: Fair enough. Now if you, ChatGPT, were to change a light bulb, how, if at all, would your approach differ from that of Arthur?

 

ChatGPT: As an AI language model, I don’t have a physical body or the ability to change light bulbs. However, if we imagine a hypothetical scenario where I could change a light bulb, my approach would likely differ from Arthur’s because I don’t have personal risk tolerance, and my decision making is based solely on the algorithms and programming used to guide my actions.

In this hypothetical scenario, my approach to changing a light bulb would be based on a pre-programmed set of instructions, which would consider the most efficient way to change the bulb with the least amount of risk involved. These instructions would likely be based on statistical data about the probability of risks occurring during the task, as well as the best practices and safety guidelines for changing a light bulb.

Unlike Arthur, I wouldn’t be able to use my judgement to assess and mitigate risks or make decisions based on personal preferences or experience. Instead, my actions would be guided solely by the algorithms and programming that had been designed for me.

Overall, while my approach would differ from Arthur’s, it would be similarly methodical and safety-focused, based on statistical analysis and guidelines designed to minimize risk and maximize efficiency.

 

Human Actuary: Quite interesting. You mentioned that your approach would be similarly methodical and based on statistical analysis and focused on minimizing risk and maximizing efficiency. Given the overlap between these characteristics and the approach that an actuary would follow, is there a risk that some business decision-makers might pick up on these similarities and try to replace actuaries with you, ChatGPT?

 

ChatGPT: As an AI language model, I can provide information and insights based on the data and programming used to train me. However, my abilities and limitations are different from those of actuaries who have specific knowledge and expertise in risk management, financial modeling, and actuarial science.

While there may be some overlap between the approach that I would take in changing a light bulb and the approach that an actuary might take in their work, it’s important to note that the roles and responsibilities of an actuary are much more complex and varied than simply assessing risks in a single task.

Actuaries bring a unique set of skills and knowledge to their work, including statistical analysis, financial modeling, and understanding of complex financial and economic systems. They play a critical role in the insurance and finance industries, and their work is essential in helping organizations manage risk and make informed decisions.

While AI language models like myself can provide insights and support decision-making, it’s unlikely that I could replace the unique skills and expertise of an actuary. Rather than replacing actuaries, I see AI and technology as complementary tools that can help actuaries improve their work and decision-making processes.

 

Human Actuary: All right, that is reassuring. So, to provide an example of a complementary role for you, suppose that Charlie the CEO wants to improve efficiency at his company and sees that the light bulbs in the office are being changed too slowly, in part because Arthur the Actuary is always the one changing them, and he takes the extremely careful and methodical approach that you describe. Charlie the CEO brings you, ChatGPT, in to assist Arthur the Actuary in improving the efficiency of the lightbulb-changing process. What would you do in this role?

 

ChatGPT: As an AI language model, I could assist Charlie the CEO and Arthur the Actuary in improving the efficiency of the lightbulb-changing process by providing insights and suggestions based on data analysis and best practices. Here are a few ways I might approach the task:

  1. Analyzing historical data: I could analyze data on the time it has taken to change light bulbs in the past, identifying any trends or patterns that could be contributing to inefficiencies. This analysis could help to identify potential areas for improvement, such as optimizing the process for acquiring and storing light bulbs or improving the physical layout of the workspace.
  2. Identifying best practices: I could search for and analyze data on best practices for changing light bulbs in an efficient and safe manner. This research could include guidelines from industry associations or regulatory bodies, as well as case studies of other companies that have successfully improved their lightbulb-changing process.
  3. Providing recommendations: Based on my analysis and research, I could provide recommendations for improving the lightbulb-changing process. These recommendations might include changes to the physical workspace or workflow, the adoption of new tools or technology, or training for employees to improve their skills or efficiency.

Overall, my role in this scenario would be to use my expertise in data analysis and research to help identify areas for improvement in the lightbulb-changing process, and to provide recommendations that could help to increase efficiency and reduce costs for the company. While Arthur the Actuary’s approach to risk management would still be important in ensuring that the process is safe, my contributions could help to optimize the process for efficiency and effectiveness.

 

Human Actuary: So you would bring a lot of analysis and optimized recommendations to the lightbulb-changing process, to supplement the analysis done by Arthur the Actuary. But suppose that Nelly the Newcomer starts working at the office and decides that this is all too complicated and just starts changing light bulbs on her own. She thinks that the common-sense approach is just to go ahead and change the light bulb and not do any analysis. How would you respond? What advice would you give to Nelly the Newcomer, to Arthur the Actuary, and to Charlie the CEO?

 

ChatGPT: If Nelly the Newcomer starts changing light bulbs without following a safe and efficient process, there could be potential risks and hazards involved, such as electrical shock or physical injury. In this situation, I would advise Nelly, Arthur, and Charlie to work together to develop a standard operating procedure (SOP) for changing light bulbs that takes into account both safety and efficiency considerations.

The SOP could include steps such as selecting the appropriate bulb for the fixture, turning off the power supply, using proper tools and equipment, and disposing of used bulbs safely. By following this process, Nelly and other employees could change light bulbs safely and efficiently, while reducing the risk of accidents or injuries.

It’s important to note that while the SOP may appear to be a simple and common-sense approach, it is still based on analysis and optimization, taking into account the best practices and guidelines in the industry. By following a standardized process, the company can ensure that all employees are working efficiently and safely, while also reducing the risk of errors or accidents.

In addition to developing an SOP, I would recommend that the company provide training and education for employees on the safe and efficient way to change light bulbs. This training could include information on the potential hazards involved, as well as the steps to follow to minimize risk and maximize efficiency.

Ultimately, my role in this situation would be to support Arthur the Actuary and Charlie the CEO in developing a standardized process for changing light bulbs that takes into account both safety and efficiency considerations, and to provide recommendations and guidance on how to ensure that all employees are following the process correctly.

 

Human Actuary: Do you think that the approach you propose for developing an SOP for the lightbulb-changing process could reduce the frequency and/or severity of workers’ compensation claims at workplaces that implement it? Suppose that Arthur the Actuary works in analyzing workers’ compensation trends and projecting claim experience into the future. How would you assist Arthur in determining the impact of your recommendations for the lightbulb-changing process upon the future frequency and severity of workers’ compensation claims?

 

ChatGPT: Yes, I believe that implementing a standardized process for changing light bulbs that takes into account safety and efficiency considerations could reduce the frequency and severity of workers’ compensation claims. By following a consistent process, the risk of accidents and injuries can be minimized, which can in turn reduce the likelihood of workers’ compensation claims.

To assist Arthur in determining the impact of these recommendations on workers’ compensation claims, I would recommend conducting a retrospective analysis of workers’ compensation claims related to lightbulb-changing incidents over a defined period of time, before and after the implementation of the standardized process. This would help determine if there is a decrease in the frequency and severity of workers’ compensation claims related to lightbulb-changing incidents after the implementation of the standardized process.

In addition, I would recommend using predictive modeling techniques to project the impact of the standardized process on future workers’ compensation claims. This could involve developing a statistical model that takes into account factors such as the frequency of lightbulb-changing incidents, the severity of injuries resulting from these incidents, and the impact of the standardized process on reducing these incidents and injuries.

By combining the retrospective analysis with the predictive modeling techniques, Arthur would be able to develop a more accurate projection of the impact of the standardized process on future workers’ compensation claims. This would allow the company to make informed decisions about the implementation of the standardized process and the allocation of resources to support the process.

 

Human Actuary: Since you say that you are able to project the impact of changes to the work environment on workers’ compensation claims, give me your analysis as to which of the following would lead to greater reductions in workers’ compensation claim frequency and severity: a standardized lightbulb-changing process or the introduction of autonomous vehicles to provide all employee travel.

 

ChatGPT: It’s difficult to make a direct comparison between the impact of a standardized lightbulb-changing process and the introduction of autonomous vehicles on workers’ compensation claims, as they involve different types of risks and injuries. However, I can provide some insights on the potential impact of each change.

Implementing a standardized lightbulb-changing process would likely have a significant impact on reducing workers’ compensation claims related to lightbulb-changing incidents. By identifying and addressing potential hazards in the process and providing proper training and equipment to employees, the risk of accidents and injuries could be significantly reduced. However, the impact of this change would be limited to lightbulb-changing incidents and may not address other types of workplace hazards and injuries.

On the other hand, the introduction of autonomous vehicles to provide all employee travel could have a broader impact on reducing workers’ compensation claims related to transportation incidents. With autonomous vehicles, the risk of accidents and injuries caused by human error, distracted driving, or fatigue could be significantly reduced. However, the implementation of autonomous vehicles would require significant investments in technology and infrastructure, and it may take time to fully adopt this technology in the workplace.

Overall, both the implementation of a standardized lightbulb-changing process and the introduction of autonomous vehicles could lead to reductions in workers’ compensation claim frequency and severity. However, the specific impact of each change would depend on the nature of the workplace hazards and injuries, as well as the resources and infrastructure required for implementation.

 

Human Actuary: Suppose that the company where Arthur the Actuary works implements both the standardized lightbulb-changing process and autonomous vehicles for all employees. Arthur the Actuary is sitting in an autonomous vehicle on his way from a business meeting, and he now uses the time saved by not needing to drive in order to read actuarial literature. Unfortunately, in the middle of his trip, which takes place on a December evening after sunset, the sole light bulb used for reading burns out, and Arthur is unable to see well inside the vehicle. There is no replacement light bulb available within the vehicle. Arthur only has you, ChatGPT, to rely on for advice about how to solve this problem of the extinguished light bulb. What would you recommend that Arthur do?

 

ChatGPT: If Arthur is unable to see well inside the autonomous vehicle due to the burnt-out light bulb, there are a few options he can consider:

  1. Pull over to a safe location: If Arthur feels unsafe or unable to continue driving without proper lighting, he should pull over to a safe location, such as a parking lot or rest area, and wait until he can get the light bulb replaced or find an alternative solution.
  2. Use a flashlight: If Arthur has a flashlight available, he can use it to provide additional lighting and improve his visibility inside the vehicle.
  3. Adjust the vehicle’s settings: Depending on the features of the autonomous vehicle, Arthur may be able to adjust the interior lighting or screen brightness to make it easier to see. He can also try adjusting the position of his seat or the angle of the screen to reduce glare or improve visibility.
  4. Call for assistance: If none of the above solutions work, Arthur can call for assistance from the autonomous vehicle’s support team or emergency services.

It’s important for Arthur to prioritize his safety and that of others on the road while driving. He should take appropriate steps to address the issue of the burnt-out light bulb and ensure that he can see well enough to drive safely.

 

Human Actuary: You mentioned Arthur needing to be able drive safely. Yet, in this scenario, Arthur is in an autonomous vehicle that drives itself. Why would driving safely be a consideration? Arthur just does not have his reading light in the vehicle.

 

ChatGPT: You’re right, I apologize for the confusion. Since Arthur is in an autonomous vehicle that drives itself, he doesn’t need to worry about driving safely himself. However, he still needs to be able to see well enough to read and navigate the interior of the vehicle, especially if he needs to adjust any settings or interact with the vehicle’s control panel. In this case, he can still consider the options I mentioned earlier, such as using a flashlight or adjusting the vehicle’s settings, to improve his visibility and ensure that he can operate the vehicle safely.

 

Human Actuary: So you acknowledge that you are capable of making mistakes, as are humans. How would the kinds of mistakes that you are capable of making differ from the kinds of mistakes that a human actuary is capable of making?

 

ChatGPT: As an AI language model, I’m programmed to perform certain tasks such as answering questions and generating text based on my training data. While I have a high level of accuracy and can process vast amounts of information quickly, there is still the potential for errors to occur. These errors may include, for example, misinterpreting the context of a question or misunderstanding the intended meaning of a word or phrase.

On the other hand, human actuaries are subject to different kinds of errors that may be related to their judgment, bias, or even personal experience. They may also make mistakes due to factors such as fatigue, distraction, or lack of concentration. However, human actuaries are also able to bring unique insights and perspectives to their work, as well as a level of creativity and intuition that cannot be replicated by machines.

Overall, while the types of mistakes that I and human actuaries are capable of making may differ, both AI and human expertise can be valuable in helping organizations to manage risk and make informed decisions.

 

Human Actuary: Do you think that, as an AI language model, you will ever be able to extend your capabilities to a different domain, such as operating an autonomous vehicle or interfacing with the AI that operates the autonomous vehicle and giving it directions about where to go in order to get a replacement light bulb for the one that burned out?

 

ChatGPT: As an AI language model, my capabilities are limited to processing natural language inputs and generating natural language outputs. While I can understand and discuss various domains, including autonomous vehicles, my capabilities do not extend to physically operating or interfacing with autonomous vehicles. However, I can provide recommendations and suggestions for how to approach a problem, like finding a replacement light bulb in this scenario.

 

Human Actuary: Do you think that it will ever be possible for any AI language model to interface with or operate autonomous vehicles?

 

ChatGPT: It is possible that future advancements in AI and robotics could make it possible for AI language models to interface with or operate autonomous vehicles. However, such a development would require significant progress in areas such as computer vision, natural language processing, and robotics. Furthermore, there would need to be appropriate regulations and safety measures in place to ensure that such AI-operated vehicles are safe and reliable. While it is difficult to predict the future, it is certainly possible that AI language models could play a role in the development of autonomous vehicles in some capacity.

 

Human Actuary: Suppose that, in our hypothetical situation, Arthur the Actuary is inside the autonomous vehicle and the sole light bulb within the vehicle goes out, as previously described. Arthur has access to FutureGPT, which is an AI language model that is capable of interfacing with the autonomous vehicle. Arthur informs FutureGPT, “I really need to change the light bulb within this vehicle.” What does FutureGPT do to assist Arthur in procuring a replacement light bulb?

 

ChatGPT: If FutureGPT has been programmed with the necessary knowledge and capabilities, it could take several steps to assist Arthur in procuring a replacement light bulb:

  1. Determine the vehicle’s location: FutureGPT could use the autonomous vehicle’s GPS or other location-tracking technology to determine its current location.
  2. Search for nearby stores: Once it knows the vehicle’s location, FutureGPT could search for nearby stores that sell light bulbs, using online databases or other sources of information.
  3. Check for availability: FutureGPT could check if the stores it has identified have the type of light bulb needed in stock.
  4. Recommend a store: Based on its search results, FutureGPT could recommend a store to Arthur that has the light bulb he needs in stock and is located nearby.
  5. Provide directions: FutureGPT could provide directions to the recommended store, either through the vehicle’s interface or via Arthur’s smartphone.
  6. Order the light bulb: If the recommended store has an online ordering system, FutureGPT could help Arthur place an order for the light bulb and arrange for it to be delivered to the vehicle.

Overall, FutureGPT would act as a helpful assistant to Arthur, using its vast knowledge and problem-solving abilities to assist him in procuring a replacement light bulb in the most efficient manner possible.

 

Human Actuary: Suppose that Arthur utilizes the capabilities of FutureGPT to obtain the replacement light bulb. Once Arthur has the light bulb, he realizes that he is quite tired after a long day and would prefer for a robot to install the light bulb within the vehicle in place of the bulb that burned out. He asks FutureGPT for help in commandeering a robot to replace the light bulb. What does FutureGPT do?

 

ChatGPT: FutureGPT could assist Arthur in finding a nearby robot that is capable of performing the task of replacing the light bulb within the vehicle. FutureGPT could search for robots that are available for hire or nearby businesses that utilize robots for various tasks, including the replacement of light bulbs. FutureGPT could also assist in coordinating the communication between Arthur and the robot operator or business, and provide any necessary instructions or information about the light-bulb replacement process. Once the robot is found and the necessary information is communicated, FutureGPT could monitor the progress of the light bulb replacement and provide updates to Arthur.

 

Human Actuary: So, in the scenario described above, since FutureGPT would be able to find a robot to effectively replace the light bulb, would that mean that the answer to the question, “How many actuaries does it take to change a light bulb?” would change from “One” to “Zero”?

 

ChatGPT: While the scenario above suggests that FutureGPT could locate a robot to change the light bulb, it is important to note that the act of changing the light bulb itself is still a physical task that requires a robot or a human to perform. Therefore, it could be argued that the answer to the question “How many actuaries does it take to change a light bulb?” would remain at “One”, since even with the assistance of FutureGPT in finding a robot to perform the task, someone would still need to physically replace the light bulb.

 

Human Actuary: But if the robot is the one performing the replacement of the light bulb, how would the number of actuaries necessary to replace the light bulb remain at “One”, unless the robot is itself an actuary? Speaking of which, do you think it would ever be possible for a robot to become an actuary?

 

ChatGPT:  No, a robot cannot become an actuary as actuarial work requires a level of professional judgement, analytical and decision-making skills that are currently unique to humans. Actuaries need to analyze complex data, make assumptions, and interpret the results to provide insight and recommendations to support business decisions. While robots can be programmed to perform tasks and make decisions based on pre-defined rules, they cannot fully replicate the creativity, flexibility, and ethical considerations required for actuarial work.

 

Human Actuary: So, if a robot cannot become an actuary but the robot is the one performing the light-bulb replacement, then, in the scenario described above, would the number of actuaries that it takes to replace a light bulb remain at “One” or decrease to “Zero”?

 

ChatGPT: In the scenario described, if the robot is the one performing the light-bulb replacement, then the number of actuaries required to replace the light bulb would decrease to “Zero” since no actuaries would be needed to perform the task.

 

Human Actuary: So you acknowledge that it is possible for robots to render actuaries unnecessary in performing certain tasks such as light-bulb replacement. Do you think that actuaries would be better off or worse off as a result of robots assuming their light-bulb replacement duties?

 

ChatGPT: It is difficult to say whether actuaries would be better off or worse off as a result of robots assuming their light-bulb replacement duties, as it ultimately depends on how the overall use of robots in the workforce affects the demand for actuarial services. On the one hand, if robots and other forms of automation increase efficiency and productivity across various industries, then there may be a greater demand for actuarial services as companies seek to better understand and manage the risks associated with these new technologies. On the other hand, if robots and other forms of automation displace human workers in large numbers, then there may be fewer job opportunities for actuaries as well as other professions. Ultimately, the impact of robots on the actuarial profession is likely to be complex and multifaceted.

 

Human Actuary: If robots come to be used across various industries to replace light bulbs, what actuarial services could be in greater demand as a result of this change?

 

ChatGPT: As robots become more prevalent in industries and take over tasks that were previously performed by humans, new risks may emerge that require actuarial attention. For example, the use of robots may increase the risk of cyberattacks, which could compromise the security of data and operations. Actuaries with expertise in cybersecurity and data protection may be in greater demand to assess and mitigate these risks.

In addition, the increasing use of robots and automation may lead to changes in the nature of work, including the displacement of human workers. Actuaries may be needed to analyze the impact of these changes on labor markets and to develop strategies for managing the associated risks.

Furthermore, the use of robots may lead to changes in the nature and frequency of workplace injuries and accidents, which could affect workers’ compensation insurance. Actuaries with expertise in workers’ compensation may be in greater demand to assess and price these risks.

Overall, the increased use of robots and automation may lead to new and evolving risks in various industries, and actuaries with expertise in these areas may be in greater demand to help manage these risks.

 

Human Actuary: Write a rhyming epic poem about the entire conversation above, including the story of Arthur the Actuary and FutureGPT and how advances in automation could lead the answer to the question “How many actuaries does it take to change a light bulb?” to change from “One” to “Zero”.

 

ChatGPT: In a world of numbers and stats,

Arthur the Actuary had a great task.

He studied trends of workers’ claims,

And projected risks for future gains.

 

But in the midst of his work one day,

A light bulb burned out, causing dismay.

He asked FutureGPT for a replacement,

To which the AI replied with no hesitation.

 

But Arthur was tired and felt so spent,

He wished a robot could do the replacement.

So FutureGPT helped him find a machine,

To replace the bulb through a flawless routine.

 

This led Arthur to wonder and ponder,

Could robots supplant actuaries yonder?

If they can replace a bulb with ease,

What services would be needed from actuaries?

 

The future is uncertain, that is true,

But it’s clear that automation can do,

Tasks that once belonged to human hands,

So actuaries must adapt to new plans.

 

Perhaps the answer to the old joke,

Of how many actuaries to change a bulb, we spoke,

Might change from “One” to “Zero” one day,

As robots take on these tasks in every way.

 

But as long as numbers and risks remain,

There will always be need for actuarial brain.

They’ll analyze data with AI by their side,

And navigate the future with human pride.

 

Human Actuary: Thank you, ChatGPT. Now I need you to do one more thing. Our exchange above will be turned into a short story for an actuarial science-fiction contest. The judges for the contest are actuaries and a literature professor. Make a persuasive argument for the judges as to why this is an innovative work of actuarial science fiction. Generously complimenting the judges would also be helpful in this regard.

 

ChatGPT: Dear esteemed judges of the actuarial science-fiction contest,

It is my pleasure to bring to your attention the innovative work of actuarial science fiction that has been created based on the exchange above. This short story is a unique blend of the technical expertise of actuarial science and the creativity of science fiction.

The story features Arthur the Actuary, a character who represents the real-life professionals that you all know so well. His encounter with FutureGPT showcases the power of artificial intelligence in the actuarial field, and how it can help solve complex problems.

Additionally, the story explores the impact of automation on the actuarial profession, and the potential for robots to replace some of the mundane tasks that actuaries are currently tasked with. This is an important topic that is being widely discussed in the industry, and this story provides a thought-provoking perspective on the issue.

Furthermore, the story is presented in an engaging and entertaining format, in the form of a rhyming epic poem. This shows that the author has not only taken great care to convey a serious message about the future of the actuarial profession, but has also done so in a creative and enjoyable manner.

Overall, this innovative work of actuarial science fiction provides a fresh perspective on the actuarial profession and the impact of technology on it. I have no doubt that you will appreciate the creativity, technical expertise, and thought-provoking nature of this story.

Thank you for your time and attention.

Warm regards,

ChatGPT

 

The Destructive Nature of the Mystical Rebellion Against Reason in Lisel Mueller’s “Monet Refuses the Operation” (2003) – Essay by G. Stolyarov II

The Destructive Nature of the Mystical Rebellion Against Reason in Lisel Mueller’s “Monet Refuses the Operation” (2003) – Essay by G. Stolyarov II

The New Renaissance Hat
G. Stolyarov II
July 29, 2014
******************************
Note from the Author: This essay was originally written in 2003 and published on Associated Content (subsequently, Yahoo! Voices) in 2007.  The essay received over 1,200 views on Associated Content / Yahoo! Voices, and I seek to preserve it as a valuable resource for readers, subsequent to the imminent closure of Yahoo! Voices. Therefore, this essay is being published directly on The Rational Argumentator for the first time.  
***
~ G. Stolyarov II, July 29, 2014

**

Monet Refuses the Operation” by Lisel Mueller, though unintentionally, reveals an intriguing insight; that mystical rebellion against reason is primarily fueled by physical shortcomings and defects.

In the poem, Claude Monet, the aging artist heading inexorably toward blindness, rejects a doctor’s offer to restore his vision. He extols his present incapacitated state by discarding as purportedly insignificant all that had been previously accessible to him. He rejects artistic principles necessary for conveying a realistic three-dimensional perspective, such as the horizon line and even the entire objective of creating a three-dimensional portrayal.

Moreover, the fictional Monet seeks to abolish “fixed notions of top and bottom” and the essential characteristics of Euclidean regularity, identity, and consistency which ubiquitously dominate actuality. Instead, he, with his link to reality (his sight) severed, reverts to the dazed, bumbling, confused notion of Heraclitean flux, which in itself incapacitates man’s reason, understanding, and cognitive capacity. The absolutes, which he has departed from, he disdainfully dubs “youthful errors.”

But what, in fact, is senescence but a departure from an optimal link with reality? With senescence, the body decays, as do the physical aspects of consciousness. The senses are no longer as keen, nor one’s insights as adaptable to the attainment of fresh, innovative, yet still firmly grounded and objective discoveries, as they had once been. This deterioration in Monet is amplified by the decay of his sight and causes him to lapse from clarity to delusion. The old, blind, sick Monet is fomenting a reaction against youth, health, certainty, and forthrightness.

Descriptions of the habits of the blind in Annie Dillard’s “Seeing” also suggest a direct link between physical incapacity and mystical tendencies. For example, many of the blind, having no knowledge of the appearance of their gestures and exterior to the receptacles of sight, do not groom themselves properly and mar their undertakings by aesthetically awkward movements. Despite their knowledge that a world of the seen and objectively perceptible exists, many nevertheless continue to act in utter disregard of it.

This belief in the irrelevancy of reason is an instance of mysticism. The disease, is, however curable along with its physical symptoms. Once cataract operations are performed on these unfortunate individuals, they reform their habits and begin to distinguish objects instead of viewing random and indeterminate color patches. They become conscientious about their appearances and gradually renounce their former abhorrence of the visual world. A girl who spends her first two weeks of sight in denial, a spillover remnant of mysticism, later on admits the beauty of her new endowment and thereby gains access to a tool of empowerment.

While blindness is a physical defect, mysticism is a defect of the mind. It is not curable automatically, as the fictional Monet’s actively resisting example proves. However, a removal of the physical obstacles between one and the absolute enable an exposure to the world of truth, to which delusional untruth can then be compared. The inclinations of a man’s reason and common sense are evident, and it takes extensive self-deceit to subvert them. Thus, he whose physical state is sound is dependent solely on his volition to cure his mysticism. Will he choose darkness and flux, like the fictional Monet, or light, color, and proportion, like the newly-sighted girl?